agreed - Human Brain Project

Transcription

PROPOSAL
HUMAN BRAIN PROJECT
FRAMEWORK PARTNERSHIP AGREEMENT
U N I F Y I N G
O U R
U N D E R S TA N D I N G
O F
T H E
H U M A N
B R A I N
COVER PAGE
Title of Proposal: The Human Brain Project - Framework Partnership Agreement (HBP-FPA)
LIST OF PARTNERS:
Name
Country
École Polytechnique Fédérale de Lausanne
CH
2
Aalto-korkeakoulusäätiö
FI
3
Academisch Ziekenhuis Leiden - Leids Universitair Medisch Centrum
NL
4
Athens University of Economics and Business
GR
5
Barcelona Supercomputing Center - Centro Nacional de Supercomputacion
ES
6
Bauhaus University Weimar
DE
7
Bergische Universität Wuppertal
DE
8
Bloomfield Science Museum Jerusalem
IL
9
Cardiff University
UK
Centre National de la Recherche Scientifique
FR
11
Commissariat à l'énergie atomique et aux énergies alternatives
FR
12
Consiglio Nazionale delle Ricerche
IT
13
Consorzio Interuniversitario Cineca
IT
14
Danmarks Tekniske Universitet
DK
15
Debreceni Egyetem
HU
16
De Montfort University
UK
17
École Normale Supérieure
FR
18
Eidgenössische Technische Hochschule Zürich
CH
19
Fonden Teknologirådet
DK
Forschungszentrum Jülich GmbH
DE
21
Fortiss Gmbh
DE
22
Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
DE
23
Fundacao D. Anna Sommer Champalimaud E Dr. Carlos Montez Champalimaud
PT
24
Heinrich Heine Universität Düsseldorf
DE
25
Helsingin yliopisto
FI
26
HITS gGmbH
DE
27
Hospices Cantonaux CHUV
CH
28
Imperial College of Science, Technology and Medicine
UK
Partner No
1
10
20
HBP Framework Partnership Agreement Proposal
I
List of partners • June 2014
Name
Country
29
L’ Institut du Cerveau et de la Moelle Épinière Fondation
FR
30
Institute of Experimental Medicine, Hungarian Academy of Sciences
HU
31
Institute of Science and Technology Austria
AT
32
Institut Jozef Stefan
SI
33
Institut National de Recherche en Informatique et en Automatique
FR
34
Institut Pasteur
FR
35
Johann Wolfgang Goethe Universität Frankfurt am Main
DE
36
Karlsruher Institut für Technologie
DE
37
Karolinska Institutet
SE
38
King's College London
UK
39
Kungliga Tekniska Hoegskolan
SE
40
Laboratorio Europeo di Spettroscopie Non Lineari
IT
41
Les Hôpitaux Universitaires de Geneve
CH
42
Linneuniversitetet
SE
43
Medizinische Universität Innsbruck
AT
44
National and Kapodistrian University of Athens
GR
45
Norges miljø- og biovitenskapelige universitet
NO
46
Oesterreichische Studiengesellschaft für Kybernetik
AT
47
Rheinisch-Westfälische Technische Hochschule Aachen
DE
48
Ruprecht-Karls-Universität Heidelberg
DE
49
Sabanci University
TR
50
Scuola Superiore di Studi Universitari e di Perfezionamento Sant'Anna
IT
51
Stichting Centrum voor Wiskunde en Informatica
NL
52
Stichting Katholieke Universiteit
NL
53
Stiftung FZI Forschungszentrum Informatik am Karlsruher Institut für Technologie
DE
54
Technical University of Crete
GR
55
Technische Universität Dresden
DE
56
Technische Universität Graz
AT
57
Technische Universitaet München
DE
58
Tel Aviv University
IL
Partner No
II
Name
Country
59
The Chancellor, Masters and Scholars of the University of Cambridge
UK
60
The Chancellor, Masters and Scholars of the University of Oxford
UK
61
The Hebrew University of Jerusalem
IL
62
The University of Aberdeen
UK
63
The University of Edinburgh
UK
64
The University of Manchester
UK
65
Universidad Autonoma de Madrid
ES
66
Universidad de Castilla - La Mancha
ES
67
Universidad de Granada
ES
68
Universidade Do Minho
PT
69
Universidad Politécnica de Madrid
ES
70
Universidad Rey Juan Carlos
ES
71
Universita degli Studi di Pavia
IT
72
Universität Bern
CH
73
Universität Bielefeld
DE
74
Universitätsklinikum Aachen
DE
75
Universitätsklinikum Hamburg-Eppendorf
DE
76
Universität Zürich
CH
77
Universitat de Barcelona
ES
78
Universitat Pompeu Fabra
ES
79
Université d’Aix Marseille
FR
80
Université de Bordeaux
FR
81
Universiteit Antwerpen
BE
82
Universitetet i Oslo
NO
83
University College London
UK
84
Uppsala Universitet
SE
85
Weizmann Institute of Science
IL
Partner No
III
Table of Contents
1. Excellence. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.0 Concept. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.0.0 Vision. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2
1.0.1 Flagship Strategic Objectives (SFO). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.0.2 The Core Project and the Partnering Projects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.0.3 Core Project Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.0.4 List of Planned Actions under Framework Partnership Agreement FPA: (Core Project). . . . . . . . . . . . . . . . . . . . . 5
1.0.5 Why Some Objectives are in FPA and Others are Outside (Core and Partnering Projects). . . . . . . . . . . . . . . . . . 10
1.0.6 Gender Balance in HBP Recruitment and Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.0.7 Gender Balance in HBP Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.1 Scientific and technological quality of individual partners and of the consortium as a whole in view
of the objectives and roadmap of the flagship. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.1.1 Role and Expertise of Individual Partners. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.1.2 International Involvement in the HBP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.1.3 The Whole Consortium. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.2 Quality and relevant experience of the individual partners and the consortium as a whole with
regard to non-scientific aspects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.2.1 Role and Expertise of Individual Partners. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 7
2. Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.1 Contribution to Expected Impacts Listed in the Work Programme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.1.1 Describe Formalised Commitment of Partners to Realise Action Plan of FPA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.1.2. Actions to Create a Stable and Structured Environment and to Ensure the Continuity
and Coherence of the Initiative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.1.3 Other Impacts Mentioned in the Work Programme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1
2.2 Measures to Maximise Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2.1 Impacts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2.2 Outline Communications and Dissemination Strategy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.2.3 Potential of Consortium to Exploit Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.2.4 Measures to Protect IP, Ensure Effective Exploitation and Realise Innovation Potential. . . . . . . . . . . . . . . . . . . . 28
2.2.5 Contributions to Education and Training. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.2.6 The HBP Museums Programme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.2.7 Knowledge Management (Apart from IPR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3 Access to resources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3.1 Estimated costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.3.2 Funding sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2
2.3.3 Resources made available by Partners. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.4 Fostering Complementarity with Regional, National, European and International
Research Programmes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.4.1 Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.4.2 Implementation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.4.3 Measurement of Success. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3. Implementation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.1 Quality of Governance and Management Structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38
3.1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.1.2 Flagship Governance Forum (FGF). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.1.3 Framework Partnership Board (FPB). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.1.4 The Flagship Coordinator (COORD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.1.5 The Core Project General Assembly (CP-GA). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.1.6 HBP Research Board (RB). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.1.7 HBP Executive Committee (ExCo). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2
3.1.8 Subproject Committees (SPCs). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.9 Partnering Projects Committees (PPCs). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.10 Advisory Bodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.11 Dispute Resolution Agreement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.1.12 The Foundation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2 Openness and flexibility. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
IV
Table of Contents • June 2014
3.2.1 How Will we Provide Openness over the Duration of the Consortium?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.2.2 Support for Activities Elsewhere in the Flagship (outside the FPA)?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3 Mechanisms for Monitoring Progress and Quality Assurance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3.1 Management Key Performance Indicators (M-KPIs). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3.2 Quality Assurance of HBP Deliverables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.3.3 Measuring Scientific Progress. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
4. Members of the Consortium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5. Ethics and safety. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
5.1 Meeting National, Legal and Ethical Requirements in Countries where Research is Carried Out . . 160
5.1.1 SP1 Targeted Mapping of the Mouse Brain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
5.1.2 SP2 Targeted Mapping of the Human Brain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
5.1.3 SP7 Medical Informatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
5.2 General Approach to Ethical Issues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5.2.1 Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5.2.2 Research Methodology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5.2.3 Potential Impact of the Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
Appendix 1: Overview of the Flagship objectives and strategic research Roadmap. . . . . . . . . . . . . . . . . 168
1. Concept and strategy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
2. Strategic Flagship Objectives (SFOs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
3. Research Roadmap. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
3.2 Subproject 1: Targeted Mapping of the Mouse Brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
3.2.1 General and Operational Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
3.2.2 State of the art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
3.2.3 Advances over State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
3.2.4 Actions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
3.2.5 Output Targets and Milestones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
3.2.6 Risk Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
3.2.7 Impact and Innovation Potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
3.3 Subproject 2: Targeted Mapping of the Human Brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
3.3.2 State of the art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
3.3.4 Operational Objectives and Related Actions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
3.3.5 Output Targets and Milestones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .179
3.3.6 Risk Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
3.4 Subproject 3: Theoretical and Mathematical Foundations of Neuroscience . . . . . . . . . . . . . . . . . . . 180
3.4.1 General and Operational Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
3.4.2 State of the art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
3.4.3 Advances over the State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
3.4.4 Operational Objectives and Related Actions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
3.4.5 Output Targets and Milestones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
3.4.6 Risk analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
3.5 Subproject 4: Neuroinformatics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
3.5.2 State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
3.5.3 Advances Beyond the State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
3.5.5 Output Targets and Milestones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .184
3.5.6 Risk Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
3.6 Subproject 5: Brain simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
3.6.2 State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
3.6.3 Advances over the State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
V
3.6.5 Output Targets and Milestones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
3.6.6 Risk Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
3.7 Subproject 6: High Performance Computing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
3.7.1 General and Operational Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
3.7.2 State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
3.7.3 Advances over the State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
3.7.4 Operational Objectives and Related Actions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .193
3.7.6 Risks and Contingencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
3.7.7 Impact and Innovation Potential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
3.8 Subproject 7: Medical informatics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
3.8.2 State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
3.8.6 Risk Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
3.9 Subproject 8: Neuromorphic computing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
3.9.1 General and Operational Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
3.9.2 State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
3.9.6 Risk Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
3.10 Subproject 9: Neurorobotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
3.10.1 General Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
3.10.2 State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
3.10.3 Advances over State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
3.10.4 Operational Objectives and Related Actions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
3.10.5 Output Targets and Outcomes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
3.10.6 Risk Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
3.10.7 Impact and Innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
3.11 Subproject 10: Ethics and Society. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
3.11.1 General and Operational Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
3.11.2 State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
3.11.3 Advances over State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
3.11.4 Operational Objectives and Related Actions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
3.11.5 Output Targets and Milestones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210
3.11.6 Risk Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210
4 Partnering Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
5 Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216
VI
EXCELLENCE
1. EXCELLENCE
1.0 Concept
1.0.0 Vision
Human Brain Project Global Perspective
Understanding the human brain is one of the greatest
challenges facing 21st century science. If we can rise to it,
we can gain profound insights into what makes us human,
build revolutionary computing technologies and develop
new treatments for brain disorders. Today, for the first
time, modern ICT has brought these goals within reach.
ATIONAL FUND
ING
ERN
T
IN
A plan for data
in today’s
fragmented
environment
ONAL FUNDING
I
T
NA
Data
Neuroscience is generating exponentially growing
volumes of data and knowledge on specific aspects
of the healthy and diseased brain in animals of different ages and genders, belonging to a broad range of
species. However, we still do not have effective strategies to experimentally map the brain across all its levels
and functions. Modern supercomputing technology
makes it possible—for the first time—to integrate these
data in detailed reconstructions and simulations. These
new methods allow researchers to predict missing data
and principles, and enable measurements and experimental manipulations that would be ethically or technically impossible in animals or humans. New in silico
neuroscience has the potential to reveal the detailed
mechanisms leading from genes to cells and circuits,
and ultimately to cognition and behaviour – the biology
that makes us human.
Individual
Institutional
Country
Global
Medicine is experiencing a data explosion driven by
advances in genetics and imaging. But again, we lack
effective strategies to integrate the data, and to protect
patient privacy. New databasing and data mining technologies offer a solution, making it possible to federate
and analyse the data accumulating in hospital archives,
without moving it to central storage, allowing researchers to identify the biological changes associated with
disease (“biological signatures of disease”) and opening
possibilities for early diagnosis and personalised medicine. In the longer term, the data will make it possible to
modify models of the healthy brain to simulate disease.
Disease simulation will provide researchers with a powerful new tool to probe the causes of neurological and
psychiatric disease, and to screen putative treatments.
Disease and drug simulation has the potential to accelerate medical research, reducing the huge economic and
social burden of brain disease.
Curation
Knowledge
Neuroscience
Medicine
Computing
Core
Project
Unifying our
understanding
of the
Human Brain
Partnering
Projects
world, to understand the human brain and its diseases,
and ultimately to emulate its computational capabilities.
1.0.1 Flagship Strategic Objectives (SFO)
SFO1 Future Neuroscience
Achieve a unified, multi-level understanding of the
human brain that integrates data and knowledge
about the healthy and diseased brain across all levels
of biological organisation, from genes to behaviour;
establish in silico experimentation as a foundational
methodology for understanding the brain.
SFO2 Future Computing
Develop novel neuromorphic and neurorobotic technologies based on the brain’s circuitry and computing principles; develop supercomputing technologies
for brain simulation, robot and autonomous systems
control and other data intensive applications.
SFO3 Future Medicine
Develop an objective, biologically grounded map of
neurological and psychiatric diseases based on mul-
The goal of the Human Brain Project is to translate these
prospects into reality, catalysing a global collaborative
effort to integrate neuroscience data from around the
Future
Understanding
Computing can be similarly transformed. The human
brain performs computations inaccessible to the most
powerful of today’s computers – all while consuming
no more power than a light bulb. Understanding how
the brain computes reliably with unreliable elements,
and how different elements of the brain communicate,
can provide the key to a completely new category of
hardware (Neuromorphic Computing Systems) and to a
paradigm shift for computing as a whole. The economic
and industrial impact is potentially enormous.
Organizing
existing data
& Generating
new data
NAL FUN
REGIO
DIN
G
FUNDING
EAN
OP
R
EU
2
Excellence
FU
RE
TU
NEUROSC
IEN
Develop &
operate six ICT
platforms, making
HBP tools, methods and data available
to the scientific community
FU
T
tilevel clinical data; use the map to classify and diagnose brain diseases and to configure models of these
diseases; use in silico experimentation to understand
the causes of brain diseases and develop new drugs
and other treatments; establish personalised medicine for neurology and psychiatry.
to address previously intractable issues in neuroscience; develop novel computing technologies and
applications; and improve understanding, diagnosis
and treatment of brain disorders. Partnering Projects
will be selected and coordinated by the Core Project,
working in close coordination with funding agencies
and other organisations supporting the projects.
1.0.2 The Core Project and the Partnering Projects
After the current Ramp-Up Phase of the HBP, these goals
will be pursued through a Core Project (CP), and Partnering Projects (PPs), which together constitute the HBP
Flagship Initiative. The Core Project and the Partnering
Projects are equally essential to achieving the strategic
goals of the Flagship Initiative.
The present document describes the Action Plan for the
CP. The Research Roadmap for the whole HBP Flagship
Initiative and its relationship to the Actions planned in
the CP are described in Appendix 1.
1.0.3 Core Project Objectives
The Core Project (CP) will lead the implementation of
the Action Plan. The Project aims to achieve the following objectives.
• The Core Project, funded by the FET Flagship Programme, will build and operate six ICT Platforms
enabling the scientific community to perform
radically new kinds of research in neuroscience,
computing and medicine. The Core Project will be
articulated in several (probably three) phases, each
regulated by a Specific Grant Agreement between
the Partners and the European Commission.
CPO1 Simulate the Brain: Develop ICT tools to generate high-fidelity digital reconstructions and simulations
of the mouse brain, and ultimately the human brain.
Reconstructions and simulations of the brain provide a
radically new approach to neuroscience, helping to fill
gaps in the experimental data, connecting different levels
of biological organisation, and enabling in silico experiments impossible in the laboratory. Such experiments
can provide fundamental new insights into the biological
mechanisms underlying cognition and behaviour, make
it possible to test hypotheses of disease causation, and
provide a valuable new tool for drug development.
• The Partnering Projects, funded from regional,
national, European, international and other sources
(e.g., private industry, donors), will develop new ideas,
approaches and technologies spontaneously proposed by independent research groups. Partnering
Projects will perform research that adds novel capabilities to the Platforms, and that uses the Platforms
I
U
R
Drive translation of HBP research
results into technologies, products &
services
IC
Figure 1: HBP Core Project Activities
Develop
interactive
super
Drive
Perform targeted computing collaboration
mapping of the
with other
mouse brain
research
& the human
initiatives
brain
D
E
C
Education
& knowledge
management
HBP
CORE
PROJECT
Develop
brain-inspired
computing
and
robotics
Catalyse
revolutionary
new
research
E
P
OM
Map
brain
diseases
Simulate
the
brain
FUTU
R
E
ME
UTING
Pursue
a policy
of responsible
research
Develop a
innovation
multi-scale
theory for
the brain
CE
N
HBP Core Project Activities
3
Excellence
CPO2 Develop Brain-Inspired Computing and
Robotics: Develop ICT tools supporting the re-implementation of bottom-up and top-down models of
the brain in neuromorphic computing and neurorobotic systems.
theory-based, top-down and data-driven, bottomup approaches.
Theory developed in the HBP will provide a framework for understanding learning, memory, attention and goal-oriented behaviour, the way function
emerges from structure; and the level of biological
detail required for mechanistic explanations of these
functions. Simplification strategies and computing
principles resulting from this work will make it possible to implement specific brain functions in Neuromorphic Computing Systems.
HBP Neuromorphic Computing Systems will use
brain-like principles of computing and architectures
to achieve high-energy efficiency and fault tolerance,
together with learning and cognitive capabilities
comparable to those of biological organisms. Neurorobotic systems will use them as controllers, enabling
a new category of closed loop experiment that dissects how different levels of brain organisation contribute to cognition and behaviour.
CPO7 Develop and Operate six ICT Platforms, Making
HBP Tools, Methods and Data Available to the Scientific Community: Develop and operate six specialised
Platforms dedicated respectively to Neuroinformatics, Brain Simulation, High Performance Computing,
Medical Informatics, Neuromorphic Computing, Neurorobotics, and a Unified Portal providing a single
point of access to the Platforms.
CPO3 Develop Interactive Supercomputing: Develop
hardware architectures and software systems for
visually interactive, multi-scale supercomputing
moving towards the exascale.
The new systems will make extreme computing
accessible to neuroscientists and clinicians, supporting the requirements of brain simulation and of high
throughput, big data analytics, and enabling a broad
range of other data-intensive applications.
The Platforms and the Unified Portal will provide a collaborative, transdisciplinary environment and community
services that enable industry and academic researchers
to use HBP methods, tools, data, and know-how in their
own independent research, and to address a practically
unbounded range of novel research questions.
CPO4 Map Brain Diseases: Develop ICT tools to federate and cluster anonymised patient data.
CPO8 Catalyse Revolutionary New Research: Leverage investment in platform development to catalyse a
phase shift in neuroscience, computing, and medical
research.
The new tools will make it possible to identify patterns of alteration across different levels of biological
organisation, suggesting new diagnostic indicators
and drug targets, facilitating the selection of subjects for clinical trials, providing the data required for
disease modelling and simulation, and facilitating the
translation of knowledge about the brain from the
laboratory to the clinic.
The HBP Platforms will enable industry and academic
researchers to apply radically new methods in their
research and provide European companies with unique
R&D capabilities. Researcher-driven studies, made possible by the new methods, have the potential to achieve
breakthroughs in different areas of neuroscience, computing and medicine, many of vital importance to European industry and European citizens.
CPO5 Perform Targeted Mapping of the Mouse Brain
and the Human Brain: Generate targeted data sets
that can act as anchor points for future data generation and for high-fidelity reconstructions of the brain.
CPO9 Drive Collaboration with other Research Initiatives: Establish synergistic collaborations with
national, European, international and transnational initiatives contributing to the Strategic Flagship Objectives.
Targeted data sets for mouse will make it possible to develop the integration and algorithmic
reconstruction processes required for high fidelity
reconstruction of the mouse brain across all levels
of biological organisation, from genes to cognition. Parallel data sets for humans will enable the
application of technologies developed in animals
to mapping the human brain, facilitate translation
of knowledge about the mouse brain to the human
brain and constrain human brain models. The availability of these data sets will expose critical gaps
in our current knowledge, catalysing collaboration
with large-scale brain mapping initiatives around
the world, Detailed data on brain structure at different levels of biological organisation will provide
a vital tool for functional studies mapping the links
from genes to cognition and behaviour.
Global collaboration is essential to multiply the value
created by research, avoiding duplication of effort and
building momentum behind the global effort to understand the brain and its diseases. The HBP will build a
large network of collaborations with other large initiatives around the work, and will contribute enthusiastically to plans for a Global Network of Brain Initiatives.
CPO10 Drive Translation of HBP Research Results
into Technologies, Products and Services: Promote
engagement with industry to translate HBP research
results into technologies, products and services benefitting European citizens and European industry.
CPO6 Develop a Multi-Scale Theory for the Brain:
Develop a multi-scale theory of the brain that merges
4
Excellence
Expected HBP results in brain-inspired computing
and medicine have the potential to give European
industry a leading position in key areas of the 21st
century economy.
ciples governing the spatial architecture of brain
regions, neuronal populations and synapse types;
develop a theory of structural-functional relationships; develop techniques to characterise cognitive
architectures, developmental models and variability;
develop techniques for big data management and
links to HBP Brain Atlases; develop validation tests
for brains models and simulations.
CPO11 Education and Knowledge Management:
Implement a programme of transdisciplinary education to train young scientists to exploit the convergence between ICT and neuroscience, and to create
new capabilities for European academia and industry.
WP1.5. Integrative map: develop an integrative,
multi-level map of the whole mouse brain including
data on cell numbers and distributions, neuron-glial
ratios, excitatory-inhibitory ratios, cellular composition (location-dependent composition in terms of
morphological, electrical, projection, molecular and
genetic subtypes of neurons), gene and protein
expression (e.g., ion channels, receptors, synapses),
and single-cell transcriptomes; identify topographical and metabolic relationships between blood
vessels, neurons and glial cells; identify principles of
structural segregation (cortical areas and nuclei);
visualise cells and fibres in the whole brain; develop
whole brain reconstructions from transparent brains;
identify principles of functional segregation.
The HBP Education Programme will give students
the transdisciplinary skills they will need to participate in the HBP, to use the HBP Platforms and HBP
data in their own research, and to apply HBP research
results in the development of commercial technologies, products and services.
CPO12 Pursue a Policy of Responsible Research
Innovation: Implement a strategy of Responsible
Research Innovation, monitoring science and technological results as they emerge, analysing their social
and philosophical implications, and raising awareness of these issues among researchers and citizens,
involving them in a far-reaching conversation about
future directions of research.
WP1.6 Scientific coordination: coordinate scientific
activities within the SP and with other SPs, Partnering Projects and international collaborations; coordinate quality assurance, organisation of meetings
and workshops and reporting.
1.0.4 List of Planned Actions under
Framework Partnership Agreement FPA:
(Core Project)
The Core Project Objectives will be implemented through
11 Subprojects (SPs), organised into Work Packages,
implementing the specific Actions described below.
1.0.4.2 Subproject 2: Targeted Mapping of the
Human Brain
1.0.4.1 Subproject 1: Targeted Mapping of the
Mouse Brain
WP2.1 Genetic and molecular architecture: characterise inter-individual genetic variation; obtain single
cell transcriptomes, together with data on epigenetics,
genetic regulatory networks, proteome composition
and organisation, and the distribution of transporters,
ion channels, receptors and complexes.
WP1.1. Genetic and molecular architecture: characterise inter-individual genetic variation; generate
single cell transcriptomes, together with data on
epigenetics, genetic regulatory networks, proteome
composition and organisation, and the distribution of
transporters, ion channels, receptors and complexes.
WP2.2 Architecture of synapses, neurons and glial
cells: characterise micro projections (e.g. synaptic
connections between neighbouring neurons); measure
the density and distributions of excitatory and inhibitory synapses, and numbers and distributions of organelles (e.g. mitochondria); identify synaptic selectivity
principles; characterise the structural relationships
between neurons, glial cells and the vascular system;
capture the morphologies of neurons and glial cells.
cells: characterise micro projections (e.g., synaptic connections between neighbouring neurons); measure the
density and distributions of excitatory and inhibitory
synapses, and numbers and distributions of organelles
(e.g., mitochondria); identify synaptic selectivity principles; capture the morphologies of neurons and glial
cells; characterise structural relationships between
neurons, glia and the vascular system.
WP2.3 Circuit architecture: characterise afferent
and efferent axonal projections within (meso) and
between (macro) brain regions and nuclei, and their
relationship to microstructure; obtain whole brain
maps using transparent brains and PLI; characterise
tract structure (fibre composition and distribution,
topographical organisation); characterise inter-subject variability in circuit architecture.
WP1.3 Circuit architecture: characterise afferent and
efferent axonal projections within (meso) and between
(macro) brain regions and nuclei, and their relationship
to microstructure; obtain whole brain maps using transparent brains and PLI; characterise tract structure (fibre
composition and distribution, topographical organisation).
WP2.4. Theory and informatics: identify principles
for use in predictive neuroinformatics, mouse-human
comparisons and multi-scale theory. Identify principles governing the spatial architecture of brain
WP1.4. Theory and informatics: identify principles
comparisons and multi-scale theory; identify prin-
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Excellence
WP3.5 Brain-scale network models: develop theoretical
frameworks making it possible to construct and simulate multi-layer network models based on connectivity
rules; compare the behaviour of detailed models with
the approaches developed in WP3.2, contributing to a
multi-scale theory of the brain; provide a complimentary
substrate for top-down modelling in WP3.4; link concepts
developed in SP3 to bottom-up models developed in SP5.
regions, of neuronal populations and of synapse
types, develop a theory of structural-functional relationships; develop techniques to characterise cognitive architectures; develop techniques of big data
management and link to HBP Atlases; develop benchmarks for modelling and simulation.
WP2.5. Integrative map: develop an integrative,
multi-level map of the whole human brain including
expression (e.g. ion channels, receptors, synapses),
and single-cell transcriptomes; identify topographical
and metabolic relationships between blood vessels,
neurons and glial cells; characterise inter-subject variability; identify principles of structural segregation
(cortical areas and nuclei); visualise cells and fibres
in the whole brain; develop whole brain maps from
transparent brains; identify principles of functional
segregation; develop and apply advanced topographical and image fusion methods.
WP3.6 Scientific coordination: operate the European
Institute for Theoretical Neuroscience, and its visiting scientists program, coordinate scientific activities within the
SP, and with other SPs, Partnering Projects and international collaborations; coordinate quality assurance, organisation of meetings and workshops and reporting.
1.0.4.4Subproject 4: Neuroinformatics
WP4.1 Brain atlas tools, ontologies and shared data
space: develop a shared data space and navigation
tools, a generic atlas builder and tools for a “KnowledgeSpace” (a wiki of multi-level knowledge about
the brain); develop agreed ontologies.
WP4.2 Mouse Brain Atlas: develop and maintain a multilevel atlas of the mouse brain, mapping the full spectrum of data at each level to its 3D coordinates; bring
together targeted data from SP1, large-scale brainmapping data from the Allen Institute Mouse Brain
Atlas, the US BRAIN Initiative and others, predicted data
from SP5, theoretical insights from SP3 and knowledge
from the literature literature and from mouse models of
human brain disease (via the KnowledgeSpace).
activities within the SP, and with other SPs, Partnering Projects and international collaborations; coordinate quality assurance, organisation of meetings
1.0.4.3 Subproject 3: Mathematical and Theoretical
Foundations
WP3.1 Theory across SP boundaries: develop strategies, principles, and algorithms enabling comparative
assessment of data from the mouse and human brains,
and different modelling approaches; develop theoretical frameworks to predict brain function from structure and its clinically relevant dysfunctions, compare
brain models with implementations in Neuromorphic
Computing Systems, and Neurorobotic closed-loop
experiments.
WP4.3 Human Brain Atlas: develop and maintain a
multi-level atlas of the human brain, mapping the full
spectrum of data at each level to its 3D coordinates;
bring together targeted data from SP2, biological signatures of disease from SP7, large-scale brain-mapping data from the Allen Institute Human Brain Atlas,
the US BRAIN Initiative and others, predicted data
from SP5, theoretical insights from SP3 and knowledge from the literature (via the KnowledgeSpace).
WP3.2 Bridging scales: develop simplification strategies and simplified models from the single cell to
the circuit and higher levels; derive mean field and
point neuron models from morphologically detailed
models; investigate multi-scale aspects of neural
computation, from single cells to circuits; characterise the biophysical mechanisms underlying brain
signals at different scales, from single units to LFP,
EEG, MEG and fMRI.
WP4.4 Theory and big data engineering: develop
theory-driven methods for predictive neuroinformatics, feature extraction, and data clustering; develop
tools, models and Data-management technology for
efficient, large-scale provenance tracking, data analysis, data mining and management of exascale data;
develop algorithms for large-scale predictive data
analytics and for the generation, maintenance, and
mining of provenance links.
WP3.3 Learning and memory: develop plasticity algorithms; develop models for supervised and
unsupervised learning, reward and punishment, and
goal-oriented behavioral learning, suitable for implementation in Neuromorphic Computing Systems.
WP4.5 Neuroinformatics Platform: design, implement
and operate an ICT Platform providing community
access to the Atlases and related tools; provide documentation, training and support for users of the Platform; integrate the Platform with the HBP Unified Portal.
WP3.4 Models of cognitive processes: develop topdown models of single and multiple brain areas, their
dynamics and cognitive functions, for implementation in Neuromorphic Computing Systems; contribute
to a multi-scale theory of the brain.
activities within the SP and with other SPs, Partnering Projects and international collaborations; coordinate quality assurance, organization of meetings
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Excellence
1.0.4.5 Subproject 5: Brain Simulation
WP6.2 Data-intensive supercomputing: develop programming models, middleware, libraries, algorithms
and data stores to exploit data locality and avoid data
movement on supercomputing systems.
WP5.1 Algorithmic reconstruction of the brain:
develop algorithms for multi-level (molecular, subcellular and cellular level) reconstruction of neurons,
synapses, glia and vasculature, microcircuits, mesocircuits (brain regions), and macro-circuits (the whole
brain); implement theoretical insights from SP3 in
algorithms for synaptic plasticity, re-wiring, axon
remodelling and neuromodulation; develop tools
enabling automated integration of data from the Neuroinformatics Platform; develop methods for provenance tracking and validation of brain models.
WP6.3 Interactive visualisation software: develop
middleware and functionality for large-scale visual
data analysis, including semantic linking; develop
software for large-scale, interactive and immersive
visualisation environments.
WP6.4 Dynamic resource management: develop
libraries, APIs, and scheduler software enabling applications to dynamically change their use of resources;
develop middleware and libraries for in situ and coscheduled execution of analysis and visualisation
filters on heterogeneous hardware.
WP5.2 Multi-scale simulation software: development, updating and maintenance of brain simulation
engines for molecular dynamics, reaction-diffusion
dynamics, cellular-level simulation and point neuron
network simulation.
WP6.5 Performance modelling and hardware/software co-design: develop tools, models, description
languages, and simulation frameworks to model software performance on different machine architectures.
WP5.3 Molecular models and simulations: build and
simulate molecular-level models of neurons, synapses,
glia and vasculature; develop multi-scale (atomistic
and coarse-grained) molecular modelling and simulation to characterise molecular interactions (notably,
protein-protein and protein-drug interactions) and to
obtain thermodynamic and kinetic parameters, filling
gaps in experimental knowledge.
WP6.6 High Performance Computing Platform:
design, implement and operate an ICT Platform providing access to the tools, models and simulations
developed in SP5; support industry-strength software
deployment through software development processes, continuous integration, continuous deployment, and Platform as a Service (PaaS); support
performance tools and auto-tuning for efficient userdriven analysis; provide documentation, training and
support for users of the Platform; integrate with the
HBP Unified Portal.
WP5.4 Mouse brain models: develop models of the
mouse brain at the subcellular, cellular, micro (column/
module/nucleus), meso (region), and macro (whole
brain) levels.
WP5.5 Human brain models: develop models of the
human brain at the subcellular, cellular, micro (column/
brain) levels.
activities within the SP, and with other SPs, Partnering Projects and international collaborations; coordinate quality assurance, organisation of meetings and
workshops and reporting; coordinate supercomputer
procurement and the PPI (Public Procurement of
Innovation) process.
W P 5 . 6 T h e o r y : u n d e r st a n d t h e re l a t i o n s h i p
between brain structure and function, contribute to
a multi-scale theory of the brain; generate simplified models for implementation in Neuromorphic
Computing Systems.
1.0.4.7 Subproject 7: Medical Informatics
WP5.7 Brain Simulation Platform: design, implement
and operate an ICT Platform, enabling researchers to collaboratively reconstruct and simulate the
brain; provide documentation, training and support
for users of the Platform. Integrate with the HBP
Unified Portal.
WP7.1 Clinical data infrastructure: develop tools to harmonise heterogeneous clinical databases, and for data
anonymisation; develop interfaces for ontology-based
querying; develop methods for federated search and
intensive distributed analysis of clinical data; coordinate
implementation of these tools in the HBP Unified Portal.
WP5.8 Scientific coordination: coordinate scientific activities within the SP and with other SPs, Partnering Projects and international collaborations; coordinate quality
assurance, organisation of meetings and workshops
and reporting.
WP7.2 Hospital recruitment and data gathering: recruit
hospitals, clinics and other sources of data (large-scale
clinical studies, pharmaceutical companies, biobanks,
etc.); formalise agreements with these organizations;
provide required installation services, demonstrations
and training.
1.0.4.6Subproject 6: High Performance Computing
WP7.3 Data models and features of disease: develop
and apply tools and descriptive statistical analysis;
extract brain morphology, genomic and proteomic
features from clinical and research databases; extract
patterns of variation in brain morphology, genes and
proteins associated with neurological and psychiatric
WP6.1 Simulation technology components: develop
specialised methods and libraries for the data structures, algorithms and numerical methods used in
brain simulator software; develop domain-specific
languages and tools for code generation.
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Excellence
WP8.4 Theory - principles of brain computation:
extract principles of brain computation and learning
from experimental data in neuroscience and cognitive science and simulations; use these principles to
provide desired functional properties to neuromorphic systems, neurorobotic systems and other applications; investigate and address systematic problems
that arise in specific application domains.
diseases; identify biological signatures of disease;
develop a map of brain diseases; contribute data and
biological signatures of disease to the Human Brain
Atlas developed in SP4.
WP7.4 Biological signatures of disease, theory and
disease models: develop new techniques for big data
analysis; introduce novel mathematical methods for clustering multi-level clinical data, enabling the identification
of biological signatures of disease; develop predictive and
prescriptive medical informatics, enabling the identification of biological signatures of disease; develop generative models of causal mechanisms and resilience.
WP8.5 Neuromorphic Computing Platform: design,
implement and operate an ICT Platform providing a
single point of access to the software and hardware
infrastructure developed in SP8; provide documentation, training and support for users of the neuromorphic Platform; integrate with the Unified Portal;
enable researchers, technology and applications
developers to design, implement and test a spectrum of Neuromorphic Computing Systems and to
develop products and services.
WP7.5 The Medical Informatics Platform: design, implement and operate an ICT Platform providing a single
point of access to clinical data from hospitals and other
sources and advanced analysis tools; integrate the Platform with the Unified Portal; provide support, training,
maintenance and coordination; enable medical and
pharmaceutical researchers to address novel research
questions; enable clinicians to use and advance new
techniques of personalised medicine.
WP8.6 Scientific coordination: coordinate scientific activities within the SP, and with other SPs, Partnering Projects and international collaborations; coordinate
quality assurance, organisation of meetings and workshops and reporting.
activities within the SP, and with other SPs, Partnering Projects and international collaborations; quality
assurance, organisation of meetings and workshops
and reporting.
1.0.4.9 Subproject 9: Neurorobotics
WP9.1 Virtual robots and environments: develop a
Robot and Environment Designer, and a World Simulation Engine; construct virtual robots and virtual
environments from reusable parts; build and curate
databases of sensors, motors and other parts for
robots and environments; develop HPC-based physics
engines for high-fidelity simulation of sensory-rich,
physically realistic worlds with multiple interacting
robots and agents.
1.0.4.8 Subproject 8: Neuromorphic Computing
WP8.1 Physical model implementation: design, build
and operate three versions of a physical model
Neuromorphic Computing System (NM-PM-1, 2, 3),
enabling the scientific community to perform largescale neuromorphic computing with physical emulation of brain models; design required chips and
boards, manufacture, assemble and commission
neuromorphic computer systems; carry out targeted
R&D on connection technologies, in particular waferboard interconnects required for the construction of
NM-PM-3; develop and implement low-level software
and firmware.
WP9.2 Virtual neurorobotics laboratory: develop
capabilities to plan, run and analyse in silico experiments with Neurorobotics Systems and test them
in pilot experiments; develop tools for immersive
high-fidelity rendering and real-time user interaction, enabling lifelike neurorobotics experiments with
users in the loop.
WP8.2 Digital model implementation: design, build
and operate 2 versions of a many-core neuromorphic
computing system (NM-MC-1, 2), enabling the scientific community to perform neuromorphic computing
with digital many-core simulations of brain models;
design required chips and boards; manufacture,
assemble and commission Neuromorphic Systems;
carry out targeted R&D on 3D memory integration as
required for the construction of NM-MC-2; develop
and implement the low-level software required.
WP9.3 Brain-body integration: build models of
spinal cord, sensory, motor and vestibular systems;
close the sensory-motor loop with the CNS, PNS and
body; establish reflexive control and motor primitives;
establish basic motor control; establish basic drives,
value-systems and motivations for autonomy.
WP9.4 Bridging the reality gap: develop technology
to construct and calibrate virtual robots, and virtual
physics to match real-world physics.
WP8.3 Tools: develop and implement high-level software tools for the operation of the neuromorphic
systems developed in WP8.1 and WP 8.2; integrate
the Neuromorphic Computing Platform into the HBP
Unified Portal; integrate available HPC resources into
the neuromorphic computing workflow; develop and
carry out performance benchmarks for neuromorphic computing.
WP9.5 Neurorobotics models: develop and test a
prototype of a complete closed-loop system with a
brain, a body and an environment sufficiently rich and
accurate for use in cognitive and behavioural research.
WP9.6 In silico behaviour, cognition and social interaction: run in silico experiments in which neurorobotic
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Excellence
1.0.4.11Subproject 11: Management and Coordination
systems are coupled to models of the healthy and
the diseased brain; run experiments with multi-agent
neurorobotic systems, investigating the role of social
interaction in the development of cognitive systems.
WP11.1 Governance, performance and risk management: coordinate the governance, leadership and
decision-making mechanisms of the HBP Flagship
Initiative, ensuring balanced representation for stakeholders; support the governing and advisory bodies
in their operations; develop and implement performance and risk management schemes.
WP9.7 Technology bridge: translate virtual robots and
brain-derived controllers to physical prototypes; transfer
controllers to state-of-the-art embedded systems.
WP9.8 Neurorobotics Platform: design, implement
access to Neurorobotics capabilities; provide documentation, training and support for users; integrate
with the Unified Portal; enable a new paradigm of in
silico research for investigations of the links between
the multi-level structure of the brain, cognition and
behaviour; enable industry to develop new Neurorobotic applications.
WP11.2 Administrative coordination: coordinate
administrative actions necessary for the effective management of the project, including financial management, internal reporting, and reporting
to the EU; support the partners in administrative
matters; coordinate the signature and amendment
of contractual documents.
WP11.3 Writing and editing: Provide science writing,
editing and research services; review and edit HBP
deliverables and reports, create, edit and review
written materials required for administration and dissemination; undertake background research on topics
relevant to HBP management decisions.
workshops; reporting.
1.0.4.10 Subproject 10: Ethics and Society
WP11.4: Science and technology monitoring:
monitor scientific and technological work; monitor
and support partners’ progress towards Milestones
and Deliverables; review scientific and technological Deliverables; analyse indicators; review scientific
progress reporting; ensure that Partners are following
the Research Roadmap; ensure compliance with open
data standards.
WP10.1 Foresight: conduct systematic surveys of the
technological and clinical potential of HBP research
in neuroscience, computing and medicine, and assess
their economic, social and ethical implications.
WP10.2 Conceptual and philosophical issues: assess
the conceptual and philosophical implications of HBP
research with special reference to concepts of personhood, consciousness, the relationship between the
brain, the mind and the environment, and simulation.
WP11.5 Unified Portal: design, implement and deploy
the HBP Unified Portal, providing a single point of
access to all HBP platforms; provide interfaces for a
project management platform.
WP10.3 Public dialogue and engagement: create a
constructive dialogue with private and public stakeholders and with the general public; create and
manage Online Deliberations, Citizens’ Forums and
Stakeholder/Expert Forums.
WP11.6 Web services and IT: deploy, support, maintain and manage web and other IT services required
for the smooth running of the project; create and
maintain an interactive map of HBP; support projectwide knowledge management and data integration.
WP10.4 Researcher awareness: systematically investigate researcher perceptions of ethical and social
issues arising from HBP research; organise special
sessions in summer schools and workshops to raise
awareness (especially among young scientists) and
to involve researchers in ethically important decisions.
WP11.7 Communication and dissemination: implement an HBP communications strategy; create a
brand identity and communications tools; communicate to internal, external and scientific audiences;
organise a Museums Programme; conduct media relations; seek potential sponsors; assist the Partners to
develop country-specific communication strategies.
WP10.5 Governance and regulation: support HBP
decision-making on issues with significant ethical,
legal or social implications; manage an independent
secretariat for the ELSA (see paragraph 3.1.10.2) and
the REC (see paragraph 3.1.10.3).
WP11.8 Education and knowledge management:
coordinate a programme of transdisciplinary education for young scientists working on the frontiers
between neuroscience, ICT and medicine; exploit
the data, tools and other capabilities provided by
the Platforms and the unique range of expertise of
HBP researchers and platform users to dynamically
create educational solutions to address emerging
challenges; organise workshops and summer schools;
develop and implement a strategy to integrate and
disseminate knowledge generated by the project.
WP10.6 Scientific coordination: Coordinate scientific
activities within the SP; coordinate with other SPs,
Partnering Projects and international collaborations;
coordinate quality assurance, organisation of meetings and workshops and reporting.
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Excellence
WP11.9 Coordination of Partnering Projects and collaborations: promote Partnering Projects and support their
integration with the SPs; liaise with funding agencies
and other sources of funding; coordinate HBP collaborations with other national, European and international
initiatives; raise awareness of the HBP and its potential
among key stakeholders in Europe and elsewhere.
Criteria for participation in the Core Project:
Criteria for Core Projects
Research & development critical for building and operating
the HBP Platforms
WP11.10 IP, tech transfer and innovation management: create and maintain science-to-market conduits; coordinate and exploit IP; develop sustainable
Service Level Agreements; drive the HBP innovation
strategy; support the setup of European innovation
hubs; develop links with innovation support mechanisms in Europe and beyond; help create a culture of
innovation throughout the HBP and coordinate entrepreneurship training for HBP scientists.
Research & development that is unique and unlikely to receive
funding from other sources
Research & development whose primary goal is to translate
cutting-edge science into novel technologies and services for
the scientific community
Research that requires tight integration with work by other
researchers and teams across multiple disciplines
Coordination of the Flagship initiative
WP11.11 Strategic development and coordination:
design and implement strategies to further develop
the HBP and make it sustainable; coordinate all HBP
Flagship Initiative activities ensuring implementation
of the HBP and alignment with strategic objectives;
coordinate Core Project activities; manage SP11; brief
the Executive Committee and involve it appropriate
in decision making and implementation; report on
SP11 activities.
Partnering Projects (PPs) will develop new ideas,
approaches and technologies, proposed spontaneously
by independent research groups. Partnering Projects will
add novel capabilities to the Platforms and use the Platforms to address questions far beyond the capabilities of
any individual laboratory.
Criteria for participation in the Partnering Projects:
1.0.5 Why Some Objectives are in
FPA and Others are Outside
(Core and Partnering Projects)
Criteria for Partnering Projects
As described in paragraph 1.0.1, the Flagship Initiative will
consist of a Core Project and Partnering Projects, each
of which will carry out specific Actions in the Action Plan.
Research that provides capabilities to the Platforms, beyond
those developed by the Core Project
The Core Project (CP) will be responsible for executing a
detailed plan of tightly coordinated research and development, critical to building and operating the HBP Platforms and for the overall governance and coordination of
the Flagship Initiative. In addition to research, addressing fundamental challenges in neuroscience, computing and medicine, the responsibilities of the CP include
scientific coordination, communication and dissemination, education, promotion of innovation and industry
collaboration, citizen engagement, and other activities to promote and enforce the Consortium’s policy of
Responsible Research Innovation. The specific Actions
assigned to the CP are listed in paragraph 1.0.4.
Scientifically excellent research that can only be performed
using the HBP Platforms
Research that has won or is likely to win funding through
the competititve selection processes, operated by regional,
national, European, International, and other sources of funding
Research whose primary goal is to achieve breakthroughs in
specific areas of neuroscience, computing or medicine
Research that can be performed autonomously by
independent reserchers, research groups or consortia
The Actions assigned to the PPs in the Research Roadmap
are listed below.
1.0.5.1 SP1: Targeted Mapping of the Mouse Brain
WP1.7 Physiological Data: collect targeted physiological data going beyond the data sets collected
in the Core Project; candidate data sets include
data on whole brain dynamics neuroendocrinology
and neuroimmunology, metabolism and energetics,
microcircuit dynamics and information processing,
the physiology of neurons and synapses, receptor
and channel biophysics, and gene expression.
WP1.8 From Genes to Cognition: Perform experimental and informatics studies on the link between genes
and cognition and the impact of normal genetic vari-
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Excellence
WP3.8 Novel brain-Inspired concept for information processing: Develop HPC architectures inspired
by theoretical and experimental insights into the structure and function of the brain (joint work package with
WP6 and WP7).
ations and mutations; develop links to human brain
disease signatures established in SP7 and to human
work in SP2.
WP1.9 Functional Architectures of Cognition: Collect
data on functional architectures of cognition in mouse;
possible themes include multi-modal perception and
action, motivation, reward and decision-making, synaptic plasticity, learning, memory and goal-oriented
behaviour, representations of space time and quality
in planning and navigation, and the architecture of
gene-behaviour-environment interactions.
WP3.9 Disease Modelling: Develop theory-driven
models of disease from the biological signatures of
disease and the disease classifications identified by
researchers using the Medical Informatics Platform
(joint work package with SP5 and SP7).
1.0.5.4 SP4: Neuroinformatics
WP1.10 Comparative Studies: Perform research comparing structural and physiological data in mouse, humans
and other animals (joint work package with SP2).
WP4.7 Methods and tools: develop methods and
tools expanding the functionality of the Neuroinformatics Platform and integrate them into the Platform;
possible tools include but are not limited to tools and
1.0.5.2 SP2: Targeted Mapping of the Human Brain
WP2.7 Physiological Data: Collect targeted physiological data going beyond the data sets collected in
the Core Project; possible data sets include data
on whole brain dynamics neuroendocrinology and
neuroimmunology, metabolism and energetics,
the physiology of neurons and synapses, receptor
and channel biophysics, and gene expression.
methods for the analysis of large volumes of structural brain data (e.g., image stacks) and for the analysis of large volumes of functional data.
WP4.8 Sensory organs, the spinal cord and the
peripheral nervous system: expand the mouse and
the human brain atlases to accommodate data on
sensory organs, the spinal cord and the peripheral
nervous system in mouse and in humans; generate
initial data sets to populate the expanded atlases.
WP2.8 From Genes to Cognition: Perform experimental and informatics studies on the link between
genes and cognition and the impact of normal
genetic variations and mutations; develop links to
human brain disease signatures established in SP7
and to human-related work in SP1.
WP4.9 Atlases for other species: create multi-level
atlases for the brains of species not covered by the
HBP Mouse Brain and Human Brain Atlases on the
Neuroinformatics Platform; integrate the atlases
with the HBP Mouse Brain and Human Brain atlases,
enabling cross-species comparisons.
WP2.9 Functional Architectures of Cognition: Collect
data on functional architectures of cognition in
humans; possible themes include but are not limited
to multi-modal perception and action; motivation,
reward and decision making; synaptic plasticity,
learning, memory and goal-oriented behaviour; representations of space time and quality in planning
and navigation; the architecture of gene-behaviourenvironment interactions.
1.0.5.5 SP5: Brain Simulation
WP5.9 Tools, methods and workflows: develop tools,
methods and workflows expanding the functional capabilities of the Brain Simulation Platform; possible topics
include new techniques for multi-scale simulation, new
simulation engines and enhancements to existing engines,
new tools for data analysis and visualisation, and virtual
instruments (in silico molecular imaging, large-scale synaptic imaging, whole-brain in silico electrical recording,
in silico optogenetics, virtual MRI, DTI, and PET).
WP2.10 Comparative Studies: Perform research comparing structural and physiological data in mouse,
humans, non-human primates and other animals (joint
work package with SP1).
WP5.10 Brain reconstruction: develop high-fidelity
reconstructions of specific regions of the mouse or
human brain, or of specific levels of biological organisation not fully covered by HBP models; create highfidelity reconstructions of the brains of species not
covered by the HBP; create data-driven models of
sensory organs or the spinal cord.
1.0.5.3SP3: Theoretical and Mathematical
Foundations of Neuroscience
WP3.7 Model Development: Develop theory-driven
models of brain function suitable for implementation
on the Brain Simulation, Neuromorphic Computing
or Neurorobotics Platforms; use the Platforms for in
silico experiments validating and refining the models;
possible themes include but will not be restricted
to perception-action, surprise, novelty, multi-sensory
integration, decision making, goal-oriented behaviour,
reward, wakefulness, sleep, dreams and the wake-sleep
cycle, learning and memory, working memory, declarative memory, skills and habits, symbols and language
(development in conjunction with SP8 and SP9).
WP5.11 In silico neuroscience: use the Brain Simulation Platform (where necessary, in combination with
the Neuromorphic Computing or Neurorobotics Platforms) for in silico experiments in basic neuroscience,
cognition and behaviour.
WP5.12 Disease and drug simulation: use biological
signatures of disease from the Medical Informatics
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Excellence
Platform and simulation capabilities from the Brain
Simulation Platform to gain new clinical insight; possible themes include mechanisms of disease causation, mechanisms of action of known therapeutic
agents, and screening of drug candidates (joint work
package with SP7).
bilities from the Brain Simulation Platform to gain new
clinical insights; possible themes for research mechanisms of disease causation, mechanisms of action
of known therapeutic agents, and screening of drug
candidates (development in conjunction with SP5).
WP7.9 Services for personalised medicine: use the
capabilities of the Medical Informatics Platform to
develop and trial new services for personalised medicine: personalised diagnosis and prognosis, personalised treatment, etc.
WP5.13 Other Applications of Brain Simulation:
Develop other applications of brain simulation of
commercial and/or clinical value; examples include
fast prototyping of new experimental methods; fast
prototyping of neuroprosthetic devices, etc.
WP7.10 Methods and tools: develop and integrate
new tools and methods contributing to the capabilities of the Medical Informatics Platform; possible
tools and methods include integrated machine learning, data mining, and data intensive analysis for the
identification of clusters in large volume of data.
1.0.5.6 SP6: High Performance Computing
WP6.8 Technologies and architectures: develop
supercomputing technologies and architectures
meeting the specific requirements of brain simulation and expanding the capabilities of the High Performance Computing Platform; possible themes for
research include but are not limited to novel solutions for multi-scale simulation, novel solutions for
resiliency, fault tolerance and self repair; new hardware/software solutions for memory and I/O hierarchies, new interconnect architectures; joint work with
WP6.9 for HW/SW co-design.
1.0.5.8 SP8: Neuromorphic Computing
WP8.7 Applications for neuromorphic computing: use the NM-PM and NM-MC systems to demonstrate applications of Neuromorphic Computing
Systems; potential application areas include pattern
detection in spatio-temporal data streams, finding
causal relations in big data, data mining, temporal
sequence learning, approximate computing; feed
back the results for further development and feature
upgrades of the Neuromorphic Platform systems.
WP6.9 Software, algorithms and numerical methods:
develop software, algorithms and numerical methods
that meet the specific requirements of brain simulation and expand the capabilities of the High Performance Computing Platform; joint work with WP 6.8
for HW/SW co-design.
WP8.8 Portable hardware systems for neuromorphic
computing: use the NM-PM and NM-MC systems to
derive specialised and resource efficient neuromorphic circuit architectures for custom, special purpose
low-power, compact, low-cost hardware implementations as neuromorphic cores or complete stand-alone
systems; application areas include robotics, automotive,
manufacturing, telecommunication.
WP6.10 Hybrid HPC-neuromorphic architectures:
develop conceptual designs for hybrid HPC-neuromorphic computing systems for energy efficient, accelerated
simulations in neuroscience; demonstrate feasibility using
the Neuromorphic Computing Platform and the HBP
Platform; possible architectures include hybrid systems
linked across networks, on-board hybrids, on-chip hybrids
(Neuromorphic cores) (joint work package with SP8).
WP8.9 Devices for neuromorphic computing: develop
and evaluate new device technologies for neuromorphic computing; simulate, construct and evaluate
small- scale demonstrator systems; evaluate integration into the HBP Neuromorphic Platform systems;
possible themes for development work include resistive memories, magnetic memories, organic devices,
3D Integration, and distributed powering.
WP6.11 Novel brain-inspired concepts for information processing: develop HPC concepts inspired by
theoretical and experimental insights into the structure and function of the brain (joint work package
with SP3 and SP5).
1.0.5.7 SP7: Medical informatics
WP8.10 Hybrid HBP-neuromorphic architectures:
develop conceptual designs for hybrid HPC-neuromorphic computing systems for energy efficient,
accelerated simulations in neuroscience; demonstrate feasibility using the Neuromorphic Computing Platform and the HBP Platform; possible
architectures include hybrid systems linked across
networks, on-board hybrids, and on-chip hybrids
with Neuromorphic cores.
WP7.7 Clinical studies: use the data and analysis tools
provided by the Platforms to gain new insights into
the diagnosis, and classification of brain disorders
and to identify potential targets for treatment; studies
may include cluster analysis of data from retrospective studies, analysis of changes in disease signatures
at different stages in disease progression, re-analysis
of data from clinical trials and epidemiological studies
(e.g. measure impact of common genetic and/or environmental risk factors).
1.0.5.9 SP9: Neurorobotics
WP7.8 Disease and drug simulation: use data from
the Medical Informatics Platform and simulation capa-
WP9.10 Software, tools and technologies: develop
software, tools and technologies that expand the capa-
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bilities of the Neurorobotics Platform; possible themes
include the high-performance, high-fidelity simulation
technologies for robots and their environments.
careers show, in fact, that activities designed to promote
the advancement of women have no lasting effect
without major changes in management and organisational structures [3] [4, 5], [1],[6].
WP9.11 Embodied neurorobotics: perform research
on the physics and function of bodies (bones, muscles,
tissue), sensors (vision, audition, touch, balance) and
peripheral nervous system (spinal cord) and integrate
the results into the Neurorobotics Platform.
In view of these findings, and of the high profile of
FET Flagships in European research, the HBP will play
a pioneering role in achieving a well-balanced share
of male and female scientists at all hierarchic levels
within the Project, in particular among Subproject
and Work Package leaders and in the Project’s governing bodies.
WP9.12 Social neurorobotics: expand the Neurorobotics Platform to enable experiments involving interactions among multiple neurorobotic systems.
Since the original Project proposal was submitted, the
HBP has modified its leadership structure to include
more women (see Table 1). As a result, the proportion of
women amongst leaders and co-leaders in the Research
Board has increased from 15% at the beginning of the
Ramp-Up Phase to 20% today.
WP9.13 Neurorobotics as a tool for in silico neuroscience: use neurorobotic systems to perform in silico
experiments investigating fundamental issues in basic
neuroscience, cognition and behaviour.
WP9.14 Applications: use the Neurorobotics Platform to develop applications of commercial or clinical value; possible applications include applications
in manufacturing and mechanical engineering, personalised neuro-prosthetics and neuro-muscular controllers, robots for healthcare, robotic vehicles, and
robots for domestic applications.
Group
1.0.5.10 SP10: Ethics and Society
WP10.7 Ethical, conceptual and philosophical issues:
perform research on ethical, conceptual and philosophical issues, going beyond the research already
planned within the Core Project.
WP10.8 Public outreach: organise outreach activities
to promote public debate and participation on issues
related to HBP research.
Research Board
20.00%
Work Package Leaders
17.60%
Ethics Legal and Social Aspects
Committee
38.50%
Research Ethics Committee
50.00%
Table 1: Female participation in key HBP bodies and activities
The HBP has set annual targets for the proportion of
female researchers at different levels within the Project
(Ph.D. students, post docs, Work Package leaders, Subproject leaders and co-leaders, senior management positions) and for different Project activities (Core Project
research, Partnering Projects, research grants and studentships, management). In the case of senior researchers, the goal is to increase the proportion of female
Subproject and Work Package leaders by between 2%
and 3% every year, so that by the end, between 20% and
30% of these personnel are women.
1.0.6 Gender Balance in HBP Recruitment and
Management
Research in the Human Brain Project includes work in a
broad range of disciplines, from molecular and cellular
biology to mathematics, medicine, computer engineering,
robotics and even philosophy. These disciplines are characterised by widely differing rates of female participation,
often with large variations between countries. Nonetheless
two tendencies stand out. First, in all major disciplinary
areas, except engineering, manufacturing and construction, at least 40% of new Ph.Ds. in the EU-27 countries are
female (data for 2006). Second, in these same countries,
the proportion of women decreases with each successive
level from students to researchers to professors.
Annual targets for the
proportion of female researchers
at different levels
A recent EU study found that in 2010 just 32% of scientists and engineers in the EU-27 were women. Only
in three countries - Iceland (50%), Bulgaria (50%), and
Poland (53%) - did the proportion of female scientists
and engineers reach 50% or higher. The same study
showed a worrying drop in women’s share of higher
ranking positions: “from 35% of female Ph.D. graduates,
the proportion of women drops to 32% in grade C academic staff, 23% in grade B and just 11% in grade A” [1]
For the Project’s governing bodies, (e.g., the Governing Board, the Science Advisory Board, the Presidents’
Advisory Council, the Ethical Legal and Social Aspects
Committee, the Research Ethics Committee) the goal is that
each body should include at least 10% of women from the
start of the Project and that by the end of the Project this
proportion should rise to at least 30%. Additional Actions
to promote equal opportunities include the following:
This inequality is “largely due to employer policies and/
or strategies” [2] Many studies on female professional
Percentage led
by women
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Excellence
1.0.7 Gender Balance in HBP Research
Management Culture: HBP senior management will
follow a systematic top-down approach, defining a
comprehensive mission statement on gender equality
and organising a workshop to sensitise SP/WP/TaskLeaders to gender and diversity issues.
1.0.7.1 Overview
As pointed out in a recent European Commission publication,
“Sex and gender can influence all stages of
research or development processes, from strategic considerations for establishing priorities and
building theory to more routine tasks of formulating questions, designing methodologies, and
interpreting data” [7].
Promoting Women’s Careers: The HBP Education
Programme will implement a special coaching and
mentoring programme for young female scientists,
and especially for female scientists in Task Leader or
Work Package Leader positions.
For instance, many experiments in behavioural neuroscience avoid problems related to the oestrogen cycle by
using only male rodents, but the results obtained may
only apply to males. Similarly, drugs affecting the brain
can act differently in males and females due to differences in brain microstructure and in the hormonal and
biochemical environment.
The programme will provide similar training to all participants—regardless of their country, culture or institution of origin—strengthening their orientation towards
career development, improving their communicative capabilities, helping them build a career oriented
network and preparing them for senior positions in the
HBP and elsewhere. Implementation activities include
HBP workshops for female scientists, and dedicated
sections in the HBP website.
Failure to consider these and other gender differences
in experimental subjects can lead to unreliable results.
It is thus imperative that researchers in basic and clinical include subjects of both genders in their studies and
take gender into account in their analyses.
Reconciling Professional and Family Life: Women
and men pursuing a scientific career face immense
pressures due to short-term contracts, high mobility
and long working hours. To alleviate these pressures,
the HBP Partners will support flexibility in working
hours and places of work, facilitating part-time work
and time-sharing for both genders. Additionally, the
HBP PIs will cooperate with their institutions dual
career centres, where they exist, and make their best
effort to ensure their staff have adequate access to
advice on child-care (family services), extensions of
their contracts to accommodate parenthood, and
training in self-management and work-life balance.
Regular information about HBP Actions and success
stories in this area will be distributed via the Project’s
internal newsletter.
HBP research will pay special attention to sex and
gender in SP1: Targeted Mapping of the Mouse Brain,
SP2: Targeted Mapping of the Human Brain and SP7:
Medical Informatics.
1.0.7.2 SP1 Targeted Mapping of the Mouse Brain
Wherever possible, SP1 research will generate, assemble, and analyse data from balanced selections of male
and female mice. In some situations, where required by
established protocols or where only male mice are available, only male samples will be studied. SP1 Partners will
record the gender of individual animals used in experiments, allowing for separate analysis of data on genetics, proteomics, cell morphologies and behaviour in male
and female animals. The recording of gender data will
make it easier to align mouse data with human data from
mixed populations.
Talent Management: The HBP Partners will promote
the personal development of staff members, support
equal opportunities and help members of staff to reconcile their professional and family lives by:
1.0.7.3 SP2 Targeted Mapping of the Human Brain
Sex and gender differences in brain architecture and
cognition represent a fundamental issue in neuroscience,
with sex differences making a significant contribution
to inter-subject variability, in particular on the systemic
level. The relationship of these differences to cognitive
function and behaviour is a research question that needs
to be formulated in different ways according to the
level of brain organisation under consideration and the
methods used in the research.
Providing guidelines for senior scientists on how to
promote gender equality and diversity among their staff
Conducting regular interviews with staff of both genders
about their professional and personal goals
Collecting and monitoring data concerning the gender
composition of HBP staff
SP2 will not stratify all its data for gender. For example,
the multi-modal brain atlas will sometimes refer to individual brains (which are either male or female); in other
cases it will use results by averaging hundreds of MR data
sets for human brains. In this way, inter-subject variability
will be considered as a facet of human brain organisation, in the same way as age and handedness. The atlas is
flexible enough to be extended if specific scientific questions require other templates in the future.
Keeping senior scientists informed of gender
developments via the HBP internal newsletter and a
yearly workshop (peoples’ day).
In addition to the above activities, the HBP will work
with external organisations with a proven track record
in promoting the role of women in science and business
(e.g., the independent non-profit European Academy for
Women in Politics and Business).
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Excellence
All SP2 experiments will record metadata on inter-subject variability, including sex. All single cell experiments
on human brain tissue from neurosurgery will test for
dependence on patient gender and age. Given the small
number of subjects studies (N=12), we do not expect to
find significant sex differences All morphometric data
from post mortem studies will be tested for sex differences to identify sources of variation in the structure
and function. Since sample sizes will be small, we expect
that few if any differences will be statistically significant.
Finally, we will adapt and apply methods developed by
HBP Partners in their previous research. These methods
have already demonstrated the existence of significant
sex differences in the Broca region [8], the motor cortex
[9], the extrastriate visual cortex [10], and other systems.
Epidemiological studies show that there are large gender
imbalances in the prevalence of many neurological and
psychiatric diseases. For example, diagnoses of Mild
Cognitive Impairment are more frequent for males, while
diagnoses of Alzheimer’s disease are more frequent in
the female population. Gender differences remain largely
unexplained at the biological level. Including gender and
sex will help us to determine different risk factors and
discover different pathways. The same reasoning applies
to the variable “age”.
1.1 Scientific and Technological
Quality of Individual Partners and
of the Consortium as a Whole in
View of The Objectives and Roadmap
of the Flagship
1.0.7.4 SP7 Medical Informatics
SP7 will build models of brain diseases. To be useful, the
models need to be accurate, represent the whole human
population, and explain important sources of inter-individual differences. In this context, sex and gender will be
included in the analyses. Variables corresponding to sex
and gender are used in two different circumstances.
1.1.1 Role and Expertise of Individual Partners
Information on the contribution of individual Partners
to the Science and Technologies objectives and Actions
listed in paragraph 1.0 is provided in Appendix 1 Chapter 4.
1.1.2 International Involvement in the HBP
First, they are included in the models as a covariate.
Global covariates (e.g., sex, total-intracranial volume,
head size) make it possible to measure the signifcance of the biological variables (e.g., local grey-matter
volume) over and above the global effects captured by
the covariates.
The idea of strengthening international collaboration
in science has always been central to the HBP. The
Operational Phase of the HBP will be shaped by the
FPA, which is a new and untried European Commission instrument. It has therefore been agreed that international partners (based outside Europe) will not be
included in the FPA at this stage. However, However
HBP policy on openness and flexibility (see paragraph
3.2) provides that new Partners may be admitted to
the Core Project (see paragraph 1.0.2) each time a new
Specific Grant Agreement (see paragraph 3.1.1.1) is for-
Second, gender and sex will also be considered as variables of interest. It is important to consider sex and
gender not per se, but their interactions with the
different biomarkers of the diseases.
AT 4.5%
IL 4.5%
SE 4.5%
IT 5.6%
GR 3.4%
CH 6.7%
NL 3.4%
FR 8.9%
PT 2.2 %
NO 2.2%
Other 13.15%
ES 8.9%
BE 1.1%
HU 2.2%
SI 1.1%
TR 1.1%
UK 10.12%
FI 2.2%
DE 17.20%
DK 2.2%
Figure 2: Distribution of partner institutions by country
15
Excellence
Country
SP1
SP2
SP3
SP4
SP5
Austria
1
Belgium
1
SP6
SP7
SP8
SP9
1
1
Denmark
1
Finland
2
France
1
2
3
Germany
2
2
1
Greece
Hungary
6
2
1
1
2
1
1
5
1
1
6
1
1
1
2
2
1
1
1
1
1
1
2
1
2
1
2
3
1
1
3
2
2
2
Sweden
1
Switzerland
2
2
1
1
1
2
2
2
Slovenia
1
3
2
3
1
1
1
3
1
1
Turkey
United Kingdom
1
1
1
2
Norway
Spain
2
1
2
2
2
Netherlands
Portugal
2
SP11
2
Israel
Italy
2
2
SP10
2
2
1
4
1
3
3
Table 2: Number of beneficiaries involved in each Subproject by country
mulated and there is no reason why these should not
include international partners. International entities are
also eligible to propose HBP Partnering Projects (see
paragraph 1.0.2) and will take part in the international
collaborations envisaged by the HBP (see 2.4). The HBP
is currently working with other large Brain Initiatives in
Australia, China, Japan. and the USA, to create a Global
Network of Brain Initiatives. The HBP is also discussing
cooperation in disease classification and intellectual
property with WHO and WIPO.
Figure 1 and Table 2 provide a breakdown of the partners by
country and their distribution across Subprojects. A complete
list of the Partners can be found in the table at the beginning
of this document. Further details on these partners such as
their role in the Research Roadmap and the resources they
bring to the Project, can be found in Chapter 4.
The majority of partners are universities, public research
organisations or non-profit organisations. At the moment,
there are no SMEs or large enterprises in the FPA Consortium. These organizations will participate in the Flagship Initiative primarily through the Partnering Projects.
1.1.3 The Whole Consortium
1.1.3.1 Complementarity and Balance
The HBP Consortium for the Ramp-Up Phase currently
comprises 112 organisations in 24 countries. During the
writing of the FPA proposal, the Consortium membership was revised to include only those participants who
are expected to contribute to the core project for the
whole duration of the HBP Flagship Initiative. As a result,
the FPA Consortium now comprises 85 organisations in
19 countries. Given the short time available for the preparation of the FPA and the relative novelty of the instrument, and potential legal issues related to the signature
of the FPA, non-EU or AS countries such as Canada, the
United States, Japan and China were not included for
the time being. Once the FPA has been approved, the
ten partners from these countries will probably be reinvited to join the agreement. This will occur before the
start of the first SGA.
The Partners provide the knowledge and competencies necessary to cover the Project’s three main areas
of research, namely neuroscience and computing and
medicine. Within each discipline, different groups
provide different, complementary expertise. In neuroscience, the Project has a large number of groups working
in mouse and human neuroscience; this knowledge is
complemented by a similar number of groups working
on theoretical modelling. The Project brings together different kinds of complementary knowledge, from leading
groups in high performance computing to experts in
massive data management, neuromorphic computing
(where the Project covers the complementary “physical
model” and “multicore” approaches) and neurorobotics.
Of course there are overlaps; for instance, competences
in brain simulation overlap with competencies in basic
and theoretical neuroscience, and high performance
computing. These overlaps enhance the integration of
the Consortium. In medical informatics, the HBP brings
together groups actively engaged in the analysis of
imaging data with more technical groups working in the
areas of distributed querying, and advanced data analy-
All countries whose partners participated in the Ramp-Up
phase will also participate in the FPA, with the single
exception of Cyprus that is no longer represented in the
Core Project.
16
Excellence
sis. Brain simulation groups aim to integrate these two
very different kinds of knowledge in unifying models.
1.2 Quality and Relevant Experience
of the Individual Partners and the
Consortium as a Whole with Regard to
Non-scientific Aspects
Finally, the HBP has brought together a strong team in
ethics and society, including sociologists, philosophers,
and historians, practicing neuroscientists and researchers
with practical experience in medical ethics.
1.2.1 Role and Expertise of Individual
Partners
Considered as a whole, the team appears to have an
extremely good balance, which will be further enhanced
through the Partnering Projects.
Information on the contribution of individual Partners to the
non-scientific objectives and Actions listed in section 1.0 is
provided in Chapter 4.
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Excellence
IMPACT
2. IMPACT
2.1 Contribution to Expected Impacts
Listed in the Work Programme
responsible for specific Actions have been assigned.
These Partners will be eligible for funding under the FPA.
Before the beginning of each new phase in the CP, the
Roadmap will be adapted to take account of stakeholder
priorities and of scientific and technological advances
inside and outside the Flagship Initiative. This will be the
responsibility of the HBP Research Board (see paragraph
3.1.6). In some cases, the Research Board may initiate
new lines of research or abandon research that duplicates work outside the HBP.
2.1.1 Describe Formalised Commitment of
Partners to Realise Action Plan of FPA
2.1.1.1 Signatories of the FPA – Participants in Core Project
The FPA represents a formal commitment of the signatories to support the objectives of the HBP Flagship Initiative and those of the Core Project, and to contribute
personnel and knowledge in the areas assigned to them
in the Research Roadmap. These commitments will be
further detailed in the Specific Grant Agreement signed
at the beginning of each phase in the Core Project
(approximately every two years).
Each revision of the Research Roadmap will specify which
partners will take part in the next phase of the CP. These
will include signatories of the FPA, Partners from PPs that
have worked successfully in the preceding phase of the
Project, and completely new Partners. New partners will
be invited to join the FPA. In this way, the FPA will always
include the best research talent available.
In addition to these commitments, many Partners will
make additional financial and in-kind contributions,
directly or with the support of national, EU, and other
funding sources. Given the structure of these funding
instruments most Partners can only make commitments for a limited period of time. The overall value of
these contributions amounts to EUR 497 million and is
expected to increase as the Project proceeds.
2.1.2.3 A Stable Set of Relationships with the
European Commission, the Member States, other
Stakeholders and the General Public
The HBP has stable long-term relationships with the
European Commission, the Member States, industry, and
other stakeholder organisations as well as with regional,
national, European and International initiatives in relevant areas of research and development.
Existing and future commitments will be formalised in
the form of Core Commitment Agreements signed by
the Partner, and the HBP Foundation (see paragraph
3.1.12). The value of Partners’ effective commitments will
be subject to audit if and when necessary.
At the institutional level, the exchange of information
with the Member States and the European Commission
will be coordinated through the Flagship Governance
Forum (see paragraph3.1.2).
2.1.2 Actions to Create a Stable and
Structured Environment and to Ensure the
Continuity and Coherence of the Initiative
2.1.2.1 Stable Governance and Management
At the implementation level, the HBP’s Relations Office,
formerly known as the European Research Programme
Office, is already working to build long-term relationships with the European Commission, National Funding
Agencies, large-scale European and international programmes, and the Consortium Partners. The next phase
of the Project will see a strengthening and expansion of
this role.
The HBP Research Board (see paragraph 3.1.6), together
with its Executive Committee (paragraph 3.1.7), Subproject Committees (paragraph 3.1.8), advisory bodies (paragraph 3.1.10) and the HBP’s permanent management
structures will provide continuity with the Ramp-Up
Phase. The Flagship Governance Forum – a new body
- (paragraph 3.1.2) will give a voice to national funding
agencies and other stakeholders who are not represented in the HBP’s current governing bodies. The Framework Partnership Board (paragraph 3.1.3) will provide
a consultative mechanism between the HBP and the
European Commission. The HBP Foundation – whose
role is expected to expand over the duration of the
Project – will give the HBP a legal personality, allowing
it to establish formal agreements with organisations and
initiatives outside the HBP and providing a vehicle for
additional fund-raising.
The Project will engage the scientific community through
normal channels of scientific communication (publications in scientific journals, participation in conferences
and workshops) but also through new channels that
exploit the potential of the HBP Platforms and of “dissemination systems” created within the Project (see
paragraph 2.2.2.2).
The Initiative will also initiate a broad range of activities
to engage the general public. These include a large-scale
Museums Programme, involving science museums in
many different countries (see paragraph 2.2.6), a largescale education programme addressing Ph.D. students
and post-docs in the CP, the PPs and outside the HBP
Flagship Initiative (see paragraph 2.2.5), as well as public
engagement activities organised by the HBP Ethics and
Society Programme (see paragraph 2.2.2.3).
2.1.2.2 A Stable Model for Maintaining and Revising the
Research Roadmap and the Membership of the FPA
Appendix 1 provides a detailed Research Roadmap for
the Flagship Initiative, identifying which Actions will
be carried out in the CP, and which in the PPs. This
document presents an Action Plan for achieving the
objectives defined in the Roadmap, and identifies an
initial set of Partners (the initial signatories of the FPA)
20
Impact
2.1.2.4 A Stable Model for Funding and Financial
Sustainability
An important goal for the Flagship Initiative is to steadily
increase the proportion of HBP funding from outside
the FET Flagship Programme and to ensure the longterm financial sustainability of the HBP after the end of
Horizon 2020.
The main sources of extra-Flagship funding are expected
to be other EU programmes (other parts of Horizon
2020 and successor programmes, EU structural funds
etc.), and research programmes funded by the Member
States. These will be supplemented by private donations,
commercial sponsorship, and revenues from the sale of
commercial services based on the HBP Platforms, and
licensing revenues. Possible services include the use of
the Brain Simulation Platform to facilitate drug discovery
and screening by the pharmaceutical industry, the sale of
data mining services and services for personalised medicine based on the Medical Informatics Platform, and use
of the Neuromorphic Computing and the Neurorobotics
Platforms to develop commercial products and services.
At the institutional level, the Flagship Governance Forum
(see paragraph 3.1.2) will enable the HBP to maintain a
continuous dialogue with representatives of potential
funding agencies. Additional funding will be channelled
through the HBP Foundation (see paragraph 3.1.12).
Area
Impact
Neuroscience
The HBP will give Europe a key
role in integrating neuroscience
data from research around the
world, multiplying the value of
billions of dollars of research
investment. Europe will build
the first ever high-fidelity
reconstructions of the mouse
brain and the human brain,
leading the world in in silico
neuroscience.
Computing
Europe will lead the development
of interactive supercomputing
and multi-scale simulation at the
exascale and beyond, meeting
the needs of different domains of
science, medicine and engineering
and of many branches of European
industry.
Europe will also lead development
of neuromorphic and neurorobotic
technologies, and the application
of knowledge about the brain to
High Performance Computing.
HBP capabilities will give
European industry a leading edge
in commercial applications of
these technologies.
Medicine
Services
Fundraising
Funding
Instruments
Industry
R&D
IP
Licensing
Innovation
Hubs
Table 3: Support for European leadership in key areas of 21st century
neuroscience, medicine and computing
2.1.3.2 A More Efficient ERA, Reducing Fragmentation and Optimising Complementarities between
European and National Programmes/Large-scale
Long-term European Partnerships
Figure 3: A stable model for funding and financial sustainability
The FPA provides a Roadmap for European research in
neuroscience and related areas of computing and medicine. The Partners in the FPA will contribute to the efforts
of the European Commission, the Member States, funding
agencies, industry and other stakeholders to coordinate
European and national research where it is related to the
goals defined in the Roadmap. In particular, the HBP will
work with the Commission and with national funding agencies to identify Partnering Projects with academic and
industrial Partners, which contribute to the HBP Platforms
and/or use the Platforms to perform research relevant to
the Project’s strategic goals. The HBP will also work with
other large-scale national and European research initiative
to maximise synergies and eliminate duplication of effort
within the HBP.
2.1.3 Other Impacts Mentioned in the Work
Programme
2.1.3.1 Provide European leadership
The Flagship Initiative will contribute to European leadership in key areas of science, technology and in clinical
and industrial applications, and will make an important
contribution to Europe’s competitive position and to
prospects for European growth and employment (see
Table 3; for a more detailed account, see the Research
Roadmap in Appendix 1).
The HBP will give Europe
leadership in federating clinical
data and in extracting new value
from clinical data already paid
for by National Health Services
and insurance companies. Europe
will lead the development of
new biologically grounded
classifications of disease, new
techniques of disease and drug
simulation and the extension
of personalised medicine to
disorders of the brain.
21
Impact
IMP2.2:The data collected in SP2 will provide the initial
scaffolding and validation tests for high fidelity
reconstructions and simulations of the human
brain, to be filled in with data from the HBP’s
European and International collaborations and
with predictions from reconstructions.
Institutionally, exchanges of views with the European
Commission and the Member States will be coordinated through the Flagship Governance Forum. The HBP
Research Board and its advisory bodies will ensure that
HBP processes related to the Partnering Projects are fair
and efficient, maximising their contribution to the HBP
Flagship Initiative and multiplying the value of European
investment in research.
IMP3.1: SP3 will generate new theoretical insights into
issues of key importance to neuroscience. These
include the link between different levels of biological organisation in the brain, the dynamics of
single neurons, plasticity mechanisms and their
impact, network dynamics and the mechanisms
underlying specific cognitive functions.
2.2 Measures to Maximise Impact
2.2.1 Impacts
2.2.1.1 Scientific Impacts
IMP1.1: The data collected in SP1 will make a vital contribution to the Multi-level Atlas of the Mouse Brain,
created in SP4.
IMP3.2:SP3 will implement theoretical insights in highlevel operational models, suitable for implementation in neuromorphic computing.
IMP1.2: The data collected in SP1 will enable the use
of gene expression data to predict features of
the brain that have not been measured experimentally, drastically reducing the number of
experiments necessary to build high fidelity
reconstructions of the brain.
IMP4.1:SP4 will facilitate neuroscience research, inside
and outside the HBP, by creating and maintaining
multi-level atlases of the mouse and human brain
and related atlasing tools, and by making them
available to European and international researchers through the HBP Neuroinformatics Platform.
IMP1.3: The data collected in SP1 will provide the initial
scaffolding and validation tests for high-fidelity
reconstructions and simulations of the mouse
IMP4.2:By creating a major public data resource, SP4
will strengthen Europe’s position as leader in
international neuroscience research.
IMP1.4: Comparative assessment of the data collected
in SP1 and SP2 will identify principles allowing
the use of mouse data to predict features of the
human brain for which experimental data are
not available.
IMP5.1: SP5 will establish high-fidelity reconstructions
and simulations of the brain as an essential tool
for integrating and curating multi-level experimental data.
IMP2.1: The data collected in SP2 will make a vital contribution to the Multi-level Atlas of the Human
Brain, created in SP4.
IMP5.2:SP5 will establish in silico experimentation as a
powerful method for addressing scientific questions that cannot be addressed experimentally.
Human Brain Project
N e u ro s c i e n ce
Computing
M e di c i n e
Figure 4: The Human Brain Project will amplify the value of global research investment
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Impact
IMP5.3:SP5 will establish brain simulation as an effective technique for understanding the cascades
of biological events implicated in psychiatric and
neurological diseases.
symptom and syndrome-based methods of diagnosis, this will represent a major step forward.
IMP7.4: “Biological signatures of disease”, identified in
SP4, will provide the data required for high fidelity reconstructions and simulations of disease
and possible treatments. Simulations will provide
a novel tool for understanding the causes of
brain disease, and simulating the effects of drug
candidates and other treatments.
IMP5.4:The Brain Simulation Platform will make it possible for the first time for academic researchers to
use reconstructions and simulations of the brain
in their research.
IMP5.5:SP5 will generate fundamental new insights into
the basic computational mechanisms underlying
human and animal cognition and behaviour.
IMP8.1: SP8 will establish designs and technologies for
large-scale neuromorphic devices and systems
with novel learning capabilities, low energy consumption and high reliability.
IMP5.6:Simplified reconstructions of the brain, generated by SP5, will serve as the basis for novel neuromorphic computing systems and devices.
IMP8.2:The Neuromorphic Computing Platform will
offer academic researchers and technology
developers the possibility to experiment with
and test state-of-the-art neuromorphic devices
and systems.
IMP5.7:SP5 will establish European scientific leadership in high-fidelity reconstructions and simulations of the brain and their technological and
clinical applications.
IMP9.1: SP9 will establish neurorobotics as a valid technique for exploring the causal relationships
between the multi-level structure of the brain,
cognition and behaviour.
IMP6.1: The High Performance Computing Platform will
provide neuroscientists and developers with
unprecedented access to sub-exascale and
exascale supercomputing capabilities.
IMP9.2:The HBP Neurorobotics Platform will make it
possible, for the first time, for researchers to
design and perform behavioural and cognitive
experiments using virtual robots connected to
HBP brain simulations and inhabiting virtual
experimental set-ups.
IMP6.2:SP6 will establish completely new technologies
for remote interactive simulation, visualisation
and analytics in high performance computing.
The new technologies will facilitate the adoption of simulation-based research methods in
neuroscience, the other life sciences and many
other domains.
IMP9.3:Research performed in SP9 will contribute to
creating a new multi-level understanding of the
relationships between brain structure, cognition
and behaviour.
IMP6.3:SP6 will establish the use of low-power neuromorphic technologies in High Performance Computing.
IMP7.1: SP7 will establish novel techniques and practices for the extraction of clinically valuable
information from large volumes of patient data,
exploiting the competitive advantage offered by
European National Health Systems, and establishing European leadership in a broad field of
medical research. The techniques established
by the Subproject will have a major impact on
medical research outside the HBP
IMP9.4: SP9 will create the first prototype applications
exploiting the novel cognitive and behavioural
capabilities of physical robots with neuromorphic controllers.
IMP10.1:SP10’s Foresight Lab will inform the debate on
the social and economic implications of HBP
research in neuroscience, medicine and computing, helping to allay groundless fears, while identifying areas of genuine concern.
IMP7.2: The Medical Informatics Platform will offer
researchers unprecedented access to large
volumes of anonymised patient data, creating new opportunities for basic and applied
research. The federation and querying methods
at the core of the Platform will make it possible
to leave personally sensitive data in the systems
and formats where they were originally stored,
without moving them to a central system. Tools
and methods supporting this strategy will have
a substantial impact on future medical research.
IMP10.2:SP10 will have an important impact on the
emerging academic debate around the conceptual and ethical implications of recent neuroscience research, in particular of brain simulation.
2.2.1.2 Social and Economic Impact
IMP7.5: Biologically grounded classifications of brain
disorders established by SP7 will allow more
effective diagnosis and treatment of psychiatric and neurological disease, and more effective
selection of participants in clinical trials.
IMP7.3: SP7 will contribute to establishing objective, biologically grounded classifications of neurological
and psychiatric disease. Compared to current
IMP7.6: Disease and drug simulations will facilitate the
development of drug and other treatments.
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Impact
IMP7.7: The data and tools made available by the Medical
Informatics Platform will facilitate the development of personalised treatments.
IMP6.5: Novel HPC hardware based on low-power neuromorphic technologies also has the potential to
generate licensing revenue.
IMP7.8: Better understanding, diagnosis and treatment
of brain disease will reduce costs for National
Health Services and insurance companies and
reduce the burden on patients and their families.
IMP7.9: SP7 will enable commercial services allowing clinicians and pharmaceutical researchers to query
and analyse anonymised patient data.
IMP7.10: SP7 will enable commercial services allowing clinicians and pharmaceutical researchers to simulate brain diseases and candidate treatments.
IMP8.3:The technologies and systems developed in SP8
have the potential to revolutionise computing
technology, enabling a very broad range of completely novel applications.
IMP7.11:SP7 will enable commercial services for personalised medicine (diagnosis, prognosis, selection
of optimal treatment).
IMP8.4: The services offered by the Neuromorphic Computing Platform will facilitate the emergence
of a rich ecosystem of academic and industrial
researchers, exploring and ultimately commercialising completely novel applications.
IMP8.6: SP8 has the potential to develop commercial
services offering industry researchers and technology developers the possibility to experiment
with and test applications based on state-ofthe-art neuromorphic devices and systems.
IMP8.5: SP8 will establish European leadership in an area of
research of vital importance to the European computing industry and to applications developers.
IMP8.7: Neuromorphic designs and technologies developed in SP8 have the potential to generate
licensing revenues from industry and applications developers.
IMP9.5:Physical robots with neuromorphic controllers
will have functional capabilities (e.g., learning,
effective handling of multimodal real-time input)
not present in current robotic technologies.
These capabilities will have a major impact over
a broad range of domains from manufacturing
to transport, healthcare, and the home.
IMP8.8: Neuromorphic technologies developed in SP
have the potential to generate commercially
valuable applications for manufacturing, transport, health care, and consumer electronics.
IMP10.3:SP10 will build public awareness of the economic
and social potential of HBP research and encourage public participation in priority setting and
decision-making. Public acceptance of and participation in the Project is a pre-condition for effective
commercial exploitation of Project results.
IMP9.6: The Neurorobotics Platform will enable the HBP
to realise commercial services offering industrial
researchers the possibility to experiment with
state-of-the-art neurorobotics setups.
IMP9.7: HBP neurorobotic technology has the potential
to generate significant licensing revenues.
2.2.1.3 Impacts with Innovation Potential
IMP5.8:The research conducted in SP5 will make it possible to create brain simulation services for commercial researchers in neuroscience, computing,
medicine, and pharmacology.
IMP9.8:Applications developed based on neurorobotic
technology have the potential to generate significant licensing revenues.
IMP5.9:Tools for brain reconstruction and simulation
have the potential to generate licensing revenues from commercial users in the pharmaceutical and computing industries.
IMP5.10:Models of specific diseases have the potential to
generate licensing revenues from users in clinical
and pharmacological research.
IMP5.11: Simplified brain models have the potential to
generate licensing revenues from technology
developers wishing to develop their own Neuromorphic Computing Systems.
IMP6.4: New technologies for remote interactive simulation, visualisation and analytics, generated by
SP6, have the potential to generate significant
licensing revenue.
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Impact
2.2.2 Outline Communications and
Dissemination Strategy
The content, which will include general information regarding global brain research, will also be used for the website.
A printed version will be produced for conferences.
2.2.2.1 Communications and Dissemination Strategy
Dissemination of the HBP’s activities is crucial to ensure
its visibility to the wider world. Care needs to be taken
to ensure balanced exposure of all Subprojects and Partners. Effective dissemination will require participation by
all HBP Partners, under the coordination of the central
communications team.
2.2.2.2 Dissemination to the Scientific Community
The ICT Platforms
The HBP’s most important channel for communicating with
the scientific community will be the Project’s ICT Platforms,
which will be accessible through a Unified Portal. Internal releases of the Platforms (the Neuroinformatics Platform, the Brain Simulation Platform, the High Performance
Computing Platform, the Medical Informatics Platform, the
Neuromorphic Computing Platform, the Neurorobotics Platform) will be available to selected scientists as of Month 18.
Fully operational versions of the Platforms will be released
in Month 30. From that date onwards, the Project will
operate the Platforms on a 24/7 basis, providing access as a
service to the Partnering Projects and the community, and
offering all necessary documentation, training and technical
support. Quality of service will be defined in Service Level
Descriptions (SLDs). Institutions and commercial companies wishing to guarantee access to a Platform for their
researchers will also be able to do so, in return for a fee.
The HBP’s achievements will be shared with stakeholders through a variety of channels, including scientific
publications and conferences, as well as the Internet and
social media. Outreach to the public will be via digital,
print, and electronic media, as well as science museum
exhibits. A monitoring process and other systems will be
implemented, maximising the efficiency and effectiveness of partner, industry and government information
collection and dissemination.
Media Dissemination and Monitoring
The HBP will utilise a journalist database to disseminate
HBP news to targeted journalists and a news monitoring
service to monitor relevant global news. The journalist
database will provide validated contact information, and
support for targeted press release distribution, journalists’
tweet tracking and topic/specialist segmentation. The
news monitoring service will monitor global news, so we
can validate and post relevant news to the HBP website
and to social networking environments (see below).
Data and Software
The Platforms will provide access to data and tools generated by the Project. Software for academic use will be
released under a variety of open source licenses.
Access to Neuromorphic Hardware
("Dissemination Systems")
The HBP has already created a small number of low-cost
USB-based neuromorphic computing systems and made
them available to students, researchers and developers.
The Project will continue with this policy in the future,
making the systems available without payment or for a
nominal fee. The HBP will use these systems to leverage
community talent and enthusiasm, funding awards and
competitions for novel applications.
Social Media
The HBP will develop content specifically for the social networking environment and maintain an on going dialogue
with targeted audiences via Twitter, Facebook, Instagram
Google+, and other emerging systems. YouTube will be
used to host videos describing the HBP and its component
Subprojects. A professional network for HBP personnel
and researchers outside the HBP will be constructed using
LinkedIn and similar online environments.
Publications and Conferences
Scientific publications: The HBP publishes its methods
and results in international journals and at leading international conferences. As much as possible, papers will
be published in Open Access Journals and/or deposited
on pre-print. In addition to publications in journals, the
Project will fund the publishing of a series of monographs
dedicated to different aspects of the Project (neuroscience, brain simulation, medical informatics, neuromorphic
computing, neurotechnologies, neurorobotics and ethics).
Public website
The HBP will develop and update its website to inform
the public about its activities and impact, creating an
authoritative information resource on the HBP’s collaborative brain research. A calendar will allow HBP Partners
to provide prominent information about their meetings,
conferences and special events.
HBP Communications Online Team Portal
The HBP will disseminate its communication and identity materials (visual guidelines, presentations, images
and videos, facts and figures) to its Partners through a
communication intranet portal hosted within the HBP
website. In addition, the portal will provide Partners with
a way to exchange material and request graphic design
and other services, along with a blog facility to discuss
communications and dissemination ideas.
Conferences: The HBP organises a series of annual conferences (two during the CP-CSA) dedicated to themes
relevant to the Project. Each includes speakers from
outside the HBP.
The World Wide Web and other online media: The HBP
website is being updated to include sections for scientists and technologists in specific disciplines. Other online
channels for scientific audiences include science blogs,
Facebook pages, as well as live streaming and videos of
events and lectures. Plans for the use of new media will be
regularly updated as technology evolves.
HBP News Magazine
A digital news magazine will be used to disseminate information about Partners activities and other relevant news
to internal audiences, stakeholders and decision makers.
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Impact
2.2.2.3Ethics and Society Programme (SP10)
The first four HBP Citizen Conventions (years 2, 4, 6, 8)
will include 5-10 European countries each. The final Convention (year 10) will include all 28 Member States. Each
Convention will address a theme of special interest at a
particular phase in the Project.
In addition to the HBP’s overall dissemination strategy,
the HBP Ethics and Society Programme (SP10) will
conduct a major public outreach programme based
on “Four Citizen Conventions”. These events, held each
second year, will use a range of public participation
methods fitting the specific purpose of each consultation. These methods include:
The broad theme of the Citizen Conventions will be science-society relations. In general, each convention will
address several different societal issues. For example, a
single Convention could examine the social, economic,
health, environment, consequences and benefits of a
specific science or technology result coming from an
HBP research group.
Interview meetings, in which 30 citizens in each meeting
receive introductory information, listen to presentations
from experts, discuss an issue, fill out a questionnaire and
participate in group interviews. The interviews are analysed with support from the quantitative data from the
questionnaire. Meetings will be held in different countries
with one or more meetings per country. This method
is especially good for providing insight into citizens'
informed reflections. The combination of qualitative and
quantitative data helps to avoid analytical artefacts.
The Citizen Conventions will be conducted in close collaboration with actors inside and outside the HBP Flagship Initiative. Feedback from experts and stakeholders
will help to secure quality and balance.
2.2.3 Potential of Consortium to Exploit Results
2.2.3.1 Opportunities for Exploitation
The FPA aims to “drive the translation of HBP research
results into technologies, products and services benefitting European citizens and European industry" (CPO10).
Revenue from HBP exploitation activities will help to guarantee the long-term financial sustainability of the Project.
The broad theme of Citizen
Conventions will be
science-society relations.
Citizen Hearings, in which 50-100 citizens express their
needs, concerns and hopes on a specific issue. Participants brainstorm the points they wish to make, cluster
them, prioritise the clusters, and examine highest-ranked
clusters in detail. This method can be used to provide
ideas on issues that the citizens think are important. The
issues discuss range from the implications of research
and innovation, to the policy domain.
Revenue flows are expected to come from the sale of
services provided through the HBP Platforms (e.g., brain
simulation and medical informatics services for pharmaceutical companies and neuromorphic computing
and neurorobotics services for technology developers);
licensing of HBP technology to companies wishing to
use them in their own products and services; and the
creation of joint ventures and spinoffs to develop specific technologies and applications.
Citizen Summits, which bring together 100-500 citizens.
Before the meeting, participants receive thorough and
balanced information material. The meeting agenda is
split into sessions lasting 1-1 1/2 hour each. Each session
begins with information on the theme of the session.
Participants vote on 4-8 predefined questions. Citizen
summits are very good at harvesting well thought-out
quantitative answers to policy questions.
Work during the Ramp-Up Phase has already identified
expected HBP research outcomes with strong innovation
potential (see paragraph 2.2.1.1).
2.2.3.2 Innovation Management
Innovation management will focus on market-oriented
exploitation of HBP research, enabling the transition of
technology to products and markets and the creation
of start-ups. The Innovation management process considers the whole value chain and views innovation as a
cycle with many closely interrelated activities including research, interaction with end users and designers,
assessment of market opportunities, IP management,
demonstrations and trials, industrialisation.
Consensus Conferences, which bring together a lay jury
and an expert panel. A lay jury of 12-16 citizens, with
backgrounds as diverse as possible, holds two preliminary meetings (one weekend per meeting), to define the
issues they wish to investigate within the main theme of
the conference and to identify the questions they wish
to answer. At the conference itself, which lasts two days,
the expert panel answers the questions in a thorough
dialogue with the jury. The jury then writes a consensus document containing its agreed assessments and
recommendations. This method is very good at getting
deep insight into the consensus rationality of diverse
groups of citizens.
The HBP defines its vision, approach and objectives for
innovation and IP management in an overreaching Innovation Management Strategy. Guidance in implementing
the strategy, including on IP management and engaging with industry, will be provided by the ITTC (see paragraph 3.1.10.4). The strategy will be implemented through
two Plans: the “HBP IP and Tech Transfer: Plan for use
of Results” and the “Industry Engagement Strategy and
Plan.” The two plans are mutually supportive and consider the needs and opportunities of a broad spectrum
of potential users and uses including research, commercial, investment, social, environmental, policy-making,
Other methods include Focus Groups (providing insight
into the thinking of special segments of society), Scenario Workshops (identifying preferred futures likely to
win support from citizens and stakeholders) and Future
Labs (turning criticism into constructive proposals).
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Impact
standard setting, and educational training in laying out
the path for market-oriented exploitation.
areas of work include translation of research results into
commercial products and services (e.g. in High Performance Computing, Medical Informatics, Neuromorphic
Computing and Neurorobotics), deployment of commercial services based on the HBP Platforms, maintenance
and support for the operation of the Platforms.
Innovation
management
strategy
Innovation &
Technology
Transfer
Committee
Guidance
Industry
Advisory
Board
IP and Tech
Transfer Plan
for use of
Results
Framework
Industry
engagement
strategy &
action plan
Business Landscape: HBP Management will identify new
industry partners through a multi-faceted effort that
includes reviews of the R&D strategies of HBP-relevant
industries, participation in industry summits and events,
dialogue with industry representatives, participation
in European industry networks, and continuous interactions with HBP industry partners. The main focus of
these efforts will be on SMEs.
Industry Collaborations: The HBP will work with industry
to promote the exploitation of HBP technologies. Industry
collaboration will take different forms, including exchanges
of know-how open innovation, joint project development,
joint research, training, sponsorship, etc. Industry will be
regularly informed of developments in HBP technology
and IP development through the Unified Portal and regular
newsletters. HBP-industry days will bring industry and HBP
research teams together to discuss and explore opportunities for collaboration and exploitation.
Figure 5: Framework for Innovation Management
The innovation management process in the HBP will use
a broad range of tools to:
Business Development: Based on the experience gained
during the Ramp-Up Phase, the HBP's business development effort will focus on identifying Partners and sources
of finance that will contribute funding to the HBP and
help to create a sustainable “lab to market” innovation
chain. The HBP will collaborate with industry partners,
national governments and others to create HBP Innovation Hubs in selected European countries. The Hubs will
have the mandate to license and exploit HBP technologies and intellectual property.
Capture and track ideas as they migrate from conception
into technologies
Inspire creative thinking and work within the HBP and
across the SPs
Track global technology trends
Understand industry needs and identify industry partners
Identify regions in Europe that could
collaboration partners for start-ups and hubs
become
Inspiring Innovation within the HBP: The HBP will promote
innovation and entrepreneurship through a range of
activities designed to motivate, inspire and empower
HBP teams involved in innovation. These activities include
training, facilitating collaboration between SPs, supporting the negotiation of licensing agreements, developing
industry collaborations, creating start-ups, and exploring novel funding opportunities. In particular, HBP Management will actively pursue the possibility of creating
start-up companies to operate the HBP Platforms and to
provide support to users.
Engage with visionaries and potential partners in industry,
government, non-governmental organization and others
Understand and exploit mechanisms for financing innovation in Europe
HBP Technology Portfolio: Over the lifetime of the Project,
the HBP will generate a range of IP with strong commercial potential. Technology and IP developments within
the HBP will be systematically tracked to ensure innovative ideas are identified early and can be tracked and
communicated as they mature. Ideas identified in this
way will be captured in the HBP Technology Portfolio.
The Portfolio will be developed and updated through
regular interactions with HBP SP managers, participation in SP meetings and workshops, reviews of quarterly
reports and other activities.
The required management structures and strategies
are being implemented during the Ramp-Up Phase
and will continue into the HBP Core Project.
IP Management: HBP structures responsible for IP management will establish clear and efficient procedures to
protect new results, protect results before dissemination,
and establish agreements on access rights and ownership.
Partnership and commercialisation activities are coordinated by an Innovation and Technology Transfer
Committee (ITTC) (see paragraph 3.1.10.4) made up
of the representatives of the ten Project Partners with
the largest budgets. The ITTC is already in operation via a Core Group composed of EPFL, CHUV and
Heidelberg University.
Spinoffs: HBP Management will encourage the creation of
spinoffs contributing to the SFO and the CPO. Candidate
An internal management team dedicated to partnership
and commercialisation supports the ITTC. The ITTC and
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Impact
the internal management team coordinate closely with
Innovation and Technology Teams in partner organisations (Partners in the CP, Partners in the PPs).
IP revenues, net of the costs of protection and enforcement and not on the number of patents generated by
the Project. At its discretion, HBP Management may
decide to make some research results e.g. software
tools for scientific users, available free of charge, via an
Open Source Licensing Agreement.
The Actions of the ITTC and the internal management
team will be supported by the HBP Foundation (see paragraph 3.1.12), which will receive a non-exclusive, non-obligatory mandate to commercialise innovations and patents
generated during the lifetime of the HBP, and, when
authorised by the Partners, to sign legally binding agreements on their behalf. The Foundation will be established
before the end of the Ramp-Up Phase.
National innovation hubs
The HBP Partnership and commercialisation team
and the National Innovation Hubs will provide a single
point of contact for companies and other organisations
wishing to access HBP technologies and know-how. The
HBP Foundation will represent the HBP Partners in commercial agreements with companies or other organisations wishing to exploit HBP IP.
The internal Management Team will build relationships with
industry, promote HBP services and technology to potential
industry partners, and scout actively for SMEs with an interest in HBP results. The team will work with these and other
stakeholders to set up dedicated National Innovation Hubs
that promote the take-up of HBP technology in specific
countries. The National Innovation Hubs will promote awareness of HBP technologies among local companies, especially
SMEs; act as a single point of contact for companies wishing
to exploit HBP IP; help local companies to access regional,
national and European funding for innovation activities; and
provide companies with access to relevant HBP expertise
(know-how in business planning, IP, science and technology,
European funding mechanisms, etc.).
As in the current phase of the Project, IP will be owned
by the organisations that produced it, and where local
law requires, by the individual scientists and developers responsible. The owners of HBP-generated IP maintain the right to exploit the IP as they see fit, providing
access to other HBP Partners in line with the requirements of the SGAs and the Consortium Agreements
for the Core Project and equivalent agreements for the
Partnering Projects.
Communal IP sharing scheme: As a highly collaborative
project, some of the HBP's non-patented IP (e.g. the
ICT Platforms) will be owned collectively by all of the
HBP Partners, including Partners in the Core Project and
Partners in the Partnering Projects.
The HBP’s IP strategy will be defined and monitored by
the ITTC as described in the previous paragraph.
2.2.5 Contributions to Education and Training
Future progress in neuroscience and medicine will be
increasingly dependent on ICT, and leadership of these
fields will be assumed by scientists who have an understanding of computer science and how it can be harnessed to help advance their own disciplines. However,
people with such trans-disciplinary education are still
rare and this scarcity is a constraint for the HBP and
more generally for European growth. The HBP therefore
includes an Education Programme (EP) that will:
The commercial revenues generated by communally owned
IP will be channeled through the Foundation and divided
amongst the Partners, following the scheme below:
Each HBP Partner will receive a share of the commercial
revenues based on its total financial contribution to the
HBP project, including its part of the EC funding, funding
from other sources, and its own funds.
Each Partner’s share will be proportional to its financial
contribution towards total HBP funding.
Provide young HBP scientists specialised in neuroscience,
medicine or ICT with an appropriate introductory education in the other disciplines they will need to participate in
transdisciplinary research inside and outside the project.
A fixed percentage of the initial commercial revenues will
be attributed to the HBP Foundation; the remainder will
be distributed amongst HBP Partners, according to the
criterion set out above.
Offer them complementary education in research ethics,
the societal impact of research, intellectual property
rights (IPRs), and the translation and exploitation of
research results.
Any funding that is not anticipated in the FPA Financial
Plan, from sources such as private donations, NGOs and
sponsors, will be used to fund the HBP as a whole.
Make the same trans-disciplinary and complementary
education available to the broader scientific community
and general public.
2.2.4 Measures to Protect IP, Ensure
Effective Exploitation and Realise Innovation
Potential
The goal of the HBP’s IP strategy is to maximise the benefits of HBP research for European citizens; facilitate
take-up of research results by European industry, health
care services and academia; and generate revenues
contributing to the financial sustainability of the Project.
The HBP’s IP strategy will therefore focus on maximising
The EP curriculum will comprise five separate syllabi.
Teaching will take a Massive Open Online Courses
(MOOC) approach, in which webinars are complemented by a face-to-face workshop and hands-on
sessions with the HBP Platforms. The syllabi will be
developed and taught by senior scientists leading or
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Impact
working on HBP Subprojects.
They will introduce young scientists to disciplines outside
the speciality in which they have been trained, and expose
them to the HBP Platforms. Syllabus teaching materials will be made available via an EP website, , accessible through the Unified Portal, that will direct students
towards further reading material. The syllabi will be complemented by an annual summer school, which will provide
a forum for learning and sharing insights into cutting
edge research issues within a specific HBP discipline.
they publish their research. Partners will be expected to
include funds for publication fees in their research budgets.
2.2.7.2 Data
The CP and the PPs will use and generate petabytes of
Mouse Brain Data for the HBP Mouse Brain Atlas
Human Brain Data for the HBP Human Brain Atlas
The HBP EP will support a Student Community, providing infrastructure to facilitate interaction between young
scientists across the HBP and provide them with privileged access to HBP data, knowledge and resources.
The Student Community will give young HBP scientists
a voice in HBP decision-making via a seat for a student
representative on the HBP Board. The HBP EP will also
provide special support and encouragement for young
female scientists.
Models from research in theoretical neuroscience
Brain atlases and the Brainpedia (a wiki of information
about the brain) made available through the
Neuroinformatics Platform
Brain simulation data used and generated by the Brain
Simulation Platform
High performance computing data generated by the
High Performance Computing Platform
2.2.6 The HBP Museums Programme
Clinical data made accessible through the Medical
Informatics Platform
There are approximately 3,000 science centres and
museums around the world, most of which participate
in national, regional and global public education associations. The HBP has reached out to these organisations
though a privately funded science centre and museum
programme designed to make the public aware of HBP
research and its scientific, social and economic impact.
Data used and generated by the Neuromorphic
Computing Platform
Data used and generated by the Neurorobotics Platform
Data used and generated during exploration of novel
applications
The HBP is working with its partners institutions to
produce scalable exhibitions targeting families, educational institutions, and the rest of the general public.
Content will be periodically updated to make the public
aware of the Project's latest achievements. An HBP
Science Centre Advisory Group will provide input on
strategic direction.
Ethical documentation generated by the Ethics and
Society Programme
Software and technical documentation for the Platforms
Administrative documentation
The exhibitions will be rich in 2D and 3D content that is
highly interactive and educational. A particularly important goal is to engage the public in a conversation about
the ethical and social impacts of HBP’s research.
data. Broad categories of data include:
The HBP has already created a Data Management Plan
(Deliverable D13.3.2) that defines general principles for
managing the data generated by the Project and applies
these principles to the different categories of data
described above. The plan, which will be continuously
updated over the lifetime of the Project, is based on the
template defined by the Horizon 2020 programme, and
defines, and defines specific provisions for data sharing,
backup, archiving and preservation for each data set.
As part of this effort, the HBP will develop its own
science centre ("The HBP Neurosphere") located on the
new Geneva Biotech campus. The Neurosphere will bring
scientists together with the public in a planetarium-like
structure including an area reserved for scientists and a
teaching area open to the public. The centre is scheduled
to open in 2017. Content developed for the centre will be
fed into the rest of the Museums Programme.
The HBP strongly supports European policy on Open Data,
and will define its policies for data access in line with the
requirements of the policy. In principle, the Project will
follow a dual licensing policy. Academic users will access
project data, software, and documentation free of charge.
Commercial users may be required to pay a fee. In line with
European policy, the Project reserves the right to restrict
access to specific data sets, where this is necessary for
reasons of security, to allow protection of Intellectual Property, or to protect the privacy of human subjects. Any such
restrictions will be made explicit in the Data Identification
Cards, annexed to the Project’s Data Management Plan.
2.2.7 Knowledge Management (Apart from IPR)
2.2.7.1 Publications
The HBP strongly supports European policy on Open
Access. To meet the requirements of the policy, all HBP
scientific publications will be deposited in an HBP-managed searchable repository, accessible via the Unified
Portal (Green Open Access). HBP researchers will also be
encouraged to deposit their publications in other wellknown repositories, giving the publications the broadest
possible audience, and in particular with the European
OpenAIRE repository.
2.3 Access to Resources
The initial financial plan, submitted in the 2012 HBP
Proposal, involved total costs in the order of EUR 1,160
HBP scientists will be free to choose the journals where
29
Impact
million, of which EUR 652 million was to be funded by
the Commission, and EUR 507 million by the Partners
of the HBP Consortium and other funding organisations.
This plan included EUR 221 million for projects using
the HBP platforms, to be allocated through Competitive Calls. Since the Competitive Call mechanism will no
longer be used in H2020 part of the HBP Flagship Initiative, projects making use of the Platforms will now be
funded through the Partnering Projects mechanism. This
has led to a revision of the HBP financial plan.
nering Project components are significantly larger. This
is because most of the neuroscience data used by the
project is expected to come from Partnering Projects.
The Core Project will focus on a few critical datasets.
2.3.1 Estimated costs
The overall cost of the planned ten years of the HBP Flagship Initiative is estimated at around EUR 1,019 million. The
Initiative will be separated into three components: the
Core Project (CP), the Partnering Projects (PP) and other
EU-funded, Flagship-related projects, such as FLAG-ERA
and other Coordination and Support Actions (CSA).
The Initiative will be implemented in four phases, based
on the different phases and Specific Grant Agreements
(SGAs) of the CP.
Ramp-up Phase: October 2013 to September 2016
SGA1: April 2016 to March 2018
SGA2: April 2018 to September 2020
SGA3: October 2020 to September 2023
Figure 6: Budget per phase of the project and component
Most of the project’s budget goes to the SPs that will
build the ICT Platforms (SP4 to 9). The budget for these
SPs amounts to EUR 617 million covered. The SP with the
largest budget is SP2 – Targeted Mapping of the Human
Brain, with a budget of EUR 132 million. A large proportion of the SP2 budget, EUR 94 million, is expected to
come from Partnering Projects.
Figure 6 shows budgets for each phase and each component (CP, PP and Other). The Ramp-Up Phase falls
under FP7; it is therefore the only phase of the CP for
which the total budget (EUR 73 million) is higher than
the EU contribution (EUR 54 million). The annual budget
for the project (between EUR 122 and 127 million per
year) is expected to be approximately stable. The apparent increase from phase to phase, shown in the figure is
due to differences in the duration of the phases.
Theoretical work will be carried out both in a dedicated
SP and by dedicated Work Packages in most of the other
SPs. The total budget for theory-related activities (EUR
69 million - 7% of the total budget) is thus much larger
than the amount for SP3 alone.
The HBP Core Project budget can be further divided
by Subproject (SP), as shown in Figure 7. The Subproject structure, shown in the figure, introduces a number
of changes with respect to the Ramp-Up Phase. These
changes concern two subprojects dedicated respectively to “Cognitive Architectures” (SP3 in the Ramp-Up
Phase) and to “Applications (SP11). These subprojects no
longer appear explicitly in the subproject structure. Part
of the Cognitive Architectures SP has been integrated
into SP2; the remainder of the SP has been allocated to
Partnering Projects in other subprojects. The three work
Packages in the Applications SP have been integrated in
the new SP7 (Medical Informatics), SP8 (Neuromorphic
Computing) and SP9 (Neurorobotics). Figure 8 shows,
for each SP, the proportion of budget allocated to the
Core Project and the proportion allocated to the Partnering Projects. In most SPs, the Core Project component is
approximately equal to the Partnering Projects component. The exceptions are SP1 and SP2, where the Part-
Management work will be carried out in SP11. Estimated
EU funding for management over the 10 years of the
project amounts to EUR 38.2 million, of which EUR 28.0
million in the period covered by the FPA. Additional
management services, of roughly equivalent value are
provided by the COORD, as contribution to the project.
The extensive cost planning exercise that preceded the submission of the 2012 Proposal, prepared a detailed budget for
each cost category that provides the basis for our current
(adjusted) estimates. The totals for each cost category
(excluding other EU-funded Flagship-related projects) are
shown in Figure 9. These numbers will be reviewed when a
more detailed budget is created for the SGA proposals.
The largest cost by far is personnel with a total value of EUR
30
Impact
797.5 million: almost 80% of the total budget.
The second largest cost is consumables, with a value of
With an average cost of EUR 75,000 per person-year, this
gives an equivalent of 10,627 person-years over the whole
project. In other words, in any given year, the HBP will
employ more than 1,000 people per year across Europe.
EUR 70.6 million or 7 % of the overall budget. The largest
expense in consumables is planned for SP8 – Neuromorphic Computing, with an estimated value of EUR 36.8
million. SP8 is followed by SP1 and SP2, which have consumables budget in the order of EUR 12.4 and 6.1 million,
respectively.
Figure 8: Core Project and Partnering Projects component of each SP
The third largest cost is equipment, with EUR 51.0 million or
5% of the total budget. SP7 – High Performance Computing is planning the largest expenditure on equipment. This
will take the form of a Public Procurement of Innovative
Solutions (PPI) project, with a estimated budget of EUR
25 million. The PPI will follow the current HBP Pre-Commercial Procurement (PCP) project for High Performance
Computing technology solutions. Other SPs planning large
equipment costs include SP1 (EUR 10.4 million for the purchase of characterisation equipment) and SP9 (EUR 7.4
million for the purchase of robotic hardware).
Travel costs amount to 4% of the total budget, an
Figure 7: SP budgets in each phase
Figure 9: Budget per cost category
31
Impact
average of EUR 3,864 per person-year. Certain SPs have
larger than average travel costs. In particular SP3, dedicates 10% of its budget to travel, because of the visitor’s
programme at the EITN; SP11 spends 8% of its budget
on travel, because of its international relations and coordination activities. The travel budget assumes that the
Partnering Projects will have their own travel budgets.
details of this process can be seen in the Appendix, Chapter
4.
2.3.2.1 Education Programme funding
Most of the funding for the HBP Education Programme
will come from EU-funded Partnering Projects. The Education Programme Office and the Education Programme
Committee have already made plans to exploit Horizon
2020 programmes, which meet the requirements and
objectives of education and training for HBP Early Stage
Researchers (ESR) and Experienced Researchers (ER),
as defined by the Marie Sklodowska-Curie programme.
The initial focus will be on Marie Sklodowska-Curie
actions of the Initial Training Networks (ITN) type, such
as European Training Networks (ETN), European Joint
Doctorates (EJD), European Industrial Doctorates (EID),
and fellowships. Initial preparations for four ITN applications to the next two calls in 2015 and 2016 are already in
a planning phase. The four planned topics for HBP ITNs
and their tentative beneficiaries from the current HBP
Consortium are:
Other beneficiaries from the relevant sectors will be
Planned subcontracting expenses amount to EUR 22.8
million. Of this, EUR 12 million is planned for the installation and operation of the medical data federation
system in SP7 – Medical Informatics. About EUR 8 million
is planned by SP11 for the commissioning of software
systems, legal services and other consulting services. A
EUR 2.6 million PCP project is currently running under
SP6 and is also considered as a subcontracting activity.
Finally, EUR 27.4 million is allocated to other costs. The
majority of these costs are for the housing and care
of mice in SP1 (EUR 18.5 million) and the organisation
of events in SP11 (EUR 2.6 million). The hosting Partner
or sponsors will cover most of the cost of events and
project meetings.
2.3.2 Funding sources
It is estimated that the EUR 1,019 million HBP budget will
be funded from three sources:
Figure 10 shows sources of funding for the different com-
From cognitive to computer architectures (UHEI,
UMAN, JUELICH, AMU, KIT, TUGRAZ): application
deadline 13 January 2015
Multi-scale brain imaging (INRIA, CEA, JUELICH, UDUS,
LENS, UCL): application deadline 13 January 2015
European Commission: EUR 500 million
Neuronal basis of cognitive architectures (JUELICH,
KIT, KNAW, UM, UGR, UPF): application deadline
January 2016
National, public & private organisations: EUR 500 million
Core Project Ramp-Up Phase Partners: EUR 19 million
Medical Informatics, Diseases and Applications (KTH,
TAU, IMU): application deadline January 2016
ponents of the project. As mentioned before, the EUR 19
million contributed by the Ramp-Up Phase Partners comes
from the difference between the total costs and the EU
contribution in the FP7-funded phase of the HBP. To reach
the ambitious goal of leveraging EUR 500 million for the
Partnering Projects, the Management and Coordination SP,
along with the Partnering Projects Committees, will spare
no effort to communicate the Partnering Projects concept
and topics to potential funding organisations. Further
added as the planning for the ETNs progresses. With an
estimated 540 person-months per ETN, a total of 2,160
person months will be reached for these four ETNs. At
EUR 7,210 per ESR-month, including living allowance,
mobility allowance, family allowance, research, training
and networking costs, and management and indirect
costs, this leads to an estimated total funding of EUR
15,573,600 for the four ETNs in the next phase of HBP.
It is estimated that six other ETNs could be created in
the last two phases of the project for a total amount
of EUR 23,360,400. Finally, based on an estimation of
three ER fellowships of 36 months each per year in the
period of 2016 to 2020 (540 person months in total),
the total budget of ER fellowships could be around EUR
3,888,000. This brings the potential budget for Education Programme-related Partnering Projects to a total of
EUR 42.8 million.
The HBP Education Programme Office will provide incentives to HBP Partners for collaborating with the Office
and enabling proper coordination and monitoring of
grant applications. Incentives will include guidance
and advice for structuring the networks and proposals
according to the Horizon 2020 work programme and the
objectives of the HBP. These coordinating actions will
Figure 10: Components of the project and their funding sources
32
Impact
avoid duplication, overlaps or redundancies of proposals
from different HBP partners and consortia.
without claiming their cost. The value of personnel made
available in this way amounts to EUR 182 million. The personnel provided by the partners will produce 2426 manyears of effort at an average cost of 75,000 per man-year.
For Personnel, the largest contributors are EPFL with EUR
98.5 million (mainly for SP4, 5, 6 and 11), JUELICH with
EUR 31.4 million (mainly for SP 2 and 6) and UPM with EUR
7.5 million (mainly for SP1 and 4).
In addition, the Education Programme Office will provide
limited funds for meetings and other measures to foster
the formation of consortia. ITN ESRs will have the added
value of access to the HBP Platforms and enrolment in
the HBP Education Programme curriculum. The Education Programme Office will coordinate and foster transdisciplinary bridging activities between HBP-related
ITNs. The expertise and experience of the SP11 team in
writing proposals will provide an established professional
service to HBP Partners for future annual calls beyond
2016 (MSCA and other).
Major laboratory equipment amounts to EUR 26 million.
Products and services made available to the project
amount to EUR 22 million.
2.3.2.2Museum Programme funding
The HBP Science Centre and Museum Programme is a
privately funded public outreach and education effort.
The "Neurosphere" is a working title for a planetarium-like
structure at the Geneva campus of the HBP. The Neurosphere will comprise an area reserved for scientists and
a teaching area, open to the public, which is expected to
cost EUR 30 - 45 million to construct. The funding for Neurosphere will be sought from private foundations during
2014. The exhibition will be offered to science and technology museums and centers around the world, through
a shared funding model among museums, sponsors and
private foundations.
2.3.3 Resources made available by Partners
In addition to the budgets described above, each Partner
in the HBP Core Project has provided a list of resources
currently or planned to be made available to the HBP over
the duration of the project and beyond. Details for each
individual partner can be found in Chapter 4 of this document. The amounts presented there are estimates. At the
time of the writing, the estimated value of the resources
made available by partners amounts to EUR 497 million.
Figure 11 shows the allocation of these resources between
five categories. The most important is Research and Technical Infrastructure with EUR 240 million or 48% of the
total resources made available. The partners contributing
the most to this category are JUELICH with EUR 81 million
(HPC, visualisation and characterisation resources), EPFL
with EUR 65 million (HPC and animal experimentation
resources), FG with EUR 50 million (Clean room facilities),
CINECA with EUR 26 million (HPC resources).
Figure 12: Resources made available by Partners by country
The resources provided by partners can be directly linked
to countries in which these partners are located, as shown
in Figure 12. The two countries whose partners contribute
most to the project are Switzerland (EUR 214 million) and
Germany (EUR 182 million). Other important contributors are Italy (EUR 37 million), Spain (EUR 15 million) and
Sweden (EUR 11 million).
2.3.3.1 Financial resources
Financial resources identified by partners include grants
received by partners for HBP-related activities and grants
that the partners expect to apply for and receive in the
future. It is difficult or even impossible for funding agencies, governments and other sources to make financial
commitments beyond their normal planning horizon. Furthermore, the experience of the HBP shows that funding
agencies and other sources are more willing to commit to
the funding of HBP activities once they are certain that
EC funding will also be available. Nevertheless, current
estimated financial resources expected to be available for
HBP have already reached EUR 425 million. Of this sum,
Figure 11: Resources made available by Partners by category
Many Partners will provide personnel to the project
33
Impact
2.3.3.2Supercomputing resources
The HBP Supercomputer at Jülich for the phases after the
ramp-up phase will be built in stages. A data-centric "preexascale" system of the order of 50 PFlops with a memory
capacity of up to 20 PBytes is planned for 2016-18. Preferably, this system will be procured through an EC-supported Public Procurement of Innovative Solutions (PPI),
building on the results of the ongoing HBP PCP. Over its
expected lifetime of 5 years (2017/18-2022/23), the total
cost of ownership (TCO) of the pre-exascale system is
estimated at EUR 200 million (EUR 100 million each for
investment and operating costs, respectively). Of this
sum, EUR 25 million (12.5% of total / 25% of investment
costs) should be covered by the EC-contribution to the
PPI, EUR 75 million (37.5% / 75%) by the German Federal
Government and the State of North Rhine-Westphalia
through the Gauss Centre for Supercomputing (GCS),
and EUR 100 million (50% / 100% of operating costs) by
the German Federal Government and the State of North
Rhine-Westphalia through the Programme-oriented
funding of the Helmholtz Association. The full capability
of the machine will be available to the HBP. Up to 25%
of the total available compute capacity (computing time
or core-hours) will be reserved for peer-reviewed HBP
research. A similar funding scheme is foreseen for the
exascale version of the HBP Supercomputer.
Figure 13: Financial resources made available by Partners by category
EUR 279 million from national funding sources, EUR 100
million from European funding sources, EUR 34 million
from regional funding sources, and EUR 13 million from
international funding organisations. Figure 13 shows the
distribution of financial resources by category. Expected
European grants include EUR 25 million for the procurement of HPC resources through a PPI project and EUR 43
million for MSCA ITNs and fellowships.
Figure 14 shows that the country that will provide the
largest contribution is Switzerland (EUR 190 million), followed by Germany (EUR 68 million), Italy (EUR 11 million),
Spain (EUR 8 million), the United Kingdom (EUR 7 million),
Norway (EUR 7 million) and Sweden (EUR 7 million).
The three successive versions of the HBP Development
Supercomputer, located in Lugano, operated by CSCS
(ETHZ) and procured by EPFL, will be totally funded
by the Swiss Government through its Blue Brain Project
National Research Infrastructure and will be fully dedicated to HBP research. The total cost of ownership of
each machine is estimated at EUR 23 million.
The HBP Molecular Dynamics Supercomputer will be
located at the Barcelona Supercomputing Center. The
first phase (2013-16) is estimated to cost EUR 30 million
and will be 100% funded by the Spanish Government.
The second phase (2016-18), also 100% funded by the
Spanish Government, is expected to cost around EUR
50 million. Finally, the third machine (2018-21) is planned
to be funded 50 % by the Spanish Government, 30%
by the European Commission and 20% by the users. Its
expected value is EUR 100 million.
A fourth major High-Performance Computing resource
used by HBP will be the HBP Data Analytics Supercomputer,
located at CINECA in Italy. Its cost, currently unknown, will
be funded primarily by the Italian Government.
2.4 Fostering Complementarity with
Regional, National, European and
International Research Programmes
2.4.1 Objectives
Figure 14: National and regional financial resources by country
Since the CP will focus on the development of technologies
allowing for the integration of data from multiple sources, the
success of the Action Plan will depend on the HBP’s success
in building collaboration with organisations and initiatives
outside the HBP. It is these organisations that will contribute
the majority of the data and knowledge the Project uses.
Screening and selecting potential collaboration Partners will
As the project proceeds, HBP efforts in dissemination
of results and awareness-raising will be used to raise
additional funds. The updated financial plan for the FPA,
released at the start of each SGA, will reflect the funding
commitments generated by these activities.
34
Impact
be the responsibility of the HBP Research Board. Implementation of collaborations will be the responsibility of the Subprojects concerned. The Research Roadmap (see Appendix
1, section 3) specifies areas of research and potential Partners with which the Projects have already identified possibilities for collaboration. Details of the collaborations planned
by individual Subprojects are found in the relevant sections
of Appendix 1.
by formal collaboration agreements negotiated by the
RO, acting on behalf of the HBP Research Board. Collaborations will take different forms according to the nature
and objectives of the organisations concerned.
Promotion of Synergies and Efficiency in Research:
The HBP will establish formal collaboration agreements
with other large national, European, international and
global research agreements. The joint activities foreseen in these agreements may include exchanges of
information and staff; joint workshops and conferences;
sharing of data, tools and infrastructure; and joint
research projects.
The HBP will Identify and establish collaborations with
national, European and transnational, international and
global initiatives in relevant areas of research and development, avoiding duplication of effort and building
momentum behind the global effort to understand the
brain and its diseases (CPO9).
Promotion of PPs and use of the HBP Platforms: The HBP
will work with national funding agencies and European
funding programmes outside FET to encourage proposals for PPs that facilitate the development of the HBP
Platforms, or that use the Platforms to perform research
contributing to the HBP’s Strategic Goals. Planned promotional activities include: HBP participation in coordination meetings (such as those currently organised
by FLAG-ERA), exchanges of information about relevant national and European funding programmes, HBP
contributions to the formulation of work programmes
in relevant areas of research, and HBP participation in
meetings, info days and other activities. Partnership
Projects that pass the HBP selection process (see paragraph 1.0.5 (criteria) and 3.1.8 (process)) will become
Maximise use of the HBP platforms
and HBP know-how
Such collaborations will help to maximise use of the
HBP Platforms and HBP know-how by organisations
that are not signatories of the FPA. It will also promote
translational research that transforms HBP research
results into products and services that are valuable to
European citizens and that strengthen the competitive
position of European industry (CPO10). Collaboration
with other initiatives will help the parties concerned
to make the best possible use of the data, know-how,
tools and infrastructures they have created, contributing to the development of standards, resources and
infrastructures of general benefit to the scientific community. Collaboration will make it easier for the parties
to contribute to the formulation of national and European research priorities, to national and European policymaking, and to regulatory decision-making in areas
relevant to the Project (e.g., data protection, research
ethics etc.).
2.4.2 Implementation
Building and maintaining relationships with other national,
European, international and global research initiatives
and with relevant funding sources is the responsibility
of the HBP’s Relations Office (RO), which is already in
operation, and will continue its activities for the whole
duration of the CP.
The HBP Description of Work identifies a non-exhaustive list of eight European initiatives (BIOMEDBRIDGES,
CERN, ELIXIR, ESFRI, FLAG-ERA, ICON, IMI, PRACE)
and eight International initiatives with which the HBP is
attempting to build relationships. The RO has already
held meetings with seven of these organisations
(CERN, PRACE, FLAG-ERA, IMI, INCF, Allen Institute,
BRAIN Initiative) and has established a close working collaboration with the FLAG-ERA. Contact with the others
will be established before the end of the Ramp-Up Phase.
The RO is currently working to identify other organisations with which the HBP should build relationships. This
activity will continue for the whole duration of the HBP
Flagship Initiative.
Collaborations with outside initiatives will be regulated
35
Impact
full members of the HBP Flagship Initiative, with full
access to HBP Platforms and know-how and full access
to HBP training and education activities.
and animal experimentation.
2.4.3 Measurement of Success
The success of the HBP’s efforts to collaborate with other
initiatives will be measured in terms of:
Standards Development: The HBP will work with other
research initiatives to develop standards of general
benefit to the research community. These may include
standard protocols, ontologies and file formats for
experimental data and metadata, and standardised
approaches to informed consent for human subjects.
The number of formal collaboration agreements in place
The number of collaboration agreements that are active
Contributions to Policymaking: The HBP will work with
other national and European initiatives to contribute
to the formulation of national and European research
priorities and to policymaking and regulatory activities
in relevant areas of research. Possible themes include the
planning of future national and European research programmes, data protection regulations, informed consent
and protection of human subjects in medical research,
The number of proposals for Partnering Projects and the
geographical and disciplinary diversity of the proposals
The number of participants in other initiatives who are
active users of the HBP Platforms
The number of other initiatives that are actively sharing
data, know-how and tools with the HBP.
36
Impact
IMPLEMENTATION
3. IMPLEMENTATION
3.1 Quality of Governance and
Management Structure
3.1.1 Overview
3.1.1.1 The FPA
Core Project
The FPA Consortium includes 85 institutions, although
not all may be active at the same time. We assume this
number will remain stable for the first two phases of the
CP, possibly tapering off in the final phase.
The FPA creates a multi-year non-financial commitment between the European Commission on the one
hand, and the HBP Core Project (CP) and its Consortium
of Partners on the other hand. Through the FPA, the
European Commission commits to support the activities
of the CP through the FET Flagship Programme. Funding
will be regulated through Specific Grant Agreements
(SGAs) between the Commission and the signatories
of the FPA. Three such agreements over the life of the
Flagship Initiative are currently planned.
Partnering Projects
The HBP’s 2013-14 Competitive Call attracted some 350
proposals. Due to the focused nature of the call and corresponding budget limitations, only 5% were selected for
funding. Nonetheless the call resulted in an intake of 32
new Partners. In view of the broad scope of the research
topics assigned to PPs in the Research Roadmap, the
larger candidate pool and the availability of funding from
outside the CP, we expect the PPs to bring in many more
partners. This will require enhancements in the absorptive
capacity of the internal management team and the CP.
The FPA defines the CP’s commitment to the Commission.
It specifies the objectives of the CP, related actions, and
the Consortium tasked with their implementation. The CP
will remain relatively constant in its scope over the lifetime
of the FPA. The Research Roadmap and the list of Partners will be updated before the beginning of each new
phase in the CP and the definition of the associated SGA.
3.1.1.3 Requirements
3.1.1.2 Growth
Given the nature of the HBP Flagship Initiative and its
planned growth, the Initiative’s governance mechanisms
should provide:
As shown in Figure 15, the Flagship Initiative comprises
the CP plus an evolving group of Partnering Projects
(PPs) (see paragraph 1.0.2). The PPs will be independent research projects with their own funding that collaborate with the CP through non-financial partnering
agreements. PPs will be selected through the process
described in Appendix 1, Chapter 4.
Strong, pragmatic governance arrangements to ensure that
the Initiative can achieve its objectives with the financial
resources available.
Ways to engage PPs meaningfully in the governance of the
Initiative without blurring roles and responsibilities.
Flagship
Governance
Forum
A formal consultative mechanism allowing the Member
States and Flagship participants to become aware of their
respective needs and to align their strategies and priorities.
Framework Partnership Board
Tight coordination with the European Commission via its
FET Flagship Unit.
HBP Research Board
HBP Foundation Board
The relevant stakeholders will jointly elaborate the exact
modalities, terms and conditions of the collaboration,
including the rights and obligations of Partners in the CP
and the PPs. In each case, the aim will be to preserve the
coherence of the Initiative and to build a sense of community; to bring value to all parties and make a genuine
contribution to implementation of the Flagship; and to
strengthen the interest, alignment and involvement of
national and regional programmes in the Flagship Initiative.
Flagship Initiative
Core Project
General Assembly
Individual Partnering
Projects Governance
Core Project Partners
Partnering Project Partners
HBP Subproject Committees
Figure 15: Flagship Governance - a bird’s-eye view
38
Implementation • June 2014
The governance and decision-making structures illustrated in Figure 15 address these needs, defining the
relevant contractual relations and the resulting accountabilities. They will consist of the following bodies:
The objectives of the FGF are to:
Create an exchange of information on the overall direction
and strategy of the FET Flagships
Coordinate the planning of national, regional and transnational
activities in the areas of research relevant to the Flagships
Flagship Governance Forum (FGF)
Framework Partnership Board (FPB)
Flagship Coordinator (COORD)
Promote an environment that stimulates innovation by
linking Flagship science and technology development to
innovation policies at the national and European level
Core Project General Assembly (CP-GA)
Encourage international collaboration.
Research Board (RB)
Committees of the Research Board:
3.1.2.2 Composition, Size, Selection
- Executive Committee (ExCo)
The Flagship Governance Forum is composed of representatives of the Member States and other states participating
in Horizon 2020, the European Commission, and up to four
representatives from each of the Flagship Consortia. Each
of these constituencies will select its own representative(-s).
The European Commission will convene the FGF, and an EC
official will serve as its chair. The FGF is established for the
duration of Horizon 2020. However, it may stop its operations earlier, if agreed by its members.
- Subproject Committees (SPC)
- Partnering Projects Committees (PPC)
dvisory Bodies of the Research Board and Executive
A
Committee:
- Strategic Advisory Board (SAB)
- Ethics, Legal and Social Aspects Committee (ELSA)
- Research Ethics Committee (REC)
- Innovation and Technology Transfer Committee (ITTC)
Foundation Board (FOB).
3.1.3 Framework Partnership Board (FPB)
3.1.2 Flagship Governance Forum (FGF)
3.1.3.1 Responsibilities
In line with the terms of the FPA Agreement, the FPB’s role
is to maintain dialogue among the participants, to monitor
the Research Roadmap, and to provide input to the H2020
Work Programme. The members of the FPB may agree to
undertake certain actions within the scope of their respective roles, but the FPB is not a decision-making body per se.
The role of the Flagship Governance Forum (FGF) is to
promote openness and to contribute to the development
of a common European effort based on the Research
Roadmaps defined by the two FET Flagships. It will do
this by supporting the Flagships’ evolution, creating synergies between the Core Project of each Flagship and
related activities that the FGF’s members are funding at
the regional, national, transnational or European level.
The FGF will also help to harness their innovation potential. It is not a decision-making body.
Flagship
Coordinator
Framework
Partnership
Board
European
Commission
Figure 17: The Framework Partnership Board
European Commission
Flagship
Coordinators
Flagship
Governance
Forum
EU Member and
Associated States
The FPB will be a small, operational steering mechanism
convened by the European Commission and co-chaired
by the Commission and the Flagship. A member of the
HBP ExCo will represent the HBP Flagship Initiative on
the Board.
Figure 16: The Flagship Governance Forum
39
3.1.4 The Flagship Coordinator (COORD)
the FPA Partners contributing to the current phase of the
Project. The CP-GA’s role is to represent the collective will
of the Partners, notably with regard to:
The Coordinator is the legal entity that acts as the intermediary between the HBP Flagship and the European Commission. In addition to the responsibilities it shares with all other
Consortium members, the Coordinator is responsible for:
Content, finances and intellectual property rights (e.g.,
proposals for changes to the Description of Work and related
budget; proposals for joint exploitation of IP)
volution of the Consortium during the SGA (e.g., entry
E
and withdrawal of Partners and the conditions under which
Partners may join or leave).
Providing the headquarters for the HBP and hosting its
central management and ICT services
Discharging the fiduciary duties of the HBP
Ensuring the effectiveness of Flagship governance and
decision-making processes
The CP-GA is composed of one representative for each
signatory of the SGA currently in force. Each Partner will
appoint one permanent representative and one alternate.
To encourage balance between administrative and scientific engagement in the project, the CP-GA member
and alternate will be drawn, wherever possible, from
the Partner institution’s administrative leadership. The
CP-GA may pass resolutions representing its collective will (e.g., designation of the institution hosting the
Annual Summit) or take decisions by vote. The majorities
required for specific decisions will be fixed in the Consortium Agreement for the SGA. The votes assigned to each
Partner will be proportional to the EU funding that each
partner receives for its participation in the SGA.
Convening and chairing the CP-General Assembly, the
Research Board and the Executive Committee
Staffing and supervising the Central Management Team (SP11)
Monitoring all aspects of the Project, both scientific
and administrative
Collecting, reviewing and submitting reports and other
Deliverables to the European Commission
Communicating with the European Commission on all official
matters concerning the Project and conveying information
back to the Consortium and its governing bodies
Coordinating the planning, writing and timely submission
of SGA proposals to the European Commission on behalf
of the Consortium.
3.1.6 HBP Research Board (RB)
The Coordinator is assisted in carrying out these duties by
a Chief Governance Officer (CGO). The CGO coordinates
HBP’s governance and decision-making activities and
keeps the HBP governing bodies abreast of developments
related to corporate governance. In addition, the CGO:
The RB is the HBP Flagship Initiative’s strategic decisionmaking body. Its role is to steer the Initiative’s Research
Roadmap and to maintain the Initiative on the agreed
course, ensuring that it achieves the objectives defined
in the FPA.
Ensures that the HBP’s organisational practices are consistent
with the letter and the intent of its internal rules and with
applicable external requirements.
HBP Research Board
rives the organisational performance management framework
D
at the COORD level.
Chair:
Coordinator
ontributes to policy development and other discussions as and
C
when required, and advises members of the legal, governance,
accounting and tax implications of proposed policies.
Subproject 1 Committee
iaises with external advisors, such as lawyers, auditors, local
L
and national authorities with regard to the HBP’s current and
future governance arrangements.
erforms assessments of the governance practices and structure
P
of the organisation and identifies opportunities for improvement.
Communicates issues of new and evolving governance practices
to the European Commission and other project stakeholders.
A Chief Operating Officer (COO), chosen by the COORD
and approved by the Research Board, ensure the smooth
running of the Central Management Team.
3.1.5 The Core Project General Assembly (CP-GA)
Subproject
Co-Leaders
The CP-GA will be the supreme governing body for the
CP, with respect to the activities defined for a particular
SGA. Its membership at any one time will be composed of
Subproject
Leaders
Figure 18: The HBP Research Board
40
To fulfill this role, the RB and its members have the
following duties:
The Research Board is
the HBP’s strategic
decision-making body.
Governance
- Appoint the members of the Executive Committee (see
paragraph 3.1.7)
Scientific Steering:
The RB is composed of one representative per SP (the
Leader of the SP) with an alternate (the SP co-Leader) who
can stand in for the SP Leader if he or she is unable to attend
a meeting. Exceptionally, the Management and Coordination
Subproject (SP11) will have two co-leaders. Each Subproject
has one equal vote. Votes cast on behalf of a Subproject
must be agreed between the Leader and the co-Leader(s).
- Ensure that the CP achieves the Core Project Objectives and
that the PPs contribute to the Strategic Flagship Objectives
- Revise the Research Roadmap as required, to take
account of scientific and technological advances inside
and outside the Project
- Make necessary adaptations to the composition of the
FPA Consortium for each SGA
- Address emerging scientific issues, evaluate progress and
The Coordinator chairs the RB and holds the casting vote.
In the absence of the Coordinator, another member of
the Executive Committee (see paragraph 3.1.7) chairs the
board meetings.
give recognition for major successes
Resource Management and Project Management:
- Prepare and implement an SGA for each stage of the
CP including the distribution of the budget and other
resources, consistent with the Research Roadmap and
Although each RB member represents his or her particular area of research, members’ first duty is to ensure that
the Project meets the SFOs and the CPOs.
financial plan defined in the FPA.
Partnerships and Collaboration:
- Direct Partnering Project Committees to evaluate and
Membership in the RB resides with current leaders and coleaders of the Subprojects and will change if this changes.
The Chairmanship changes if the Coordinator changes.
select PP proposals
- Approve proposals for PPs
- Approve external collaborations
Policymaking - establish Initiative-wide policies for:
The initial RB is composed as follows:
- Communications
- Commercial exploitation of Project results, IP and
technology transfer
- Partnerships and collaborations
Advocacy:
SP1: Targeted Mapping of the Mouse Brain: Javier DeFelipe
(UPM), Seth Grant (UEDIN)
- Advocate for the HBP
- Advocate for research to understand the brain and its
SP2: Targeted Mapping of the Human Brain: Katrin Amunts
(JUELICH), John Ashburner (UCL)
disorders, and to develop computing technologies
inspired by knowledge of the brain.
SP3: Theoretical and Mathematical Foundations: Alain Destexhe
(CNRS), Idan Segev (HUJI)
In carrying out these duties, the RB must put the following specific items to the CP-GA for its approval:
SP4: Neuroinformatics: Sten Grillner (KI), Sean Hill (EPFL)
SP5: Brain Simulation: Henry Markram (EPFL), Jeanette HellgrenKotaleski (KTH)
SP6: High Performance Computing: Thomas Lippert (JUELICH),
Thomas Schulthess (ETHZ)
Proposals to the CP-GA for changes to the Description of
Work of an SGA
SP7: Medical Informatics: Richard Frackowiak (CHUV), Anastasia
Ailamaki (EPFL)
Proposal to the CP-GA for entry of a new Party to the SGA
Consortium
SP8: Neuromorphic Computing: Karlheinz Meier (UHEI), Steve
Furber (UMAN)
Proposal to the CP-GA for a withdrawal of a Party from the
SGA Consortium
SP9: Neurorobotics: Alois Knoll (TUM), Marc-Oliver Gewaltig
(EPFL)
Definition of remedies to be performed by a Defaulting SGA Party
Termination of a Defaulting SGA Party’s participation in the
Consortium and related measures
SP10: Ethics and Society: Kathinka Evers (UU), Jean-Pierre
Changeux (IP)
SP11: Management and Coordination: Henry Markram (EPFL),
Karlheinz Meier (UHEI), Richard Frackowiak (CHUV)
41
Non-voting members entitled to join meetings of the RB include:
In addition, the ExCo leads and supervises the HBP’s
internal management and support structures as well
as the Project’s national, European and international
collaborations (see paragraph 1.1).
One representative of the HBP Ethics, Legal and Social
Aspects Committee (ELSA) (upon invitation)
One representative of the Research and Ethics Committee
(REC) (upon invitation)
HBP Research Board
HBP Foundation Board
The Chairman of the Strategic Advisory Board (SAB) (upon
invitation)
HBP Executive
Committee
The Chairman of the Governance Oversight Committee (GOC)
(upon invitation)
One representative of the Science and Technology Office
HBP Management
The Chief Governance Officer
Figure 19: The HBP Executive Committee
The Chief Operations Officer
The Chief Technology Officer
In carrying out these duties, the ExCo is required to:
One representative of students enrolled in the HBP Education
Programme (upon invitation)
Members of HBP Management and support structures may be
invited to participate in RB meetings, as required
Maintain the unity of the HBP’s mission and ensure that all
HBP activities are fully aligned with the SFOs and the CPOs
In order to legitimately deliberate, a meeting of the RB
must have a quorum of two-thirds of its voting members
present or represented. As far as possible, the RB will
decide by consensus. If consensus cannot be reached
decisions may be taken by vote, with each present or
represented SP Leader exercising one vote in a quorate
meeting. Decisions will be considered as carried when a
certain fraction of votes is reached. The fraction varies
depending on the relative impact of passing a vote on
the project, for example:
Coordinate Subproject research, monitor Milestones and
Deliverables, and lead the organisation of project-wide
meetings, discussions, and events
Regularly assess the progress of the Project (at least once
every six months) and its compliance with the Research
Roadmap, and, if necessary, propose modifications of the
Research Roadmap to the RB.
Coordinate proposals for future SGAs for consideration by the RB
Set the RB’s Agenda and recommend strategies and Actions
and, in so doing, seek guidance from the HBP’s advisory
bodies - the SAB, the ELSA, the REC and the ITTC
Assist the advisory bodies in setting their agendas, and give
them specific mandates where the project can benefit from
their advice
Unanimity to change the Strategic and Specific Project Objectives
75% to change the Research Roadmap within the parameters of
the strategic and specific objectives or to change the Coordinator
Oversee the Management Subproject (SP11) and its staff
66% to change a Subproject leader, Committee chairperson,
composition of the SAB and positions in any other bodies
over which the RB has jurisdiction
Support the Coordinator in preparing meetings with the European
Commission and in preparing related data and Deliverables
Prepare the content and timing of press releases and
joint publications by the Consortium or proposed by the
European Commission.
66% to pass a new policy resolution
51% to change a Subproject co-leader
In principle, other decisions require a simple majority
The ExCo, established in the Ramp-Up Phase, has three
members (including the Coordinator), each representing
one of the three Strategic Flagship Objectives.
The RB will normally meet on a quarterly basis. It may
also call extraordinary meetings when prescribed by the
Consortium Agreement, or when a meeting is requested
by a simple majority of Board members.
• Future neuroscience (SFO1)
• Future computing (SFO2)
• Future medicine (SFO3)
Execution of the RB’s decisions and strategies will be the
responsibility of the Executive Committee.
The Committee is chaired by the representative of the
Coordinator and decides only by consensus.
3.1.7 HBP Executive Committee (ExCo)
The ExCo currently comprises:
• Henry Markram (EPFL, representing SF01) (ExCo
Chair, representative of Coordinator)
• Karlheinz Meier (UHEI, representing SF02)
• Richard Frackowiak (CHUV, representing SF03)
The Executive Committee (ExCo) aligns and balances
activity across the HBP and its three Research Areas. Its
role is to execute the decisions of the RB and to oversee
implementation of the HBP Research Roadmap.
42
In the event that a member of the ExCo is no longer able
to fulfill his or her duties, a replacement is chosen by the
RB, maintaining the balanced representation of the SFOs.
Candidate
Partnering Projects
3.1.8 Subproject Committees (SPCs)
HBP Research
Board
2. Partnering Project Committee(s)
select new Partners
Chair: Subproject
Leader
HBP
Foundation
Board
3. Research Board approves selected projects &
mandates the Foundation Board to enter
into Partnering Agreements
Members: Work Package
and Task Leaders
Work
Package
Partnering
Projects
Committee(s)
1. Management distributes proposals to the relevant
Partnering Project Committee(s)
Subproject Committee
Work
Package
Partnering
Projects
Applications
Portal
Figure 21: Partnering Projects Committees: role in Partnering Project
selection
Work
Package
Each Subproject has a Partnering Project Committee (PPC),
made up of the leaders of the WPs in the Subproject.
Task
3.1.10 Advisory Bodies
Figure 20: The HBP Subproject Committee
A Strategic Advisory Board (SAB), an Ethics, Legal and
Social Aspects (ELSA) Committee, a Research Ethics
Committee (REC), and an Innovation and Technology
Transfer Committee (ITTC) will advise the Board of Directors and the ExCo.
To promote integration, coordination and local management, each SP operates an SP Committee whose responsibilities are to:
Ethics, Legal and
Social Apsects
Committee (ELSA)
Plan, supervise and monitor the Subproject activities defined in
the Research Roadmap
Strategic Advisory
Board (SAB)
Guarantee the timely production and the quality of Deliverables
HBP Research Board
Identify emerging problems and take corrective action as required
HBP Executive Committee
Report progress to the ExCo and the RB
Formulate proposals to the RB for modifications to the Research
Roadmap and the allocation of budget and resources, consistent
with the Research Roadmap and Financial Plan defined in the FPA
Research Ethics
Committee (REC)
Innovation and
Technology Transfer
Committee (ITTC)
Coordinate Subproject activities requiring collaboration with
other Subprojects
Figure 22: HBP Advisory Bodies
Coordinate the planning of the project’s scientific activities for
future phases of the CP
3.1.10.1 Strategic Advisory Board (SAB)
Responsibilities
The SAB is an independent body that provides advice to
the RB and the ExCo. Composed of internationally recognised leaders in neuroscience, medicine and computing,
selected by the RB, it covers all three areas of research
present in the Project (neuroscience, computing, medicing). Its terms of reference are defined as follows:
Ensure that the Subproject makes an appropriate contribution to
HBP scientific dissemination activities.
SPCs are chaired by the SP Leader, assisted by the coLeader, and composed of the WP Leaders and Task Leaders.
3.1.9 Partnering Projects Committees (PPCs)
“The Strategic Advisory Board consists of a group of
eminent scientists and technologists, who are independent of the HBP’s management and Partners and will not
participate directly in the HBP and its planned research
activities. The Board will elect its own chair and define
its own procedures. The Board and its members, who
will have advanced access to all Project Deliverables, will
collectively and individually advise the Board of Directors, the Coordinator and the Partners on issues related
to planned research and development in the HBP. Advice
HBP Management will distribute proposals for Partnering Projects to the relevant Partnering Project Committees (PPCs) who screen the projects in line with
the procedures described in Appendix 1, Chapter 4.
Selected projects are submitted for approval to the RB.
Formal agreements between approved Partnering Projects and the HBP are negotiated and signed by the HBP
Foundation.
43
will be offered at annual meetings of the SAB and on the
request of the Coordinator.”
criteria and on this basis proposed a list of 11 nominees.
The proposal was communicated to the European Commission Policy and Programme Officer, who waived
requesting an opinion from the European Group on Ethics
in Science and New Technologies (EGE), and accepted the
proposal under the condition that the Committee should
include an additional member with expertise in data protection. The final Committee is made up of 12 members.
The SAB will hold at least one yearly meeting with the
ExCo, during which it will report on activity, the state of
the art and plans for the year ahead.
Composition, Size, Selection
The SAB is chaired by Torsten Wiesel, (Rockefeller University, Neuroscience and medicine).
The ELSA provides
strategic oversight for ethical,
legal and social issues
Two representatives of Future Neuroscience
Two representatives of Future Medicine
Two representatives of Future Computing
Members of the ELSA have an initial term of office of
five years. Where the Committee believes that the
current membership is unbalanced or insufficiently
representative, or that it lacks key competencies, it has
the power to co-opt additional members. If the ELSA
seeks to exercise this option it will:
Three Industry representatives (neuroscience, medicine,
computing)
The members of the Board for the H2020 period will be
nominated by the RB upon signing of the FPA.
3.1.10.2Ethics, Legal and Social Aspects Committee
(ELSA)
Responsibilities
Strategic oversight for ethical, legal and social issues
will be provided by the ELSA, which acts in an advisory capacity to the RB and the ExCo. The ELSA may
act either on its own initiative or in response to specific
requests. Where it believes useful, the ELSA may also
formulate recommendations for national and European
regulators, raising issues it believes should be the object
of broad public debate.
Formulate a proposal for a revision of the composition of the
committee, on the basis of nominations received
Communicate the proposal to the European Commission,
which may, at its discretion, request the opinion from the
European Group on Ethics in Science and New Technologies
(EGE). If the Commission makes no requests for change, the
proposal will be submitted for approval to the HBP RB.
The Committee was established during the Ramp-Up
Phase, applying the following selection criteria:
The ELSA meets in plenary sessions twice per year at
dates fixed by the Committee, elects its own chair, and
fixes its own agenda. It will also hold at least one yearly
meeting with the ExCo, during which it will report on
activity, the state of the art, and plans for the year ahead.
During plenary meetings, the committee will identify
issues that require further attention and appoint Working
Groups to examine them in depth. Working Groups will
formulate draft recommendations, which the Committee
will formally adopt or reject. Where the Committee or the
Working Groups believe this could be useful for their work,
they will organise hearings where HBP managers and scientists and invited experts from outside the Consortium
will present and answer questions about specific areas of
HBP strategy, research and technology development.
Gender balance (approximately 50% of the members should
be women)
Geographical balance (the membership should include all of
the main countries participating in the HBP, and all of the main
geographical and cultural areas in Europe)
“Main schools of thought” (the Members of the committee
should come from a broad range of religions, ideologies and
political beliefs. However, the Committee should not include
official delegates from any particular grouping)
The Committee will be supported by a small secretariat,
independent of HBP Central Management, which will
organise meeting dates and logistics, and take responsibility for meeting agendas and minutes.
Balance of competencies (a broad range of competencies
including competencies in law, medicine, medical research,
animal experimentation, and privacy/data protection).
The selection of members of the Committee was assigned to
an ad hoc selection committee made up of three members
nominated by the HBP External Advisory Board (EAB) and
three nominated by the Presidents’ Advisory Council (PAC).
The Selection Committee invited HBP Partner organisations and individuals involved in the HBP to propose
candidate members for the committee. The Selection
Committee reviewed candidates against the selection
44
3.1.10.3Research Ethics Committee (REC)
such as the World Intellectual Property Organisation
(WIPO) to take part in its deliberations.
Responsibilities
A separate Research Ethics Committee (REC), independent of the ELSA, helps the Partners to ensure that HBP
research meets the highest possible ethical standards. It
also helps Partners ensure that HBP research complies
with relevant European, national and regional laws, as
well as with the deontological standards imposed by relevant professional bodies.
3.1.10.5 Governance Oversight Committee (GOC)
Responsibilities
The GOC is responsible for monitoring governance
within the HBP. Its duty is to present to the Research
Board governance actions that its members feel are
required, and recommend practicies and policies.
The GOC will be chaired by Sten Grillner (Karolinska
Institute Member) within the HBP Core Project, but who
is not a member of the Research Board.
The initial members of the GOC will be:
• Alex Thomson (UCL, Chair)
• Kathinka Evers (UU, Member)
The work of the Committee includes preparing and revising guidelines, responding to researcher queries, and
reviewing HBP local research ethics applications prior
to their submission to local Independent Review Boards.
The REC will additionally be responsible for investigating
and deciding on any allegations of scientific misconduct
that arise during the Project. The REC will meet quarterly,
and will be supported by a permanent staff from the HBP
Ethics and Society Division. It will also hold at least one
yearly meeting with the ExCo, during which it will report on
activity, the state of the art, and plans for the year ahead.
The staff will organise meetings, keep track of changes in
national and European regulations, and provide regular
information on these changes to committee members and
to HBP research groups. It will also maintain a website and
a secure database containing details of past and on-going
ethics applications (successful and unsuccessful), and
communications with IRBs. Parts of this database will be
made available to the public.
3.1.11 Dispute Resolution Agreement
All members of HBP governing bodies will adhere to a
dispute resolution agreement. The agreement consists
of a preamble recalling the Partners’ commitments, an
ethics statement, operating principles, and a description of the dispute process itself including roles and
responsibilities. The agreement is one of several operating procedures currently under development.
3.1.12 The Foundation
3.1.12.1 Rationale
The Committee was established during the Ramp-Up
Phase by applying criteria and procedures similar to
those used to select the ELSA. The Committee, which is
already in operation, consists of six members.
HBP Foundation
Board
3.1.10.4 Innovation and Technology Transfer
Committee (ITTC)
HBP Platforms
support
Responsibilities
The ITTC is responsible for defining and implementing
HBP policies on issues related to intellectual property
(IP). It acts as an advisory body to the RB and the ExCo
and will work closely with HBP Management to create
and implement the IP scheme for the Project (see
paragraph 2.2.4). It will thus play an important role in
harnessing IP and contributing to the development of
goods and services that can benefit European industry
and European citizens.
Industry R&D
Funding Instruments
IP Licensing
Fundraising
Innovation Hubs
Services
Figure 23: The Foundation: Linkages with the HBP Core Project
The HBP needs to make legally binding contractual
agreements with the Partnering Projects. Such agreements will govern the terms and conditions of the collaboration, reciprocal access rights, use of HBP marks,
licensing, etc. Because the Project does not have a legal
personality, we have examined several options for creating an entity able to act at law on behalf of the HBP and
the FPA Consortium.
The Committee will monitor new IP generated by the
Consortium, and, when required, arbitrate disputes
among Consortium members or between members and
external parties.
The Committee began its operations during the
Ramp-Up Phase starting with a core group composed
of EPFL, CHUV and Heidelberg University. The HBP
ITTC Manager facilitated the core group. Ultimately, the
ITTC will consist of one representative from each of the
10 largest Partners in the HBP Consortium (as defined
by their share of EU funding for HBP research). Where
it deems appropriate, the Committee may invite the
representatives of other universities or organisations
HBP
Foundation
In addition to this immediate requirement, the HBP also
has longer term needs that would best be addressed
by a permanent organisation capable of maintaining an
international network of Partnering Projects, implementing a long-range organisational strategy, fund-raising,
and protecting the HBP’s legacy, identity and know-how.
To find a solution that meets these requirements, the HBP
45
HBP
Core Project
Work Package
Work Package
Work Package
HBP
Foundation
Selection
Integration
Integration
Integration
Partnering Projects
Subproject
Committee
authorizing its use through appropriate agreements,
suspending or cancelling such authorization in the event
of non-compliance and taking appropriate measures
against any misuse; Establishing mechanisms, companies, funds, or other suitable means to facilitate the protection, administration and commercial exploitation of
Intellectual Property for the benefit of the Human Brain
Project; Creating a network of partner organizations in
any part of the world; Cooperating with other organizations whose activities are conducive to these Purposes”.
3.1.12.4 Foundation Governance
Figure 24: Partnering Projects: Linkages with the CP and the Foundation
The Foundation would be entered in the Commercial Register of the Canton of Geneva, Switzerland, and would thereby
be placed under the supervision of the Swiss Federal Department of the Interior.
Central Management Team has benchmarked different
legal forms and locations, applying criteria such as mission,
sustainability, ease of operation, and cost of doing business. A selection of these criteria is listed below:
The Foundation Board (FOB) would be the supreme governing body. Unlike a non-profit association, a foundation does
not require a general assembly. The FOB would be responsible for the distribution of funds in accordance with the Purposes of the Foundation and with the advice of appropriate
technical and scientific experts from within the HBP international network and/or from outside.
Mission and governance
- Entity of indefinite duration designed to perpetuate and
sustain activities and assets
- Non-political, non-commercial mission that is nevertheless
inclusive of government and business stakeholders
The Foundation Secretariat would consist of a professional
staff reporting to an executive director and ultimately, to the
FOB. This staff would be responsible for managing the dayto-day operations of the Foundation. One of its immediate
roles would be to create the framework and support system
for the HBP Partnering Projects. Its activities would also
encompass business development and commercialisation of
the HBP’s scientific discoveries, and could include some management and administrative support to the ICT Platforms.
- Possibility of government participation in governing bodies
- Light, lean decision-making structure
Non-profit and income-generating activities
- Ability to raise funds in the host country and abroad
- Ability to receive EU funding
- Ability to own income-generating subsidiaries and receive
funding through them
- Recognition of public utility and related tax relief offered by
the host country
3.1.12.5 Timescale
Geographic presence
- Ability to create and maintain an international network of
presences.
The Foundation will be established soon after the signing
of the FPA.
3.2 Openness and flexibility
3.1.12.2 Conclusions
3.2.1 How Will we Provide Openness over the
Duration of the Consortium?
The strongest option appears to be a not-for-profit
foundation under Swiss law. This option would match
HBP’s nature as a global research initiative while allowing the new organisation to manage, use and develop
HBP assets, thus promoting commercial exploitation of
discoveries and inventions coming out of the Project
and creating a vehicle for financial sustainability. Once in
operation, the Foundation will seek official recognition of
its international legal personality.
The HBP will be structured to facilitate integration of new
ideas and Partners, both in the Core Project and in Partnering Projects (PPs).
3.2.1.1 The Core Project
The Foundation’s Purposes are still under development
and will be submitted for discussion with the European
Commission, which we expect to play an appropriate and
mutually defined role. They can be provisionally defined
as follows:
The current FPA lists Partners that are expected to participate in the Core Project for the full duration of the
project. Prior to the beginning of a new SGA the RB will
determine the list of partners that will be active in the
coming phase. Where necessary, the RB may introduce
new Partners, introducing new competencies to the Core
Project or strengthening its existing competencies. The
selection process will give priority to Partners who have
demonstrated their potential and competencies in a PP.
“To perpetuate and sustain the activities of the Human
Brain Project, notably by: Ensuring the evolution of the
Human Brain Project’s status to that of a permanent
organization with the appropriate legal status, structure and resources to carry out its mission; Owning
and protecting the identity of the Human Brain Project,
The main mechanism through which independent academic
and industry researchers can become Partners in the HBP
Flagship Initiative will be through the Partnering Projects.
This openness is key to the Flagships ability to remain agile
and at the cutting edge of science. Furthermore, PPs will
3.1.12.3Purposes
3.2.1.2 Partnering Projects (PPs)
46
3.3.1 Management Key Performance
Indicators (M-KPIs)
enable the Flagship to take on board the best research available anywhere in Europe, and beyond.
“High-level” aspects will be monitored via Key Performance Indicators (KPIs), under the supervision of HBP
Central Management. M-KPIs include Resource Metrics,
and metric of Organisation Evolution.
More details on the selection, evaluation and integration
of the PPs can be found in Appendix 1, Chapter 4.
Relations between PPs and the HBP will be regulated by
Partnering Project Agreements (PPA). Partnering Project
Agreements (PPAs) will give new Partners access to the
HBP Platforms, online discussions, meetings, knowledge,
and education facilities. The PPAs will set out principles
and guidelines for cooperation, such as Open Access,
commitment to exploit IP, etc.
Resource metrics track resource allocation and
utilisation, measure progress towards gender and
diversity targets, and show the project’s European and international dimensions. Organisational
evolution metrics, coupled with financial performance
data (see Figures 25 and 27), support decision-making
by tracking top-level results and productivity, enabling
year-on-year comparisons and showing trends in
performance.
3.2.2 Support for Activities Elsewhere in the
Flagship (outside the FPA)
The main beneficiaries of support for activities outside the
FPA will be the Partnering Projects, which together with
the CP constitute the HBP Flagship Initiative. An important pillar will be the HBP’s relationships with national
funding agencies and member/associated state governments, through instruments like FLAG-ERA and its successors, which will contribute to the initial set-up and
funding of PPs. A well-defined and organised integration
process (see Appendix 1, chapter 4) will facilitate seamless scientific integration with the relevant SPs.
Languages Spoken 2011
Arabic
Gender Balance by Country
Bengali
Urdu
Danish
Turkish
Denmark
Dutch
Swedish
Germany
Switzerland
English
Spanish
France
Finland
French
United Kingdom
Female
Serbo
German
Russian
Netherlands
Belgium
Portuguese
Sweden
Austria
Hebrew
Israel
Hindi
Norwegian
Mandarin
Spain
Italian
Japanese
Staff by Country of Origin
Male
10 10
9
9
Women in Senior Roles per Country
9
9
United Kingdom 2%
Austria 3%
Belgium 3%
Denmark 23%
Switzerland 17%
PPs will also receive communications support, including
visibility on HBPs website and digital media, as well as
access to information and marketing materials.
5
5
4
4
3
4
4
3
Sweden 3%
4
3
3
Spain 0%
3
3
Netherlands 11%
2
2
Finland 17%
2
Israel 0%
1
1
1
1
Germany 11%
China
Japan
Serbia
Turkey
Lebanon
USA
Australia
Canada
Pakistan
Bangladesh
India
Israel
Argentina
South Africa
United Kingdom
Italy
Spain
Sweden
France
Germany
Portugal
Netherlands
Austria
FInland
Belgium
The HBP Education Programme and participation in workshops, conferences, and web-based exchanges are open to
all Flagship partners, supporting a productive exchange of
knowledge within the FS. HBP will provide funding for workshops; travel support for students / PhDs / Postdocs will
also be possible. As the Flagship grows, an internal exchange
programme and conference travel grants may be set up.
Denmark
France 6%
Percentage of Staff by Country
Number of Partners per Country
Management 9%
Austria 2
Belgium 1
United Kingdom 3
Denmark 2
Switzerland 3
Finland 1
Other Functions 38%
France 3
Scientific Staff 53%
Sweden 2
PPs will also have access to HBPs international network,
and will be actively integrated in scientific workshops,
conferences, and other networking activities.
Spain 1
Programming 21%
Germany 3
Netherlands 4
Administration 17%
Israel 2
Average Age by Country
Percentage of Researchers by Field
United Kingdom 61
Neurology 10%
IP generated in or jointly with PPs will be integrated in
HBPs databases and innovation support mechanisms,
like the HBP innovation hubs, are fully available to all
Flagship partners.
Sweden 41
Policy 7%
Netherlands 52
Theory 7%
Israel 49
Programming 7%
France 56
CH 5,6%
GR 3,4%
NL 3,4%
SE 5,6%
Data-sharing
Platform Use(gigabytes)
86
JP 2,2%
JP 2,2%
HU 1,1%
Other 8,10%
PT 1,1%
HU 1,1%
3.3 Mechanisms for Monitoring
Progress and Quality Assurance
85%
500
Gross income
88%
Net income
growth rate
Expenditure
Net income
500
ROI
100
74%
80
Expenditure
Net income
Net income growth rate
68%
2014
2015
2016
2017
20
0
2013
100
2015
2015
2016
2016
2017
2017
0
2018
20 2013
15
10
10
10
5
2014
2015
2016
2017
2018
0
85
86700
85
700
90
600
500
80
75
75
80
80
DK 1,1%
200
150
2017
2016
2019
2018
0
2014
2014
2019
70
80
70
2018
2017
80
80
200
70 72
2016
2015
300
80
200
BE 1,1%
CN 1,1%
80
2015
2014
400
80
70
2014
200
150
86
86
200
90
75
2015
2016
2016
2016
2017
2017
2017
2018
2018
2018
2019
2019
2014
2019
0
2015
2014
150
90
80
70
70
70
70
2015
2015
70
70
2016
2015
2017
2016
2018
2017
2019
2018
2014
2019
2015
20
Gross income
Expenditure
Net income
ROI
410
290
250
200
2013
2014
2014 2015
2016
2015
2017
2016
2015
2016
2017
200
120
100
0
10
20
30
40
50
60
70
0
10
20
30
40
50
60
70
20
2018
2017
0
2013
2014
2015
2016
2017
2018
Operating reserve
47
5
2014
86
300
300
120
20
15
5
86
500
80
400
Operating Reserve (months)
Operating reserve
15
0
700
86
85
75
74%
20
2014 2014
20
Operating reserve
Number of G
72
New Fundraising ROI ($100K)
500
200
35%
40
20
2013
Data-sh
1200
1000
800
800
90
PT75
1,1%
70
2014
0
2019
250
200
200
120
20
2013
75
700
85
600
HU 1,1%
FI 1,1%
400
290
35%
100
20
75
68%
60
250
200
40
DE 16,20%
70
70
300
290
60
35%
80
Data in Number of Projects
Data out
88%
80
300
40
86
500
ES 7,9%
410
68%
60
700
86
300
200
2018
ROI
400
74%
Number of Groups
1000
1000
CA 1,1%
New Fundraising
($100K)
AnnualROI
Income
Growth
Gross income
85%
410
1200
72
TK 1,1%
2017
The progress monitoring and quality assurance mechanisms, which the HBP established for the Ramp-Up Phase,
will be retained and strengthened in the Operational Phase.
80
NO700
2,2%
JP 2,2%
85
72
88%
85%
400
70
Figure 26: Sample KPIs for Platform use: (data are fictitious)
Annual
Income Growth
New
Fundraising
ROI ($100K)
100
Net income growth rate
60
80
75800
Other 8,10%
400
FR 7,9%
CN 1,1%
2016
50
Data-sharing
(gigabytes)
Data-sharing
(gigabytes)
80
1000 75
800
600
UK 7,9%
80
BE 1,1%
80
70
2015
40
1200
Data in
Data out
Number Number
of Groups
of Groups Number Number
of Projects
of Projects
72
1000
AT 2,2%
90
75
70
2014
Annual Income Growth
86
PT 1,1%
75
72
100
800
DK 1,1%
DE 16,20%
ES 7,9%
BE 1,1%
CN 1,1%
30
1000
CA 1,1%
DK 1,1%
20
NL 3,4%
800
US 6,7%
FI 1,1%
FR 7,9%
CA 1,1%
DE 16,20%
1200
80
GR 3,4%
CH 5,6%
TK 1,1%
TK 1,1%
FI 1,1%
10
Data-sharing
(gigabytes)
Platform
Use
Data-sharing
(gigabytes)
1200
out
Number Data
of Projects
1000
1000 SE 5,6%
IL 4,5%
CH 5,6%
1000
85
UK 7,9%
Other 8,10%
FR 7,9%
ES 7,9%
Data in
Number of Groups
80
NO 2,2%
US 6,7%
NO 2,2%
US 6,7%
1200
Number of Projects
AT 2,2%
UK 7,9%
Austria 45
Figure 25: Sample corporate metrics (values are fictitious)
NL 3,4%
AT 2,2%
Belgium 60
Laboratory 15%
0
GR 3,4%
IL 4,5%
CH 5,6%
Finland 55
Denmark 38
Circuitry 8%
Platform Use
Number of Groups
IL 4,5%
4
Simulation 7%
Non-research partners (education, dissemination, international organisations, etc.) will receive tailor-made
access to HBPs support functions as part of their engagement with the Flagship.
SE 5,6%
Germany 39
Diagnostics 10%
The HBP Communications and Dissemination Programme
will give visibility to research by the Partnering Projects.
A specially important role will be played by the Museums
Programme which will have a world-wide reach.
CH 5,6%
Spain 66
Biology 11%
Microscopy 5%
CH 5,6%
Switzerland 44
Informatics 8%
Ethics 5%
2018
0
2014
2015
2016
2017
2018
0
10
20
30
Category
Goal
Indicator
Financial
sustainability
Diversification
of the funding
%Funding
by source
Collection
method
Available
from
Legal entity
Post-M31
Traffic light
values
Graphic type
Level
Funding by Source(¤ 100K)
base
25%
8%
Private
Institutions
Countries
NGOs
Foundations
RedAmberGreen
9%
-Board and
Consortium
7%
(WWO)
-Website
34%
Figure 27: Sample KPI table showing progress toward a diversified funding base (data are fictitious)
3.3.2 Quality Assurance of HBP Deliverables
The CTO should also minimise duplication of effort, by
ensuring that the theree review functions share their
reviews with each other as well as with the Subproject
responsible for the Deliverable.
Quality Assurance of HBP Deliverables prior to their finalisation and submission to the European Commission is
ensured by an internal review process, designed to guarantee scientific and technical quality, alignment with
the Research Roadmap and effective communication of
content (document structure and language).
3.3.3 Measuring Scientific Progress
Scientific progress is monitored by the Science and
Technology Office (STO). The STO supplies information
on the monitoring process to the RB, which will take any
required corrective actions
Responsibility for implementing the internal review is
distributed as follows:
The STO collects Scientific Key Performance Indicators
(S-KPIs) on a monthly basis. S-KPIs are numerical values that
show the progress of individual tasks or tasks component
over time. Different tasks involve different types of S-KPIs,
depending on the nature of the activity being monitored.
The Chief Technology Officer (CTO) is responsible for
ensuring that HBP Deliverables are of high scientific quality.
The Science and Technology Office (STO) is responsible for
ensuring that HBP Deliverables are aligned with the Research
Roadmap.
For example, data generation and other production tasks
are measured by counting input or output units. Model
generation activities are measured by percentage completion, usually against time targets.
The Editorial Office is responsible for ensuring that the
structure and language of written HBP Deliverables allow
their contents to be communicated effectively.
Software development is measured by completion of
specified functions, in some cases against a predetermined timetable, in others, using the more flexible SCRUM
methodology. The Subprojects use their S-KPIs for internal monitoring and project management purposes.
The internal review process will be coordinated by the
CTO. To ensure the timely review and submission of successive batches of Deliverables, the CTO will develop
and maintain an overall review timetable, established
in consultation with Subproject leaders and the various
internal review functions. The timetable will communicate clearly in advance to all parties key deadlines
including dates for:
STO officers participate regularly in Subproject committee meetings. Because the STO works across
all the Subprojects, its involvement helps to identify cross-SP needs. The STO’s monitoring activities
also provide the Technology Transfer Office (TTO)
with indicators on emerging innovation potential in
Subprojects work.
Submission by Subproject of outline plan for Deliverable for review
eturn to Subproject of all review comments on outline plan for
R
Deliverable
Submission by Subproject of first draft Deliverable for review
eturn to Subproject of all review comments on first draft
R
Deliverable
Submission by Subproject of final draft Deliverable for review
ubmission of reviewed and approved Deliverable to European
S
Commission
The CTO will organise and monitor the timetable to prevent
blockages by ensuring adequate time for each review.
In particular, the review schedule must be arranged to
avoid multiple Deliverables arriving on one reviewer’s
desk at the same time.
48
MEMBERS OF THE CONSORTIUM
Core Project Partners
P31
P6
P43
P7
P46
P20
P21
P56
P22
P24
P1
P26
P18
P35
P27
P41
P36
P72
P47
P76
P48
P53
P55
P57
P73
P74
P75
P14
P19
P5
P65
P66
P67
P69
P70
P77
P78
50
Members of the Consortium
P2
P25
P81
P10
P11
P17
P45
P29
P82
P33
P34
P79
P23
P80
P68
P4
P37
P39
P44
P42
P54
P84
P15
P32
P30
P49
P8
P58
P61
P85
P12
P9
P13
P16
P28
P40
P50
P38
P71
P59
P60
P62
P3
P63
P64
P51
P83
P52
51
51
SP Personnel
SP2
Javier DeFelipe
Rafael Lujan Nuno Sousa
Robert Williams Francesco Pavone
Jean-François Mangin Sten Linnarsson
Karl Zilles
SP1
John Ashburner
Simon Eickhoff
Jean-François Mangin
Rafael Lujan
Pedro Larrañaga
SP3
Dirk Feldmeyer
Seth Grant
Bruno Weber
Markus Axer
Misha Tsodyks
Douglas Armstrong
Seth Grant
Francisco Clasca
Katrin Amunts
Chris Ponting
Bertrand Thirion
Markus Diesmann
Pierre Magistretti
Chris Ponting
Walter Senn Idan Segev
Viktor Jirsa Olivier Faugeras
Javier DeFelipe
Zoltan Kisvarday
Douglas Armstrong Markus Axer
Gaute Einevoll
Katrin Amunts Pierre Magistretti
Robert Williams
SP4
Nuno Sousa
Jeanette Hellgren-Kotaleski
Abigail Morrison Sonja Grün
Sten Linnarsson Karl Zilles
Alain Destexhe
Sten Grillner Sonja Grün
Paul Tiesinga Jeffrey Muller
Francesco Pavone
Tamas Freund
Neil Burgess
Pedro Larrañaga Katrin Amunts
Minos Garofalakis Martin Kersten
Catherine Zwahlen
Jan Bjaalie
Peter Jonas Seth Grant
Karl Zilles
Fabien Delalondre
Gaute Einevoll Katrin Amunts
Henry Markram Egidio d'Angelo
Fabien Delalondre Wulfram Gerstner Sean Hill
Markus Diesmann Alain Destexhe Paolo Carloni
Sean Hill
Ralph Niederberger
Nuno Sousa
Daniel Mallmann Dirk Pleiter
Nenad Buncic
Kathryn Hess Natalia Manola
Torsten Kuhlen Stefan Eilemann
Peter Buneman Pascal Fua
Felix Schürmann Markus Diesmann
Michael Griebel John Biddiscombe
Felix Wolf
Michele Giugliano Alex Thomson Martin Telefont
Jeanette Hellgren-Kotaleski Marc-Oliver Gewaltig
Pierre Magistretti Felix Schürmann Jan Bjaalie
Luis Pastor Jesus Labarta Thomas Schulthess
Colin John McMurtrie
Kathinka Evers
Sten Grillner Jeffrey Muller Nuno Sousa
Anastasia Ailamaki Marcus Hardt
Anastasia Ailamaki Alexis Brice
Richard Lavery
Javier Bartolome Bernd Schuller
Gabriel Wittum
Andrew Pocklington Ferath Kherif
Antoine Triller Javier DeFelipe
Wolfgang Frings
Andreas Frommer Fabien Delalondre
Michael Owen Thomas Heinis
Bruno Weber Eilif Muller Idan Segev
Bernd Mohr Giovanni Erbacci
Rosa M. Badia Judit Gimenez Klaus Wolkersdorfer
Abigail Morrison Thomas Lippert Vicente Martin
SP7
Michele Migliore Rebecca Wade Karl Zilles
Nenad Buncic Ran Levi
SP6
Anastasia Ailamaki
José M. Peña Fred Hamprecht
SP5
Julian Shillcock
Wulfram Gerstner
Gustavo Deco Shimon Ullman
Richard Frackowiak John Ashburner
Boudewijn Lelieveldt Jean-Marc Orgogozo
Mira Marcus-Kalish
Bogdan Draganski
Alexandra Durr
SP8
Frank Schneider
Peter Buneman Vasilis Vassalos
Mihai PetrovicI
Sašo Džeroski Yannis Ioannidis
Steve Furber Volkan Özguz
Giovanni Frisoni
Markus Diesmann David Lester
Yasar Gürbüz Andrew Davison
Rene Schüffny Erwin Laure
Oswin Ehrmann
Robert Trappl
Patrick van der Smagt Henrik Hautop Lund
Sebastian Höppner Anders Lansner
Yusuf Leblebici Wolfgang Maass
Alois Knoll
Bernd Fröhlich Murray Shanahan
Cecilia Laschi Steve Furber Ville Kyrki
Karlheinz Meier Ulrich Rückert
Sebastian Schmitt Johannes Schemmel
SP9
Gudrun Klinker
SP10
Nuno Sousa
Karlheinz Meier
Silvestro Micera Gregoire Courtine Mark Sagar
Lars Klüver
Fritz Frenkler Jörg Conradt Andreas Engel
Barbara Sahakian
Matias Palva Sten Grillner Auke Ijspert
Bernd Carsten Stahl
Arleen Salles
Claire Marris
Ricardo Sanz Marc-Olivier Gewaltig
Paul Levi Olaf Blanke Mel Slater
Jean-Pierre Changeux
Michael Herzog Peter Hunter
Abdul Mohammed
Eduardo Ros
Kathinka Evers
SP11
Nikolas Rose
Sylvie Renaud
Karlheinz Meier
Alois Saria
Maya Halevy
David Horrigan Jeffrey Muller
Richard Frackowiak Björn Kindler
Nenad Buncic Amanda Pingree
Irina Kopysova Annika Hjelm
Christian Fauteux
Henry Markram
Richard Walker
52
P1
EPFL, École Polytechnique Fédérale de Lausanne (Switzerland)
Laboratory Profile
Launched in 2005, and directed by Prof Henry Markram, the Blue Brain Project (BBP) is the first comprehensive attempt to use detailed modelling and simulation as tools to systematically integrate data about the brain.
The key to the BBP’s strategy is to develop the field of Predictive Neuroinformatics, aimed at accelerating data
integration by using fundamental generalising principles of the brain’s structural and functional organisation,
thus filling huge gaps in knowledge. The BBP also runs a state-of-the-art multi-patch-clamp and molecular and
cell biology experimental lab to validate these principles, the state of the model and the results from the simulations. The BBP has developed a novel suite of software, as well as the workflows that form a coherent platform
for collaborative brain simulation. The BBP has published a series of more than 45 neuroscientific, theoretical,
modelling and computer science papers on data integration, automated modelling and the use of supercomputers for brain simulation, visualisation and analysis, including a paper in a prestigious IEEE journal on a novel
method for visualising detailed neural models. Recently published papers revealing new insights include a paper
in PNAS showing how the connectome can be informatically and algorithmically derived by following biological
rules, two PLoS Computational Biology papers presenting a data-driven strategy to automatically build electrical models of neurons, another on objective classification of neurons, and a J. Physiology paper showing how
in silico synapses match biological synapses and how intrinsic morphological diversity enables robustness and
invariance of synaptic pathways. In 2008 the BBP succeeded in running the first large-scale simulation of a neocortical column, and at the 2012 annual meeting of the Society for Neuroscience (SfN2012) it presented twenty
posters on the detailed reconstruction of the neocortical column. The BBP facility already hosts an extensive
programme of in silico experimentation and is evolving into a true community asset. The BBP has been declared
one of Switzerland’s three National Research Projects, and is composed of some 45 scientists and engineers.
With an annual budget of around CHF20M the BBP will be a major contributor of matching funds and in-kind
support for the HBP.
Key Personnel
Prof. Henry Markram (male) • Executive Committee Member, Chair / SP 5 Leader / SP 11 Leader / WP 5.1
Leader / WP 5.5 Leader / WP 5.8 Leader / WP 11.11 Leader / Research Board Chair - is the founder of the
Brain Mind Institute (EPFL), founder and director of the Blue Brain Project, and the coordinator of the Human
Brain Project. After earning his Ph.D. at the Weizmann Institute of Science (Israel), with distinction, he was a
Fulbright scholar at the National Institutes of Health (USA), and a Minerva Fellow at the Max-Planck Institute for
Medical Research, Germany. In 1995 he returned to the Weizmann Institute, becoming an Associate Professor in
2000. In 2002 he became a full professor at EPFL. Markram’s research has focused on synaptic plasticity and
the microcircuitry of the neocortex, in which he has discovered fundamental principles governing synaptic plasticity (e.g. STDP, RSE, LTMP, neuromodulation) and the structural and functional organisation of neural microcircuitry. Key co-discoveries include the concept of Liquid Computing and the Intense World Theory of Autism. In
2005 he launched the Blue Brain Project to develop a general strategy for data integration in neuroscience and
a specific strategy of predictive reconstruction to make experimental mapping of the brain tractable. Markram
has published over one hundred papers, cited over 17,000 times and has an H-index of 61. Since 2002, Markram
has spearheaded Switzerland’s ambition to become a world leader in High Performance Computing and to prioritise simulation-based research; these fields are now two of the three national research priorities declared by
the Swiss government. Markram is also founder of Frontiers (frontiersin.org), a new model for peer-reviewed
open-access publishing.
Prof. Sean Hill (male) • SP 4 Co-leader / WP 4.1 Leader / WP 4.6 Leader / Research Board Member • is coDirector of the Blue Brain Project and co-Director of Neuroinformatics in the European Union funded Human
Brain Project (HBP) at the École Polytechnique Fédérale de Lausanne (EPFL). Dr. Hill also serves as the Scientific
Director of the International Neuroinformatics Coordinating Facility (INCF) at the Karolinska Institutet in Stockholm, Sweden. Dr. Hill has extensive experience in building and simulating large-scale models of brain circuitry
and has also supervised and led research efforts exploring the principles underlying the structure and dynamics of neocortical and thalamocortical microcircuitry. He currently serves in management and advisory roles on
several large-scale clinical informatics initiatives around the world. After completing his Ph.D. in computational
neuroscience at the Université de Lausanne, Switzerland, Dr. Hill held postdoctoral positions at The Neurosciences
53
P1 EPFL, École Polytechnique Fédérale de Lausanne (Switzerland)
Institute in La Jolla, California and the University of Wisconsin, Madison, then joined the IBM T.J. Watson Research
Center where he served as the Project Manager for Computational Neuroscience in the Blue Brain Project until his
appointment at the EPFL.
Prof. Felix Schürmann (male) • WP 5.2 Leader / WP 6.2 Leader • is adjunct professor at the Ecole Polytechnique Fédérale de Lausanne and co-director of the Blue Brain Project. He studied physics at the University of
Heidelberg, Germany, supported by the German National Academic Foundation. Later, as a Fulbright Scholar,
he obtained his Master’s degree (M.S.) in Physics from the State University of New York, Buffalo, USA, under the
supervision of Richard Gonsalves. During these studies, he became curious about the role of different computing substrates and dedicated his master thesis to the simulation of quantum computing. He studied for his Ph.D.
at the University of Heidelberg, Germany, under the supervision of Karlheinz Meier. For his thesis he co-designed
an efficient implementation of a neural network in hardware. Now, at the Blue Brain Project, he oversees all
computing related aspects such as high performance computing, visualization, computing infrastructure and
computational science and engineering processes.
Dr. Marc-Oliver Gewaltig (male) • SP 9 Co-leader / WP 9.5 Leader / Research Board Member • co-directs the
Neurorobotics subproject of the EU FET Flagship “Human Brain Project” and leads the Neurorobotics Section
of the Blue-Brain Project at the EPFL in Lausanne. In his research, Marc-Oliver Gewaltig investigates the computational properties of the neocortical column in closed action-perception loops. He also has a strong interest
in the computer science for large-scale neural simulations and is co-author of the neural simulation tool NEST
(www.nest-inititive.org). Before joining the EPFL in 2011, Marc-Oliver Gewaltig was Principal Scientist (20032011) and Project Leader (1998-2002) at the Honda Research Institute Europe in Offenbach, Germany, where
he worked on detailed columnar models of information processing in the primate visual cortex and on learning
and plasticity. In 1999, Marc-Oliver Gewaltig received his PhD in Physics for his work on activity propagation in
cortical networks.
Nenad Buncic (male) • WP11.6 Leader • leads IT Services task of the EU FET Flagship “Human Brain Project”
and leads the Core Services Section of the Blue-Brain Project at the EPFL in Lausanne. Nenad Buncic has held
senior positions in different companies and industries. For 6 years he served as a chief information officer and
a director in a company in the financial industry. Prior to that he spent 4 years as a software architect in on-line
media industry. He has also been a member of the ROOT team at CERN where he helped to develop an object
oriented framework for large-scale data analysis. Nenad holds a degree in Computer Science and an MBA in
Management of Technology.
Dr. Fabien Delalondre (male) • leads the High Performance Computing Section of the Blue Brain Project at
the EPFL in Lausanne. The section’s principal tasks include a) the development and optimization of HPC/HTC
scientific applications in collaboration with BBP scientists, b) the development of tools and services to support
and extend the BBP HPC platform and 3) exploring future hardware/middleware/software solutions to enable
Exascale computing. The different tasks involve collaborations with members of both the Brain Simulation and
HPC sub-projects for the EU FET Flagship “Human Brain Project” as well as the Swiss National Supercomputing
Centre (CSCS).
Fabien Delalondre’s research interests include parallel computing and infrastructure, numerical methods and
multiscale modeling, error estimation and adaptation, software engineering. Before joining BBP in 2011, Fabien
was a Senior Research Associate at the Scientific Computation Research Center (SCOREC) in Rensselaer Polytechnic Institute, NY, USA. He received his PhD in Computational Mechanics from Mines ParisTech in 2007
where he worked at the Centre for Material Forming (CEMEF) on the development of parallel adaptive numerical methods to support the modeling of Adiabatic Shear Band (ASB) phenomenon that occurs in high speed
machining.
Stefan Eilemann (male) • leads the visualization team in the Blue Brain Project and Human Brain Project since
2011. His work involves working towards large-scale visualization for Exascale simulations based on the interactive integration of simulation, analysis and visualization. He is the CEO and founder of Eyescale since 2007 and
the lead developer of various open source projects, most notable the Equalizer parallel rendering framework. He
has worked in SGI’s Advanced Graphics Division from 2000 to 2003 as the technical lead of OpenGL Multipipe
SDK - a toolkit for scalable, parallel visualization software on shared memory supercomputers. He received his
Engineering Diploma in Computer Science in 1998.
54
Dr. Eilif Muller (male) • leads the In Silico Experimentation section of the Blue Brain Project at EPFL, which
develops and continuously refines anatomically and physiologically accurate in silico reconstructions of neocortex, to investigate the biological principles of its function and dysfunction. Research topics of his section include
detailed neuron modeling and dendritic computation, network structure-function relationships, synaptomics,
regimes of network dynamics, reliability of information processing, methods for reconstruction and validation,
tissue biophysics, and synaptic and microcircuit plasticity. Eilif received his BSc (honours) in mathematical
physics from Simon Fraser University, Canada in 2001, and his PhD in physics from the University of Heidelberg,
Germany in 2007 for developing analytical approaches to understand how neuronal ensemble dynamics are
determined by intrinsic neuronal properties.
Jeffrey Muller (male) • WP5.7 Leader • After working as a self-taught software developer and manager in the
game industry for 5 years, Jeff decided to go back to school. He received a Bachelor’s of Mathematics from
the University of British Columbia in 2003. Upon completion of his degree, he became a freelance software
developer and entrepreneur. In the 10 years prior to joining the Blue Brain, he owned and ran a contract software development company working in the areas of sonar imaging, computer vision and highly interactive web
applications. He has held senior management and executive positions in the game development and logistics
software industries. In the Blue Brain Project, Jeff leads the Platform Development team. The Platform Development team is working to build the Unified Portal (UP), a web-based collaborative research platform. The UP is
intended to integrate the work of the various Subproject Platform teams into a cohesive intuitive user interface.
The UP also provides a common layer of web services which can be used by Scientific Developers to develop
and share provenance-tracked, web accessible analysis capabilities
Dr. Julian Shillcock (male) • leads the Algorithm Development Section of the Blue Brain Project at the EPFL in
Lausanne. The Section’s principal tasks are to create in silico representations of neurons for electrical simulation and to construct computational models of their sub-cellular dynamics. This work involves collaborations
with members of the Brain Simulation subproject of the EU FET Flagship “Human Brain Project” who design
and perform molecular dynamics and coarse-grained simulations of neuronal biochemistry. Julian Shillcock’s
research involves performing coarse-grained molecular simulations of the dynamics of cellular membranes,
the fusion of synaptic vesicles, and the interactions of membranes with proteins and engineered nanoparticles.
Before joining the EPFL in 2011, Julian Shillcock was Associate Professor at the University of Southern Denmark
(2007-2011) and a Group Leader at the Max Planck Institute of Colloids and Interfaces in Golm, Germany (19992007). He received his PhD in Physics from Simon Fraser University, Canada, for his work on Monte Carlo simulations of fluid and polymerised membranes under stress.
Nenad Buncic (male) - WP11.6 Leader - leads IT Services task of the EU FET Flagship “Human Brain Project”
and leads the Core Services Section of the Blue-Brain Project at the EPFL in Lausanne. Nenad Buncic has held
senior positions in different companies and industries. For 6 years he served as a chief information officer and
a director in a company in the financial industry. Prior to that he spent 4 years as a software architect in on-line
media industry. He has also been a member of the ROOT team at CERN where he helped to develop an object
oriented framework for large-scale data analysis. Nenad holds a degree in Computer Science and an MBA in
Management of Technology.
Dr. Martin Telefont (male) • leads the data integration section of the Blue Brain Project at EPFL. This group
of scientists and engineers leads the semi-automatic integration of historic key datasets, and the development
of workflows for automatic ingestion and registration of novel data sets made available by HBP partners and
contributors. As part of this work, the group provides tools and guidance to members of the HBP Consortium,
and the biomedical community at large, to perform data integration and curation using the framework developed by and for the HBP. During his university education, Telefont used histological, molecular, behavioural and
pharmacological techniques to answer questions concerning development, molecular mechanisms of sexual
response, and social and anxiety-related behaviour. He performed high data throughput experiments during
his PhD, which led to his work in data organisation, information extraction and knowledge engineering. Telefont
continued this work after joining the Blue Brain Project in 2010, and as part of the HBP, has taken on a crossdiscplinary role to coordinate the integration of all HBP laboratory data.
Dr. Catherine Zwahlen (female) • WP4.5 Leader • received her Ph.D in Physical Chemistry in 1994 from the University of Lausanne, Switzerland with a dissertation in NMR spectroscopy. As a post-doctoral fellow at the University of Toronto, she focussed her work on protein structure determination. During that time, she became interested
in bioinformatics and its application to predicting protein structure. In 2001, she joined GeneProt, a proteomic
start-up company, to model protein structures and later to develop bioinformatic pipeline for proteomic data
analysis. In the following years, Catherine has participated in the development of different bioinformatic projects
focussed on the modelisation of information of human proteins. She has joined the Human Brain project as section
manager in data mining early 2014.
55
Laboratory Profile
The Data-Intensive Applications and Systems (DIAS) laboratory focuses on database systems and applications. Researchers in the laboratory adapt data management technology to computer architecture trends by
designing data manipulation techniques that make optimal use of the underlying hardware and I/O devices. By
automating physical database design for complex datasets, and revolutionising access methods for specialised
data structures and scientific models, DIAS research enables new scientific discoveries Headed by Anastasia
Ailamaki, DIAS laboratory results are regularly featured in top database conferences and journals, such as ACM
SIGMOD and VLDB. Recent honours awarded to colleagues, he has received the Best Paper Award at ICRA2002
(the largest conference in robotics), the Industrial Robot Highly Commended Award at CLAWAR2005, and Best
paper award at Humanoids 2007.
Key Personnel
Prof. Anastasia Ailamaki (female) • SP 7 Co-leader / WP 7.1 Leader / Research Board Member • is a Professor of Computer Sciences at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland. She earned
her Ph.D. in Computer Science from the University of Wisconsin-Madison in 2000. Her research interests are in
database systems and applications, specifically in strengthening the interaction between the database software
and the underlying hardware and I/O devices, and in automating database design and computational database
support for scientific applications. She has received a Finmeccanica endowed chair from the Computer Science
Department at Carnegie Mellon (2007), a European Young Investigator Award from the European Science Foundation (2007), an Alfred P. Sloan Research Fellowship (2005), six best-paper awards at top conferences (20012006), and an NSF career award (2002). Ailamaki will co-direct the Medical Informatics Subproject and direct
the Big Data management research.
Laboratory Profile
The research of the Laboratory of Computational Neuroscience at EPFL focuses on theoretical and computational neuroscience, with a special emphasis on synaptic plasticity and learning in networks of spiking neurons.
The laboratory is headed by Professor Wulfram Gerstner and is affiliated with the school of Computer and
Communications Sciences and the school of Life Sciences. The staff of about fifteen lab members includes
about ten PhD students, three post-docs, as well as students working on semester and master projects, and a
half-time administrative assistant. The lab is equipped with state- of-the art computers and receives generous
basic funding from the Swiss Federal Government. The lab has on-going collaborations with experimental neuroscientists at the EPFL and with other theory groups in Switzerland.
Key Personnel
Prof. Wulfram Gerstner (male) • WP3.3 Leader • is the director of the laboratory. He studied physics at the
universities of Tubingen and Munich and received a Ph.D. from the Technical University of Munich. His research
in computational neuroscience concentrates on models of spiking neurons and spike-timing dependent plasticity, on neuronal coding in single neurons and populations, and on the role of spatial representation for navigation of rat-like autonomous agents. He currently has a joint appointment at the School of Life Sciences and the
School of Computer and Communications Sciences, where he teaches courses for physicists, computer scientists, mathematicians, and life scientists.
56
Laboratory Profile
The Laboratory of Neuroenergetics and Cellular Dynamics (LNDC) works to unravel the intimate metabolic
and functional connections between glia and neurons in the central nervous system. One of the group’s most
important goals is to identify the mechanisms that couple neuronal synaptic signals to the entry of glucose into
the brain parenchyma and the provision of energy substrates to neural tissue. The laboratory is also interested
in on‐line microscopic imaging techniques for the visualisation of dynamic cellular processes, including those
involved in plasticity. The lab collaborates with the LNC and with the Advanced Photonics Laboratory in the
application of digital holographic microscopy combined with atomic force microscopy, fluorescence microscopy
and other coherent imaging approaches.
Key Personnel
Prof. Pierre Magistretti, MD, Ph.D. (male) • is the Director of LNDC research unit at the EPFL. The author of
over a hundred and fifty publications, he has been elected to the International Chair 2007-2008 of the Collège
de France, Paris, and is a member of Academia Europeae and of the Swiss Academy of Medical Sciences. He
served as the secretary-general of the International Brain Research Organization (IBRO), from 2010 – 2012,
and is currently its President. He was also the president of the Federation of European Neuroscience Societies
(FENS). Since 2010, he has been Director of the National Center for Competence in Research (NCCR) of the
Swiss National Science Foundation.
Laboratory Profile
The Microelectronic Systems Laboratory (LSM) at EPFL operates as a part of the Institute of Electrical Engineering (IEL). Its main areas of research include design and implementation of high-performance digital and
mixed-signal VLSI circuits, language-based modelling and validation of SoC components, neuromorphic / bioinspired system architectures, and integration of novel technologies for complex system design. The teaching
objective of LSM is to offer comprehensive undergraduate and graduate education programmes in digital /
mixed-signal IC design and VLSI system design to our Electrical Engineering and Microengineering (Microtechnique) students. Lab facilities include a state-of-the-art EDA environment for VLSI design, as well as test and
measurement labs for detailed chip-level and system-level characterisation.
Key Personnel
Prof. Yusuf Leblebici (male) • has degrees from Istanbul Technical University and the University of Illinois
at Urbana-Champaign (UIUC) and has been active in the field of computer and electrical engineering since
1990. Between 1991 and 2001, he worked as a faculty member at UIUC, at Istanbul Technical University, and at
Worcester Polytechnic Institute (WPI). Since 2002, he has been a Chair Professor at EPFL, and director of the
Microelectronic Systems Laboratory. His research interests include the design of high-speed CMOS digital and
mixed-signal integrated circuits, computer-aided design of VLSI systems, intelligent sensor interfaces, modelling
and simulation of semiconductor devices, and VLSI reliability analysis. He has authored five major textbooks on
VLSI circuits, and received many honours from the IEEE.
57
Laboratory Profile
The Homotopy Theory Group (GR-HE), led by Prof. Kathryn Hess Bellwald, focuses on algebraic topology and
its applications. Homotopy theory, category theory and knot theory are particular areas of expertise of the
research group. Group members are also involved in research projects concerning applications of algebraic
topology in breast cancer research (topological data analysis applied to microarray data) and neuroscience
(homology of Blue Brain-simulated microcircuits, category-theoretic models of brain function).
The Homotopy Theory Group consists of two permanent, senior faculty members, two postdocs and several
graduate students. Each year group members supervise numerous student and masters research projects. The
group organizes a weekly seminar, in which the group’s many visitors participate.
Key Personnel
Prof. Kathryn Hess Bellwald (female) • obtained her PhD in mathematics from the Massachusetts Institute of
Technology, then was a postdoc at the University of Stockholm, the University of Nice, the University of Toronto,
and the EPFL. She is now professor of mathematics and Director of the mathematics PhD program at the
EPFL. She is an algebraic topologist, with an extensive publication record primarily in pure mathematics, but
with a long and varied history of interdisciplinary collaboration. She has participated in or supervised projects
involving applications of topology in polymer science, theoretical computer science (distributed computing and
concurrency), dynamical systems with applications to atomic physics, neuroscience and breast cancer research.
Laboratory Profile
The Biorobotics Laboratory (BIOROB) Lab has worked extensively on neuromechanical models of animal locomotion and dynamical system control for articulated robots and for exoskeletons. It has developed several
numerical models of animal motor control, including models of central pattern generators and motor primitives.
The lab is a pioneer in using robots as tools for testing hypotheses concerning the organization of motor circuits,
in particular of spinal cord circuits. It has developed and/or worked with a large variety of robots from lampreylike, salamander-like, cat-like up to humanoid robots.
Key Personnel
Prof. Auke Ijspeert • is the director of the Biorobotics Laboratory (BIOROB) and associate professor in the
School of Engineering at EPFL. He has a BSc/MSc in Physics from the EPFL (1995), and a PhD in artificial intelligence from the University of Edinburgh (1999). He as carried out postdocs at EPFL and at the University of
Southern California. His research interests are at the intersection between robotics, computational neuroscience, nonlinear dynamical systems, and machine learning. He uses numerical simulations and robots to get a
better understanding of the functioning of animals, and inspiration from biology to design novel types of robots
and adaptive controllers. He has published over 150 peer-reviewed articles (some of them in high impact journals such as Science). With his colleagues, he has received the Best Paper Award at ICRA2002 (the largest conference in robotics), the Industrial Robot Highly Commended Award at CLAWAR2005, and Best paper award
at Humanoids 2007.
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Laboratory Profile
The Translational Neural Engineering Laboratory (TNE) Lab mission is to develop effective neurotechnologies
to restore sensorimotor function in people affected by different kinds of disabilities by translating neuroscience
findings into clinical practice. We are currently working on neurocontrolled bidirectional prostheses, implantable
neuroprostheses to restore locomotion, and wearable robotics for assistance and rehabilitation.
Key Personnel
Prof. Silvestro Micera (male) • is the director of the TNE Lab and associate professor in the School of Engineering and at the Center for Neuroprosthetics at EPFL. He received the University degree (Laurea) in Electrical
Engineering from the University of Pisa, in 1996, and the Ph.D. degree in Biomedical Engineering from the Scuola
Superiore Sant’Anna, in 2000. From 2000 to 2009, he has been an Assistant Professor of BioRobotics at the
Scuola Superiore Sant’Anna where he is now Professor and the Head of the Translational Neural Engineering
Area. In 2007 he was a Visiting Scientist at the Massachusetts Institute of Technology, Cambridge, USA with a
Fulbright Scholarship. From 2008 to 2011 he was the Head of the Neuroprosthesis Control group and an Adjunct
Assistant Professor at the Institute for Automation, Swiss Federal Institute of Technology, Zurich, CH. In 2009
he was the recipient of the “Early Career Achievement Award” of the IEEE Engineering in Medicine and Biology
Society. From 2011 he is Associate Professor and Head of the Translational Neural Engineering Laboratory at the
EPFL. He is author of more than 100 ISI scientific papers and several international patents. He is currently Associate Editor of IEEE Transactions on Biomedical Engineering and of IEEE Transactions on Neural Systems and
Rehabilitation Engineering. He is also member of the Editorial Boards of the Journal of Neuroengineering and
Rehabilitation, of Journal of Neural Engineering, and of the IEEE Journal of Translational Engineering in Health
and Medicine.
Laboratory Profile
International Paraplegic Foundation Chair in Spinal Cord Repair (G-Lab) Our mission is to design innovative
interventions to restore sensorimotor functions after neurological disorders and to translate these findings into
effective clinical applications to improve the quality of life for people with neuromotor impairments. To achieve
this goal we are developing neuroprosthetic systems, robotic interfaces and advanced neurorehabilitation procedures that we combine with neuroregenerative interventions. Using genetically modified mice, optogenetics,
and novel viral tools, we also seek to uncover the neural mechanisms underlying the control of locomotion in
intact animals, as well as the processes that reestablish motor functions after neuromotor disorders.
59
Key Personnel
Prof. Grégoire Courtine (male) • holds the International Paraplegic Foundation Chair in Spinal Cord Repair and
is Associate Professor at the School of Life Sciences, Brain Mind Institute and the Center for Neuroprosthetics at
EPFL. He was trained in Mathematics and Physics, but received his PhD degree in Experimental Medicine from
the University of Pavia in Italy and the INSERM Plasticity and Repair, France, in 2003. After a Post-doctoral training at the University of California (UCLA), he established his own laboratory at the university of Zurich in 2008.
He accepted the International paraplegic foundation (IRP) chair in spinal cord repair in the center for neuroprosthetics at the Swiss Federal Institute of Technology, Lausanne (EPFL) in 2012. Over the past 15 years, Grégoire
Courtine has implemented an unconventional research program with the aim to develop radically new treatment paradigms to restore motor function in severely paralyzed people. Recently, he and his team introduced a
neuroprosthetic rehabilitation procedure that restored supraspinal control over complex locomotor movements
in rats with a spinal cord injury leading to permanent paralysis. He received numerous honors such as the 2008
UCLA Chancellor’s award, the 2009 Schellenberg Prize for his advances in spinal cord repair, the 2013 Debiopharm Prize, and a starting grant and a Proof-of-Concept grant from the European Research Council (ERC) in
2010 and 2014. Several of his works received substantial press coverage in the national and international media.
Laboratory Profile
Research at the Laboratory of Cognitive Neuroscience (LNCO) at the EPFL is carried out by a multidisciplinary
team of biologists, psychologists, medical doctors, physicists, engineers and computer scientists. We focus
our investigations on the functional and neural mechanisms of body perception, corporeal awareness, and self
consciousness. Projects rely on the investigation of healthy subjects as well as neurological patients (that suffer
from selective neurocognitive deficits and illusions) by combining psychophysical and cognitive paradigms with
state of the art neuroimaging techniques such as intracranial EEG, surface EEG, fMRI, and Virtual Reality. Our
main goals are to develop neuroscientific models of body perception, corporeal awareness, and self consciousness by linking complex phenomenological experience of body and self to brain mechanisms of multisensory
corporeal perception (vestibular, visual, proprioceptive, and tactile information).
Key Personnel
Prof. Olaf Blanke (male) • is founding director of the Center for Neuroprosthetics, Bertarelli Foundation Chair
in Cognitive Neuroprosthetics at the Swiss Federal Institute of Technology (Ecole Polytechnique Fédérale de
Lausanne, EPFL). He also directs the Laboratory of Cognitive Neuroscience at EPFL and is Professor of Neurology at the Department of Neurology at the University Hospital of Geneva. Blanke’s research is dedicated to the
neuroscientific study of multisensory body perception and its relevance for self-consciousness by using a broad
range of methods such as the neuropsychology, invasive and non-invasive electrophysiology, and brain imaging
in healthy subjects, neurological and psychiatric patients. Most recently he has pioneered the joint use of engineering techniques such as robotics and virtual reality with techniques from cognitive neuroscience and their
application to systems and cognitive neuroprosthetics and neuro-rehabilitation.
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Laboratory Profile
One of the premiere psychophysics laboratories, the Laboratory of Pyschophysics (LPSY) uses TMS, EEG,
and mathematical modelling to study visual information processing in humans. Key topics of research include
feature integration, contextual modulation, the time course of information processing, and perceptual learning,
and mathematical modelling. Clinical studies at the lab have investigated deficits of visual information processing in schizophrenic patients.
Key Personnel
Michael Herzog (male) • A student of mathematics, biology and philosophy, Prof. Michael Herzog has studied
at the Universities of Erlangen, Tübingen and MIT in the USA. His main interest, however, is the wide field of
visual perception. He obtained his Ph.D. under the supervision of Prof. Fahle at the Section of Visual Science
(Tübingen) and Prof. Poggio at MIT. After a short post-doctoral stint with Prof. Koch at Caltech, he was a senior
researcher at the University of Bremen and a temporary professor at the University of Osnabrueck (Germany).
Since 2004, he has been professor of psychophysics at the Brain Mind Institute (BMI) at the EPFL.
Laboratory Profile
Headed by Pascal Fua, the research activities of the Computer Vision Laboratory (CVLab) focus on shape and
motion recovery from images, including the modelling of neural structures from Electron and Light Micrographs,
fast object detection, and real-time reconstruction of deformable 3D surfaces. The CVLab also provides undergraduate and graduate teaching and performs technology transfer for start-up and established companies. Its
current staff includes one professor, one senior scientist, six post-doctoral fellows and twelve doctoral students
and it is funded by the Swiss Federal Institute of Technology, the National Swiss Research Foundation, and the
Federal Office for Education and Science and by several European Union projects, including a senior ERC grant.
Key Personnel
Prof. Pascal Fua (male) • is an alumnus of the Ecole Polytechnique in Paris and the University of Orsay. He
joined EPFL (Swiss Federal Institute of Technology) in 1996 and is now a Professor in the School of Computer
and Communication Science. He has previously held positions as a computer scientist at SRI International and at
INRIA Sophia-Antipolis. His research interests include shape modelling and motion recovery from images, analysis of microscopy images, and Augmented Reality. He has been an associate editor of IEEE journal Transactions
for Pattern Analysis and Machine Intelligence and has often been a programme committee member, area chair,
and programme chair of major vision conferences.
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P2
AALTO-KORKEAKOULUSAATIO
(FINLAND)
Laboratory Profile
The Department of Electrical Engineering and Automation began operating on 1 January 2014. It represents
the merger of three departments: Automation and Systems Technology, Electronics and Electrical Engineering.
All three departments have had significant shared research interests and have worked with common industrial
partners. The new department is an ecosystem where scientists and engineers from different fields interact and
work together by crossing traditional boundaries to solve the most challenging scientific and technological
problems, provide an excellent education and produce greater wellbeing for society in general. Our interdisciplinary team, which combines expertise from microsystems, electrical engineering and automation, will expand
scientific and technological knowledge. Our mission is to contribute to society through innovations, education
and research at the highest international level. The total size of the staff is 180, including 16 tenured professors.
Key Personnel
Prof. Ville Kyrki (male) • joined the School of Electrical Engineering at Aalto University as an Associate Professor in 2012. He serves as the head of the Intelligent Robotics research group. His research interests lie mainly in
intelligent robotic systems and robotic vision with a particular emphasis on developing methods and systems
that cope with imperfect knowledge and uncertain senses. His published research covers feature extraction and
tracking in computer vision, visual servoing, tactile sensing, robotic grasping, sensor fusion (especially fusion of
vision and other senses), planning under uncertainty, and machine learning related to the previous. His research
has been published in numerous forums in the area, including IEEE Transactions on Robotics, International
Journal of Robotics Research, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Haptics, and IEEE Transactions on Image Processing.
62
P3
LUMC, Academisch Ziekenhuis Leiden
Leids Universitair Medisch Centrum (Netherlands)
Laboratory Profile
The Division of Image Processing (LKEB, www.lkeb.nl) is a research group within the Department of Radiology, and has a strong track record in developing and publishing innovative biomedical image and data analysis
algorithms, and transferring these to industry under strict software quality standards (e.g. Companies such as
Medis, GE, Toshiba, Agfa, Terumo, Lightlab, Volcano, Boston Scientific). In addition, we have experience with
open-source code distribution, as evidenced by the LKEB-co-developed elastix platform for non- rigid image
registration (> 25000 downloads). This way of working has resulted in several widely used clinical software
packages, some of which have been recognized as de-facto standard in the field, in combination with a strong
publication track record. LKEB’s collaboration with the Pattern Recognition and Bioinformatics group in Delft
embodied in the research team on mining the Allen Brain Atlas gives access to state-of-the-art pattern analysis
and bioinformatics expertise, while its position within the Leiden University Medical Centre connects LKEB to
state-of-the-art neuroscience research.
Key Personnel
Prof. Boudewijn Lelieveldt (male) • is full professor of Biomedical Imaging at the Department of Radiology,
Leiden University Medical Centre, Leiden, the Netherlands, where he is heading the Division of Image Processing
(LKEB). He is also appointed at the Pattern Recognition and Bioinformatics group, faculty of Electrical Engineering, Mathematics and Computer Science at the Delft University of Technology, Delft, the Netherlands. He
is PI of two grants on data analytics from the Dutch Technology Foundation (STW) of combined imaging and
genetic data, and co-PI of the 6 Meuro STW Perspective program IMAGENE on population imaging genetics. He
is currently heading a project on interactive analysis of distributed patient data via secure lightpaths and cloud
infrastructures. He has participated in several FP7 projects (ENCITE, EMIL, DIMI, BRAINPATH), developing dedicated analysis methods for the latest longitudinal small animal imaging modalities. He recently co-initiated the
“Genes in Space” research team of five image analysis scientists and bioinformaticians with sole focus on mining
the Allen Brain Atlas (both mouse and human) to link transcriptomic, proteomic and in-vivo imaging data. He
has published > 120 peer-reviewed full papers in journals and conference proceedings.
Prof. Marcel Reinders (male) • is full professor at Electrical Engineering, Mathematics and Computer Science at
the Delft University of Technology, Delft, the Netherlands, and he has a secondary appointment with the Leiden
University Medical Centre, Leiden, the Netherlands. In Delft he heads the Pattern Recognition and Bioinformatics
group that conducts research into pattern recognition, computer vision and bioinformatics. For his own research
he focuses on bioinformatics research where couples the development of data-driven analysis methodologies
with progressing molecular biology insights using his tools (for which he intensely collaborates with numerous
molecular biologists). He initiated work on molecular classification and genetic network modelling. Nowadays
he focuses on sequencing analysis tools, network-based analysis, and integration of genomic data. He has ample
experience with finding gene signatures, also with applications in brain data (both Alan Brain Atlas data, as well
as neurodegenerative data, such as data from Alzheimer’s patients). He (co-)authored more than 250 scientific
papers of which more than 110 in peer- reviewed journals (h-factor=39, i10=98,>5500citations). He is scientific
director of Netherlands Bioinformatics Centre and he managed over 25 projects, among which Dutch Science
Foundation and European projects.
Dr. Laurens Van der Maaten (male) • is an Assistant Professor at Delft University of Technology with a secondary appointment at the Leiden University Medical Centre. Before accepting his current position, he worked
as a postdoctoral researcher at University of California San Diego and as a Ph.D. student at Tilburg University
and University of Toronto. His main expertise is in machine learning and data mining, with a particular focus on
machine learning for data visualization, (Bayesian) probabilistic graphical models, and learning from Big Data.
He has participated as a PI in several European projects (INSIDDE, SALIG++). His research is also supported by
two research grants from the Netherlands Organization for Scientific Research (NWO). He has received multiple
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P3 LUMC, Academisch Ziekenhuis Leiden - Leids Universitair Medisch Centrum (Netherlands)
awards for his work, among which the SNN Machine Learning Award 2012 for the most influential achievement
in machine learning in the Netherlands. He is regularly invited as a guest speaker by data analytics companies
and research institutes (e.g., Google and the Mind Research Network), who acknowledge the immense potential
of the t-SNE developed by dr van der Maaten. He has published over 50 peer-reviewed papers in journals and
conference proceedings.
Prof. Arn van den Maagdenberg (male) • is full professor at the Departments of Human Genetics and Neurology, Leiden University Medical Centre, where he is heading the molecular and functional neurogenetics research
aimed at unravelling disease mechanisms for devastating paroxysmal neurological disorders, with a main focus
on migraine and epilepsy. He and his colleagues at the Neurology Department made highly important contributions to the field that include spearheading the identification of genes for rare monogenic and common polygenic migraine (in active collaboration with geneticists worldwide including those at the Sanger (Hinxton, UK)
and the Broad institute (Boston, USA)), the generation and characterisation of unique migraine mouse models
with patient-specific gene mutations, and various types of clinical research. Together with his close clinical colleague Prof. Michel Ferrari, he is the coordinator of the recently funded 6Meuro FP7 EU grant EUROHEADPAIN
that will start in early 2014. He has also been involved in various FP5, FP6, and FP7 projects and is currently the
host for two Marie Curie fellows and co-PI of BRAINPATH for which he will integrate multi-level electrophysiological and imaging data to understand better the comorbidity between migraine and stroke. His translational
research activities also involve the collection and analysis of patient and mouse material with various genetic
(i.e. at the DNA, RNA and protein level), electrophysiological, and imaging approaches. His multidisciplinary data
is ideally suited for an interactive analysis as proposed in the current application and builds on a prior initiative
of close colleague Prof. Lelieveldt, who is co-PI of “Genes in Space” analysis that intends to mine the Allen Brain
database (both mouse and human) and link it with transcriptome, proteome and imaging data. Through his
clinical team van den Maagdenberg will have full access to human data. He has published > 160 peer-reviewed
full papers.
Dr. Willeke van Roon (female) • is assistant professor at the Human Genetics department of the Leiden University Medical Centre. She acquired extensive expertise on working with human brain material studying the genetic
and molecular disease pathology. Since her return to the Netherlands she has been the Principal Investigator of
the Huntington’s Disease Research group in Leiden studying transcriptional changes in a cell model of HD. These
studies have successfully been extended to protein profiling and gene expression profiling in blood from HD
patients. Aim of these studies is to unravel novel biomarkers of HD disease progress and pathology. Another line
of research concerns studying epigenetic changes in HD and the regulation of transcription at the HTT locus.
To this end, the levels of transcription at the HTT locus and differences in binding of DNA binding proteins is
studied in patient derived cells. A major line of her research is the development of therapeutic strategies for HD
and other neurodegenerative disorders. Small antibodies (VHH), specific for the huntingtin protein, are being
selected and expressed intracellular to investigate if binding of these antibodies reduce mutant huntingtin toxicity. Finally, she is investigating the use of antisense oligonucleotides as a promising therapeutic tool for HD
and other neurodegenerative disorders. Integration of molecular mechanisms, genome wide next generation
sequencing data sets and relating this back to disease specific mechanisms is an important feature of her work.
Dr. Martijn van de Giessen (male) • Martijn van de Giessen graduated as MSc from the faculty of electrical
engineering at the Delft University of Technology in 2005 on the subject of vision based control of a zeppelin.
Subsequently he was a PhD candidate at the physics department at the Delft University of Technology. His
research there was in the field of medical image processing and focused on statistical modeling of both shape
and motion of the wrist. This work resulted in a model that detects ligament damage based on pathological
wrist movement and that serves as an aid for surgical planning by estimating the healthy motion trajectory of
a pathological wrist. Currently Martijn is employed as a post-doctoral researcher in the field of image guided
surgery, specifically for tumor imaging using near-infrared fluorescence. To this end new methods are being
developed for motion correction, spectral unmixing and diffuse optical tomography. Furthermore, he assists in
the development of a new intra-operative camera system for near-infrared fluorescence imaging.
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P4
AUEB, Athens University of Economics and Business (Greece)
Laboratory Profile
The ISD Laboratory was founded in 1994 and comprises more than 35 people (10 faculty members, 10 postdoctoral researchers, over 10 Ph.D. students, Master’s students, engineers and programmers). It conducts research
and consulting on a wide range of topics and supports the Informatics Department’s Master’s programs. Current
areas of research activity include knowledge representation and conceptual modelling, ontologies, data integration, theory and systems for database management, management of non-traditional data including streaming/sensor, XML/semistructured, RDF, and text data, peer data management, semantic data access, data and
knowledge mining, big data algorithms and systems, security of information systems and critical infrastructures,
digital archiving, digital libraries, software engineering, and software testing. The Lab participates in a large
number of European and national research projects, including ARISTEIA awards and Marie Curie fellowships, as
well as advanced development and consulting projects for public and private sector organizations.
Key Personnel
Prof. Vasilis Vassalos (male) • is an Associate Professor at the Department of Informatics of the Athens University of Economics and Business. He holds a Ph.D. And M.Sc. in Computer Science from Stanford University
(2000 and 1998 respectively) and a Diploma in Electrical Engineering from the National Technical University
of Athens (1994). Prof. Vassalos has published more than 45 research papers in the areas of databases and the
Web and holds 2 US patents for work on information integration. He has led many research projects in the areas
of online distributed information processing and was a co-founder of a successful innovative startup company
in the space of Enterprise Information Integration (Enosys Software, acquired by BEA Systems in 2003). Ηe
has been a Visiting Professor at UCSD (2007-2008) and EPFL (2013), and a Marie Curie Outgoing International
Fellow in 2007-2008 and he has received numerous fellowships and awards. His research interests include database and information systems, data integration, query processing with a focus on non-traditional data, including
sensor data, text, and XML, Big Data processing and data analytics, He has been working on the challenges of
online processing of data from autonomous sources since 1996.
Dr. Tassos Venetis (male) • is currently a postdoctoral researcher at the Athens University of Economics and
Business. He received his diploma in Electrical and Computer Engineering from the National Technical University
of Athens in 2005, and his PhD from the same department in 2014. Since receiving his diploma he has participated in many Greek and European funded R&D projects, like VideoActive, Boemie and EUScreen. His research
interests include Data Integration as well as Knowledge Representation and Reasoning focused on Description
Logics and Ontology Based Data Access. He has published 7 articles in highly prestigious journals and conferences. He is leading the development of data integration tools for WP7.1 Clinical Data Infrastructure.
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P5
BSC, Barcelona Supercomputing Center
Centro Nacional de Supercomputación (Spain)
Laboratory Profile
The Barcelona Supercomputing Center (Centro Nacional de Supercomputación, BSC-CNS), was established
in 2005 and serves as Spain’s National Supercomputing Facility. The Center hosts and operates MareNostrum, the
most powerful supercomputer in Spain. Currently headed by Mateo Valero, the BSC is a consortium that includes
the Spanish Ministry of Economy and Competitivity, the Department of Economy and Knowledge of Catalunya
and the Universitat Politècnica de Catalunya (UPC). BSC-CNS’s mission is to develop and manage cutting-edge
information technology tools for scientific research. To further these goals, the BSC-CNS has brought together
a group of over 250 Spanish and more than 100 international researchers. In 2011, the Center won recognition
as a “Severo Ochoa Centre of Excellence” for its major contributions in the area of computing and applications.
Key Personnel
Prof. Mateo Valero (male) • is director of the Barcelona Supercomputing Center and professor at the Computer
Architecture Department, UPC, Barcelona. A renowned researcher on high performance computer architectures, he has been honoured with the Eckert-Mauchly Award, the Harry Goode Award, the King Jaime I Award
for Research, two national awards for informatics and engineering as well as honorary doctorates from the Universities of Chalmers, Belgrade, Las Palmas, Zaragoza and Veracruz. An Intel Distinguished Research Fellow, a
fellow of the IEEE and a fellow of the ACM, he is a member of the Royal Spanish Academy of Engineering, the
Spanish Royal Academy of Science, the Royal Spanish Academy of Doctors, and the Academia Europaea. The
European IST Programme has nominated him as one of the twenty-five most influential European researchers in
IT. He has been awarded with an ERC Advanced Grant in 2012.
Prof. Jesus Labarta (male) • WP 6.4 Leader • is full professor at the Computer Architecture department at UPC
since 1990. Since 1981 he has been lecturing on computer architecture, operating systems, computer networks
and performance evaluation. His research interest has been centered on parallel computing, covering areas
from multiprocessor architecture, memory hierarchy, parallelizing compilers and programming models, operating systems, parallelization of numerical kernels, metacomputing tools and performance analysis and prediction tools. He has leaded the technical work of UPC in some 15 industrial R+D projects. Significant performance
improvements were achieved in commercial codes owned by partners with whom he has cooperated. Since 1995
he was director of CEPBA and currently he is director of the Computer Sciences research department at BSC.
Dr. Rosa M. Badia (female) • holds a PhD on Computer Science (1994) from the Technical University of Catalonia (UPC). Since year 2008 she is a Scientific Researcher from the Consejo Superior de Investigaciones Científicas (CSIC) and manager of the Grid Computing and Cluster group at the BSC since 2005. She has been an
Associated Professor at the UPC from 1997 to 2008. From 1999 to 2005, she was also involved in research and
development activities at CEPBA. Her current research interests cover the programming models for complex
platforms (from multicore to the Grid/Cloud) and interoperability in Clouds. She has participated in several
European projects. Dr. Badia has been IP of project SIENA, and is currently IP of project EU-Brazil OpenBIO a
member of the HiPEAC2 NoE. She is main investigator for other projects where BSC was not the coordinating
partner, such as OPTIMIS, TERAFLUX, VENUS-C, TransPlant or ScalaLife
Javier Bartolomé (male) • earned his degree in Computer Science from the Technical University of Catalonia
(UPC). In 2001, he began working for the European Center for Parallelism of Barcelona (CEPBA) in the System
Administration Group. Javier joined Barcelona Supercomputing Center - Centro Nacional de Supercomputación
(BSC) in 2005 as the head of the Systems Management Group. He is currently responsible for Hardware and
Software Operations of MareNostrum in addition to supporting the BSC organizational infrastructure. Javier has
expertise in UNIX multi-processor systems and storage systems and is currently involved in National and European projects (HPC-Europa and DEISA). His is also responsible for the coordination of the systems deployment
& operations for the Spanish Supercomputing Network (RES).
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P5 BSC, Barcelona Supercomputing Center - Centro Nacional de Supercomputación (Spain)
Judit Gimenez (female) • received an Engineering degree in Computer Science in 1989 from the Universitat
Politecnica de Catalunya (UPC). Her first work was at UPC on a European project developing an operating system
for distributed memory environments. After 3 years working as technical support for a parallel computer based
on the transputer processor manufacturing company, she came back to work for the university in 1994. From
1994 to 2000 her main tasks have been in the area of technology transfer including the participation in the management of 3 European initiatives that grouped 28 projects to transfer the parallel technology to SMEs. Nowadays she is the leader of the Performance Tools team in the Computer Sciences department at BSC. She has been
responsible for the tools development and distribution for the last 12 years. Currently she participates on different
projects and initiatives targeting exascale, tools integration and spreading the usage of performance tools.
P6
BAUW, Bauhaus University Weimar (Germany)
Laboratory Profile
The Virtual Reality and Visualization Research Group carries out research and development in stereoscopic
display technology, 3D human-computer interaction, information visualization, scientific visualization and realtime rendering. We developed and operate the only projection-based stereoscopic display that provides six
users with individual perspectively correct 3D images and, for the first time, enables effective teamwork when
visualizing complex 3D models. Recent work on immersive group-to-group telepresence allows distributed
groups of users to meet in shared virtual 3D worlds and explore them together. Our innovative user interfaces
are designed and evaluated for complex two- and three-dimensional tasks in collocated and distributed virtual
reality environments. We also develop the rendering and visualization infrastructure for the real-time display of
large multi-variate image, volume and time-dependent data sets, which occur in medicine and other fields. The
VR group received various awards for their work during the past years (www.uni-weimar.de/medien/vr).
Key Personnel
Prof. Bernd Froehlich (male) • is a full professor of Computer Science at Bauhaus-Universität Weimar. He
is chair of the Virtual Reality and Visualization Research Group. He focuses on basic and applied research in
multi-user virtual reality and 3D user interfaces, visualization and rendering algorithms for very large datasets as well as information visualization. He holds a PhD in computer science from the Technical University of
Braunschweig. After completing his PhD, he worked at the German National Research Center for Information
Technology (GMD) and was a research associate with the computer science department at Stanford University.
He is a cofounder and member of the steering committee of the IEEE Symposium on 3D User Interfaces, chair
of the steering committee of the IEEE Virtual Reality conference and received the 2008 Virtual Reality Technical Achievement Award. He is associate editor of the journals IEEE Computer Graphics and Applications and
Frontiers in Virtual Environments.
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P7
BUW, Bergische Universität Wuppertal (Germany)
Laboratory Profile
The Institute of Mathematical Modelling, Analysis and Computational Mathematics (IMACM) exploits the
expertise of mathematical groups at the Bergische Universität Wuppertal to solve real-life problems in the
natural and social sciences, economics and engineering. The focus of the Applied Computer Science Group is
on efficient numerical algorithms for computer simulation in the sciences, and in particular on numerical linear
algebra, algebraic multi-level methods and the numerical solution of PDEs on highly parallel super-computers. Key application fields include theoretical physics (quantum chromodynamics) and particle simulation. The
group currently consists of three professors, two permanent scientific staff, two post-docs and about ten PhD
students financed by the University of Wuppertal and by projects funded by DFG, the German Science Foundation. The group has strong ties of cooperation with the Jülich Supercomputing Centre.
Key Personnel
Prof. Matthias Bolten (male) • is Junior professor of Applied Mathematics/Computer Science at the Department of Mathematics and Science. After completing the work for his PhD research at the Jülich Supercomputing
Centre he worked as a post-doctoral researcher in Jülich, later he became Juniorprofessor in Wuppertal and
he held an interim-professorship in Numerical Analysis at the TU Braunschweig. The focus of his research is on
parallel numerical DIAS members include the ACM SIGMOD 2011 Best Demo Award, the ICDE 2006 Best Demo
Award, the USENIX FAST 2005 Best Paper Award and the ICDE 2004 Best Paper Award.
Prof. Andreas Frommer (male) • is Professor of Applied Computer Science at the Department of Mathematics
and Science. His research interests are parallel numerical algorithms, scientific computing in theoretical physics,
numerical linear algebra, validated numerics. He is editor of SIAM: Journal on Matrix Analysis and Applications, and
an associate editor of ETNA: Electronic Transactions on Numerical Analysis, Linear Algebra and its Applications.
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P8
BSMJ, Bloomfield Science Museum Jerusalem (Israel)
Laboratory Profile
The Bloomfield Science Museum Jerusalem is one of Israel’s leading informal cultural and educational institutions. The goals of the museum are to increase the interest of the general public in science and technology, to
present science and technology as an integral part of human culture and to develop dialogue between scientists and civil society. The museum promotes public engagement with science using exhibitions of cutting-edge
research and innovative technologies and debates to promote the exchange of ideas. Currently planned activities include the launching of a Science Café and a series of film screenings (‘Science and movies’). The BSMJ
operates under the auspices of The Hebrew University of Jerusalem. The museum is very active in the European
Network of Science Centres and Museums (ECSITE); the Association of Science and Technology Centers (ASTC)
and the European Science Events Association (EUSEA). BSMJ has participated in several EU SiS projects under
FP6 and FP7 and is currently the coordinator of the ENGINEER project.
Key Personnel
Maya Halevy (female) • has been part of the Bloomfield Science Museum, Jerusalem, since it was created and
its director since 1995. In 1983, she joined Prof. Peter Hillman to lead a development team that introduced the
museum as one of the first interactive science centers in Israel. Combined with her studies in museology, her
background as an architect helped her to develop and design the Exhibits Department for the new science
centre. Maya is an active member in ECSITE and a governing member of the US ASTC (Association of Science
and Technology Centers). As Israel’s expert representative on the European Commission’s Science in Society
committee and with her background in public policy studies, she has actively promoted science and society
programmes. In recent years, she has initiated and participated in several Israeli-Palestinian Science Museum
programmes – part of the people-to-people philosophy that encourages cooperation in science education.
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P9
CF, Cardiff University (United Kingdom)
Laboratory Profile
MRC Centre for Neuropsychiatric Genetics and Genomics (MRC CNGG) focuses upon common psychiatric and neurodegenerative disorders. The Centre brings together strong gene discovery programmes which
are supported by MRC, Wellcome Trust, EU and other major funders and organized into three broad disease
themes: Psychosis and Mood Disorders (schizophrenia (SZ), bipolar disorder (BD), puerperal psychosis, depression), Developmental Disorders (ADHD, childhood depression, carriers of structural chromosomal rearrangements) and Neurodegenerative Disorders (Alzheimer disease (AD), Parkinson Disease (PD), fronto-temporal
dementia (FTD), Huntington disease (HD)). This work is complemented and enhanced by four crosscutting
themes: Biostatistics and Bioinformatics, Neuroimaging, Cellular and Animal Models, and the National Centre
for Mental Health. The work of the CNGG involves genetics and genomics including large-scale GWAS and NGS
studies. It also includes work on genomic epidemiology, brain imaging (MRI, fMRI, MEG, EEG), iPSC and animal
models of disease mutations and other forms of genetic risk.
Key Personnel
Prof. Michael Owen (male) • is the Director of the Medical Research Council’s Centre for Neuropsychiatric
Genetics and Genomics and of the Cardiff University Neuroscience and Mental Health Research Institute. His
research has focused on the genetics of major psychiatric and neurodegenerative disorders including schizophrenia, bipolar disorder, Alzheimer’s disease, Attention Deficit Hyperactivity Disorder (ADHD) and depression.
He has used a combination of molecular genetic approaches including genome-wide association, copy number
variant analysis and new generation sequencing to identify the specific genetic variants that confer risk to
psychiatric and neurodegenerative disorders. In recent years his group has identified novel genetic risk factors
for schizophrenia, bipolar disorder, Alzheimer’s disease and ADHD. This has allowed him to study the impact
of genetic risk factors across diagnostic boundaries and to influence contemporary attempts to re-define the
boundaries of major mental disorders. His recent work on schizophrenia has identified shared genetic risk with
other psychiatric disorders and points to the involvement of specific synaptic proteins in disease pathogenesis.
As well as continuing his work on psychiatric genetics, he is currently establishing research programmes aimed
at translating recent genetic findings into a greater understanding of disease mechanisms and into the development of novel biomarkers to aid classification and diagnosis.
Dr Andrew Pocklington (male) • is a Senior Lecturer in Bioinformatics at the Medical Research Council’s Centre
for Neuropsychiatric Genetics and Genomics at Cardiff University. Initially studying the functional organisation
of the synapse proteome, his research now centres upon the identification of biochemical processes disrupted
in major psychiatric disorders. He develops approaches for interrogating human genetic datasets using proteomic, gene expression, functional genetic and other data sources. He has made the first detailed bioinformatic/network analysis of a neurotransmitter receptor complex and its functional organisation and constructed
the first models of synapse molecular evolution and its relationship to brain region specialisation. His analysis of
de novo copy number variation implicated specific postsynaptic complexes in the aetiology of schizophrenia.
He is also interested in using machine learning and other techniques to facilitate the analysis of human genetic
data and identify disease-relevant interactions.
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P10
CNRS, Centre National de la Recherche Scientifique (France)
Laboratory Profile
CNRS UPR 3293 Unité de Neuroscience, Information et Complexité (CNRS-UNIC, Gif sur Yvette) CNRS-UNIC
was formed in 2000 as a multidisciplinary research unit combining experimental and theoretical neuroscience.
This Unit, directed by Pr. Yves Frégnac, has played a leading role in the Biology coordination of FET integrated
projects (Facets and BrainScales) and in the Marie Curie training network (FACETS-ITN). UNIC is currently one of
the major partners in integrative and computational neuroscience in the FP7 integrated project BrainScales, one
of the foundations of the Human Brain Project. The research led synergistically by the seven multidisciplinary,
interactive teams composing UNIC focuses on 1) multi-scale acquisition of in vitro and in vivo electrophysiological and imaging data, related to information processing and multi-sensory integration in cortical-like structures
in different species (mouse, rat, cat, ferret, electric fish), 2) on theoretical modelling of cortical dynamics and
3) on the creation of tools for large-scale data-driven neural network simulation. This highly integrated interdisciplinary work has provided significant advances in generic concepts for brain theory and strategic data for
computational neuroscience and neuromorphic hardware developers.
Key Personnel
Dr. Alain Destexhe (male) • SP3 Leader / WP3.2 Leader / WP3.6 Leader / Research Board Member • is
physicist and Research Director (DR1) at CNRS. He is head of computational neuroscience group in the Unité
de Neuroscience, Information et Complexité (UNIC), CNRS UPR 3293. He leads the computational neuroscience group comprising office space and workstations, one complete NeuroLucida reconstruction system, and
has access to a 128-node cluster (common to UNIC) for high-performance computing. He is Editor in Chief of
The Journal of Computational Neuroscience, and in the board of 5 other journals including Journal of Neuroscience and Journal of Neural Engineering. He has been involved in European projects (such as FACETS and
BrainScales, where he was WP leader), and numerous grant review committees. He is author of 2 monographs,
3 edited books, and about 200 publications, including more than 100 peer-reviewed journal articles. In 2014,
Alain Destexhe initiated the European Institute for Theoretical Neuroscience (EITN) in Paris, which he now leads
as Director, in the framework of HBP.
Dr. Andrew P. Davison (male) • WP8.3 Leader • is a senior research scientist (CR1) at CNRS in the Unité
de Neurosciences, Information and Complexité (UNIC) of the Centre National de la Recherche Scientifique,
France, CNRS UPR 3293 where he leads the Neuroinformatics group. His research interests focus on biologically
detailed modeling, simulating neuronal networks (particularly the mammalian visual system), and developing
tools to improve the reliability, reproducibility, and efficiency of biologically realistic simulation. Davison has a
PhD in computational neuroscience from the University of Cambridge.
Dr. Irina Kopysova (female) • will substitute Dr.Kirsty Grant who has contributed to the education section of
the Management Division during the run-up phase of the project. She is Computer Science Engineer (IE1) at the
CNRS. Dr. Kopysova applies physics, numerical methods and theoretical modelling to neuroscience. Her field of
expertise can be divided in four parts: application of differential equations for the description of physiological
processes in neurones; simulation of the electrical behaviour of neurones with detail description of morphological and biophysical properties; processing and analysis of neuronal images including the acquisition and statistical analysis of morphological parameters of neurones using NEUROLUCIDA (MicroBrightField, Inc) systems and
software developed by herself. She has participated in FP6 projects FACETS and Brain-i-Nets, and in FP7 Marie
Curie ITN FACETS-ITN and ICT-FET IP BrainScaleS, whose themes have ranged from experimental and theoretical neuroscience to Neuromorphic computation and bio-inspired robotics.
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P10 CNRS, Centre National de la Recherche Scientifique (France)
Laboratory Profile
CNRS UMR 5086 Institute of Biology and Chemistry of Proteins and University of Lyon (CNRS-BIBCP, Lyon)
This Institute is composed of six research groups, where only one works in the field of HBP related thematics
(BISI: Bioinformatics, structures and interactions). The BISI group is directed by Richard Lavery. Its interests are
centred on structural studies using molecular modelling and molecular simulation and also on method development. Our main research efforts involve understanding and predicting biomolecular interactions. This work
targets two distinct areas. First, we are interested in studying protein interaction networks and, in particular,
in predicting protein interactions in both structural and thermodynamic terms. To this end, we are exploiting
existing sequence and structural information and also developing new high-throughput simulation methods
applicable to large numbers of individual proteins or to large protein complexes. We have notably developed a
coarse-grain protein model that is already giving very promising results. This research activity also underlies our
participation in the Human Brain Project, where we are targeting the molecular aspects of signalling cascades
within neurons. Our second area of interest is in protein-nucleic acid interactions where we are analysing the
mechanisms that enable proteins to specifically bind to their biological target sites. As part of this goal we have
played an active role in creating the ABC international consortium which aims at understanding the sequencedependent structure and dynamics of DNA (and will, in turn, fuel the development of coarse-grain methods
applicable to the study of large protein-nucleic complexes).
Key Personnel
Prof Richard Lavery (male) • is head of the bioinformatics group in the Institute of Biology and Chemistry
of Proteins, Lyon, CNRS UMR 5086 / University of Lyon. Prof. Lavery is expert in molecular simulation and in
particular in recognition processes involving biological macromolecules. His research targets the mechanisms
of molecular recognition and assembly using both all-atom and coarse-grain models and exploiting grid and
supercomputer resources..
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P10 CNRS, Centre National de la Recherche Scientifique (France)
Laboratory Profile
CNRS UMR 5218 Laboratoire de l’Intégration du Matériau au Système and Université de Bordeaux et Institut Polytechnique de Bordeaux (CNRS-IMS, Bordeaux, IPB) IMS the Laboratoire d’intégration du matériau au
système is a joint research unit between CNRS, the University of Bordeaux and the IPB (Institut Polytechnique
de Bordeaux). IMS has 10 research departments (total ~400 personnel), conducting research in Information
technologies, from material to systems, and from fundamental to applied research. IMS is part of the IDEX University of Bordeaux, one of the first « Campus of Excellence » granted in 2011.
Key Personnel
Prof. Sylvie Renaud (female) • is Professor in Institut Polytechnique de Bordeaux (IPB) and IMS Laboratory,
CNRS UMR5218. Prof Sylvie Renaud graduated in electronic engineering (MSc) in Supelec (Paris-France) in
1986. She received her PhD in Physics at the University of Bordeaux (France) in1990, and her HDR (Research
Habilitation) in 2001. After a postdoctoral stay at Brandeis University (MA, USA) in 1991_1992, she was appointed
as an Assistant-Professor, then Professor in ENSEIRB Bordeaux (National Engineering School) where she was
recently appointed as the Deputy Director for Research in the Institut Polytechnique de Bordeaux. She created
in 1994 the Engineering of Neuromorphic Systems group in IMS-Labs (University of Bordeaux, CNRS UMR5218),
and now heads the BioElectronics group. Her research interests are: analog and mixed neuromorphic VLSI;
real-time hardware simulation platforms of spiking neural networks; hybrid systems interfacing living and artificial neurons; analog ASICs for biological signal conditioning and events detection; active VLSI implants for
neurodegenerative diseases and diabetes; closed-loop living-artificial systems. With her group, she participated
or coordinated 12 international and national research projects, authored more than 50 reviewed international
articles and communications. Professor Renaud is an expert for the EU commission on FET and ICT calls, and
for NSF-NIH on research calls related to neuromorphic engineering. She is a reviewer for numerous IEEE journals
and conferences and organizes special sessions, tutorials and workshops in IEEE and INNS conferences on a
regular basis. She coordinates an annual EU doctoral program on biomedical engineering.
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P11
CEA, Commissariat a l’énergie atomique et aux énergies alternatives (France)
Laboratory Profile
Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO) is a group at NeuroSpin involved in algorithmic
research in neuromaging. LNAO is headed by Jean-François Mangin. The aims of the group include the study
of the dynamics and variability of the cortical folding process and the organisation of MRI defined white matter
bundles. The strategy followed by the group relies on building bottom-up representations of individual data
to be matched to graph-based models of human brain architecture. The resulting computer vision tools have
been used to create brain atlases of cortical folds and brain fibre bundles, to infer biomarkers of psychiatric
syndromes and to study brain plasticity.
Key Personnel
Dr. Jean-François Mangin (male) • WP2.3 Leader • is the head of the Neurospin LNAO group and the director of CATI, a 40 fellow French national platform for multicenter neuroimaging studies. In 1989, he graduated
from Ecole Centrale Paris, majoring in applied mathematics, and in 1995 received his Ph.D in image analysis
from Télécom ParisTech. His methodological interest is in building up computer vision systems dedicated to the
complex structures embedded in neuroimaging data. His neuroscience interest is in understanding and simulating the dynamics of the cortical folding pattern, and mapping the U-fiber bundles of white matter. Finally, in
the context of the CATI platform, his ultimate goal is the inference of imaging-biomarkers from large databases
using machine learning.
Laboratory Profile
The Nuclear Magnetic Resonance Imaging and Spectroscopy Unit (UNIRS, headed by, Cyril Poupon) of the
NeuroSpin centre is in charge of driving the research ad methodological developments in the field of MR Physics,
including MR Imaging and Spectroscopy, focused on the use of a unique ultra-high field MR platform (3 clinical systems at 3T, 7T and 11.7T whole-body (90cm), 3 preclinical systems at 7T, 11.7T and 17T small-bore (26cm)
horizontal magnet) to push the limits of spatial, temporal and spectral resolutions of brain imaging.
Key Personnel
Dr. Cyril Poupon (male) • is an alumnus of the Institut National des Sciences Appliquées de Lyon, the CREATIS
lab at Ecole Nationale des Télécommunications de Paris, Paris 5 University and the Service Hospitalier Frédéric Joliot (Orsay). His initial research focused on studies of the human connectome using diffusion weighted
MRI. After three years as a research engineer, he joined the MR physics group of SHFJ where he worked to
build bridges between bio-informatics and Magnetic resonance physics. Today, his research focuses on highresolution diffusion imaging and more specifically on the use of diffusion imaging to infer the human brain connectome and to study the cytoarchitecture of the human brain. As the current head of LRMN and co-Principal
Investigator for the Multi-scale architecture research and Magnetic resonance imaging at ultra high field programmes, his work aims to provide anatomofunctional mapping of the human brain and anatomical, diffusion
and functional imaging at very high resolution.
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P12
CNR, Consiglio Nazionale delle Ricerche (Italy)
Laboratory Profile
The Italian National Research Council (CNR) is a public organization; its duty is to carry out, promote, spread,
transfer and improve research activities in the main sectors of knowledge growth and of its applications for the
scientific, technological, economic and social development of the Country. CNR Institutes are distributed all over
Italy. The Institute of Biophysics is based in Genoa and has four separate research divisions located in Milan, Pisa,
Palermo (where HBP activities will be carried out) and Trento. The Palermo division has tight connections with
several universities, a very active groups of researchers, and several ongoing international collaborations with
leading laboratories.
Key Personnel
Dr. Michele Migliore (male) • is Senior Research Scientist at the Institute of Biophysics of the Italian National
Research Council since 1983. He is Visiting Professor of Cybernetics at the Department of Mathematics and
Informatics of the University of Palermo (Italy) and Visiting Scientist at the Department of Neurobiology of the
Yale University School of Medicine (New Haven, USA). Michele Migliore leads a very active group of collaborators working on modelling realistic neurons and networks, synaptic integration processes, plasticity mechanisms,
and ion channels, to study their role in modulating neuronal excitability, firing behaviours, and the emergence
of pathologies and dysfunctions. Through an extensive network of international collaborations and projects
with leading Institutions, his lab is deeply involved in investigating the emergence higher brain functions from
cellular processes, using state of the art simulation environments on different supercomputer systems. He is
serving as reviewer for many international journals and funding programs, and has published over 90 papers on
international ISI journals. Selected most recent publications include: Migliore et al. (2014) Front. Comp. Neurosci.
8:50; Yu Y. et al., (2013) PLoS Comput Biol. 9:e1003014; Miceli F et al., (2013) Proc Natl Acad Sci USA. 110:438691; Ferrante M, et al. (2013) J Neurosci. 33:2156-65; Migliore M, Migliore R. (2012), PLoS One. 7:e36867; Halnes
G et al., (2011), PLoS Comp. Biol. 7:e1002160; Ascoli GA, et al. (2010), J. Neurosci., 30:6422-6433;Ferrante M
et al., (2009), Proc. Natl. Acad. Sci. USA, 106:18004-18009; Shah MM et al., (2008), Proc. Nat. Acad. Sci. USA,
105:7869-7874; Migliore M., and Shepherd, GM. (2005), Nature Rev. Neurosci. 6:810-18; Migliore M and Shepherd,
GM (2002), Nature Rev. Neurosci. 3, 362-370.
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P13
CINECA, Consorzio Interuniversitario Cineca (Italy)
Laboratory Profile
CINECA is a non-profit consortium of 69 Italian Universities, the National Institute of Oceanography and Experimental Geophysics (OGS), the National Research Council (CNR), and the Ministry of Education, University and
Research (MIUR). CINECA is the largest Italian supercomputing centre with an HPC environment equipped with
cutting-edge technology and highly-qualified personnel which cooperates with researchers in the use of the
HPC infrastructure, in both the academic and industrial fields. CINECA’s mission is to enable researchers to use
HPC systems in a profitable way, exploiting the newest technology advances in HPC. The current HPC system
are the IBM BG/Q FERMI (10 Frames, 163840 cores with 1GB RAM per core and a peak performance of 2 PFlop/s,
N. 15 in Top500 rank, November 2013) and PLX hybrid cluster Linux (3288 core Intel Westmere with 14 TB RAM
and 548 GPUs nVIDIA m2070 with a peak performance of 283 TFlop/s). CINECA represents Italy in PRACE and
is one of the four PRACE Tier-0 Hosting Centres. A big data facility of several PetaByte of high performance
storage integrates the HPC systems. The CINECA data centre is equipped to provide business continuity technology. Besides the national scientific HPC facility CINECA manages and exploits the supercomputing facility
of the Italian Energy company (ENI), an integrated HPC facility with more than 30.000 cores. A virtual theatre,
where viewers can make a semi-immersive virtual reality experience, completes the entire infrastructure.
CINECA has acquired several years of experience in EU projects since FP3. In FP7, besides coordinating HPCEuropa2 (www.hpc-eurpa.eu), is one of the four hosting members in PRACE and an active partner in the PRACE
IP projects (www.prace-ri.eu) since the beginning. Furthermore CINECA is partner in EUDAT (www.eudat.eu)
and the Exascale projects MONTBLANC (montblanc-project.eu) , DEEP (deep-project.eu), the Exascale software initiateive EESI2 (eesi-project.eu) and some National and Regional projects. The Italian Ministry of University and Research is a member of CINECA Consortium and has a direct role in supporting this proposal.
In HBP CINECA will provide the Massive Data Analytics Supercomputer which will provide the data-centric HPC
resource for managing, processing, analysing and storing the large volumes of data, which will be generated by
the HBP. In the ramp-up phase, the 2.1 PFlops IBM Blue Gene/Q system FERMI (200 TB main memory), the 300
TFlops GPU cluster PLX, and a data-intensive computing system are available at Cineca for massive data analytics and post-processing. The three systems are integrated with a Data Facility of 50 TB fast storage SSD, around
6 PB on-line disk storage repository and 12 PB for long-term data preservation, providing efficient data life-cycle
management of structured and un-structured data generated by the HBP. The infrastructure will evolve for the
entire life cycle of HBP Project.
In 2017-18, the HPC system will evolve further into the range of 50 PFlops, integrated with an enhanced fast
storage data facility suitable to manage the Big Data analytics and visualisation activity related to the data produced by the HBP.
In the 2020-23 time frame, it is foreseen that the HPC system will reach a performance in the order of 500
PFlops and that the Data Facility will increase its capacity and performance accordingly.
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P13 CINECA, Consorzio Interuniversitario Cineca (Italy)
Key Personnel
Dr. Giovanni Erbacci (male) • holds a laurea in Computer Science from the University of Pisa. Today, he is
responsible for the Division for the Academic and EU HPC Projects in the CINECA’s Supercomputing Application and Innovation Department. He has vital experience in promoting HPC activities and methodologies, and
is also involved in CINECA’s training and education activities. He has been actively engaged in PRACE projects
since the beginning of the initiative. Actually leads the HPC Services for Industrial Users WP in PRACE-3IP. He is
also a member of the PRACE-2IP Executive Board and the PRACE 3IP Technical Board. In HBP he leads the Task
T7.5.4: The HBP supercomputer for massive data analytics.
Dr. Giuseppe Fiameni (male) • holds a degree in Computer Science from the University of Bologna and has
been working in CINECA since 2004 when he joined the middleware and infrastructure group of the Super Computing Department. He has contributed to many European projects (EMBRACE, DEISA, A-WARE, PRACE, EMI)
maturing a strong experience in distributed systems, authentication and authorization mechanisms, computational and data resource management. Currently, he is leading the “Middleware for HPC services” group of the
SuperComputing Application and Innovation department at Cineca. He is also member of the EPOS ICT board
and leader of the Data Staging Task Force within EUDAT, the European Data Infrastructure.
Roberto Mucci (male) • holds a degree in Statistics at the “University of Bologna” in 2004. He has a permanent position on the “Middleware for HPC services” group of the SuperComputing, Applications and Innovation
department at CINECA. Working within national and international projects as software developer, mainly focused
on scientific visualization and data management. Maintainer and developer of the remote visualization service
being available on CINECA HPC resources.
Luigi Calori (male) • received the M.Sc. degree in Mathematics from Bologna University of Technology 1986, since
1989 he works at CINECA in the HPC Projects Division. He developed application and visualization in different
application fields: astrophysics (Cosmolab EU project, AstroMD tool for n-Body visualization); medical data analysis and visualization (VISU and ADAM EU projects); meteo Grads package contribution; forensic application of
image processing, haptic interfaces (RACINE EU project) landscape and geographic data visualization applied to
both cultural heritage as well as scientwific visualization. He is currently involved in browser embedded 3D applications in cultural heritage and scientific visualization, based on OpenSceneGraph open source library.
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P14
DTU, Danmarks Tekniske Universitet (Denmark)
Laboratory Profile
The Center for Playware at DTU has a research focus on modular robotic hardware development and constructionist methods for developing robotic applications, and on robot morphology-control relationship. The research
center uses its extensive experience in biologically inspired robotics and modern artificial intelligence to develop
user-guided approaches based on behaviour-based robotics, evolutionary robotics, multi-agent systems, and
neural network control for modular robotic systems. The underlying hypothesis is based on a modular robotics
concept, which make the robotic devices applicable in a vast range of application areas, and which allow users
to generate knowledge by hands-on development of artefact morphology. The center collaborates with large
companies such as LEGO and utilises insight into modern artificial intelligence, interaction design, and modular
robotics to create novel intelligent artefacts with seamless interface for end-users in rehabilitation, therapy,
elderly care, sport, music, education, children care, and home entertainment.
Key Personnel
Prof. Henrik Hautop Lund (male) • is head of the Center for Playware at Technical University of Denmark (DTU
Electro). Professor Henrik Hautop Lund combines research in modular robotics and modern artificial intelligence
to create novel solutions to problems that occupy the citizens. For more than two decades, he work on crossing the reality gap between simulation and real robots has influenced the research community, and his work
on biomimetic robotics since the mid-1990s and on self-reconfigurable modular robots since the early 2000s
has paved the way to numerous projects and developments in these areas. His Center for Playware has shown
how the combination of a modern artificial intelligence, modular robotics and entertainment may provide novel
opportunities in play, rehabilitation, sport, music, teaching, third World development, etc., by allowing nonexpert users easy access to robotics inspired technology in a playful and motivating way. Professor Henrik
Hautop Lund has published more than 150 scientific articles in the field of robotics, he has been a member of
the Danish Research Council, he invented the RoboCup Junior robot football game for children, and his group
won the RoboCup Humanoids Free Style World Championship 2002.
Prof. David Johan Christensen (male) • is an associate professor at Center for Playware at the Technical University of Denmark. DJC has been active in research to develop the principles, methods,and systems to study the
intersection between embodied artificial intelligence and modular robotics for the last decade. DJC received his
M.Sc. degree in computer systems engineering in 2006 and a Ph.D. degree in robotics in 2008 from the Maersk
McKinney Moller Institute, University of Southern Denmark. He was a postdoctoral researcher at University of
Southern Denmark until 2010 where he joined the Center for Playware at Technical University of Denmark, first
as an Assistant Professor and since 2013 as an Associate Professor. DJC research interests include adaptive
and self-organizing control of modular robots for self-reconfiguration, locomotion, playful interaction and rehabilitation. His work includes distributed control strategies for scalable and fault-tolerant self-reconfiguration of
modular robots and programmable matter.
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P15
UoD, Debreceni Egyetem (Hungary)
Laboratory Profile
The Laboratory for Cortical Systems Neuroscience (LCSN) is a multidisciplinary research which focuses on
the organisation of the cerebral cortex at her micro- and mesocircuitry levels. The main profile of the group is
investigating input-output relationships of neuronal types of the cerebral cortex and their role in visual contour
integration processes. To this in vivo functional imaging (intrinsic signal optical imaging), single and multi unit
electrophysiology and a host of anatomical labelling techniques have been employed. The anatomical correlates
of functional properties are determined and the impact on wiring and communication of the cortical network
estimated. Recent work of the group concerns anatomical mapping of human cortical tissue for intrinsic cortical
architecture and its correlate with connectivity clustering rules. The group is well equipped with the necessary
experimental devices and benefits from core research facilities of the University.
Key Personnel
Dr. Zoltan Kisvárday (male) • obtained his degree in biology at the Eötvös Lóránd University in Budapest and
received postgraduate training in neuroanatomy at the Dep.Anatomy of the Semmelweis University Medical
School, Budapest. The early works of Dr. Kisvarday were concerned with the synaptic organisation of the mammalian visual cortex (rodent, carnivore, primate) and its relay nucleus, the visual thalamus. As a junior research
fellow he spent several years in the UK (MRC Anat. Neuropharmacology Unit, Dept. Exp. Psychology of Oxford
Univ., Dept. Pharmacology of Oxford Univ.), in Australia (Flinders Univ., Adelaide) and Germany (Ruhr-Univ.
Bochum). Since 2004 he is head of a research group at the University of Debrecen. His work provided compelling evidence for the significance of lateral inhibition in shaping orientation and direction selectivity and
unravelled the relationship between the type of effects resulting from cell-to-cell interactions. His team discovered previously unknown features concerning the subcellular organisation of the axonal branches of individual
neurons.
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P16
DMU, De Montfort University (United Kingdom)
Laboratory Profile
The Centre for Computing and Social Responsibility (CCSR), a research centre located in DMU’s Faculty of
Technology, is the largest research centre of its kind in the UK and one of few in Europe and the world. It includes
eight full-time academics including two professors and two readers. The CCSR has undertaken funded research
for a range of stakeholders including private organisations, professional bodies, NGOs, the UK government and
the EU. As one of the leading research centres in the field of information technology ethics, the CCSR has set up
and continues to run the ETHICOMP conference series. Since 2008, members of the CCSR have led successful
research funding bids leading to a research income for the group of more than 2 million.
Taking an interdisciplinary approach, the CCSR has gained an impressive reputation as a key player in the
international research network for the ethical and social implications of ICT. With a growing demand from both
the public and government to deliver acceptable ICT, its mission is to undertake research and provide teaching, consultancy and advice to individuals, communities, organisations and governments at local, national and
international levels on the actual and potential impacts of computing and related technologies on society and
its citizens.
Key Personnel
Prof. Bernd Carsten Stahl (male) • WP10.4 Leader • is Professor of Critical Research in Technology and Director of the Centre for Computing and Social Responsibility. He has a Masters Degrees in Philosophy, Economics,
Industrial Engineering and Business Law as well as a Ph.D. in Information Systems. An internationally recognised
scholar in ethics and ICT, he is widely published and active in fields of computer ethics, information systems and
critical research. From 2009 to 2011 he served as coordinator of the EU FP7 research project on “Ethical Issues
of Emerging ICT Applications”, ETICA and from 2012 to 2015 he served as coordinator of the EU FP7 research
project “Civil Society Organisations in Designing Research Governance“ (CONSIDER). He is also co-investigator
in a UK, EPSRC funded project on a “Framework of Responsible Research and Innovation in ICT” and has served
as a reviewer for a number of EU projects in the area of ICT. He is also an active member of the FP7 / H2020
ethics review procedure.
Mark Christopher Shaw (male) • is a Research Fellow in the Centre for Computing and Social Responsibility
(CCSR) at De Montfort University, Leicester, UK. He qualified as a medical doctor (University of London, 1987)
and specialized in Public Health Medicine (Member of the Faculty of Public Health, London, 2001) and changed
careers, obtaining a second degree in computer science (Open University 2000). His main role in the CCSR is to
develop research into health informatics and into quality assurance.
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P17
ENS, Ecole Normale Superieure (France)
Laboratory Profile
The goal of the Cell Biology of Synapse Group is to understand the basic mechanisms regulating synaptic function in normal and pathological situations. Since 2001, the group has combined methods from cell biology and
physics, to study the movement of receptors in real time. In 2003, in collaboration with Maxime Dahan, it developed new techniques of video microscopy using nano-semiconductor particles also known as quantum dots.
The new approach made it possible to directly visualise the movement of receptors, in and out of synapses. This
single particle tracking (SPT) method has made it possible to characterise the diffusive properties of receptors
in submembrane domains and has validated the mechanism of diffusion capture for the stabilisation of receptors at central synapses. The group is composed of five permanent researchers, six post-docs, six PhD students,
three engineers and technicians.
Key Personnel
Prof. Antoine Triller (male) • is responsible for the revelation that synaptic receptors are accumulated in front of the
presynaptic zone (J. Cell Biol 1985). He then developed the use of quantum dots for single molecule tracking (Science
2003), considered by Science magazine as one of the ten breakthrough of the year. He went on to suggest that the
plasma membrane can be analysed globally using a formalism derived from statistical mechanics (Biophys J 2006, Phys
Rev E 2009, Phys Rev Let 2011). With these tools, he was able to identify new mechanisms for the adaptation of inhibition
to excitation involving PKC, CamK2 and calcineurin dependant phosphorylations (Neuron 2008, 2009) and to identify
their molecular determinants (EMBO J 2011). He went on to demonstrate that integrins are key actors in the regulation
of the tuning of excitation-inhibition coupling (Nat Neurosci 2010) and in the physiopathology of neurodegenerative
diseases (Neuron 2010).
Dr. Leandro G. Almeida (male) • is a senior post-doctoral researcher at the Ecole Normale Superiour. Has 4 years
of post-doctoral experience in simulation of equilibrium and non-equilibrium systems. He has also developed several
methods for characterizing data which are in current use in international scientific collaborations. Responsible to construct molecular model associated homeostasis and plasticity in inhibitory excitatory interaction.
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P18
ETHZ, Eidgenössische Technische Hochschule Zürich (Switzerland)
Laboratory Profile
Founded in 1991, the Swiss National Supercomputing Centre (CSCS) partners with Swiss universities and
research institutions on all issues related to high performance computing. Headed by Thomas Schulthess, CSCS
provides scientists with the computing infrastructure and expertise they need, from cutting-edge super-computers to a full range of services delivered by an international fifty-person team. CSCS is an autonomous unit of
the Swiss Federal Institute of Technology in Zurich (ETH Zurich) and it is located in Lugano, in the Italian-speaking region of Switzerland. CSCS also caters for users from business and industry and works with the world’s
leading computing centers and hardware manufacturers to guide and develop the state of the art.
Key Personnel
Prof. Thomas C. Schulthess (male) • SP 6 Co-leader / WP 6.6 Leader / Research Board Member • is the director of the Swiss National Supercomputing Centre (CSCS) and leads the Swiss initiative for High-Performance
Computing and Networking. In this capacity, his research interests are centered around highly scalable computational methods and implementations that map optimally on new and emerging computer architectures,
including (most recently) hybrid multi-core systems with GPUs. He has led research teams in computational
materials science that were finalists for the Gordon Bell Prize three times during the past five years – winning
the prize twice in 2008 and 2009, and an honorable mention in 2010. Since 2010 he has co-led the team that
is redesigning the COSMO regional climate and meteorology model for hybrid multi-core systems. This new
implementation of a model used by five weather services (including Meteo Swiss and Deutscher Wetter Dienst)
and about 50 universities is scheduled to be ready for production at Meteo Swiss in 2016, and will enable large
ensemble simulations (a problems that is in principle comparable to high-throughput high-performance simulations needed in the present NCCR projects) for weather forecasting. On the side he leads a research group at
ETH Zurich that is developing computational methods and algorithms for quantum simulations. Present focus is
on quantum cluster methods as well as materials specific models for the study of strongly interacting electron
systems, as well as Eigensolver algorithms for hybrid multi-core systems that are used to accelerate ab initio
electronic structure calculations. In Zurich, he presently supervises one postdoctoral fellow and three PhD students in computational physics and one PhD student in computer science.
John Biddiscombe (male) • graduated from Warwick University in 1989 with a BEng in Electronic Engineering and worked at the Rutherford Appleton Laboratory on Digital Signal Processing methods for altimetry and
remote-sensing radar. Following this he implemented 3D algorithms for cellular radio propagation, in particular,
modelling signals around buildings and trees and designed a propagation toolkit derived from the VTK library
for these simulations. This work in turn led to an interest in visualization algorithms and he now works (since
2004) as a Computational Scientist at the Swiss National Supercomputing Centre (CSCS) with a specialization
in parallel visualization and supercomputing. Recent work has focused on interactive visualization and analysis
of running supercomputing applications using distributed resources, and implementing communication middleware to enable the sharing of data between applications.
Dr. Ben Cumming (male) • works as a computer scientist at the Swiss National Supercomputing Center, working
closely with vendors and the user community to port and benchmark codes on accelerator technologies. He
obtained PhD in computational mathematics from the Queensland University of Technology in Brisbane, Australia in 2012.
Cristian Mezzanotte (male) • is a System Engineer with over 13 years experience in HPC System Management,
Scientific Computing, Grid Computing and Distributed Systems. He successfully integrated the ECMWF infrastructure into the DEISA EU Project.
Colin McMurtrie (male) • is a mechanical engineer with more than 14 years’ IT experience in the academic sector
including more than 7 years in HPC. At CSCS since 2009, he managed the National Systems group for 4 years
and recently became group leader of the newly formed Systems Integration group. He has extensive project
management experience, is a PRINCE2 Registered Practitioner and has ITIL certification.
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P18 ETHZ, Eidgenössische Technische Hochschule Zürich (Switzerland)
Katarzyna Pawlikowska (female) • graduated from Cracow University of Economics, with Master Degree in
International Relations. She has more then 10 years of experience in EU project management and implementation, as practitioner, trainer and advisor to public universities, institutions and various European organisations.
As Research Collaboration Coordinator at CSCS she is responsible for development, control and reporting of a
meta-project plan integrating all scientific and technical European cooperation initiatives.
P19
FT, Fonden Teknologirådet (Denmark)
Laboratory Profile
The Danish Board of Technology Foundation (DBTF) is a non-profit private research foundation committed to
deliberation, engagement and participatory processes in relation to the development of science and technology. The DBTF specialises in applied social research and policy advice for decision-makers at the local, regional,
national, European and global levels. Focusing on issues that are often socially contested, the Board has initiated
and guided a number of important dialogue and deliberation projects, covering issues such as nanotechnology,
biotechnology and neuroscience, and the safeguarding of drinking water supplies, adaptation to climate change
and the challenges facing the health care system. The DBTF’s methods toolbox include Scenario Workshops,
Future Labs, Future Search Conferences, Voting Conferences, Citizen Hearings, Crowdsourcing, and Multi-Site
Citizen Participation processes.
The DBFT has historically emphasized the importance of citizen participation in technological development,
administrative planning, and political decision-making. In its 30 years of methodological development it has
built a world-class skillset for the facilitation of trans-disciplinary dialogue and solution-oriented research. The
many years of experience has given the DBFT significant practical experience in the use of participatory methodology as well as a technical and scientific knowledge in a number of fields, which the DBTF sees as essential
to gaining recognition from all involved actors.
Key Personnel
Lars Klüver (male) • WP 10.3 Leader is the director of the Danish Board of Technology Foundation and is recognized
as an international expert in technology assessment (TA) and foresight methodology, and has been advisor on a multitude of national and international research, foresight and technology assessment activities.
Dr. Lise Bitsch (female) • has PhD and post-doc level research experience with social and ethical issues of technoscientific innovations in relation to genomics, biobased economy and more generally with the conceptualization and execution
of responsible research and innovation.
Anders Jacobi (male) • has comprehensive experience and knowledge within the area of Science, Technology and
Innovation Policy and Jacobi has led several projects with sociological methods involving participation, expert consultation, interviews and questionnaire techniques, policy development and innovation processes.
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P20
JUELICH, Forschungszentrum Jülich GmbH (Germany)
Laboratory Profile
Institute of Neuroscience and Medicine - Structural and Functional Organisation of the Human Brain (INM-1),
headed by Katrin Amunts, is developing a 3-D model of the human brain, which considers cortical architecture,
connectivity, genetics and function – the JuBrain. To reach this goal, researchers collaborate closely with the
Jülich Supercomputing Centre and the Virtual Reality Group at RWTH Aachen University. The institute is currently developing a multimodal human brain atlas that integrates data on cellular and molecular architecture,
connectivity, and brain function. It hosts fully equipped labs for histological processing and receptor autoradiography of entire human brains. INM-1 has developed state-of-the-art and unique post mortem brain characterisation methods for quantitative cyto and receptor architecture, 3D-reconstruction, atlasing and visualisation.
During the last years, methods of high performance computing and big data analytics have been integrated in
the portfolio. The Institute has approximately 90 researchers, technicians and doctoral students. Current collaborations include an NIH project with UCLA and a GIF project with the University of Tel Aviv, as well as projects with the Department of Psychology, Stanford University and the Ahmanson Brain Imaging and Neurology
Center, UCLA.
Key Personnel
Prof. Dr. med. Katrin Amunts (female) • SP 2 Leader / WP Leader / WP 2.5 Leader / WP 2.6 Leader / WP 4.3
Leader / Research Board Member • did postdoctoral work in the C. & O. Vogt Institute for Brain Research at
Düsseldorf University, Germany. In 1999, she moved to the Research Centre Jülich and set up a new research unit
for Brain Mapping. In 2004, she became professor for Structural-Functional Brain Mapping at RWTH Aachen
University, and in 2008 a full professor at the Department of Psychiatry, Psychotherapy and Psychosomatics at
the RWTH Aachen University as well as director of the Institut of Neuroscience and Medicine (INM-1) at Forschungszentrum Jülich. In 2013, she became a full professor for Brain Research at the Heinrich-Heine University
Düsseldorf, director of the C. and O. Vogt Institute for Brain Research, Heinrich-Heine University Düsseldorf and
director of the Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich. Since 2007 Katrin
Amunts is a member of the editorial board of Brain Structure and Function. Since 2012 she is member of the
German Ethics Council. She is the programme speaker for the programme “Decoding the Human Brain” of the
Helmholtz Association, Germany.
Prof. Karl Zilles (male) • established the Institute of Neuroscience and Medicine INM at the Research Centre
Juelich between 1998 and 2008, and was the founding director of the whole institute. He served as director
INM-2 from 2008 to 2012. From 1991 to 2012 he was also director of the C. & O. Vogt Institute for Brain Research
at Düsseldorf University, Germany. Since 2013 he has a joint JARA-Senior-Professorship at the Research Centre
Juelich and the Department of Psychiatry, Psychotherapy and Psychosomatics at the RWTH Aachen University. He is Fellow of the German National Academy of Sciences Leopoldina, and Fellow of the North-Rhine
Westphalia Academy of Science and Arts. He is Editor-in-Chief of Brain Structure and Function. Since 2013 he
is Elected Chair/Chair of the International Organization of Human Brain Mapping. He is active for more than
thirty-five years in the field of brain mapping using molecular, microscopical and functional imaging techniques.
His research ranges from the analysis of the molecular organisation of human, non-human primate and rodent
brains to the development of cyto- and receptor-architectonic atlases for use in multimodal brain models. He
has developed quantitative receptor autoradiography to map more than twenty receptor types and to study the
balance between them in cortical and subcortical areas. Recently, he has initiated and collaborates on ultra-high
resolution fibre analysis based on polarized light imaging. The aim of this activity is an analysis of fiber-architecture of cortical areas and white matter as well as connectivity in the brain of rodents, non-human primates and
humans (in collaboration with Katrin Amunts and Markus Axer).
Dr. rer. nat. Markus Axer (male) • is head of the group “Fiber Architecture” in the Institute of Neuroscience
and Medicine (INM-1) at Forschungszentrum Jülich, Germany. He is physicist, and oversees the development of
3D-polarized light imaging (3D-PLI), which includes the design of polarimetric systems, image acquisition and
big data analyses. This neuroimaging technique opens up new avenues to unravel the nerve fiber architecture
in the brain at different levels of detail and establishes the so far missing link between the microscopic and the
macroscopic characterization of the anatomical connectivity of the human brain. In 1999, Markus graduated
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P20 JUELICH, Forschungszentrum Jülich GmbH (Germany)
from the RWTH Aachen University, and in 2003 received his awarded Ph.D. in Particle Physics from the RWTH
Aachen University. After a two-years research fellowship at the European Organization for Nuclear Research
CERN, Geneva (Switzerland), Markus joined the field of neuroscience at the INM.
Laboratory Profile
The institute INM-2 Molecular organization of the brain investigates organizational principles of the brain from
the molecular level to that of small neuronal networks. The different research groups want to gain insight into
the distribution and function of neurotransmitters, the structural properties of synapses and connectivity of
small neuronal microcircuits. Based on these key structures of neuronal information processing, the researchers want to understand principles of sensory, motor, cognitive, and emotional performances of the brain, and
to enable predictions about (patho)physiological processes and the underlying morphological changes. Within
INM-2, Dirk Feldmeyer’s laboratory focuses on structural, functional and developmental characteristics of neuronal connectivity in the neocortex as well as aspects of neuronal modulation in the neocortex in normal animals
and models related to neurological/psychiatric diseases.
Key Personnel
Prof. Dr. rer. nat. Dirk Feldmeyer (male) • did his Ph.D. in physiology. He worked as a postdoc in the Dept. of
Cell Physiology of Ruhr University Bochum and at the Dept. of Pharmacology of University College London.
He obtained also two fellowships for research work in Debrecen, Hungary and Tokyo, Japan. He led a research
group on ‘Cortical Microcircuits’ in the Dept. of Cell Physiology, Max-Planck Institute of Medical Research (Head
Prof. Bert Sakmann). Currently is head of the group ‘Function of Neuronal Microcircuits’ in the Institute of Neuroscience and Medicine (INM-2) at the Research Centre Juelich, Germany and of the group ‘Function of Cortical
Microcircuits’ in the Dept. of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, where
he is also professor since 2008. His research is in the field on the identification of neuronal cell types in rodent
brain and on the synaptic microcircuits they form. Here, he investigates the properties of unitary excitatory and
inhibitory connections, their development and regulation by modulatory neurotransmitters. His scientific goal is
to understand neuronal networks and their dynamics on a cellular level.
Laboratory Profile
INM-6 is specialized in the integration of experimental data on the structure and the dynamics of the brain into
mathematical models and in overcoming bottlenecks in simulation technology and workflows. The group “Statistical Neuroscience” led by Sonja Grün focuses on the development and application of methods to analyze
multi-channel activity data in close contact to experimental groups. A focus is the connection between neural
data recorded on different temporal and spatial scales and on the structure of correlations of spiking activity. The group “Computational Neurophysics” headed by Markus Diesmann focuses of bottom-up approaches
in order to integrate physiological and anatomical data into models, in particular model development, theory
of neuronal networks, and correlation dynamics. This also requires the development of simulation technology
for neural networks. The group “Functional Neural Circuits” led by Abigail Morrison investigates mechanisms
underlying neural computation through the development of models on the level of networks of spiking neurons.
It applies a predominantly top-down approach to discover functional constraints on structure, plasticity and
dynamics, particularly with respect to learning and memory. Secondary focus is on simulation technology for
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high-performance computers. The focus of this group is the investigation of mechanisms shaping the correlated
and oscillatory activity in neuronal networks with structured connectivity on several spatial scales. This requires
the development of quantitative theoretical descriptions, adapted from statistical physics, combined with direct
simulations of neuronal networks at cellular resolution. Moritz Helias’ group “Theory of multi-scale neuronal networks” focuses on the investigation of mechanisms shaping the correlated and oscillatory activity in neuronal
networks with structured connectivity on several spatial scales. This requires the development of quantitative
theoretical descriptions, adapted from statistical physics, combined with direct simulations of neuronal networks at cellular resolution.
Key Personnel
Prof. Dr. Sonja Grün (female) • WP 3.1 Leader • is the Vice Director of INM-6 at FZJ, where she heads the
Group on Statistical Neuroscience. She is also full professor for Theoretical Systems Neurobiology at RWTH
Aachen University, Germany. She received her diploma (Eberhard-Karls University Tübingen) and Dr. rer. nat. in
physics (Ruhr-University Bochum) and her habilitation in neurobiology and biophysics (University of Freiburg,
Germany). As a post-doc at the Hebrew University, Jerusalem (Israel), she performed multiple single-neuron
recordings in behaving monkeys. After that she returned to computational neuroscience to develop analysis tools for multi-electrode recordings, first at the Max-Planck Institute for Brain Research in Frankfurt/Main,
Germany, and then as an Assistant Professor at the Freie Universität in Berlin. In 2006 she became Unit Leader
and in 2010 Team Leader at the RIKEN Brain Science Institute Wako-Shi, Japan, leading the Statistical Neuroscience lab. Her research focuses on the identification and analysis of cooperative network dynamics relevant for
brain function and behaviour.
Prof. Dr. Markus Diesmann (male) • WP3.5 Leader / WP6.1 Leader • carried out his Ph.D. work at the Weizmann Institute, and the University of Freiburg in Germany and received his Ph.D. from Ruhr-University of
Bochum. He has held assistant professor and group leader positions at the Max Planck Institute in Göttingen,
Albert-Ludwigs-University in Freiburg. In 2006 he became Unit Leader and in 2010 Team Leader at the RIKEN
Brain Science Institute Wako-Shi, Japan, leading the Computational Neurophysics lab. Currently, he is professor
of Computational Neuroscience at the RWTH University of Aachen and is director of the Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience, and Institute for Advanced Simulation
(IAS-6), Theoretical Neuroscience, at the Forschungszentrum Jülich in Germany.
Prof. Dr. Abigail Morrison (female) • received a Masters degree in Non-symbolic Artificial Intelligence from
University of Edinburgh, UK and a Ph.D. from Albert-Ludwigs University and the Bernstein Center for Computational Neuroscience, Freiburg, Germany. In 2006, she performed postdoctoral work at the Bernstein Center
for Computational Neuroscience, Freiburg, Germany and then became a Research Scientist in Computational
Neurophysics, RIKEN Brain Science Institute, Wako-Shi, Saitama, Japan (2007-2009). Between 2009 and 2012
she acted as a Junior Professor for Computational Neuroscience and led the Functional Neural Circuits Group,
Faculty of Biology, Albert-Ludwigs University, Freiburg, Germany. Since 2012, she is leader of the Functional
Neural Circuits Group, INM-6, Forschungszentrum Jülich, and Professor at the Ruhr University of Bochum,
Germany. Since 2013, she is also heading the Simulation Laboratory Neuroscience at Jülich Supercomputing
Centre, Forschungszentrum Jülich.
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Laboratory Profile
The Computational Biomedicine lab uses a range of computational molecular biology approaches to dissect
structural and energetic aspects of cellular pathways that relate to perception and deranged cascades of events
in molecular medicine and neurobiology. Most of the work is conducted in collaboration with experimental labs.
Key Personnel
Prof. Dr. Paolo Carloni (male) • obtained his Ph.D. in 1993 under the supervision of Prof. M. Parrinello on molecular simulation of metalloproteins. After a postdoc at the IBM Zurich Research Lab, he became professor of
chemistry and head of the Statistical and Biological Physics sector in SISSA, Italy. In 2009 he moved to RWTH
Aachen University, Germany, to lead the Computational Biophysics group of the German Research School at
Forschungszentrum Jülich. Since 2012 he has been Director of the Computational Biomedicine lab (IAS-5) and
by December 2014 he will become Director of the Computational Biomedicine section (INM-9) at the Institute
of Neuroscience and Medicine at Forschungszentrum Jülich. He has published more than 180 articles in computational molecular medicine, bioinformatics and biomolecular simulation. He has supervised more than 30 Ph.D.
students so far in computational biophysics.
Laboratory Profile
As a European leader in high performance computing, the Jülich Supercomputing Centre (JSC) has longstanding expertise in the operation of supercomputers of the highest performance class. In cooperation with
industry partners the JSC co-designs innovative high performance computing technology – meeting the challenges of the next supercomputer generation. Led by Prof. Dr. Dr. Thomas Lippert, the JSC plays an active role
in various national and EC-funded R&D and infrastructure projects in high performance computing, networking,
and distributed/Grid computing. In particular, it has been pivotal in the creation of PRACE, the European supercomputing research infrastructure.
Key Personnel
Prof. Dr. Thomas Lippert (male) • SP 6 Leader / WP 6.7 Leader / Research Board Member • received his
diploma in Theoretical Physics in 1987 from the University of Würzburg. He completed Ph.D. theses in theoretical physics at Wuppertal University on simulations of lattice quantum chromodynamics and at Groningen
University in the field of parallel computing with systolic algorithms. At Wuppertal University he also holds the
chair for Computational Theoretical Physics. Since 2004 he is director of the Jülich Supercomputing Centre.
Thomas Lippert is the executing director of the John von Neumann Institute for Computing of the Helmholtz
Association (NIC) and the director of the Jülich Aachen Research Alliance, section HPC (JARA-HPC). Moreover
he coordinates the implementation projects of the Partnership for Advanced Computing in Europe (PRACE)
and is a member of the Gauß Centre for Supercomputing e.V. Additionally he acts as coordinator in the EU Exascale Projects DEEP and DEEP-ER. Thomas Lippert will lead and co-direct the HPC Platform of the HBP and will
oversee the development of the exascale supercomputer for the HBP.
87
Prof. Dr. Dirk Pleiter (male) • WP 6.5 Leader • is research group leader at the Jülich Supercomputing Centre
and professor for theoretical physics at the University of Regensburg. At JSC he is leading the work on application oriented technology development. During his career he has played a leading role in several special purpose
machine development projects. Currently he is principal investigator of the Exascale Innovation Center and the
NVIDIA Application Lab at Jülich.
Dr. Ing. Bernd Mohr (male) • started to design and develop tools for performance analysis of parallel programs
with his diploma thesis (1987) at the University of Erlangen, and continued this in his Ph.D. work (1987 to 1992).
During a three year Postdoc position at the University of Oregon, he designed and implemented the original
TAU performance analysis framework. At the JSC, which he joined as a senior scientist in 1996, he leads the
“Programming Environments and Performance Optimization” group. Besides being responsible for user support
and training in the area of performance tools, he is leading the KOJAK and Scalasca performance tools efforts
in collaboration with Prof. Dr. Felix Wolf of GRS Aachen. Since 2007 he is the deputy head of the JSC’s “Application Support” division. In 2012, Bernd Mohr joined the International Supercomputing Conference (ISC) program
team. He is an active member in the International Exascale Software Project (IESP) and work package leader in
the European (EESI2) and Jülich (EIC, ECL) Exascale efforts. He serves on the Steering Committees of the SC
and ISC Conference series and is the author of several dozen conference and journal articles about performance
analysis and tuning of parallel programs.
P21
FORTISS, Fortiss GmbH (Germany)
Laboratory Profile
Fortiss will be an institute associated with the Technical University of Munich (“An-Institut”) and as such a fullfledged academic research institute, while enjoying the independence granted by its legal form as a non-forprofit LLC (gemeinnützige Gesellschaft mit beschränkter Haftung – gGmbH). The shareholding partnership will
be equally divided between the Technical University of Munich’s legal entity (Technische Universtität München
(K.d.ö.R.), the Bavarian Business Development Bank (LfA Förderbank Bayern) and the Fraunhofer-Gesellschaft
zur Förderung der angewandten Forschung e.V. The mission of Fortiss is to facilitate research and technology
transfer in software-intensive systems and services, thereby triggering future-ready innovation. Fortiss is an
independent non-profit LLC (gemeinnuetzige Gesellschaft mit beschraenkter Haftung, gGmbH). The Technische
Universität Muenchen (TUM) owns 33% of Fortiss. This setup may change after 31.12.2014.
Key Personnel
Prof. Dr. habil. Alois Knoll (male) • SP 9 Leader / WP 9.7 Leader / WP 9.8 Leader / WP 9.9 Leader / Research
Board Member • is professor of embedded systems and robotics at TUM, where his research focuses on cognitive and sensor-based robots, cyber-physical systems, development tools for fault-tolerant systems, and electric
vehicles. After winning his doctorate (1988) and his lecturer’s qualification (1993) at the Technical University of
Berlin, Alois Knoll became full professor and director of the Computer Engineering group at Bielefeld University,
a position he held until 2001, when he moved to TUM. In this period, he also directed a research group at the
Fraunhofer Institute for Autonomous Intelligent Systems. Since 2009, he has been a Director of Fortiss, a TUM
affiliated Institute, and director of TUM’s Graduate School of Information Science in Health (GSISH), which he
founded in 2008. Professor Knoll is a member of the GI, the IEEE and a Fellow of the University of Tokyo. Alois
Knoll will direct the Neurorobotics Division of HBP.
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P21 FORTISS, Fortiss GmbH (Germany)
Prof. Dr. Patrick van der Smagt (male) • WP 9.3 Leader • holds a professorship on Biomimetic Robotics and
Machine Learning at TUM since 2012 and is researcher at Fortiss since 2013. He is scientific coordinator of the
TACMAN STREP project (2014-2016). He has been scientific coordinator of the following EC projects: SENSOPAC (IP), The Hand Embodied (IP); as well as coordinator of STIFF (STREP) and VIACTORS (STREP). He
has collaborated in various other European and national projects. He is the author of over 100 scientific papers
on robotics, machine learning, sensors, and neuroscience, and holds several tens of patents in these areas. He
is a member of various professional organisations and reviewer for many journals, projects, and government
agencies. In 2012 he received the prestigious Schrödinger Award from the Helmholtz Society; in 2013 the MGH/
Harvard Medical School research prize. His research work focuses on computational neuroscience, machine
learning, body-machine interfaces, and biomimetic robotics. Patrick van der Smagt runs a collaborative lab,
funded by TUM, Fortiss, and the German Aerospace Center (DLR), consisting of 13 PhD students and 2 postdocs.
P22
FG, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. (Germany)
Laboratory Profile
Fraunhofer Institut für Zuverlässigkeit und Mikrointegration is a world leader in microelectronics and microsystem packaging, offering advanced packaging concepts such as packaging material science and characterisation, package design and simulation, high density interconnect and wafer level packaging, chip and board
interconnection technologies, 3D-packaging and vertical chip integration. The WLSI Department Wafer Level
System Integration (WLSI) develops wafer level system integration technologies, including wafer level packaging (WLP), chip size packaging (CSP), thin film technology and 3D integration using through silicon vias (TSVs).
It operates two state-of-the-art clean room facilities and cooperates with manufacturers, material suppliers and
end users to create cutting-edge wafer level packaging solutions. Its technology branches develop, prototype
and produce MCM-D, wafer-level CSP with redistribution layer (RDL), 3D integration and wafer-level bumping.
Key Personnel
Oswin Ehrmann (male) • is head of the Department Wafer Level System Integration (WLSI) at the Fraunhofer
IZM in Berlin. He obtained a degree in physics from the Technical University of Berlin, has twenty-five years of
experience in packaging technologies and has managed several national and international projects.
Laboratory Profile
Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) is Europe’s largest application-oriented
research organisation. The Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), directed by
Prof Dr Michael Griebel, conducts research in the field of computer simulations for product and process development, and is a prominent corporate partner in the industrial and scientific sectors. SCAI designs and optimises industrial applications, implements custom solutions for production and logistics, and offers calculations
on high performance computers. SCAI services combine industrial engineering with state-of-the-art methods
from applied mathematics, computer science and information technology. The institute excels in coupling simulation with efficient numerical tools, and in the development of scientific visualisation software.
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P22 FG, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. (Germany)
Key Personnel
Prof. Michael Griebel (male) • has a Ph.D. (Dr. rer. nat.) in computer science from Technische Universität
München, and a Habilitation (Dr. rer. nat. habil.) at the Technische Universität München. Since 1996 he has been
professor for Scientific Computing and Numerical Simulation at the University of Bonn. Since 2003, he is director of the Institute for Numerical Simulation, University of Bonn. Furthermore, since 2010, he is also director of
the Fraunhofer Institute for Algorithms and Scientific Computing SCAI.
Dr. Jan Hamaekers (male) • is head of the department Virtual Material Design at Fraunhofer SCAI since 2010.
He studied mathematics with emphasis on scientific computing (secondary subject on computer science). He
received a diploma degree in mathematics end of 2002. Furthermore, he obtained a doctorate in natural sciences in 2009 at the University of Bonn. During his graduate studies he was a research assistant at the Institute
for Numerical Simulation at the University of Bonn. He has managed and essentially contributed to several
national, international and industrial projects in areas like numerical simulation and multiscale modeling, high
performance computing and high dimensional approximation.
P23
FCHAMP, Fundacao D. Anna Sommer Champalimaud
E Dr. Carlos Montez Champalimaud (Portugal)
Laboratory Profile
The Champalimaud Foundation (CF), based in Lisbon, Portugal, is an international organisation that aims to
stimulate novel theoretical and practical methodologies by utilising the experience of both research scientists
and medical practitioners. The foundation supports individual researchers and research teams working at the
cutting edge of biomedical science. By supporting these active research programmes, The Champalimaud
Foundation intends to stimulate further clinical research, particularly in the non-profit sector. By doing so, the
Foundation aspires to make a significant contribution to reducing the global burden of illness and disease.
The Champalimaud Neuroscience Programme (CNP) was created in 2007 through a collaborative agreement
between the Champalimaud Foundation and the Calouste Gulbenkian Foundation. It is a basic-research team
with the broad aim of understanding brain function through integrative biological approaches. CNP laboratories apply advanced molecular, physiological and imaging techniques to elucidate the function of neural circuits and systems in animal models that include Drosophila, mouse, rat and zebrafish. The CNP is based at
the Champalimaud Centre for the Unknown (CCU). The CCU is a multidisciplinary centre for neuroscience and
translational cancer research and clinical practice. The Centre contains state-of-the-art facilities for basic and
clinical research that hold cutting edge technological tools and equipment. The CNP also organises the International Neuroscience Doctoral Programme. In this programme students are provided with a broad educational
background through both formal classes and hands-on experience in basic topics of contemporary neuroscience such as cellular and synaptic physiology, sensation and action and cognitive neuroscience. Quantitative
approaches are emphasised and students also receive background courses in mathematics and programming.
Key Personnel
To be decided.
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P24
UDUS, Heinrich Heine Universität Düsseldorf (Germany)
Laboratory Profile
The C. and O. Vogt Institute of Brain Research is one of the major German centres of neuroscience, with a long
and prominent history in brain mapping. Brodmann’s cytoarchitectonic and Vogt’s myeloarchitectonic maps of
the cerebral cortex from the beginning of the 20th century have put the basis for the recent activities of the
institues in the field of modern structural and functional neuroimaging. Today, the Institute houses not only the
200,000 histological brain sections collected by the Vogts, but also other unique collections, including brains of
humans, great apes and non-human primates, and other mammals. The JuBrain atlas, a cytoarchitectonic probabilistic atlas of brain areas, that researchers of the institute have developed together with their Jülich partners,
are based on this collection. Under the leadership of Karl Zilles, the institute has been developed into a modern
institute for brain research, and has established modern quantitative tools of analysis and 3D mapping of human
brains. The lab has a staff of four post-docs, four technicians, and four doctoral students, is fully equipped for
histology, autoradiography, and in situ hybridisation, and image analysis, and has access to an animal house and
a 3T MR scanner.
Key Personnel
Prof. Dr. med. Katrin Amunts (female) • SP 2 Leader / WP 1.5 Leader / WP 2.5 Leader / WP 2.6 Leader / WP
4.3 Leader / Research Board Member • did postdoctoral work in the C. & O. Vogt Institute for Brain Research at
Düsseldorf University, Germany. In 1999, she moved to the Research Centre Jülich and set up a new research unit
for Brain Mapping. In 2004, she became professor for Structural-Functional Brain Mapping at RWTH Aachen
University, and in 2008 a full professor at the Department of Psychiatry, Psychotherapy and Psychosomatics
at the RWTH Aachen University as well as director of the Institute of Neuroscience and Medicine (INM-1) at
the Research Centre Jülich. Since 2013, she is full professor for Brain Research at the Heinrich-Heine University
Düsseldorf, director of the C. and O. Vogt Institute for Brain Research, Heinrich-Heine University Düsseldorf and
director of the Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich. In 2007 Katrin Amunts
became a member of the editorial board of Brain Structure and Function. Since 2012 she is member of the
German Ethics Council. She is the programme speaker for the programme “Decoding the Human Brain” of the
Helmholtz Association, Germany, and director of the subproject “strategic human brain data” of the HBP.
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P24 UDUS, Heinrich Heine Universität Düsseldorf (Germany)
Laboratory Profile
The Institute of Clinical Neuroscience and Medical Psychology is dedicated to the integrated understanding of
physiological and pathological brain organization. In a translational approach brain structure, function and connectivity is investigated in a multi-modal fashion based on MRI and electrophysiological approaches. Based on
the ensuing understanding of normal brain networks and their inter-individual variability, aberrations in patients
with, e.g., Parkinson’s disorder, Depression or Schizophrenia are then investigated to elucidate dysfunctional
processes and their relation to clinical symptoms.
Key Personnel
Prof. Dr. med. Simon B. Eickhoff (male) • WP2.4 Leader • studied medicine in Aachen, Sheffield, Sydney and
London. He received his doctorate degree in neuroanatomy in 2006 after working on structure-function correlations at the C. & O. Vogt Institute for Brain Research at Düsseldorf University. He continued his work on brain
atlases and multi-modal neuroimaging as a post-doctoral researcher at the Research Centre. In 2009 he was
appointed as assistant professor for Psychiatry at the RWTH Aachen. Here his work centred on functional MRI,
network analysis and computational modelling. Since 2011, Simon Eickhoff is professor for cognitive neuroscience at the Heinrich-Heine University in Duesseldorf and deputy director of the Institute of Neuroscience and
Medicine in Jülich, where he leads the Brain Network Modelling group. His main research interest is the development and application of novel analysis tools and approaches for large-scale, multi-modal analysis of brain structure, function and connectivity. Simon Eickhoff is handling editor for Neuroimage as well as Brain Structure &
Function, the developer of the SPM Anatomy Toolbox and a major contributor to ALE and the BrainMap project.
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P25
UH, Helsingin yliopisto (Finland)
Laboratory Profile
Neuroscience Center: Matias Palva Group (MPG) Neuroscience Center (NC) is an independent multi-disciplinary
research institute of the University of Helsinki. Research in NC ranges from molecular neuroscience to in vitro/
vivo electrophysiology and in vivo imaging of awake animals, human genetics, and human brain imaging. NC
has at its disposal equipment for concurrent magneto- and electroencephalography, functional and anatomical
magnetic resonance imaging, multi-site trans-cranial magnetic stimulation, and server resources for data management. Matias Palva Group performs non-invasive brain imaging and stimulation experiments with healthy
subjects and select patient groups as well as invasive stereo-encephalography recordings through collaboration projects. MPG invests considerable efforts also to data-analysis and informatics method developments and
implementing first-person video games into becoming key tools for next-generation human brain research.
Key Personnel
Dr. J. Matias Palva • obtained his M. Sc. Tech in the Helsinki University of Technology and a Ph. D. in neurophysiology in the University of Helsinki where he today is an group (12 researchers) leader at the Neuroscience Center.
The overarching research objective of J.M. Palva has been to discover the neuronal interactions and dynamics
that as systems-level mechanisms causally support multi-scale mental states. These interactions range from
millisecond scale neuronal synchronization to correlations among infra-slow multi-second fluctuations, each
with specific behavioral and cognitive correlates. J.M. Palva’s research has produced a methodological basis and
proof-of-concept for comprehensive mappings of dynamic phase and amplitude interactions with non-invasive
(MEG/EEG) and invasive (SEEG) electrophysiological methods. This work bridges systems-level neurophysiological mechanistic understanding with “neurogaming” applications for both ecologically valid cognitive neuroscience and potential brain-disease therapies.
Laboratory Profile
Neuroscience Center: Satu Palva Group (SPG) laboratory investigates the system-level neuronal mechanisms
underlying perception, attention, and memory, as well as the mechanisms that lead to short- and long-term
variability in the behavioural performance in these functions. SPG uses magneto- and electroencephalography
(MEG/EEG) to non-invasively record neuronal activity during cognitive tasks, neuroinformatics-oriented datadriven analysis approaches to identify local and large-scale cortical networks of neuronal interactions that beget
momentary task performance, and rhythmic transcranial magnetic stimulation (rTMS) to entrain or disengage
these MEG/EEG targeted cortical processes.
Key Personnel
Dr. Satu Palva (female) • obtained her Master’s degree in the Biology and Ph.D. in Psychology in the University
of Helsinki. Today she is a group (10 researchers) leader at Neuroscience Center, University of Helsinki in where
she has successfully pursued the hypothesis that phase synchronization of neuronal oscillations could underlie
the binding of scattered processing into unified attention, memory, and consciousness through the coordination
and binding of distributed neuronal activity. Work on the functional significance of transient neuronal dynamics
and phase coupling within and between frequency bands may yield mechanistic insight into the emergence of
cognitive and perceptual brain functions. SPG also addresses the changes that cortical oscillations and synchronization undergo during developmental and experience-dependent plasticity and their roles in an array of
neuropsychiatric diseases.
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P26 HITS, HITS gGmbH (Germany)
Laboratory Profile
HITS is a private, non-profit research institute that carries out multidisciplinary research in the computational
sciences. The focus of the Molecular and Cellular Modelling group is on the development and application of
computer-aided methods to predict and simulate protein interactions, using approaches based on the 3D structure of macromolecules. The group uses a broad spectrum of techniques ranging from interactive, web-based
visualisation tools to molecular and Brownian dynamics simulations. Led by Prof Rebecca Wade, the group currently includes around twelve researchers with expertise in computational structural biology, molecular modelling and simulation and bioinformatics.
Key Personnel
Prof. Rebecca Wade (female) • is an alumnus of the University of Oxford, where she obtained her B.A. Hons.
in Physics, and D. Phil. in Molecular Biophysics. She then did her postdoctoral research in the USA in Houston
and Illinois. She was a group leader in the Structural and Computational Biology Programme at the European
Molecular Biology Laboratory (EMBL) in Heidelberg from 1992 to 2001. Since then she has led the Molecular and
Cellular Modelling group at EML Research (now HITS). Since 2011, she has also held a Professorship in Computational Structural Biology at the University of Heidelberg.
P27
CHUV, Hospices Cantonaux CHUV (Switzerland)
Laboratory Profile
The “Laboratoire de recherche en neuroimagerie” (LREN) consists of a cross-disciplinary team of basic and
clinical neuroscientists with an interest in the role of human brain structure and function in neurological disorders and healthy aging. The LREN develops and applies neuroimaging analysis methods to study brain plasticity,
brain repair mechanisms, and the pathological processes that underlie neurodegenerative diseases. Ultimately,
the goal is to translate basic research findings into clinical applications for early disease detection and prediction of clinical outcomes.
Headed by Bogdan Draganski, the lab is part of the Department of Clinical Neurosciences (DNC) at CHUV, the
University Hospital of Lausanne, Switzerland. This allows close collaboration with clinicians and access to neuroimaging tools including 3T MRI, 7T MRI, and EEG. On-going collaborations with the “Centre Leenaards de la
Mémoire” (part of CHUV-DNC) and the CHUV hospital datawarehouse provide access to large, well-characterised, cohorts of patients with neurodegenerative disorders.
Within HBP the LREN is responsible for setting up the Medical Informatics Platform, under the leadership of
Prof. Richard Frackowiak and Dr. Ferath Kherif. The platform will federate hospital and other clinical data on all
brain diseases and across multiple levels of biology.
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P27 CHUV, Hospices Cantonaux CHUV (Switzerland)
Key Personnel
Prof. Richard Frackowiak (male) • Executive Committee Member / SP 7 Leader / SP 11 Co-leader / WP7.6
Leader / Research Board Member • is a clinical neurologist who has spent his life researching the human brain
with non-invasive brain imaging techniques. He is Professor and head of the Department of Clinical Neurosciences (DNC) at the Université de Lausanne (UNIL) and its Centre Hospitalier Universitaire Vaudois (CHUV). He
also holds a titular professorship at the Ecole Polytechnique Fédérale de Lausanne (EPFL) and is a co-executive
director responsible for “Future Medicine” in the EU’s Flagship of Enterprise and Technology (FET) “The Human
Brain Project”. He is leading sub-project 8 (SP8), which is putting together the medical informatics infrastructure in the ramp-up phase. He is a pioneer of human brain imaging research, developing a number of techniques and applying them to the investigation of human brain structure and function relationships in health and
disease. There is also a translational component to his research involving novel image classification techniques
for studies in individuals. His scientific output is highly cited with an h-index of 150 and he has received the Ipsen,
Wilhelm Feldberg and Klaus Joachim Zulch prizes.
Dr. Ferath Kherif (male) • WP 7.4 Leader / WP 7.5 Leader • is a Senior Lecturer at the University of Lausanne
and Deputy Director at the Laboratoire de Recherche en Neuroimagerie (LREN), Department of Clinical Neurosciences (DNC) at the University Hospital of Lausanne (CHUV). Ferath Kherif obtained his PhD in neuroscience
at the University Pierre et Marie Curie in Paris. Before joining CHUV in 2010, he has been a Research Fellow at
MRC-CBU in Cambridge and at the Wellcome Trust Center for Neuroimaging in London (UCL). Ferath Kherif,
has several years of experience in multidisciplinary research. He has deep knowledge and expertise in two key
domains: mathematical and statistical modelling, and psychology. He has used functional imaging to probe cognitive function and has used his mathematical background to test new hypotheses pertaining the explanation of
individual differences. Ferath Kherif is presently coordinating and directing the work of the various components
of the Medical Informatics Platform of the Human Brain Project.
Prof. Bogdan Draganski (male) • is Consultant Neurologist at the Department of Clinical Neurosciences, University Hospital of Lausanne (CHUV) and Director of the neuroimaging laboratory LREN. After qualifying in
medicine in Germany, he spent time working on computational anatomy research in movement disorders at the
Institute of Neurology at UCL (London UK) followed by research at the Max Planck Institute for Human Cognitive and Brain Sciences (Leipzig Germany). Professor Draganski’s ongoing projects are in the field of movement
disorders, with particular emphasis on the identification of surrogate imaging biomarkers of typical and atypical Parkinsonian disorders as an aid to the development of new therapeutic approaches especially in the field
of deep brain stimulation (DBS). His wide-ranging research interests span both Parkinson’s disease, dystonia
and Gilles de la Tourette’s syndrome. Professor Draganski is Academic Editor for the journal PLOS One, Review
Editor for the journal Frontiers in Human Neuroscience and is a member of the Dystonia Medical Research Foundation Scientific Advisory Council. Professor Draganski is presently involved in the development of the Medical
Informatics Platform of the Human Brain Project. His task is to develop strategies for future data collection.
P28
ICL, Imperial College of Science, Technology and Medicine (United Kingdom)
Laboratory Profile
Department of Computing, Computational Neurodynamics Group, Specialising in science and technology,
Imperial College London was founded in 1907, and is today considered one of the world’s leading universities. It was placed 5th in the world in the 2013/14 QS world rankings, and 10th in the world in the Times Higher
Education world rankings. The Computational Neurodynamics Group is part of Imperial College’s Department
of Computing, which is recognised internationally for its excellence in research. It has always been ranked at
the highest level in successive UK Research Assessment Exercises. The Computational Neurodynamics group
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P28 ICL, Imperial College of Science, Technology and Medicine (United Kingdom)
studies the dynamics of large-scale networks of spiking neurons using computer simulation and robotics. The
group’s members have a range of backgrounds and provide expertise and a publication track record in neural
dynamics, robotics, high-performance computing, artificial intelligence, and philosophy.
Key Personnel
Prof. Murray Shanahan (male) • is Professor of Cognitive Robotics at Imperial College London, and head of the
Neurodynamics group. He obtained his PhD in computer science from Cambridge University (King’s College)
in 1988. Since then he has carried out work in artificial intelligence, robotics, and cogitive science. He built an
international reputation in the 1990s with his work in logic-based artificial intelligence, specifically on reasoning
about actions and spatial reasoning, and with the publication of his influential book Solving the Frame Problem
(MIT Press, 1997). For the past decade or so he has turned his attention to the brain and its embodiment, and
has published significant recent results on brain connectivity and neural dynamics. Professor Shanahan has been
principal investigator on seven UK research council-funded projects since 1994, worth close to €2.2 million.
Laboratory Profile
Department of Electrical & Electronic Engineering, Personal Robotics Laboratory, The Personal Robotics
Laboratory is part of Imperial College’s Department of Electrical and Electronic Engineering, which is recognised
internationally for its excellence in research. The Personal Robotics Laboratory carries out research towards
intelligent robotic devices that interact with their users, learn from them, and adapt their assistance to maximise their users’ physical, cognitive, and social well-being. The laboratory’s research spans several topic areas,
including machine learning, user modelling, cognitive architectures, human action analysis, and shared control.
The lab’s aim is to advance fundamental theoretical concepts in these fields without ignoring the engineering
challenges of the real world, so our experiments involve real robots, real humans, and real tasks.
Key Personnel
Dr. Yiannis Demiris (male) • is a Reader (Associate Professor) in the Department of Electrical and Electronic
Engineering, and heads the Personal Robotics Laboratory. He received his BSc(Honours) and PhD from the
Department of Artificial Intelligence of the University of Edinburgh. He has significant expertise in cognitive
systems, robot human interaction, machine learning, user modelling and learning by demonstration, in particular in human action perception and learning. Dr Demiris’ research is funded by the UK’s Engineering and
Physical Sciences Research Council (EPSRC), the Royal Society, BAE Systems, General Dynamics UK, the EU
FP7 program through projects ALIZ-E, EFAA, and WYSIWYD and the BBC’s Research and Development Dept.
for the “Learning Human Action Models” project. He has guest edited special issues of the IEEE Transactions
on SMC-B on Learning by Observation, Demonstration, and Imitation, and of the Adaptive Behavior Journal on
Developmental Robotics. He has organized six international workshops on Robot Learning, BioInspired Machine
Learning, and Imitation in Animals and Artifacts (AISB), was the chair of the IEEE International Conference on
Development and Learning (ICDL -2007), as well as the program chair of the ACM/IEEE International Conference on Human-Robot Interaction (HRI) 2008.
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P28 ICL, Imperial College of Science, Technology and Medicine (United Kingdom)
Laboratory Profile
Scientific Data Management Laboratory, The Scientific Data Management laboratory focuses on inter-disciplinary research, bridging the gap between data management research as well as other sciences. Driven by the
data management challenges of researchers in different disciplines, the laboratory develops novel methods and
indexes to analyze the growing amounts of scientific data more efficient and more scalable than the state of
the art. Through the research of our lab we enable and accelerate new scientific discoveries. Headed by Thomas
Heinis, the lab results are regularly published in top database conferences and journals, such as ACM SIGMOD
and VLDB.
Key Personnel
Dr. Thomas Heinis (male) • is a lecturer (assistant professor) at Imperial College, UK where his research focuses
on scalable data management algorithms for large-scale scientific applications. His recent work is inspired by a
collaboration with the neuroscientists of the Blue Brain project (BBP). Together they have developed the data
management infrastructure necessary for scaling up brain simulations. Prior to joining Imperial, Thomas was
a post-doctoral researcher in the data-intensive applications and systems (DIAS) group at EPFL and he completed his Ph.D. in the Systems Group at ETH Zurich, where he pursued research in workflow execution systems
as well as data provenance. He has served as member of several program and organization committees and as
reviewer for many conferences and journals, particularly in database field.
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P29 ICM, L’Institut du cerveau et de la moelle épinière (France)
Laboratory Profile
Molecular basis, physiopathology and treatment of neurodegenerative diseases lab, The research group of
Alexis Brice with approximately 50 people focuses on the phenotypical and genetic characterization of patients
with different neurodegenerative conditions (Huntington’s disease-HD, Parkinson’s disease-PD, frontotemporal
lobar degenerations, etc) and has made significant contributions in the fields of genetics and physiopathology
of these disorders. Dr Dürr and Profs Brice and Corvol coordinate several national and international research
networks in PD (Parkinson’s Disease Genetics in France), inherited ataxias and spastic paraplegias (SPATAX
network), HD (French network of centers for presymptomatic testing) and FTLD (French research network on
FTLD/FTLD-MND). These networks have contributed detailed phenotypical data (including neuroimaging for a
subset) and biomaterial (DNA, cells, eventually plasma) for more than 40000 individuals with neuropsychiatric
disorders.
Key Personnel
Prof. Alexis Brice (male) • WP7.3 Leader • From 2001 to 2009, has been the Head of the Department of Genetics at the Pitié-Salpêtrière University Hospital associated with the University Pierre and Marie Curie (Paris 6)
medical school. He is also the coordinator of the National Reference Centre for Neurogenetics. Since May 2012,
he is director of the ICM (Brain and Spine Institute) and heads a research group doing research on Neurogenetics
and the DNA and Cell Bank at the Brain and Spine Institute, associating the ICM foundation, CNRS, INSERM and
the University Pierre and Marie Curie at the Pitié-Salpêtrière Hospital. A graduate of the Necker-Enfants-Malades
of Paris medical school, he received his neurological training in Paris before being appointed associate professor of Cell Biology then professor of Genetics at the University Pierre and Marie Curie. He has held positions in
a variety of national and international scientific boards including the Wellcome Trust and was vice-president of
the Inserm Avenir Program, and is a member of the editorial board of several journals in the fields of Genetics
and Neurology. He also was Chairman of the Institute for Neuroscience, Neurology and Psychiatry in Paris from
2008 to 2012. His research, which includes both clinical and basic research, aims at elucidating the molecular
basis and physiopathological mechanisms of several hereditary neurodegenerative disorders including Parkinson’s disease, frontotemporal lobar degeneration, cerebellar ataxia and spastic paraplegia. He received awards
from the Academy of Science (Institut de France: Prix François Lhermitte for research on Parkinson’s Disease
in 2005), from the Academy of Science (Institut de France: Grand Prix Lamonica de Neurologie in 2011) and the
Prize of the Roger de Spoelberch Foundation in 2012.
Dr. Alexandra Durr (female) • is a neurologist trained in genetics and specialised in neurogenetics of rarer diseases. Her hospital work is at the department of genetics of the Pitié-Salpêtrière University hospital where she
runs the national reference centre for neurogenetics. Hospital practitioner since 1998 she is being promoted full
professor in medical genetics at the University Pierre and Marie Curie. Her research is devoted to the elucidation
of the genetic bases of rare neurodegenerative diseases and their physiopathology. She is also coordinating
several, interventional or observational, clinical trials for diseases like spinocerebellar ataxias, spastic paraplegia,
Huntington’s disease. She has held positions in scientific boards (Inserm transversal committee for genetics) and
is currently member of the Scientific council of Inserm and of the Fondation pour la Recherche Médicale (FRM).
Prof Jean-Christophe Corvol (male) • was graduated at the University Pierre and Marie Curie (Paris) in Neurology (MD, 2003), and in Neurosciences (PhD, 2005). He had a post-doc position at UCSF in the Neurogenetic
laboratory of Jorge Oskenberg in 2006-2007, and he was associate professor at the and Pitié-Salpêtrière hospital between 2007 and 2013. Since 2013, JC Corvol is Professor of Neurology at the Department of Neurology
at the Pitié-Salpêtrière Hospital; he is at the head of the Clinical Research Center for Neurosciences at the ICM
since 2008 (INSERM/DGOS CIC-1422, ICM); he is co-chair of the French Clinical Research Network for Parkinson’s disease and Movement Disorders since 2010 (NS-Park network). His research is focused on the pharmacology, pharmacogenetics, and gene modifiers of Parkinson’s disease.
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P29 ICM, L’Institut du cerveau et de la moelle épinière (France)
Laboratory Profile
Motivation, Brain and Behavior (MBB) Lab, The MBB lab is led by Mathias Pessiglione. The aim of the MBB lab
is to understand human motivation. This can be reduced to knowing how we form goals and how these goals
translate into behaviour. The lab combines studies of human cognition, primate neurophysiology, and computational modelling, The long-term objective is to build a neuro-computational theory that accounts for the determination of human behaviour, and enables sound predictions of clinical and economic outcomes.
Key Personnel
Prof. Mathias Pessiglione (male) • has an MD in cellular biology, clinical psychology and cognitive science. He
obtained his doctoral degree with Léon Tremblay, working on motivation disorders in a primate model of Parkinson’s disease and did his post doctoral work with Chris Frith in London, where he focused on reward-based
behaviour using model-based pharmaco-fMRI in humans. Since 2010, he is the leader of the Motivation, Brain
and Behavior (MBB) lab and coordinator of the Cognition, Emotion and Behavior axis at the Institut du Cerveau
et de la Moëlle Epinière (ICM, Pitié-Salpêtrière Hospital, Paris). He is jointly responsible for the neuroscience
major in the CogMaster programme (Ecole Normale Supérieure, Paris), and member of the Inserm national committee for neuroscience.
P30
IEM HAS, Institute of Experimental Medicine
Hungarian Academy of Sciences (Hungary)
Laboratory Profile
The Laboratory of Cerebral Cortex Research is part of the Institute of Experimental Medicine of the Hungarian
Academy of Sciences. Research at the lab focuses on the principles that govern the structural and functional
organisation of the cerebral cortex, and specifically the operation of the neuronal microcircuits responsible for
mental operations such as conscious perception and memory. Over the past two decades the lab has made
conceptually novel steps toward uncovering: 1) the role of new molecular pathways in the communication within
nerve cells, 2) basic principles governing connectivity among nerve cells, and 3) principles governing the generation of network activity patterns by neuronal circuits. These findings shed new light not only on the normal
operations of the cerebral cortex, but also on several of its disorders at the molecular, cellular and network levels.
Key Personnel
Prof. Tamás Freund (male) • is Director of the Institute of Experimental Medicine, Hungarian Academy of Sciences, and Head of the Department of Neurosciences, Pázmány Péter Catholic University, in Budapest. He
defended his PhD under the supervision of Péter Somogyi and János Szentágothai, and spent 4 years in Oxford
working with A. David Smith and Péter Somogyi. He became head of department (1990), then deputy director
(1993), and director (2002) of the Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest. He was president of the Federation of European Neuroscience Societies (FENS, 2004-2006), and served
as Chairman of the IBRO Central and Eastern Europe Regional Committee (1999-2003). He is section editor of 2
major international journals, editorial board member of six others, and published over 230 peer-reviewed papers
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P30 IEM HAS, Institute of Experimental Medicine, Hungarian Academy of Sciences (Hungary)
in international journals. He is a member of the Hungarian Academy of Sciences (1998), and several other scientific academies. The major prizes and awards he received include: the Demuth Award (1991, Switzerland), the
Krieg Cortical Kudos Cortical Discoverer Award and the Cajal Medal of the Cajal Club (1998, U.S.A.), the Kemali
Foundation Award (1998, FENS Forum, Berlin), the Bolyai Prize (2000, Hungary), the Széchenyi Prize (2005,
Hungary), and the Brain Prize (2011, Denmark).
P31
IST, Institute of Science and Technology Austria (Austria)
Laboratory Profile
The Jonas Lab: Synaptic communication in hippocampal microcircuits, Peter Jonas’ lab at IST Austria explores
how synaptic properties determine higher brain functions. To address this question, he uses cutting edge electrophysiology, imaging, and optogenetics both in vitro and in vivo. He also develops realistic models of channels,
synapses and neuronal networks. In particular, he has pioneered techniques of nanophysiology that allow the
recording from dendrites, axons and presynaptic terminals. Elementary processes are examined at microsecond
temporal resolution and nanometer spatial resolution. Current focus of the lab is on mechanisms of mossy fiber
synaptic transmission in the hippocampal CA3 region and on fast-spiking, parvalbumin-expressing interneurons
in the dentate gyrus, the input region of the hippocampus.
Key Personnel
Prof. Peter Jonas (male) • originally studied medicine and obtained his MD in physiology. He subsequently
worked as a postdoctoral fellow at the Max-Planck Institute for Medical Research in Heidelberg, Germany, in
the Department Cell Physiology headed by the Nobel Laureate Bert Sakmann. He then was Associate Professor at the Technical University of Munich. In 1995, he was appointed Full Professor of Physiology and Director
of the Institute of Physiology at the University of Freiburg, Germany. At the same university, he also headed a
collaborative research center. In 2010, he was appointed Full Professor of Neuroscience and founding member
of a Neuroscience Research Cluster at IST Austria (Institute of Science and Technology Austria) in Klosterneuburg, Austria. He received several research awards, including The Gottfried Wilhelm Leibniz Prize (the highest
research award in Germany), The Tsung Ming Tu Award, and an ERC Advanced Grant “Nanophysiology”. He has
been member of the editorial board of several journals, and he is currently member of the board of reviewing
editors of the interdisciplinary journal Science.
P32
JSI, Institut Jozef Stefan (Slovenia)
Laboratory Profile
Department of Knowledge Technologies, The Jožef Stefan Institute is a research organization for basic and
applied research in natural sciences and technology, with a total of 962 staff (748 research). Thus, JSI is a
national institute, complementing the universities and bridging the gap between science and industry. The
Department of Knowledge Technologies performs research in advanced information technologies, aimed at
managing knowledge for knowledge-based applications, including intelligent data analysis (machine learning,
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P32 JSI, Institut Jozef Stefan (Slovenia)
data mining, knowledge discovery in databases), text and web mining, semantic web, social network analysis,
language technologies, decision support and knowledge management. We apply these technologies to practical problems in the areas of environmental and life sciences, medicine, economy and marketing. The department’s research program has been evaluated as the best research program in ICT (2004-2008) by the Slovenian
Research Agency. The Department has been and is involved in many EU-funded research projects over a period
of almost two decades (ranging from the ESPRIT III program to FP7). Members of the department have authored
Key Personnel
Prof. Sašo Džeroski (male) • is a Scientific Councillor at the Department of Knowledge Technologies, JSI, and
a professor at Jožef Stefan International Postgraduate School. His research interests are related to machine
learning and its application to practical problems from environmental and life sciences. He has made major
contributions to the machine learning areas of relational learning, computational scientific discovery, inductive
databases and constraint-based data mining. Recent contributions include methods for learning of models for
structured prediction and methods for learning dynamics from temporal/streaming data. He has used machine
learning methods to solve practical problems in many areas of environmental and life sciences, including the
analysis of heterogeneous data about patients with embryonal tumors and the analysis of data concerning the
mechanisms through which M. tuberculosis and Salmonella manipulate the human immune system. He was/
is coordinator of the EU-funded network of excellence ILPnet2, the projects IQ (Inductive Queries for Mining
Patterns and Models, FP6) and MAESTRA (Learning from Massive, Incompletely annotated, and Structured
Data,FP7), and was actively involved in many other: ILP, ILP2, ILPnet, METAL, FP5, ECOGEN, cInQ, SIGMEA,
EET Pipeline, PHAGOSYS, REWIRE, SUMO. His publication record includes more than 10 co-authored and coedited books, more than 40 book chapters, more than 120 journal papers, and almost 200 conference papers.
The latest two volumes he has edited are »Computational Discovery of Scientific Knowledge« (2007) and
»Inductive Databases and Constraint-Based Data Mining« (2010). His work is highly cited and has 10000 Google
Scholar citations (h-index = 47). He is an ECCAI fellow since 2008.
Prof. Nada Lavrac (female) • is the Head of the Department of Knowledge Technologies, and Professor at Jožef
Stefan International Postgraduate School and University of Nova Gorica. Her recent research involves relational
data mining, semantic data mining, text mining and cross-context knowledge discovery, as well as development of data mining infrastructures. She coordinated and participated in several EU projects: she was coordinator of ILPnet, co-coordinator of 5FP EU project SolEuNet, and JSI Principal Researcher in the projects ILP,
ILP2, ECOLEAD, Healthreats, BISON, eLICO, MUSE, PROSECCO, WHIM, and ConCreTe. She is currently leader
of a large national research programme Knowledge Technologies. She is co-author/editor of several books in
machine learning. Her latest book “Foundations of Rule Learning” was just published by Springer in 2013. She is
an ECCAI fellow since 2007.
P33
INRIA, Institut National de Recherche en Informatique et en Automatique (France)
Laboratory Profile
The NeuroMathComp Lab: Mathematical and Computational Neuroscience, INRIA is dedicated to fundamental
and applied research in information and communication science and technology (ICST). The long-term goal of
the NeuroMathComp group, led by Olivier Faugeras, is to unveil the principles that govern the functioning of
neuronal assemblies at a variety of spatial and temporal scales. The members of the group have extensive experience in the mathematical modelling of populations of neurons at different levels of biological organisation. An
important topic of research is the application of probabilistic descriptions to account for emerging properties
of these populations, to explain the role of randomness in the functioning of the brain, and to investigate various
aspects of the central idea of sparse representations in the neural codes.
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P33 INRIA, Institut National de Recherche en Informatique et en Automatique (France)
Key Personnel
Prof. Olivier Faugeras (male) • is a mathematician and computer scientist working in theoretical neuroscience.
He is Research Director at INRIA, where he leads the NeuroMathComp Laboratory, a joint scientific venture
between INRIA, and the JAD Laboratory at the UNSA. He is a member of the French Academy of Sciences and
the co-Editor in Chief of the Journal of Mathematical Neuroscience, published in Open Access by Springer.
Dr. Bruno Cessac (male) • is a Statistical Physicist specialized in theoretical neuroscience. He is Research Director at INRIA Sophia Antipolis in the NeuroMathComp group. His main interest concerns neuronal networks
dynamics. He has developed methods combining dynamical systems theory, statistical physics and ergodic
theory allowing to classify dynamics arising in canonical neuronal networks models like integrate and fire models
or firing rate models.
Dr. James Inglis (male) • is a mathematician with a background in probability theory and stochastic processes.
He has been working for 3 years on mean-field effects in the brain, and gained his grant to continue this research.
He is particularly interested in phenomena that emerge from large networks of interacting neurons (both from
a theoretical and numerical point of view), and has experience with many different noisy models that attempt
to bridge the gap between microscopic and macroscopic scales. Dr. James Inglis has a Starting Research Grant
for up to 6 years at Inria Sophia Antipolis - Méditerranée.
Romain Veltz (male) • is a mathematician and computer scientist and a researcher at INRIA Sophia Antipolis
(France) since Sept. 2013 in the NeuroMathComp group after postdoctoral studies at the Salk Institute (San
Diego) under the supervision of Terry Sejnowski. He is an expert in the field of bifurcation theory and delay differential equations and uses these tools for the study of emergent phenomenon in neural networks at various
scales.
Laboratory Profile
Parietal: machine learning for brain mapping, Parietal builds tools to model the anatomo-functional structure
of the brain. The tools will facilitate the analysis of data from methods such as functional MRI and will allow the
application of non-rigid coregistration techniques, image-based atlas learning methods, brain parcellation and
probabilistic model selection to model building. A key goal is to develop a model of the interactions between
spatially remote brain regions, and thus to gain new insights into functional connectivity. Headed by Bertrand
Thirion, Parietal is an INRIA team and is part of the NeuroSpin neuroimaging platform. The Parietal group has
two permanent INRIA researchers, one CEA researcher, and about twelve other members.
Key Personnel
Dr. Bertrand Thirion (male) • graduated from Ecole Polytechnique and specialised in applied mathematics,
with applications to computer vision. His Ph.D. thesis, supervised by Olivier Faugeras, dealt with the statistical
analysis of functional brain images. Since his post-doctoral work at SHFJ, Orsay, his research has focused on the
modelling of inter-brain variability in group studies, the mathematical study of functional connectivity and the
use of machine learning tools for brain activity analysis. He has co-authored about 80 papers Bertrand in neuroimaging, medical image analysis and machine learning conferences and journals. He is also core contributor of
important software for neuroimaging (Nilearn, Nipy) and machine learning (scikit learn).
Dr Gaël Varoquaux (male) • Gael Varoquaux is an tenured computer researcher at INRIA. His research develops
statistical learning tools for functional neuroimaging data with application to cognitive mapping of the brain
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P33 INRIA, Institut National de Recherche en Informatique et en Automatique (France)
as well as the study of brain pathologies. In addition, he is heavily invested in software development for data
science, as project lead for scikit-learn, one of the reference machine learning toolboxes. Varoquaux has contributed key methods to learn functional brain atlases and connectome structure from task-based and rest fMRI,
as well as methods for statistical mapping and decoding of functional brain imaging. He has a PhD in quantum
physics and is a graduate from Ecole Normale Superieure, Paris.
P34
IP, Institut Pasteur (France)
Laboratory Profile
The Integrative Neurobiology of Cholinergic Systems Lab at Pasteur Institute (Paris) works on the functional
analysis of brain circuits, adopting a multi-level approach. Specifically, it aims to understand how nicotine acts
on the brain, affects cognition, and causes addiction. Its strength lies in the association of different kinds of
complementary expertise allowing it to address this problem from an integrative point of view. It is led by Uwe
Maskos and consists of 11 people. In the HBP, the lab will take administrative responsibility for the work of Prof.
Jean-Pierre Changeux (see below) who will lead the HBP Ethics and Society Programme.
Key Personnel
Prof. Jean-Pierre G. Changeux (male) • SP10 Co-leader / WP10.6 Leader / Research Board Member • is honorary professor at the Pasteur Institute and at the Collège de France in Paris. He received his doctorate in natural
sciences from Institut Pasteur in 1964 under the supervision of Jacques Monod and completed his postdoctoral
studies at the University of California, Berkeley, and the Columbia University College of Physicians and Surgeons.
He then returned to the Pasteur Institute, where he was director of the Unit of Molecular Neurobiology from 1972
to 2006. From 1992-1998 Changeux was chairman of the French National Bioethics Committee (1992-1998). He
has written or co-written several books on neuroscience for general audiences, including Neuronal Man; Conversations on Mind, Matter and Mathematics; What Makes Us Think: A Neuroscientist and a Philosopher Argue
About Ethics, Human Nature and the Brain; and The Physiology of Truth: Neuroscience and Human Knowledge.
He is a member of the US National Academy of Science and has received many awards for his work including the Canada-Gairdner foundation award, the Richard Lounsbery Prize, the Wolf Prize, the Balzan Prize, the
National Academy of Science’s Award in Neuroscience, and the Lewis Thomas Prize for Writing about Science.
He is Grand Croix of the Légion d’Honneur. Jean-Pierre Changeux will direct the Ethics and Society Division of
the HBP.
P35 UFRA, Johann Wolfgang Goethe Universität Frankfurt am Main (Germany)
Laboratory Profile
G-CSC, the Goethe Center for Scientific Computing, is a research center of the Goethe University, Dept. of
Computer Science. currently, 25 scientists are working there on the development of models, algorithms and
software for numerous challenging applications, such as signal processing in neurons, groundwater flow and
transport and many more. Special interest is on multi-scale modeling, fast and robust solvers and high-perfor-
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P35 UFRA, Johann Wolfgang Goethe Universität Frankfurt am Main (Germany)
mance computing. The center develops the software UG 4 as a general software platform for models based on
partial differential equations. Another speciality is the development of algorithms and software for the reconstruction of cell morphologies.
Key Personnel
Prof. Dr. Gabriel Wittum (male) • is Professor for Modeling and Simulation at the Goethe-University Frankfurt
am Main, Germany. He is currently serving as dean of studies for Computer Science there. Wittum graduated
in Mathematics and Physics from the University of Karlsruhe in 1983. He earned a doctorate in Applied Mathematics from the University of Kiel in 1987 and received a habilitation from the University of Heidelberg in 1991.
Prior to Goethe-University Frankfurt, he held chaired professorships at the University of Heidelberg and at the
University of Stuttgart. His research is very broad, covering scalable algorithms for high performance Scientific
Computing, in particular fast, robust and scalable solvers for large systems of equations like multigrid methods,
development of simulation software systems, modelling and simulation of challenging applications like transdermal penetration of pharmaceuticals and drugs, of signal processing in neurons, and many more. For his scientific
work he has been honoured by prestigious awards, like the Heinz-Maier-Leibnitz prize and the doIT Software
Award. He is author of over 170 scientific publications, 34 students received a PhD under his supervision and ten
of his students hold professorships
P36
KIT, Karlsruher Institut für Technologie (Germany)
Laboratory Profile
Steinbuch Centre for Computing (SCC) operates the central computing centre of KIT to support the IT-demands
of the various research Programmes within KIT and within the Helmholtz-Association of German research centres.
It has solid experience in both, distributed computing infrastructures (DCIs) as well as identity management and
security in DCIs. SCC developed and runs the largest German university cloud storage for sync-and-share, providing access to more than 350,000 students and 100,000 researchers. SCC provides 22 PB disk (+22 PB tape)
storage to a diverse range of scientific experiments hosted at more than 130 institutes on site. SCC successfully
participated in several European projects such as CrossGrid, Int.EU.grid, EUFORIA, EGEE-1, EGEE-2 and EGEE-3,
EGI-Inspire and is currently contributing to EUDAT. SCC has coordinated the G-Eclipse project and currently
coordinates MMM@HPC. Furthermore, SCC is founding member of the OpenCirrus Cloud Initiative.
Key Personnel
Dr. Marcus Hardt (male) • earned his PhD with precise and distributed simulations of Ultrasound waves in
human tissue within the KIT project “Ultrasound Computer Tomography”, where he contributed simulations for
ultrasound waves in medical devices. He worked as founding member of WebSmart Technology GmbH and as IT
freelancer between 1999 and 2002. Since 2002 he is working as a scientist at the Research Group Cloud Computing at SCC. As a member of the CrossGrid and int.eu.grid integration teams he managed the fully automated
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P36 KIT, Karlsruher Institut für Technologie (Germany)
software build, deployment and configuration on the Europe-wide DCI. He was furthermore responsible for the
KIT activities in the EU-Project EUFORIA. In his present position Marcus Hardt is the technical coordinator of the
Large Scale Data Management and Analysis project LSDMA, a Helmholtz Portfolio extension, targeted at developing uniform interfaces for Germany’s data intensive research projects. Within the last 10 years he published
more than 20 papers in peer reviewed conferences and journals.
P37
KI, Karolinska Institutet (Sweden)
Laboratory Profile
The Nobel Institute for Neurophysiology, at the Karolinska Institute focuses on the forebrain mechanisms
responsible for the ability of the nervous system to select and initiate a set of actions and the evolution of
goal-directed movement. One of the main aims is to understand the neuronal microcircuits that subserve this
complex mechanism. As model systems, the Institute uses lamprey and mice, to which they apply a range of
neurophysiological, molecular and behavioural techniques. The laboratory, led by Sten Grillner, is also heavily
involved in promoting the development of neuroinformatics and in the International Neuroinformatics Coordinating Facility.
Key Personnel
Prof. Sten Grillner (male) • SP4 Leader / Research Board Member / Governance Oversight Committee Chair
• has an academic background in medicine and neurophysiology and has been the director of the Institute for
Neurophysiology and an active member and chairman of the Nobel Assembly, since 1986. He is also the founding chairman of the International Neuroinformatics Coordinating Facility (INCF) and a past-president of the
Federation of European Neuroscience. He is at present secretary general of the International Brain Research
Organization (IBRO). Grillner has over many years reconstructed the neural circuits of the lamprey and is the
world’s pioneer on simulation-based research. He is member of several academies of science in Sweden, Europe
and the USA, including the US Academy of Science and its Institute of Medicine. Grillner has received many
awards including the prestigious Kavli prize in 2008. He has lectured on a wide variety of topics including computational neuroscience, bionic robotics and neuroethology. He is a member of the editorial boards of various
international journals, and has served on the evaluation panels of many eminent academies including the Norwegian Research Council, the RIKEN Brain Science Institute and the German government’s Bernstein Centers.
Sten Grillner leads the Neuroinformatics Subproject of the HBP.
Laboratory Profile
The Department of Neurobiology, Care Sciences and Society at Karolinska Institute has 12 Divisions. The
KI-ADRC is involved in an EU project “Alcove” (Alzheimer Cooperative Project in Europe) which is a Joint Action
between European Member States aiming to both improve knowledge of dementia and its consequences, and
to promote exchange of information to preserve health, quality of life, autonomy and dignity of people living
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P37 KI, Karolinska Institutet (Sweden)
with dementia and their carers in EU Member States. The lab of Prof Abdul Mohammed at KI Alzheimer Disease
Research Centre (KI-ADRC) has published seminal studies on the impact of enriched environment on brain
neurotrophins during aging. The lab uses normal and genetically modified rodents in studies of aging and AD
models and seeks to develop novel behavioural methods. The lab has been involved in an EU project in development of novel group cages (Intellicages) for testing and housing of mice, seeking to minimize the stress of
behavioural testing of mice individually, and in promoting the animals well-being. The lab is collaborating nationally and internationally with a number of universities including Harvard University, University of South Carolina
and University of Zurich.
Key Personnel
Prof. Abdul Kadir Mohammed (male) WP 10.5 Leader / REC ex-officio Member • is Professor of Biological
Psychology at Linnaeus University and has served as a member of the EUROPLAT Quality Board, a network of
more than 30 universities in Europe dedicated to enhancing the quality of teaching and learning in Psychology.
He is also the Head of Behavioural Neuroscience Lab at Karolinska Institute’s Alzheimer’s Disease Research
Centre, focusing on animal models of Alzheimer’s disease, aging and brain plasticity. His has done seminal work
on the impact of environmental enrichment on brain neurotrophins at adulthood and during aging and he has
published more than 100 scientific publications. In 2002 the French government awarded him the Médaille des
Palmes Académiques, and in 2012 he was elected a Fellow of the Linnean Society of London, the oldest active
biological society which includes world leaders in each branch of biology. He has been of member of IBRO Governing Council and Chair of IBRO’s African Regional Committee for 6 years, a position that has enabled him to
actively promote and develop Neuroscience education and research in Africa. He is a member of the Research
Ethics Committee of IBRO.
Dr. Kevin Grimes (male) ELSA ex-officio Member • is a veteran clinical and forensic psychologist licensed as a
psychologist in Massachusetts (US), and newly chartered as a psychologist in the UK. He is specialised in consultancy on practical and procedural ethics in clinical, legal and academic settings. He served as a member of
the Tewksbury Hospital Medical Ethics Committee for three years, during which time he attended training at
the Ethics Leadership Council for the Harvard teaching hospitals and affiliated health care facilities. He has also
served as manager and psychologist for Behavioral Health Services, Department of Medicine, Tewksbury Hospital, Massachusetts Department of Public Health. In 2010, he founded Science Writing English Editing (www.
englishedit.eu), a company that provides editing services to scientists and science managers.
Laboratory Profile
Department of Medical Biochemistry and Biophysics: Sten Linnarsson Group. Our research focuses on singlecell biology, in particular applying single-cell expression analysis to characterize the cell types and lineages of
the mouse nervous system. We also pursue single-cell analysis of cancer genomes aiming to elucidate the cellular origin and evolution of human neoplasms. The long-term goal of our research is to map the stable cellular
states (‘cell types’) that human organs are made of, and to understand the regulatory networks that induce and
maintain them; both in normal tissues and in cancer. We have in recent years lead the development of methods
for single-cell RNA-seq, and have recently applied them at large scale to the mouse nervous system. We coinvented UMIs (unique molecular identifiers), which can be used to remove nearly all PCR bias from single-cell
experiments, and provides results on an absolute scale of molecules/cell. We are now using single-cell RNA-seq
to perform a census of cell types in the mouse nervous system.
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P37 KI, Karolinska Institutet (Sweden)
Key Personnel
Sten Linnarsson (male) • took his PhD at Karolinska Institute in 2001, studying neurotrophic factors regulating
neuronal survival, growth and plasticity. He then founded Global Genomics, a company focused on genomewide expression analysis and next-generation DNA sequencing, which was acquired by Genizon Inc. in 2007.
That year, he was awarded a position as assistant professor from the Swedish Research Council, placed at the
Karolinska Institute, Department of Medical Biochemistry and Biophysics, where he is now an associate professor.
P38 KCL, King’s College London (United Kingdom)
Laboratory Profile
The Department of Social Science, Health & Medicine was established at the beginning of 2012 at King’s College
London (KCL). Its aim is to establish King’s as a world leader in social scientific approaches to health and medicine, with innovative research and research-led teaching as the basis for a significant input into global health
policy. It undertakes the highest quality research on the social and ethical implications of developments in medicine, science and health policy, placing this in a global context with a specific focus on questions of the social
determinants of health inequality, and the role and implications of advances in biomedicine and biotechnology.
The SSHM includes a number of Laboratories: Foresight and Responsible Research Innovation Lab (FRRIL), Urban
Brain Lab, Centre for Synthetic Biology and Innovation Lab (CSynBi). Previous research labs were: BIOS, BIONET.
Key Personnel
Prof. Nikolas Rose (male) • WP10.1 Leader • is Professor of Sociology and Head of the Department of Social
Science, Health & Medicine (SSHM) at King’s College London. Before joining King’s in 2012 to establish the new
Department of SSHM, he was Martin White Professor of Sociology at the London School of Economics and Political Science, Head of the Department of Sociology from 2002 to 2006, and Director of the LSE’s BIOS Centre
for the Study of Bioscience, Biomedicine, Biotechnology and Society, which he founded in 2003. He originally
trained as a biologist before switching to psychology and then to sociology. His work explores how scientific
developments have changed conceptions of human identity and governance and what this means for our political, socio-economic and legal futures. He is a Co-director of the Centre for Synthetic Biology and Innovation
(CSynBI), Chair of the European Neuroscience and Society Network and a member of the Royal Society Science
Policy Advisory Group. He has published widely on the social and political history of the human sciences, on the
genealogy of subjectivity, on changing forms of political power, and most recently on the history and implications of developments in the life sciences and neuroscience.
Dr. Claire Marris (female) • is Senior Research Fellow in the Department of Social Science, Health and Medicine
at King’s College London. She is Deputy Leader of the SSHM Research Group Biotechnology, Pharmaceuticals and Public Policy (BPPP) and leads SSHM’s programme of research on the social dimensions of synthetic
biology. Her expertise is in social science research on the nature, role and translational possibilities of advanced
biosciences; with a focus on public participation in the governance of science and technology. Claire previously
held academic positions at the London School of Economics (2009-2011), the French National Research Insti-
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P38 KCL, King’s College London (United Kingdom)
tute for Agronomic Research (INRA, 2000-2009), the Université de Versailles-Saint Quentin en Yvelines (19982000), the French Institute for Radiological Protection and Nuclear Safety (1996-1998), the University of East
Anglia (1992-1996) and Rothamsted Research (1985-1990).
P39
KTH, Kungliga Tekniska Hoegskolan (Sweden)
Laboratory Profile
Created in 2006, the Department of Computational Biology (CB) is currently the largest computational neuroscience, neuroinformatics, and neurocomputing centre in Sweden. Prof Anders Lanser’s group is part of CB. The
group’s research focuses on attractor memory network models applied to neocortex and the olfactory cortex
and on basal ganglia modelling. The group has good access to HPC tools, via the Centre for Parallel Computers
(PDC) at KTH, Sweden’s largest national supercomputing centre, This group currently consists of 14 members.
Prof Jeanette Hellgren Kotaleski’s group, of around ten people, focuses on the use of computational modelling to investigate the neural mechanisms underlying information processing, rhythm generation and learning
in motor systems, using basal ganglia as a model system. Methods used by the group range from simulations
of large scale neural networks, using biophysically detailed and abstract systems-level models, down to kinetic
models of subcellular processes.
Key Personnel
Prof. Jeanette Hellgren Kotaleski (female) • SP 5 Co-leader / WP5.3 Leader / Research Board Member •
holds an MSc in Engineering Physics, a Licentiate degree in Medical Sciences and a Ph.D. in Computer Science.
Since her postdoctoral studies in systems biology at the Krasnow Institute, George Mason University, USA,
she has been a full professor in Neuroinformatics at KTH since 2007. She is the coordinator of an international
Erasmus Mundus joint Ph.D. programme involving partners from Germany, UK and India and is the leader of the
Swedish INCF node. Jeanette Hellgren co-leads the Brain Simulation Subproject of the HBP.
Prof. Anders Lansner (male) • is Chair of Computer Science at KTH, and the founding director of its Department
of Computational Biology, where he specialises in computational neuroscience and neurocomputing. With 25
years of post-doctoral experience in creating and carrying out field research, Prof. Lansner has forged extensive collaborations with experimental neuroscienctists and psychologists, nationally and internationally. He is
a Member of the Royal Swedish Academy of Engineering Sciences (IVA) and Swedish board member of INCF
(International Neuroinformatics Coordinating Facility). He has supervised more than twenty Ph.D. theses and
numerous Masters theses.
Prof. Tony Lindeberg (male) • is a Professor of Computer Science at KTH Royal Institute of Technology in Stockholm, Sweden, where he does research in computer vision and computational neuroscience. He is an expert on
scale-space theory, feature detection, receptive fields and early vision, and has developed normative theories
for visual and auditory receptive fields; scale-invariant, affine invariant, Galilean invariant and illumination invariant image features as well as spatial and spatio-temporal image descriptors for image-based recognition. He is
author of the book Scale-Space Theory in Computer Vision.
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P39 KTH, Kungliga Tekniska Hoegskolan (Sweden)
Prof. Erik Fransén (male) • is vice director of Dept. of Computational Biology at CSC, KTH and also Director of
Doctoral Education at School of Computer Science and Communication at KTH. He holds a PhD from Stockholm
University, was a postdoctoral fellow at Dept. of Psychology at Harvard University, MA 97-98 and is a full professor at KTH since 2012. He is a member of the scientific council of Stockholm Brain Institute since 2011. His main
research interests concern ionic mechanisms in intrinsic neuronal excitability and integration. He has addressed
problems in learning and memory as well as working memory. He also studied mechanisms of excitability in
epileptogenesis and in peripheral chronic pain.
Prof. Örjan Ekeberg (male) • is director of the Department of Computational Biology at KTH CSC, and also the
main coordinator for undergraduate education in Computer Engineering and the masters programme in Computer Science. He was an invited Resident Fellow of the Institute for Advanced Study in Berlin 2001-2002, and a
STINT Visiting Professor at Vassar College in New York 2009. He is a full professor in Computer Science at KTH
since 2011. His research is focused on the neural control of movements using models and simulation of neural
as well as biomechanical components. Current projects stretches from the sensory-motor feedback in insect
antennae to the muscular control of human voice production.
Laboratory Profile
Center for Parallel Computers (PDC) is the lead centre for high-performance computing for the Swedish academic community and is funded by the Swedish Research Council through the Swedish National Infrastructure
for Compuwting (SNIC). PDC operates cutting-edge computer resources for Swedish users and provides high
performance computing resources to many important research groups, including the Stockholm Brain Institute
(Karolinska Institute), Stockholm University, and KTH. With a capacity of up to about 500TF, PDC is the coordinator for the EU-funded ScalaLife project, a partner in the European Exascale project CRESTA, and the lead
Swedish participant in the Partnership for Advanced Computing in Europe (PRACE).
Key Personnel
Prof. Erwin Laure (male) • leads PDC and is also the co-director of the OGF Data Area, a former co-chair and
co-founder of the OGF GIN-Community Group and a member of the external advisory board of the D4ScienceII. He holds a Ph.D. in Business Administration and Computer Science from the University of Vienna (Austria) and
before joining PDC was Technical Director of the EU funded projects “Enabling Grids for E-Science in Europe”
II and III (EGEE-II and–III) at CERN. Along with heading the PDC, his research interests include Grid computing,
programming environments, languages, compilers and runtime systems for parallel and distributed computing.
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P40 LENS, Laboratorio Europeo di Spettroscopie Non Lineari (Italy)
Laboratory Profile
The Pavone Lab: Biophysics and Biophotonics Group. Francesco Pavone,s lab aims to develop innovative
imaging methodologies for an increased understanding of biological events in the brain. Novel implementations
of light-sheet microscopy are applied to resolve neuronal anatomy in whole fixed brains with cellular resolution. We combined the advantages of light-sheet illumination and confocal slit detection to increase the image
contrast in real time. Moving to living samples, real-time dynamics of brain rewiring are visualized through twophoton microscopy with the spatial resolution of single synaptic contacts. The plasticity of the injured brain is
also dissected through cutting-edge optical methods that specifically ablate single neuronal processes. Finally,
random access multi-photon microscopy in combination with novel fluorescence probes allows optical registrations of action potential across population of neurons. The development and the application of these complementary optical methodologies provides fundamental insights in brain disease and represents a whole new
approach for the investigation of the physiology of neuronal network.
Key Personnel
Prof. Francesco Pavone (male) • obtained his laurea in physics from the University of Florence and a Ph.D. in
optics from the Italian National Institute for Optics. He was successively maître de conférences associé at the
Collège de France, a collaborator at the Ecole Normale Supérieure (ENS) in Paris under Nobel Laureate Claude
Cohen-Tannoudji, associate professor of physics in the Department of Physics of the University of Perugia
(Italy), and Scientific Director of the Section of Atomic and Molecular Physics at the European Laboratory for
Non-Linear Spectroscopy (LENS) in Florence. Today he is a full professor at the University of Florence Department of Physics and Director of the European Laboratory for Non-Linear Spectroscopy.
P41
HUG, Les Hopitaux Universitaires de Genève (Switzerland)
Laboratory Profile
Laboratory of Neuroimaging of Aging. The group has a long expertise in the field of research on Alzheimer’s
disease. The main scientific interest is the neuroimaging of cognitive impairment. The most intense efforts were
directed to the translation of basic research into clinical settings to assist the diagnosis of cognitive impairment
and to better understand the pathophysiology. Specific topics of investigation were: the genotype (mainly
apoE) and the phenotype in degenerative dementias; in vivo neurobiology of Alzheimer’s disease; frontotemporal dementia with magnetic resonance imaging; clinical epidemiology of mild cognitive impairment; the biological basis of behavioral disorders in dementia. In later years, the lab has engaged in the successful development
of an advanced grid/cloud platform (neuGRID, www.neugrid4you.eu) for the diagnosis, study, and modeling of
Alzheimer’s disease and psychiatric disorders with advanced image analysis. NeuGRID offers state-of-the-art
facilities to: access and manage big imaging and non imaging data, sophisticated image processing algorithms,
adequate computational power, and training and help for the non expert user.
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P41 HUG, Les Hopitaux Universitaires de Genève (Switzerland)
Key Personnel
Prof. Giovanni B. Frisoni (male) • WP7.2 Leader • is the group leader of the Laboratory of Neuroimaging of
Aging at HUG. He is author of over 400 scientific papers and the editor of prominent journals on Aging and
Neurobiology
P42
LNU, Linneuniversitetet (Sweden)
Laboratory Profile
Department of Psychology - Faculty of Health & Life Sciences. At Linnaeus University research is carried out in
biological psychology, clinical psychology, health psychology and educational psychology. The research in biological psychology is led by Prof Abdul Mohammed. The research is interdisciplinary and involves cooperation
with neuroanatomists, neurochemists, and molecular biologists at several leading international research institutions. The research deals with neurocognition and the impact of the surroundings on the function and behavior
of the brain at ageing, with the main emphasis being on learning and memory. The role of different biomarkers
such as neurotrophins and cytokines in relation to cognitive function in the aged individuals is also investigated.
Research includes experimental and epidemiological studies of humans as well as mice. Current research at
the laboratory focuses on the impact of physical activity, cognitive stimulation and “mindfulness” on cognitive
health and neural plasticity in individuals aged between 65 and 85 years old, in relation to various biomarkers
including neurotrophins and cytokines.
Key Personnel
Prof. Abdul Kadir Mohammed (male) • WP 10.5 Leader / REC ex-officio Member • iis Professor of Biological Psychology at Linnaeus University. He has more than 100 scientific publications and his earlier research
includes the impact of environmental enrichment on brain neurotrophins at adulthood and during aging. He is
the Principal Investigator of a Family Kamprad Foundation funded project, SAGE (Successful AGing and Enrichment), which involves collaboration between Linnaeus University, Karolinska Institute, Harvard Medical School,
Medical University of South Carolina, Växjö Regional Hospital, and a psychiatric clinic in the region of Kronoberg,
Sweden. He is also a founding member of the EU-funded EUROPLAT project, a network of 30 European universities dedicated to enhancing the quality of teaching and learning in psychology, and is a member of its Quality
Board. In 2002 the French government awarded him the Médaille des Palmes Académiques, and in 2012 he was
elected a Fellow of the Linnean Society of London. The same year Linnaeus University gave him an award “for
outstanding contribution of special importance to Linnaeus University in the world”. He is a member of IBRO´s
“Research in Ethics Committee”, and has served for 6 years as a member of IBRO Governing Council and Chair
of IBRO’s African Regional Committee, a position that has enabled him to actively promote and develop Neuroscience education and research in Africa.
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P43
IMU, Medizinische Universität Innsbruck (Austria)
Laboratory Profile
Experimental Psychiatry Unit. One of the leading medical universities in Austria, Innsbruck Medical University
has a strong focus on neuroscience research. The University brings together a number of different disciplines.
Its international PhD programme in Neuroscience (“Signal Processing in Neurons”, SPIN) provides a strong, upto-date programme of neuroscience education and includes a Management Unit for Distance Education. The
Experimental Psychiatry Unit is one of the host labs for SPIN and is headed by Prof Alois Saria. Research at
the lab focuses on the mechanisms of reward and the mode of action of psychoactive drugs. It currently has 11
members of staff, including four students.
Key Personnel
Prof. Alois Saria (male) • WP11.8 Leader • is Full Professor at Medical University Innsbruck, where he leads the
Experimental Psychiatry Unit. His research focuses on the function of neuropeptides in the brain and peripheral
nervous system and more recently on the molecular and cellular mechanisms of psychoactive drugs and narcotics. He holds an executive position at the International Society for Neurochemistry (ISN) and is member of the
Finance Committee of the Society for Neuroscience (SFN). He has devoted much work to the organisation of
advanced training for young neuroscientists. He has published over 300 papers and has an H-index of 53. Alois
Saria will direct the HBP Education Programme.in Africa.Neurobiology
P44
UoA, National and Kapodistrian University of Athens (Greece)
Laboratory Profile
The Management of Data, Information, and Knowledge (MaDgIK) Group of the Department of Informatics
& Telecommunications of the University of Athens has 60+ members, including five (5) faculty, several R&D
staff, and students at all educational stages. The group focuses on several research areas of the Data-InfoKnowledge continuum, such as Database and Information Systems, Distributed and Parallel Systems, Cloud
Computing, Sensor-based and Stream Data Management, Query Optimization, Information Search, Personalization and Social Networks, Knowledge Discovery & Data Mining, Knowledge Representation and Reasoning,
Constraint Satisfaction Problems, Semantic Web and Linked Data, Semantic Sensor Web, Digital Libraries, and
Human-Computer Interaction. It participates in several national and European projects that cover the above
areas. Much of the research is done in the context of and inspired by problems in several application areas, such
as Medical Informatics, Cultural Heritage, Museum Studies, Biodiversity, Earth Sciences, Marine Science, Environment, History, and others.
Key Personnel
Prof. Yannis Ioannidis (male) • is a professor at the Department of Informatics and Telecommunications of the
University of Athens, and the President and General Director of the “Athena” Research and Innovation Center.
He received his Ph.D. degree in Computer Science from the University of California at Berkeley in 1986, his MSc
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P44 UoA, National and Kapodistrian University of Athens (Greece)
degree in Applied Mathematics from Harvard University in 1983, and his Diploma in Electrical Engineering from
the National Technical University of Athens in 1982. His research interests include database and information
systems, scientific systems and medical informatics, cloud computing, dataflow management and data analytics, social information systems, and digital libraries, topics on which he has published over a 150 articles in
leading journals and conferences and holds three patents. He is an ACM and IEEE Fellow and a member of Academia Europaea, and has received several awards for his research and teaching work including the Presidential
Young Investigator Award in the United States and the “Xanthopoulos-Pnevmatikos” Award for Outstanding
Academic Teaching in Greece. He currently serves as the Greek national delegate to the European Strategy
Forum for Research Infrastructures (ESFRI) and is a member of the Executive Committee of the SIG Governing
Board of the Association of Computing Machinery.
Natalia Manola (female) • is a Senior Software Engineer holding a B.Sc. in Physics from the University of Athens,
Greece, and an M.Sc. in Electrical and Computer Engineering from the University of Wisconsin at Madison, USA.
Her professional experience consists of several years of employment as a Software Engineer, Software Architect,
Information Technology Administrator, and Information Technology Project Manager by companies in various
Information Technology sectors in the US and Greece. The systems she has designed and implemented include
specialized ETL tools, biotechnology and genetic applications, embedded financial monitoring systems, and
heterogeneous data integration systems. She has participated and technically managed several R&D projects
funded by the European Union with a focus on building and organizing data infrastructures (DRIVER, ESPAS).
Since Dec 2008 she is the project manager of the OpenAIRE project, a flagship infrastructure EC project with 50
partners covering all Europe that supports Open Access in all scholarly communication aspects (scientific publications and research data) and promotes research data management best practices on the institutional level.
P45
NMBU, Norges miljø- og biovitenskapelige universitet (Norway)
Laboratory Profile
The Computational Neuroscience Group at the Norwegian University of Life Sciences (NMBU) has broad experience in multiscale modeling the signal-processing properties of neurons and networks in the early visual and
somatosensory systems, the generic properties of cortical networks, place-field formation in hippocampus,
astrocyte dynamics, and astrocyte-neuron interactions. The group has accumulated great experience in largescale simulations of networks of spiking neurons, developing the NEST simulation tool, with a special focus on
generating connectivity in large network models. The group has also done extensive work on the modeling of
extracellular potentials (LFP, MUA), and has developed novel methods and neuroinformatics tools for modeling and analysis of multielectrode data (iCSD, LFPy, LPA). The group, which has two core faculty (Prof Gaute
T. Einevoll, Assoc. Prof Hans E. Plesser), currently hosts about five researchers. The group is a member of the
national Norwegian Research School for Neuroscience.i
Key Personnel
Prof. Gaute T. Einevoll (male) • is professor of physics at the Norwegian University of Life Sciences (NMBU)
at Aas and founder of the Computational Neuroscience Group (compneuro.umb.no) at NMBU. Since 2007, he
has been one of the leaders of the Norwegian national node of the International Neuroinformatics Coordinating
Facility (INCF). He has been a programme director in the Organisation of Computational Neuroscience since
2011 and has been been a vice-president of the organisation since 2014.
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P46 OFAI: Oesterreichische Studiengesellschaft für Kybernetik (Austria)
Laboratory Profile
Austrian Research Institute for Artificial Intelligence Established in 1984 with support of the then Austrian
Federal Ministry for Science and Research, OFAI currently employs 22 researchers, plus several scientists from
universities on a contractual basis. It has a longstanding experience in cooperating with research institutions,
SMEs and industry, e.g. by successfully completing already 32 EC-sponsored multinational research projects,
as partner or as coordinator. From its beginning, the institute undertook research in the areas of Language
Technology, Machine Learning, Interaction Technologies, and Intelligent Software Agents, later focusing also on
emotional and social aspects of them, and their embodiment in robots. Studying results of brain research and
cognitive science further influenced our work considerably.
Research topics especially related to the HBP, some of them already being undertaken, some of them planned,
are: “Consciousness and Awareness: Functions, Theories, and Models”, “Spatial Memory and Navigation Ability
in a Physically Embodied Cognitive Architecture”, “Hierarchies in Spatial Memory Models”, “La revolution Bayésienne and Physically Embodied Cognitive Architectures”, “Social Human-Robot Interaction”, “Ethical Systems for
Robots”, “Robots for Domestic Applications, especially for Ambient Assisted Living”.
Key Personnel
Prof. Robert Trappl (male) • studied Electrical Engineering (BEng), Sociology (Diploma), and Psychology
(PhD). In addition, in 2012 he graduated as MBA. He was, for 30 years, Full Professor of Medical Cybernetics and
Artificial Intelligence and head (“Vorstand”) of a department with the same name at the University of Vienna and
he is currently Professor Emeritus at the Center for Brain Research at the Medical University of Vienna. He began
his scientific work with the analysis of interspike-interval-distributions in the optic nerve, modeling components
of the electroretinogram, and developing 3-dimensional representations of seizure-EEGs. He then moved to artificial intelligence research, both by developing technical solutions but also by trying to model mind-processes
through AI-models. His current research topics are given in the profile of OFAI. He has published more than 180
papers and he is co-author, editor, or co-editor of 35 books, recently “Wissenschaft und Medizin, 11th ed.” and
“Your Virtual Butler: The Making-of”, both in 2013. He is currently preparing a book “A Construction Manual for
Robots’ Ethical Systems: Requirements, Methods, Implementations”, to be published in 2014.
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P47
RWTH, Rheinisch-Westfälische Technische Hochschule Aachen (Germany)
Laboratory Profile
The Virtual Reality Group at RWTH Aachen University researches new visualisation and virtual reality methods
for scientific applications. Part of the University’s Centre for Computing and Communication, the group uses
high performance computing to develop comprehensive visualisation frameworks for the explorative analysis
of complex technical, physical and natural phenomena. Applications include production technology, simulation
science, neuroscience and psychology. The group maintains one of Europe’s most advanced visualisation labs,
with a high-resolution five-sided CAVE.
Key Personnel
Prof. Torsten Kuhlen (male) • WP6.3 Leader • is the founder of the Virtual Reality Group at the Center for
Computing and Communi cation of RWTH Aachen, where he is also professor of virtual reality (VR) in the
Department of Computer Science. Before taking up this position, he was a research assistant at the Institute
of Technical Computer Science, where he focussed on innovative human-computer interfaces and VR. For his
doctoral thesis at the Faculty of Electrical Engineering, he developed VR-based methods for research on the
sensorimotor organisation of the human brain. He is spokesperson for the German Computer Science Society’s
Special Interest Group on “Virtual and Augmented Reality” and is co-author of about 150 peer-reviewed publications. He has served as programme chair, committee member, and reviewer for numerous international conferences on VR, computer graphics and visualisation.
Laboratory Profile
Affiliated with the Computer Science Department of RWTH Aachen University, the objective of the Laboratory
for Parallel Programming is to develop solutions that support simulation scientists in exploiting massive parallelism on modern architectures. The laboratory specializes in programming tools for application performance
analysis and modeling, data-race detection, and parallelism discovery. Further topics include parallel algorithms
and cluster resource management. One of the lab’s key projects is Scalasca (www.scalasca.org), a performanceanalysis tool for large-scale parallel applications, which is being jointly developed with the Jülich Supercomputing Centre. Recent contributions of the laboratory to Scalasca are related to automated performance modeling
and requirements engineering for HW/SW co-design.
Key Personnel
Prof. Dr. Felix Wolf (male) • is head of the Laboratory for Parallel Programming. Before moving to Aachen, Prof.
Wolf had appointments as a senior researcher at the University of Tennessee and as a research group leader
at the Jülich Supercomputing Centre. His research concentrates on parallel programming methods and tools.
In particular, Prof. Wolf is a principal designer of the performance-analysis tool Scalasca, which is installed at
numerous HPC centres around the world and which has been successfully applied to optimize academic and
industrial codes. Wolf has published more than 90 refereed articles in journals and conference or workshop
proceedings. He has obtained research funding from European and American funding agencies including BMBF,
DFG, DOE, EU, Helmholtz Association, and NSF.
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P48
UHEI, Ruprecht-Karls-Universität Heidelberg (Germany)
Laboratory Profile
Kirchhoff-Institute for Physics (KIP) The UHEI group explores and implements novel concepts for information
processing in massively parallel, mixed-signal VLSI technologies. Founded in 1994 as a spin-off from instrumentation development for particle physics experiments, its previous projects included bio-inspired vision sensors,
sensory substitution systems, analog evolvable hardware devices and very large-scale neuromorphic information processing systems. The group initiated and led the European FACETS project and the Marie-Curie Network
on Neural Computation (FACETS-ITN). It currently leads the FP7 integrated project BrainScaleS, one of the
foundations for the Human Brain Project. In the context of BrainScaleS, it pioneered the use of wafer-scale integration for neuromorphic systems as well as the PyNN meta-language - a language providing unified access to
neural simulators in software and hardware. Among the 50+ group members are five post-doctoral researchers,
twelve PhD students as well as engineers, bachelor’s and master’s students. Its technical infrastructure includes
a microelectronics laboratory, and workshops for electronics and mechanics.
The Heidelberg group has established a renowned German center for the design and construction of microelectronics systems (The Heidelberg ASIC laboratory). The lab has at its disposal a complete design suite for
analog and digital chip design, layout and simulation, a clean room for assembling, bonding and testing microelectronics systems and an electronics workshop with technical facilities for soldering, component mounting as
well as high frequency and low noise testing facilities. A mechanical workshop with a complete manufacturing
workflow from CAD design to computer controlled production machines allows for the construction of large
scale mechanical set-ups as required for the NM-PM facility in the framework of HBP. The group also operates
Teraflop-scale compute clusters for neural and electronics system simulations as well as for the control and
analysis of experiments with Neuromorphic computing systems.
Key Personnel
Prof. Karlheinz Meier (male) • Executive Committee Member / SP 11 Co-leader / SP8 Leader / WP8.5 Leader
/ WP8.6 Leader / Research Board Member • is the founding director of the Kirchhoff-Institute for Physics and
the ASIC Laboratory for Microelectronics, where he holds a chair in experimental physics. With a strong background in instrumentation for particle physics and brain-inspired computation he has 30 years of post-doctoral
experience in large-scale experimental research. Coordinator of the FACETS, FACETS-ITN and BrainScaleS projects, he has been project leader for the PreProcessor system for the ATLAS experiment at the LHC in CERN
(Switzerland) and a leading contributor to four major particle physics experiments at the DESY (Germany) and
CERN laboratories. He has supervised more than 40 Ph.D. theses and published more than 500 research papers
(H-index of 98). As a former member of the CERN Council, chair of a European Strategy Committee and board
of the German Physical Society he played a seminal role in forming the European research landscape in physics.
He is a member of the Samsung Advanced Institute of Technology. Karlheinz Meier is co-director of the HBP and
leads the Neuromorphic Computing Division of HBP.
Dr. Johannes Schemmel (male) • WP8.1 Leader • is a senior post-doctoral researcher at the Kirchhoff-Institute
for Physics. He has 15 years of post-doctoral experience in designing and building complex microelectronics
systems for brain-inspired information processing. He pioneered the FACETS and BrainScaleS chip and systems
architectures. Johannes Schemmel is leader of WP8.1 with the responsibility to design and construct the physical model system of the HBP Neuromorphic platform.
Dr. Andreas Grübl (male) • is a senior post-doctoral researcher at the Kirchhoff-Institute for Physics. He has
7 years of post-doctoral experience in designing and building complex microelectronics systems for braininspired information processing. Andreas Grübl is a task leader in WP8.1.
Dr. Björn Kindler (male) • WP 11.4 Leader • is a senior scientific administrator with 9 years experience in managing large-scale European research projects. He acted as a scientific administrator of the FACETS, FACETS-ITN
and BrainScaleS projects.
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P48 UHEI, Ruprecht-Karls-Universität Heidelberg (Germany)
Dr. Sebastian Schmitt (male) • is a post-doctoral researcher at the Kirchhoff-Institute for Physics. He obtained
his doctoral degree with the ATLAS experiment at the LHC. He acts as software coordinator in the Heidelberg
HBP group and is a task leader in WP8.3.
Eric Müller (male) • is computing coordinator in the Heidelberg HBP group. After obtaining his PhD degree in
autumn 2014 he will be responsible for designing and assembling the integration of the NM-PM systems with
high performance computing systems to carry out closed loop experiments.
Mihai PetrovicI (male) • is coordinating the theory research in the Heidelberg HBP group with special emphasis
on stochastic computing with spiking neurons. After obtaining his PhD degree in autumn 2014 he will a task
leader in the theory workpackage WP8.4.
Laboratory Profile
Multidimensional Image Processing (MIP) The UHEI/MIP group works at the forefront of algorithms development for bioimage analysis, and is spearheading efforts to make advanced machine learning and image analysis
methods available to experimental end users. In particular, the group has coordinated development of ilastik, a
framework for image analysis which in its most recent version allows interactive machine learning on data sets
in the order of multiple terabytes. The group is also one of the leading players in the area of automated tracing,
that is, the automated extraction of brain circuit topology and connectivity in large volume electron microscopic images. Today, the group maintains active collaborations with most of the leading experimental groups
who pursue the study of the connectome, or the quest for a better understanding of neural ultrastructure, with
complementary experimental techniques, including three variants of electron microscopy as well as functional
imaging. Besides its head and senior scientist, the group currently comprises four post-doctoral researchers,
three full-time software developers, six PhD students plus undergraduate students.
Key Personnel
Prof. Fred Hamprecht (male) • is a member of the Interdisciplinary Center for Scientific Computing (IWR) of the
University of Heidelberg, and a professor in its Faculty for Physics and Astronomy. With his group, he has developed algorithms and software for a broad range of practical problems ranging from industrial quality control
via medical diagnostics to high-throughput screening. In recent years, his algorithmic focus has been on image
analysis methods that can be trained conveniently from minimal input using machine learning; while on the
application side he has focused on the analysis of the very challenging imagery produced in the neurosciences
and developmental biology. Fred Hamprecht is a founding director of the Heidelberg Collaboratory for Image
Processing, currently the largest academic center for image processing in Germany.
Dr. Ullrich Köthe (male) • is a senior scientist in the Multidimensional Image Processing Group, with 20+ years of
experience in image analysis. He is head software architect of the group, and lead developer of the VIGRA C++
library for image processing. This library is widely used for number crunching, and its architecture has inspired
more recent developments such as the IMGLIB library. Ullrich Köthe is a task leader in WP4.7, Neuroinformatics
Methods and Tools.
Dr. Anna Kreshuk (female) • is leading the technical development of the ilastik framework for interactive
machine learning in image analysis. Trained as a mathematician at Lomonosov Moscow State University, and a
former core developer of the ROOT library for physical data analysis, she is an expert in both algorithms and
scientific software development. She is the creator of the first-ever fully automated methods for synapse detection in both focused ion beam and serial sectioning transmission electron microscopy volumes. Anna Kreshuk is
a task leader in WP4.7, Neuroinformatics Methods and Tools.
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P49 SU, Sabanci University (Turkey)
Laboratory Profile
Sabanci University Microelectronics Group has extensive research programs in integrated circuits and systems
design, fabrication and testing. The group’s experience includes high frequency and microwave circuits, low
power circuits, readout circuits, analogue and mixed-signal circuits, MEMS and microsystems, biosensors and
biomimetic circuits.
The Sabanci University Nanotechnology Research and Application Center (SUNUM), provides valuable additional capabilities to the research infrastructure of the Faculty of Engineering and Natural Sciences (FENS).
Combined synergistically with the research expertise of the Faculty of Engineering and Natural Sciences, SUNUM
conducts application oriented, multidisciplinary research programs, bringing together researchers to address
applications in electronics, healthcare, structural materials, energy, agriculture, food and defence industries.
SU Microelectronics Group has extensive integrated circuits and system design capabilities on different Digital,
Analog, Mixed-Signal, RF/Microwave and THz applications with project portfolio from National and International
Funding Agencies (such as TUBITAK, EU Framework Programs, NSF) and Companies. The Group research capabilities also include Micro-electro-mechanical Systems (MEMS), Sensors and Actuators, and Microsystems for
applications such biosensors, chemical sensors, mechanical sensors, RFMEMS, IR detectors. The Group is suited
with necessary CAD tools such as Cadence ADS Design Environments, Coventorware, Momentum, Comsol and
already experienced IC technology libraries, based on CMOS and SiGe technologies from 0.35 µm down to 28
nm scale. The Group also has a board and die-level test and measurement capabilities, ranging from DC to 110
GHz operating frequency with a temperature range of 77K-cryo to 240C, along with micro/nano fabrication
capabilities in 40 m2 area of cleanroom.
SUNUM is housed in a state-of-the art, two-story, 7,500 m2 building with an 850 m2 clean room (ISO 5), 1,600
m2 for laboratories and 2400 m2 for office and general use, all furnished with high tech equipment to support
R&D in nanotechnologies. There are 12 multidisciplinary laboratories in the center: Micro/nano fabrication Lab
(Class 100 clean room), Molecular Biology Lab., Material Characterization Lab., Nanoelectronics and Nanomagnetics Lab., Micro-Nano Fluidics Lab., Surface Sciences and Energy Systems Lab., Nano Packaging and Heterogeneous Integration Lab., Advanced Microscopy Lab, Micro and Nano systems Testing and Characterization
Lab. 3D Design and Fabrication Lab., Tissue Engineering and Regenerative Systems Lab. These laboratories
include state-of-the art fabrication and characterization equipment spanning large application areas from electron lithography, nanolithography, DNA sequencing, protein analysis, Liquid, gas and mass spectroscopy, mK
cryo systems, atomic resolution TEM, SEM, FIB, confocal microscopy and 3D prototyping.
SU conducts research in other HBP related areas: biomedical information processing, brain computer interfaces,
image analysis techniques with applications to medical imaging modalities; cognitive psychology, memory and
language formation, vision and sensory information processing.
Key Personnel
Prof. Dr. Yasar Gürbüz (male) • is a faculty member in the Faculty of Engineering and Natural Sciences (FENS)
at Sabanci University since 2000 and is also one of the founding faculty members of Microelectronics, Electronics Engineering Diploma Programs and Nanotechnology Research and Application Center at Sabanci University.
Prior to that he worked as an associate research professor at Vanderbilt University (USA), between 1997-1999
and at Aselsan (Turkey) between 1999-2000. His area of expertise includes Analog and Mixed-Signal Integrated
Circuits; RF & Microwave Integrated Circuits; Sensors and Actuators; Micro-Electro-Mechanical Systems (MEMS);
Solid-State Electronic Devices. He has authored/co-authored more than 80 peer-reviewed, SCI-indexed journal/
conference publications, 1 book chapter and 5 international patent submissions (1 granted and 4 under evaluation) in his area of expertise. He is a member of IEEE and SPIE.
Dr. Volkan Özgüz (male) • is the director of the Nanotechnology Research and Application Center at Sabanci
University. A former Chief Technology Officer and Senior Vice President at Irvine Sensors Corporation, he has
been working in the semiconductor technology, packaging, microelectronics manufacturing and nanotechnology
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P49 SU, Sabanci University (Turkey)
fields since 1979. He received his BS and MSc degrees from Istanbul Technical University, his Ph.D. in electrical
engineering from North Carolina State University (USA), and has been a Fulbright and NATO Fellow. His
experience in the design and implementation of microelectronic, nanoelectronic and neuromorphic systems
spans fabrication technologies, process design and integration, facility operations and technology transfer. Dr
Özgüz has authored more than seventy journal articles, conference publications and book chapters. He has
eighteen patents and many patent applications. Dr. Özgüz is a senior member of IEEE. Dr. Özgüz is the delegate
for Turkey at EU Member States Committee on Nanotechnologies, Advanced materials, Biotechnology, Advanced
manufacturing and processing (NMBP).ogy fields since 1979. He received his BS and MSc degrees from Istanbul
Technical University, his Ph.D. in electrical engineering from North Carolina State University (USA), and has been a
Fulbright and NATO Fellow. His experience in the design and implementation of microelectronic, nanoelectronic
and neuromorphic systems spans fabrication technologies, process design and integration, facility operations
and technology transfer. Dr Özgüz has authored more than seventy journal articles, conference publications and
book chapters. He has eighteen patents and many patent applications. Dr. Özgüz is a senior member of IEEE. Dr.
Özgüz is the delegate for Turkey at EU Member States Committee on Nanotechnologies, Advanced materials,
Biotechnology, Advanced manufacturing and processing (NMBP).
P50 SSSA, Scuola Superiore di Studi Universitari e di Perfezionamento Sant’Anna (Italy)
Laboratory Profile
The BioRobotics Institute at Scuola Superiore Sant’Anna is an integrated system aimed at innovative research,
education and technological transfer. The Institute wants to act as a linking bridge to international centres of
knowledge and to create a new concept of engineers that are scientists, inventors, entrepreneurs, able to invent
and solve problems, and to create new companies in high technology sectors (biomedical engineering, microengineering, robotics, mechatronics).
Key Personnel
Prof. Cecilia Laschi (female) • WP9.4 Leader • is Associate Professor of Biorobotics at SSSA and leader of the
area of soft robotics. She has been and currently is involved in many National and EU-funded projects, among
which OCTOPUS IP (as Coordinator), ROBOSOFT CA (as Coordinator), STIFF-FLOP, CFD-OctoProp. She has
authored/co-authored more than 170 papers and she is in the Editorial Board of Bioinspira- tion & Biomimetics,
Applied Bionics and Biomechanics, Advanced Robotics, Frontiers in Bionics. She is member of the IEEE- RAS
AdCom and co-chair of the IEEE-RAS Technical Committee in Soft Robotics.
Prof. Paolo Dario (male) • is Full Professor of Biomedical Robotics and Director of the BioRobotics Institute. He
has been and currently is the coordinator of many national and EU projects, and the author of more than 500
scientific papers (more than 250 on ISI journals). He served as President of the IEEE Robotics and Automation
Society (RAS), as Member of the EU ISTAG.
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P51 CWI, Stichting Centrum voor Wiskunde en Informatica (the Netherlands)
Laboratory Profile
The Stichting Centrum voor Wiskunde en Informatica (CWI) is the Dutch national research institute for mathematics and computer science. It is a private, non-profit organization located at the Science Park Amsterdam.
CWI’s mission is twofold: To perform frontier research in mathematics and computer science, and to transfer
new knowledge in these fields to society. This is realized by several means. In addition to the standard ways of
disseminating scientific knowledge, CWI actively pursues joint projects with external partners, provides consulting services, and stimulates the creation of spin-off companies. Special efforts are made to make research
results known to non-specialist circles, ranging from researchers in other disciplines to the public at large. CWI
is headed by Jos Baeten. CWI also manages the Benelux Office of the W3C and hosts both the Semantic Web
Activity Lead and the chair of the XHTML and XForms Working Group. CWI has always been very successful in
participating in European research programmes (e.g. VITALAS, K-SPACE, QAP, CREDO, MUSCLE, and others)
and large scale national research programmes (e.g., programmes BRICKS, MultimediaN, and VL-e; NWO Veni,
Vidi, Vici grants). It has extensive experience in managing these collaborative research efforts. CWI is also
strongly embedded in Dutch university research: about thirty-five of its permanent senior researchers hold
part-time positions as professors at universities and many projects are carried out in cooperation with university research groups. CWI receives a basic funding from the Netherlands Organisation for Scientific Research
(NWO), amounting to about two third of the institute’s total income. The remaining third is obtained through
national research programmes, international programmes, and contract research commissioned by industry.
CWI hosts a staff of 235 full time employees, 50 permanent scientific staff, 135 temporary scientific staff, and
50 support staff.
Key Personnel
Prof. Martin Kersten (male) • devoted most of his scientific career on the development of database systems.
The latest incarnation is the open-source system MonetDB (See http://www.monetdb.org), which demonstrates
viability of the column-storage approach as an sufficient basis for both an efficient SQL and XQuery database
engine. The system is developed by the Database Architectures group of CWI, which he established in 1985.
Kersten received the prestigious ACM SIGMOD 2014 Edgar F. Codd Innovation Award for his influential contributions to advanced database architectures, most notably his pioneering work on columnar, in-memory, and
hardware-conscious database technologies and their realization in the MonetDB system.
Dr. Stefan Manegold (male) •is a senior researcher and head of the Database Architectures research group at
CWI. He received his PhD in Computer Science from the University of Amsterdam in 2002. His research work
comprises database architectures, query processing algorithms, and data management technology for dataintensive scientific discovery, with a particular focus on optimization, scalability, performance, benchmarking
and testing.
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P52
SKU, Stichting Katholieke Universiteit (the Netherlands)
Laboratory Profile
Founded in 2008, the Donders Institute houses the department of neuroinformatics. Research at the department currently focuses on three major themes: 1) understanding the processing of visual information in the
brain at the level of networks of spiking neurons, and its modulation by cognitive factors; 2) developing analysis methods for multivariate data, to extract and confirm inter-cortical network communication and 3) building predictive models for brain network structure and applying database and machine-learning methods to
infer missing data. An experimental lab for conducting optogenetics experiments to support the computational
studies is present. DI is a community of 500 researchers spanning the faculties of science, social sciences and
medicine as well as the Centre for Cognitive Neuroimaging.
Key Personnel
Prof. Paul Tiesinga (male) - WP4.4 Leader - is professor of Neuroinformatics and Chair of the department of
Neuroinformatics. After post-doctoral studies at Northeastern University and at the Salk Institute, he held an
assistant professorship at the University of North Carolina, before being promoted to an associate professor
position. In July 2009, he was appointed full professor at Radboud University in Nijmegen.
P53
FZI, Stiftung FZI Forschungszentrum Informatik am Karlsruher Institut für Technologie (Germany)
Laboratory Profile
The FZI Research Centre for Information Technology (FZI) in Karlsruhe is a non-profit independent research
centre with about 160 employees, whose core mission is to facilitate technology transfer of innovative solutions
in ICT and to create a bridge between academia and industry. FZI consists of four interdisciplinary research divisions working in close collaboration.
The department of Interactive Diagnosis and Service Systems (IDS) concentrates on the development of intelligent,
mobile service robots and supporting technologies. IDS is involved with a significant number of industry partners,
e.g. in the areas of Automated Guided Vehicles, manipulation, tele-operated diagnosis and inspection systems.
IDS’ project experiences allowed developing agile sensing devices and algorithms coping with complex tasks
involving robots and humans and to fulfil robustness and speed constraints needed in industrial applications.
The modular software framework MCA2 was developed at FZI and is being used in different professional applications like robust indoor navigation. Recently this real time capable framework was extended by introducing
defined interfaces to ROS (Robot Operating System).
The philosophy of the Software Engineering (SE) division is to look at software engineering in its entirety. We therefore analyze, design, develop, adapt, and evolve complex mobile and multi-platform software systems as well as the
underlying business processes from an engineering viewpoint and with continuous quality assurance in mind.
SE has been working in more than 50 co-operative and consulting actions on service-oriented software construction, model-driven software engineering, software quality assessment, and legacy software evolution with
national and European industry. SE serves numerous SMEs and large companies as Siemens, ABB, Nokia, IBM,
Deutsche Telekom, Daimler-Chrysler, or BASF. SE’s research contributes regularly to leading technological conferences like ICSE, WCRE, CSMR, or QoSA.
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P53 FZI, Stiftung FZI Forschungszentrum Informatik am Karlsruher Institut für Technologie (Germany)
Notable recent EU and national research projects are SLA@SOI (FP7-216556), MATURE (FP7-216356), DEXMART
(FP7-216239), Q-ImPrESS (FP7-215013), DBE (IST- FP6-507953), COMMROB (IST-FP6-045441), SOPRANO (ISTFP6-045212), DESIRE (BMBF), Modagile Mobile (BMBF), MOHITO (BMBF), Collaborative Research Center 588
(DFG), iBOSS (DLR), vIEMA (BMWi), ISABEL (BMBF).
Key Personnel
Prof. Paul Levi (male) - WP9.1 Leader - is a Professor for Computer Science (Distributed AI, Computer Vision).
He is currently an executive member of the FZI. His research focuses on distributed robotics and autonomous
systems (mobile robots, vehicles), multi-agent systems, distributed planning for cooperative agents, architectures for cognitive systems, swarm robotics and information theory, fusion of sensor data (laser, camera, radar)
and neuronal networks. Furthermore, he was the coordinator of the EU-funded projects SYMBRION and REPLICATOR and participated as a PI in a large number of national and international projects (e.g. RoboEarth (EC),
ASSET-Road (EC), Cybercar, I+II (EC), Angles (EC), CoCoRo (EC), I-Swarm (EC), CarTalk (EC), Nexus(SFB,
DFG), and Human Genome Project (EC, DFG).
Prof. Dr. Ing. Rüdiger Dillmann (male) is a Professor of the Department of Computer Science at the Karlsruhe
Institute of Technology (KIT), Germany. He is speaker of the KIT-Focus Anthropomatics and Robotics (APR) and
leads the Humanoids and Intelligence Systems Laboratories (HIS). Besides he is the director of the FZI department Interactive Diagnosis- and Service Systems (IDS). As a leader of these institutes he supervises several
research groups in the areas of robotics with special interests in intelligent, autonomous and mobile robotics,
machine learning, machine vision and human-machine interaction.
Dipl. Ing. Arne Rönnau (male) studied Electrical Engineering and Information Technology at the University of
Karlsruhe (TH), specialising in the fields of feedback control, automation and robotics. Since November 2008 he
has been working in the IDS department and has been active as department manager since 2011. His main field
of research is the locomotion control of multi-legged walking robots, 3D perception, physics simulations and the
design and construction of new service robots.
Dr. Ing. Henning Groenda (male) is department manager within SE and responsible for mobile and multiplatform development. He graduated from the University of Karlsruhe and received his PhD from the Karlsruhe
Institute of Technology. His focus is on the design of software architectures across platforms and (early) quality
assurance of extra-functional properties in software development. This covers the whole development process
including design, maintenance, and extension. Henning has been working in numerous consultancy projects with
both, SME and large companies. He is Certified Scrum Product Owner, tailored a quality assurance process for a
.NET-based construction system for a tool manufacturer, and experienced framework developer for Java-based
platforms.
Dr. rer. nat. Oliver Zweigle (male) obtained his M.S. (Dipl.-Inf.) degree in 2004 and his Ph.D. (Dr. rer. nat.) in 2011
from the University of Stuttgart. After working as the leader of the group “Service Robotics” at the department
“Image Understanding” at the IPVS of the University of Stuttgart for 10 years, he is working from June 2014 as
the leader of Competetive Call Human Brain project Vinero-SP at the FZI in Karlsruhe. His research currently
focuses on software architectures for robotic systems, cloud robotics and multi-agent systems. He was one of
the founders of the European Union funded RoboEarth project and is currently working on different projects
that are all focused on software development for cognitive systems, service robotics and simulation. He published about 40 papers in international journals and conferences as well as two books and has profound skills in
software and project management as well as in multiple programming languages (C, C++, Python, Java, etc.) on
multiple platforms (Linux, MacOS, iOS, Android, Windows)
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P54
TUC, Technical University of Crete (Greece)
Laboratory Profile
Software Technology and Network Applications (SoftNet). The Technical University of Crete (TUC, www.tuc.
gr), founded in 1977 in Chania, Crete, is the youngest of the two technical universities in Greece (the other one
is the National Technical University of Athens). The purpose of this state institution is to provide high-quality
undergraduate as well as graduate studies in modern engineering fields demanded by the Greek and international job market, to conduct research in cutting edge technologies as well as to develop links with the Greek
and European industry. TUC is committed to staying at the forefront of educational and intellectual development in the areas of research and teaching both in Greece and internationally. The Software Technology and
Network Applications (SoftNet), part of TUC’s Department of Electronic & Computer Engineering (www.ece.
tuc.gr), represents TUC in the Human Brain Project. The current research activities of the SoftNet group (www.
softnet.tuc.gr) focus on database management systems, data mining, centralized and distributed data-stream
processing, cloud computing, distributed and peer-to-peer systems, and sensor networks. SoftNet members
publish regularly in these areas in major international conferences and journals.
Key Personnel
Prof. Minos Garofalakis (male) received the Diploma degree in Computer Engineering and Informatics from the
University of Patras, Greece in 1992, and the MSc and PhD degrees in Computer Science from the University of
Wisconsin-Madison. He worked as a Member of Technical Staff at Bell Labs, Lucent Technologies, as a Senior
Researcher at Intel Research Berkeley, and as a Principal Research Scientist at Yahoo! Research in Santa Clara,
CA (2007-2008). In parallel, he also held an Adjunct Associate Professor position at the EECS Department of
the University of California, Berkeley (2006-2008). As of October 2008, he is a Professor of Computer Science
at the Department of Electronic & Computer Engineering of the Technical University of Crete, and the Director
of the Software Technology and Network Applications Laboratory (SoftNet). Prof. Garofalakis’ research interests include database systems, centralized/distributed data streams, data synopses and approximate query
processing, uncertain databases, and big-data analytics and data mining. He has published over 120 scientific
papers in these areas, and his work has resulted in 35 US Patent filings (27 patents issued) for companies such
as Lucent, Yahoo!, and AT&T. GoogleScholar gives over 9000 citations to his work, and an h-index value of 50.
Prof. Garofalakis is an ACM Distinguished Scientist (2011), and a recipient of the IEEE ICDE Best Paper award
(2009), the Bell Labs President’s Gold Award (2004) and the Bell Labs Teamwork Award (2003).
Kalliopi Kalantzaki (female) is a PhD student at the Department of Electronic & Computer Engineering of the
Technical University of Crete. She received her BSc and MSc degrees from the same department in 2010 and
2013, respectively. Her research interests center around data mining and machine learning techniques for bioinformatics.
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P55
TUD, Technische Universität Dresden (Germany)
Laboratory Profile
Endowed Chair of Highly-Parallel VLSI-Systems and Neuromorphic Circuits. The neuromorphic hardware
research chair, established in 1997, has an extensive track record in VLSI circuit design for advanced digital and
analog systems. Led by René Schüffny, the group consists of two professors, three post-doctoral fellows and
twenty PhD students. Its expertise encompasses the design and implementation of multi-processor systems on
chip using various deep-submicron (e.g. 28nm) processes, with a focus on high-speed, versatile on- and off-chip
digital communication (e.g. 90GB/s Network-on-chip links); and the implementation of neuromorphic hardware
and peripheral components for digital control, pulse routing and interfacing. The chair collaborates with industry
and in a number of EU projects. It has been responsible for the intra-wafer, ASIC and FPGA-based pulse communication networks for wafer-scale neuromorphic systems in the FACETS, FACETS-ITN and BrainScaleS projects.
Key Personnel
Prof. Rene Schüffny (male) received the Dr.-Ing (Ph.D.) and the Dr.-Ing. habil. (D.Sc.) degrees from Technische
Universität Dresden, Germany, in 1976 and 1983, respectively. Since 1997, he has held the Chair of Highly-Parallel
VLSI-Systems and Neuromorphic Circuits at Technische Universität Dresden and is head of the Institute of
Circuits and Systems. He has 15 years of experience as group leader in numerous research projects funded by
private industry (e.g. Infineon, Atmel, ZMDI) and various national and European research agencies. His research
interests include design and modelling of analog and digital parallel VLSI architectures, CMOS image sensors
and neural networks. He is author or co-author of more than 120 publications in the above fields and has acted
as reviewer for national funding agencies and for several international journals.
Dr.-Ing. Sebastian Höppner (male) received the Dipl.-Ing. (M.Sc.) and the Dr.-Ing. (Ph.D. Eng.) in Electrical Engineering from Technische Universität Dresden, Germany, in 2008 and 2013, respectively. He is currently working
as project manager with the Chair of Highly-Parallel VLSI-Systems and Neuromorphic Circuits at Technische
Universität Dresden. His research interests include circuit design for clocking, data transmission and power management in low power systems-on-chip. He has experience in designing full-custom circuits for multi-processor
systems-on-chip (MPSoCs), like ADPLL clock generators, register files and high-speed on-chip links, in academic and industrial research projects. He has been managing the full-custom circuit design group for various
MPSoC chips in 65nm and 28nm CMOS technology. He is author or co-author of more than 30 publications and
5 patents (2 issued, 3 pending) in the above fields.
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P56
TUGRAZ, Technische Universität Graz (Austria)
Laboratory Profile
For the last twenty years, the Institute for Theoretical Computer Science at Technische Universität Graz (Graz
University of Technology) has been developing theory and computer models to understand computation and
learning in biological neural systems and artificial networks of spiking neurons. Headed by Wolfgang Maass, it
has frequently collaborated with experimental neuroscientists on neurobiological experiments that test predictions of theoretical models. For example it has tested and verified in collaboration with Wolf Singer salient
predictions of the liquid computing model, published 2009 in PLoS Biology. It has also collaborated with neuromorphic hardware and robotics experts on applications of biologically inspired computing and learning principles. The Institute uses a wide variety of methods including machine learning and computational complexity
theory. Theoretical predictions are validated with the help of several computer clusters. Two of its best-known
software developments are the PCSIM software system for the parallel simulation and computational analysis
of biological networks of neurons, and the NEVESIM software for event-based simulations of stochastic spikebased networks in continuous time. The Institute has two full Professors (Wolfgang Maass and Franz Aurenhammer) and one Associate Professor (Robert Legenstein). In addition it has 2 University Assistants, several
Postdocs and Phd students, a system administrator, and 1.5 administrative assistants. It consists of the Maass
Lab, the Legenstein Lab (as well as the Aurenhammer Lab, which will not participate in the HBP).
Key Personnel
Prof. Wolfgang Maass (male) - WP8.4 Leader - early research was in the theory of computation in mathematics
after which he moved on to computational complexity theory and the theory of learning in theoretical computer
science. Since 1995 his research has focused on the extraction of principles of brain computation and learning
from experimental data. Maass and Henry Markram designed the liquid computing model for understanding universal computations in cortical microcircuits. This has now become a classical reference work, inspiring numerous innovative ideas in engineering. In his current research (reviewed in his invited article “Noise as a resource
for computation and learning in networks of spiking neurons” in the Proc. of the IEEE 2014), he is analysing the
role of noise and variability in computation and learning by biological neural systems. The concept of neural
sampling (developed with Lars Büsing and others, and published in PLoS Computational Biology 2011) as well as
a new theory based on Expectation Maximization for analyzing the role of STDP in spiking networks (developed
with Bernhard Nessler and others, and published in PLoS Computational Biology 2013) are widely recognized
new impulses for understanding the capabilities of biological and artificial spike-based networks with noise.
Together with Karlheinz Meier he has initiated the Fürberg Workshops in St. Gilgen (Austria) that were instrumental for establishing tight collaboration between theoreticians and designers of neuromorphic hardare. He
has published some 220 research articles and has been editor of several journals. In 2013 he has been elected
to the Academia Europaea.
Dr. Dejan Pecevski (male) is an expert for machine learning, probabilistic inference, and software design. He
has authored the PCSIM and NEVESIM software systems for efficient simulation and analysis of large models for
biological and artificial networks of spiking neurons. In addition he has coauthored two articles in PLoS Computational Biology, where he established new methods and theoretical analysis tools for reward-based learning
in spike-based systems, as well as the first rigorous method for carrying out probabilistic inference in arbitrary
graphical models through spike-based networks. I his current work he develops new methods for learning of
probabilistic inference in spike-based networks.
Dr. Zeno Jonke (male) is an expert for machine learning, computational neuroscience, and large-scale computer
simulations. In 2013 he has published in PLoS Computational Biology important findings on stochastic computations in networks of spiking neurons, that are gaining substantial impact of the analysis of data-based column
models, but also for the design of computationally powerful spike-based hardware.
David Kappel (male) is expected to receive his Phd in 2014, and to continue then to work as Postdoc in the
Institute for Theoretical Computer Science. He has constributed important research results (published in PLoS
Computational Biology 2014) on emulations of Hidden Markov Model learning in networks of spiking neurons.
In addition he has supervised research in Graz for the EU projects ORGANIC and AMARSi, that provided new
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results on applications of echo-state networks and other new neural network paradigms in speech processing
and robotics. In addition he is leading on the Graz-side the collaboration with EPFL on the investigation of computational properties of the Blue Brain column model. An important part of his current research is the investigation of stochastic computation and learning in data-based column models.
Laboratory Profile
The Legenstein Lab for Learning Principles in Biological and Bio-Inspired Systems. Robert Legenstein’s lab
uses mathematical analysis and computer simulations to investigate fundamental principles of learning and
self-organization in biological neuronal networks and neuromorphic systems. This research is often performed
in close collaboration with experimental neuroscientists and experts for neuromorphic hardware. The lab has for
example worked on the analysis of spike-timing dependent plasticity, both in the context of models for learning in biological systems and as a paradigm for neuromorphic systems. This work has bridged the gap between
biologically plausible plasticity rules and well-established statistical learning methods such as reinforcement
learning and Bayes-optimal learning. Recently, the lab has also contributed to research on learning in novel
memristor-based neuromorphic hardware.
Key Personnel
Prof. Robert Legenstein (male) is Associate Professor at the Technische Universität Graz. His primary research
interests are learning algorithms in models for biological networks of neurons, dynamical systems, and probabilistic neural computation. Dr. Legenstein has established links between STDP and several well-established statistical learning methods such supervised learning, independent component analysis, the information bottleneck
principle, and reinforcement learning. He has also contributed to the analysis of spiking neural networks from
the dynamical systems perspective. He has coordinated the FET-open project Brain-i-Nets in the FP7 framework
of the EU, which had addressed biologically inspired learning rules for neuromorphic hardware and provided
substantial insights and tools that are now used in the HBP. Currently, he is leading the work-package on theory
in the Chist-era project PNEUMA, where memristor-based brain-inspired learning architectures are developed.
Dr. Legenstein is associate editor of the IEEE Transactions on Neural Networks and Learning Systems and area
chair for the NIPS 2014 conference.
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P57 TUM, Technische Universität München (Germany)
Laboratory Profile
The “Robotics and Embedded Systems” group in the Department of Informatics of the Technische Universität München (TUM) is headed by Prof. Alois Knoll. Its primary mission is research and education of
machines for perception, cognition, action and control. More specific research topics include, but are not
limited to, algorithms (e.g. for collision avoidance and path planning), computer architecture for embedded
systems, graphics and simulation using the latest rendering devices, motor control, machine learning, natural
and spoken language, robot programming languages and controllers, as well as synthetic biology and statistical algorithms for computer vision.
Key Personnel
Prof. Dr. habil. Alois Knoll (male) - SP 9 Leader / WP 9.7 Leader / WP 9.8 Leader / WP 9.9 Leader / Research
Board Member - (http://www6.in.tum.de/Main/Knoll) is a professor of Computer Science at the Informatics
Department of the Technical University of Munich and chair of the research group “Robotics and Embedded
systems”. His research interests include cognitive, medical and sensor-based robotics, multi-agent systems,
data fusion, adaptive systems, multimedia information retrieval, model-driven development of embedded
systems with applications to automotive software and electric transportation, as well as simulation systems
for robotics and traffic. In these fields, he has published over 500 technical papers and guest-edited international journals. He has participated (and has coordinated) several large scale national collaborative research
projects (funded by the EU’s DG Research, the DFG, the German Ministries for Economy Affairs and of Education and Research, the DAAD, the Ministry for Research of the state of North-Rhine-Westphalia). He initiated and was the program chairman of the First IEEE/RAS Conference on Humanoid Robots (IEEE-RAS/
RSJ Humanoids2000), he was general chair of IEEE Humanoids2003, general chair of Robotik in 2004 and
in 2008, the largest German conference on robotics, and he served on several other organising committees as well as editorial boards of international journals. Between 2007 and 2009, he was a member of the
EU’s highest advisory board for information technology, ISTAG, the Information Society Technology Advisory
Group, and a member of its subgroup for Future and Emerging Technologies (FET). In this capacity, he was
actively involved in developing the concept of the EU’s FET Flagship projects, and he was one of the authors
of the original FET-Flagship report.
Laboratory Profile
Fachgebiet für Augmented Reality (FAR). Headed by Professor Gudrun Klinker, FAR focuses on Ubiquitous
Augmented Reality - a combination of ubiquitous computing, wearable computing and augmented reality. FAR’s
research focuses on developing technologies that can place virtual information three-dimensionally into real
environments, adapting the information provided to users’ location, work context and attentional capabilities.
Current work includes the development, use and fusion of tracking technologies in sensor networks, and the
use of novel, three-dimensional user interfaces in specific application contexts. Applications developed in the
department use a broad range of mobile devices ranging from mobile phones, PDAs and tablet PCs to HMDs,
HUDs, multi-touch displays and steerable laser projectors.
Key Personnel
Prof. Gudrun Klinker (female) - WP9.2 Leader - the author and co-author of more than a hundred scientific
publications, is the current head of FAR. She studied computer science at the Friedrich-Alexander Universität Erlangen, at the Universität Hamburg and at Carnegie-Mellon University (Ph.D), going on to join Digital
Equipment Corporation’s Cambridge Research laboratory, where she worked on a reusable tele-collaborative
environment for the analysis and visualisation of 3D and higher-dimensional data for medical and industrial
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applications. In the next stage of her career, she researched the newly emerging concept of Augmented Reality,
working both at the European Computer-industry Research Center and at the Fraunhofer Institute for Computer
Graphics. Her current research focuses on the development of new approaches to ubiquitous augmented reality
for realistic industrial applications. A co-founder of the International Symposium of Augmented Reality (ISMAR)
and chair of its steering committee she has served on many programmme committees, including the committees for VR, VRST, 3DUI, and UIST.
Laboratory Profile
The research being carried out at the Chair of Industrial Design focuses on the challenges of ecologically justifiable mass production and shifting social patterns due to demographic change, coupled with universal design.
Design skills are aligned to the principles of New Functionality (second modernity) favoured by Prof. Fritz Frenkler and the scientific orientation of design.
Key Personnel
Prof. Fritz Frenkler (male) studied industrial design at the Academy of Fine Arts (HBK) in Braunschweig. He
was managing director of frogdesign Asia, managed the company wiege Wilkhahn Entwicklungsgesellschaft
and worked as head designer for Deutsche Bahn AG. In 2000, he founded f/p design germany gmbh with
Anette Ponholzer, followed by f/p design japan inc. in 2003. He was made an honorary professor at HBK Braunschweig in 2004. In 2006, he was appointed full professor of the newly-created Chair of Industrial Design at
TUM. Fritz Frenkler is a regional advisor of the ICSID and has been jury chairman of the iF product design awards
for several years. He is a founding member of iF Universal Design & Service GmbH.
Laboratory Profile
Fachgebiet Neurowissenschaftliche Systemtheorie The NST group at TUM investigates theory, models, and
practical robotic implementations of distributed neuronal information processing, to (a) discover key principles
by which large networks of neurons operate and (b) implement those in technological systems to enhance their
real-world performance. Current applications of our research are robust tracking, efficient long range mapping,
and autonomous micro-helicopter flight stabilization; undergoing projects explore massively parallel distributed
neural computation and abstract cognitive reasoning based solely on perception and behaviour. Details of our
research are shown on our project web pages at http://www.nst.ei.tum.de/research/NST.
Key Personnel
Prof. Jörg Conradt (male) has graduated as Dipl-Ing. in Computer Engineering from TU Berlin (Erwin Stephan
Price for best Diploma); obtained a Masters of Robotics/Computer Science from the University of Southern
California, Los Angeles, USA (Fulbright Full Stipend, Academic Excellence Award); and a Ph.D. from ETH Zürich
in 2008 (ETH Medal for outstanding thesis). The NST group has started in fall 2009 with the appointment of
Jörg Conradt as Junior Professor (W1) at TUM; his group currently consists of six fully funded Ph.D. students.
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TAU, Tel Aviv University (Israel)
Laboratory Profile
The Department of Statistics and Operations Research resides in the School of Mathematical Sciences. The
department carries out an extensive research program with a mix of theory and applications. Faculty members
are engaged in research in Statistics, Biostatistics, Bioinformatics, Operations Research, and Game Theory. Much
of the research involves collaborative work with investigators across many fields of science. The department
operates a statistical consulting unit that serves academic investigators in and outside the university, as well as
private research institutes and corporations, both in Israel and abroad. The consulting unit is especially active in
all aspects of medical data analysis.
Key Personnel
Dr. Mira Kalish (female) specializes in “converging technologies” and combined statistical and modeling analysis in Bio-Medicine. Dr. Kalish was a computer programmer and system analyzer professional when she started
her the academic studies. Has a BS.c Biology and Statistics Hebrew U., Ph.D in operation research, developing
a computerized E.K.G system (1986) and did her post-doc at Harvard in the Dana Farber cancer institute and
MBCRR – Molecular Biology Computer Research and Resource. In recent years she has been involved in many
European collaborative research projects including ones the motoric functioning of the brain, and has special
interest in strategies for converging technologies.
Prof. Yoav Benjamini (male) has a B.Sc. in Physics and M.Sc. in Mathematics from the Hebrew University of
Jerusalem, and a PhD in Statistics, from Princeton(,81). He is the Nathan and July Silver Professor of Applied Statistics at Tel Aviv University, where he also heads the Excellence Centre for Statistical Approaches to Complex
Research Problems. He is also a member of the Sagol School for Neurosciences. He has spent some years at the
Wharton School as a visiting associate professor. He served as the president of the Israeli Statistical Association. Yoav Benjamini,s research is in the theory and applications of statistics, the latter including biostatistics,
genomics, functional brain imaging, computational biology and the modeling of exploratory behavior. Together
with Hochberg he introduced the concept of the False Discovery Rate into multiple testing, and ever since has
been contributing to its development in theory and practice, especially as related to high throughput measurement systems and data mining. He is the recipient of the Israel Prize for Research in Economics and Statistics.
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P59
UCAM, The Chancellor, Masters and Scholars
of the University of Cambridge (United Kingdom)
Laboratory Profile
The Department of Psychiatry promotes the mission of the University of Cambridge to contribute to society
through the pursuit of education, learning, and research at the highest international levels of excellence. Our particular focus is on the determinants of mental health conditions, their treatments and the promotion of mental
health through innovative translational research. The Department has wide ranging collaborations within Cambridge Neuroscience, the broader University and beyond into the international scientific and policy communities. We also enjoy strong links with industry, social care and the voluntary sector and the NHS, particularly with
the Cambridgeshire & Peterborough Foundation Trust to which many of our staff contribute clinical services.
Key Personnel
Prof. Barbara J Sahakian (female) FMedSci directs a laboratory of psychopharmacology at the University
of Cambridge Department of Psychiatry and the Medical Research Council/Wellcome Trust Behavioural and
Clinical Neuroscience Institute (BCNI). She has an international reputation in the fields of cognitive psychopharmacology, neuroethics, neuropsychology, neuropsychiatry and neuroimaging. She is the President of the
British Association for Psychopharmacology, a member of the CINP Council and a member of the ECNP
Review Board. She is co-inventor of CANTAB computerized neuropsychological tests (www.cantab.com).
She is a Founder Member President of the International Neuroethics Society (http://www.neuroethicssociety.
org/), co-editor of The Oxford Handbook of Neuroethics (2011) and co-author of ‘Bad Moves. How decision
making goes wrong, and the ethics of smart drugs’ (Oxford University Press, 2013). She has given the David
Kopf Neuroethics Lecture at the Society for Neuroscience Annual Meeting in 2012. She has been a lead on
many national and international neuroscience and mental health policy reports. She has a keen interest in
engagement of the public in neuroscience and ethical issues which affect society and frequently participates
in newspaper, radio and TV interviews. She has over 375publications and an h-index of 95. She is a Distinguished Research Fellow at the University of Oxford Uehiro Centre for Practical Ethics and is co-investigator
with Professor Julian Savulescu on a Wellcome Trust funded neuroethics grant.
P60
UOXF, The Chancellor, Masters and Scholars of the University of Oxford (United Kingdom)
Laboratory Profile
The MRC Functional Genomics Unit has an international reputation for the application of genetics and genomics approaches to analysing gene function in the nervous system. Genomics lies at the heart of most disciplines
in modern biology, but in the Unit it is on neuroscience that we focus our attention most because of the farreaching questions that remain unanswered in brain function and disease. The Deputy Director, Prof Ponting,
has an ERC Advanced Grant on as long noncoding RNAs which are increasingly being recognised as important
contributors to diverse cellular functions and disease, and the Unit contributes to the FP7 GENCODYS consortium. Ponting is also an Associate Faculty member at the Wellcome Trust Sanger Institute and is a founding
member, there, of the Sanger/EBI Single Cell Genomics Centre. He is also Director of the CGAT Training Centre,
and Head of the UK Node of ELIXIR. His group spans approximately 20 postdocs and 10 PhD students.
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P60 UOXF, The Chancellor, Masters and Scholars of the University of Oxford (United Kingdom)
Key Personnel
Prof. Chris Ponting (male) studied particle physics before pursuing a career in biology and DNA. Today, he
researches the changes in the genetic code that underlie differences between individual humans, and between
humans and other animals. Ponting was a major participant in the international projects that sequenced the
human, mouse, rat, dog, opossum, chicken, platypus, zebra finch and orang-utan genomes, in many cases coordinating the analyses of gene, protein and genome evolution. His recent work examines the “dark matter” of the
human genome, and the way DNA differences among mice can help us to understand human biology. His team
focuses on the molecular mechanisms underlying human diseases, such as intellectual disability, Parkinson’s
disease, autism, and obesity. Chris Ponting is Deputy Director of the MRC Functional Genomics Unit, and professor of genomics at Oxford University.
Laboratory Profile
Oxford Physiome Lab in collaboration with the Auckland Bioengineering Institute. The Auckland Bioengineering Institute (ABI) at the University of Auckland, New Zealand, in collaboration with Oxford University, has been
pioneering the development of anatomically and physiologically based models of mammalian organ systems
for the past 15 years under the umbrella of the International Union of Physiological Sciences (IUPS) Physiome
Project and, for the last 7 years, under the European Framework 7 funded Virtual Physiological Human (VPH)
project. A multiscale model of the heart, for example, was developed by Prof Hunter (ABI Director and co-Director of Computational Physiology at Oxford) and his team at the ABI, in collaboration with Professors Noble and
Paterson from the Department of Physiology, Anatomy and Genetics (DPAG) at Oxford University. Multiscale
human Physiome models have now been developed for the circulation system, the musculo-skeletal system,
the respiratory system and the digestive system. These models are based on the laws of physics implemented
on anatomically accurate tissue geometries with anisotropic, nonlinear and inhomogeneous material properties
and linked to molecular systems biology models (www.abi.auckland.ac.nz/en/about/our-research.html).
The Auckland-Oxford team have also led the development of modelling standards for the VPH-Physiome project,
most notably the CellML standard (www.cellml.org). The CellML model database contains over 600 models of
biophysical processes (models.cellml.org).
Other work, by A/Prof Sagar in the ABI, includes highly realistic modelling of the animated human face (www.
abi.auckland.ac.nz/en/about/our-research/animate-technologies.html) including neuromuscular-skin models
that respond to sensory input in real time.
Key Personnel
Prof. Peter Hunter FRS (male) studied maths, physics, engineering and physiology before pursuing a career
in bioengineering. He founded the Auckland Bioengineering Institute (ABI) at the University of Auckland in
2001 and has been its Director since that time. He is also a co-Director with Prof Denis Noble of Computational Physiology at Oxford University where he holds a visiting professorship. He led the IUPS Physiome
Project for 15 years.
Prof. Mark Sagar (male) trained in maths, physics and engineering science before embarking on a career in
the computer animation industry, including Weta Digital where he led the facial animation team for Avatar and
other movies. He has won two academy awards for his technical achievements. He returned to a position at the
University of Auckland in 2012 and founded the Laboratory for Animate Technologies within the ABI.
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HUJI: Hebrew University of Jerusalem (Israel)
P61
Laboratory Profile
Research at The Laboratory for Understanding Neurons focuses on modelling synaptic plasticity, dendritic and
axonal excitability and the dynamics of small cortical microcircuits. It is also geared to the development of analytical and computational methods for deciphering information processing at the single cell and network levels. Led by
Idan Segev, the group consists of eight doctoral and Master’s students, with projects on modelling single cells and
characterised networks. The laboratory houses a powerful computer cluster (Dual-Core AMD Opteron(tm) Processor 2220) and personal computers (Macs and PCs) for each of the students and a direct line to the BBP at the EPFL.
Key Personnel
Prof. Idan Segev (male) - SP 3 Co-leader / WP 5.6 Leader / Research Board Member - is the David and Inez
Myers Professor in Computational Neuroscience and the former director of the Interdisciplinary Center for Neural
Computation (ICNC) at the Hebrew University of Jerusalem. He received his B.Sc (1973) in Math and his Ph.D
(1982) in experimental and theoretical neurobiology, in the very same university. His work is published in reputed
journals and he has received several important awards, some for his excellent teaching abilities. He takes a keen
interest in the connection between art and the brain. Prompted by an encounter with ICNC researchers, he has
recently co-edited an “Artists” book with original etchings by ten top Israeli artists. Segev, the world’s undisputed
leader and a pioneer on model neurons, has been instrumental in theoretically ground automated building of
model neurons in the Blue Brain Project.
P62
UABER , University of Aberdeen (United Kingdom)
Laboratory Profile
The Institute of Pure and Applied Mathematics (IPAM) in the University of Aberdeen is a consortium of two
institutes: the Institute of Mathematics (IMA) and the Institute of Complex Systems and Mathematical Biology
(ICSMB). The IMA is a centre of excellence in pure mathematics, and specifically topology and geometry. Other
subjects strongly represented in IMA are group and representation theory and analysis. The unifying research
theme of the ICSMB is the study of complex dynamic and its applications.
Aberdeen is an international university built on serving one of the most dynamic regions of Europe. With over
16,000 students (46% male, 54% female and 19% mature graduates) from more than 120 nationalities and over
3000 staff the University is at the forefront of teaching and research in medicine, the humanities and sciences.
Some University of Aberdeen successes include: 5 Nobel Laureates; the generation of 21 spin-off companies and
mover 400 patents pending, high quality teaching with over 89% subjects rated Excellent/Highly Satisfactory;
97% of graduates entering directly into work, further study or training within 6 months; 85% of academic staff
who are research active and a trebling of research income in the last decade. Capital expenditure 1999-2009
totalled £229 million, with a further £148 million to be invested in infrastructure to 2019.
Key Personnel
Prof. Ran Levi (male) obtained his PhD in Algebraic Topology from the University of Rochester. He joined the
University of Aberdeen in 1998 as a lecturer, and has been working there ever since. In 2004 he became a professor of mathematics, and shortly thereafter served for two years as the head of the mathematics department
in Aberdeen. He was responsible for the establishment of the Institute of Mathematics, and more recently for
the merger of the IMA and the ICSMB into a single disciplinary unit. The bulk of Levi’s research is in algebraic
topology and application of algebraic and categorical techniques to the study of topological phenomena. His
interest in neuroscience and intense exchange with scientists involved with the Blue Brain Project motivated him
to apply topological and algebraic techniques to questions in neuroscience.
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P63
UEDIN, The University of Edinburgh (United Kingdom)
Laboratory Profile
The interests of the Database Group at the University of Edinburgh span all aspects of database systems and
theory. Topics of current interest include data cleaning, data currency, graph patterns, incomplete information in
XML and graph data, and the implementation of database technology in new memory models. One of Europe’s
foremost database research groups, the group, headed by Peter Buneman, is part of the Laboratory for the
Foundations of Computer Science in the School of Informatics, where it has close ties with scientific data and
has led the research for the UK Digital Curation Centre. Current research topics include data arWP2.1 Genetic
and molecular architecturechiving, data provenance, curated databases, data annotation and data citation.
Key Personnel
Prof. Peter Buneman (male) is Professor of Database Systems in the University of Edinburgh School of Informatics. His work focuses mainly on databases and programming languages, specifically, database semantics,
approximate information, query languages, types for databases, data integration, bioinformatics and semistructured data. He has worked on important scientific database issues such as data provenance, archiving and annotation and made contributions to graph theory and to the mathematics of phylogeny. He has served on numerous
programme committees, editorial boards and working groups, and has been programme chair for all the leading
database theory and systems conferences including ACM SIGMOD, ACM PODS, VLDB and ICDT. A Fellow of the
Royal Society, the Royal Society of Edinburgh, and the ACM, Peter Buneman is the recipient of a Royal Society
Wolfson Merit Award.
Laboratory Profile
Grant’s laboratory studies the molecular basis of behaviour and synaptic biology. Its major strengths are in
mouse genetics and proteomics approaches, which it integrates with electrophysiological and behavioural
studies. The laboratory has been responsible for initiating the UK’s Gene s to Cognition Programme where it
has used large-scale approaches to obtain data at multiple levels of biological organisation between gene and
behaviour. The G2C project has a unique database called G2Cdb and an educational website called G2COnline.
Key Personnel
Prof. Seth Grant (male) - SP 1 Co-leader / WP1.1 Leader / WP2.1 Leader / Research Board Member - has degrees in
physiology, medicine and surgery from the University of Sydney. He did his post-doctoral training at Cold Spring Harbor
Laboratory under Douglas Hanahan and later under Eric Kandel at Columbia University. He is currently Professor of
Molecular Neuroscience at Edinburgh University, Honorary Professor at Cambridge University, and John Cade visiting
Professor at Melbourne University. From 2003-2011, he was Principal Investigator at the Wellcome Trust Sanger Institute.
He is an elected Fellow of the Royal Society of Edinburgh. He will co-direct the research on the multi-level organisation
of the mouse brain in the HBP.
Prof. Robert Williams (male) - WP1.5 Leader - received a BA in neuroscience from UC Santa Cruz and a Ph.D. in
physiology at UC Davis. He did postdoctoral work in developmental neurobiology with Pasko Rakic and moved
to the University of Tennessee in 1989. He is chair of the Department of Genetics and holds the UT Oak Ridge
National Laboratory Governor’s Chair in Computational Genomics. He was a past president of the International
Society for Behavioural and Neural Genetics and founding director of the Complex Trait Community (www.complextrait.org). He is editor-in-chief of Frontiers in Neurogenomics, and serves on the editorial boards of Genes,
Brain & Behavior, Neuroinformatics, Mammalian Genome, Molecular Vision, European Journal of Anatomy, Alcohol,
BiomedCentral Neuroscience, the Journal of Biomedical Discovery and Collaboration, and Behavior Genetics. One
of Williams’ more notable contributions is in the field of systems genetics and expression genetics (eQTL analysis).
He and his research group have built GeneNetwork (www.genenetwork.org), an online resource and suite of gene
mapping code that is used widely by the genetics and molecular biology communities.
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P63 UEDIN, The University of Edinburgh (United Kingdom)
Laboratory Profile
The School of Informatics at the University of Edinburgh is one of the largest in the world and is renowned both
for its research and its teaching. The school is the largest department in the UK for research and also the highest-rated. Its citycentre premises include a new purpose-built research centre, the Informatics Forum, teaching
facilities and dedicated incubator space for knowledge transfer activities. Relevant research strengths include
database technology, theory and data mining; neural computation and systems biology modelling; probabilistic
modelling and machine learning; naturally inspired computation and robotics. The School is also home to the
highly successful ProspeKT and AspeKT initiatives – two important programmes that support the creation of
new IT businesses, knowledge creation and knowledge transfer.
Key Personnel
Prof. J. Douglas Armstrong (male) - WP1.4 Leader - is Professor of Systems Neurobiology at the School of
Informatics, University of Edinburgh. His research group is multidisciplinary and includes a computational laboratory focusing on neuroinformatics and a neuroscience wet-lab research group working in integrative physiology (www.inf.ed.ac.uk/~jda). Of particular relevance is his work on neuroinformatics databases for the Virtual Fly
Brain (www.virtualflybrain.org) and Genes2Cognition (www.g2conline.org) programmes. His has also released a
series of studies, computational models and open-source software for the analysis of protein complexes. Professor
Armstrong’s work has resulted in two successful university spin-out companies: Brainwave- Discovery Ltd (www.
brainwave-discovery.com) and Actual Analytics Ltd (www.actualanalytics.com).
P64
UMAN, The University of Manchester (United Kingdom)
Laboratory Profile
Advanced Processor Technology Group (APT). Led by Professor Steve Furber, the APT group at the University
of Manchester focuses on issues related to the complexity of microelectronic design. The UK microelectronics
design research community has identified four Grand Challenges for research in this area, of which the APT
group’s addresses three,: “Batteries not included” (minimising the energy demands of electronics; a vital objective for exascale computing); “Moore for Less” (performance-driven design for next-generation chip technology) and “Building Brains” (neuro-inspired electronic systems).
Key Personnel
Prof. Steve Furber (male) - SP 8 Co-leader / WP8.2 Leader / Research Board Member - leads the Advanced
Processor Technologies group and is known internationally for having spearheaded the creation of the ARM
microprocessor at Acorn Computer, Ltd. His current research focuses on energy-efficient processor and System-on-Chip technology, including the EPSRC SpiNNaker (Biologically-Inspired Massively-Parallel Architectures
- BIMPA) project, which he directs. This multi-site initiative, developed in collaboration with the Universities of
Southampton, Cambridge and Sheffield, uses large arrays of bespoke energy-optimised many-core processors
to model large-scale brain functions in real time. Professor Furber has been elected to an IEEE Fellowship and
is a member of the Academia Europaea. He chairs the REF 2014 sub-panel B11 and the Royal Society study of
computing in schools. Furber will co-direct the Neuromorphic Computing Division of the HBP.
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P64 UMAN, The University of Manchester (United Kingdom)
Laboratory Profile
SpiNNaker Software Group (SSG). Led by Dave Lester and part of the APT group at the University of Manchester, the group focuses primarily on the provision of low-level support software for Neuromorphic and Computational Neuroscience on the SpiNNaker or NM-MC1 and NM-MC2 platforms of the Human Brain Project. In
addition, other activities take place to support more general forms of computation such as distributed placeand-route algorithms and other distributed
Key Personnel
Dr David Lester (male) After gaining a BA in mathematics and a DPhil at the Programming Research Group in
Oxford, David Lester began his working life as the Project Leader of ESPRIT-415B programming a distributed
implementation of Functional Languages using Transputers with GEC-Marconi. In 1990 he joined Manchester
University as a Lecturer specialising in Functional Programming, Computer Arithmetic, and more recently Neuromorphic Engineering. His role in the Human brain Project is to direct the software aspects required to make
NM-MC1 and NM-MC2 platforms usable.
P65
UAM, Universidad Autonoma de Madrid (Spain)
Laboratory Profile
Thalamus laboratory - Dept. of Anatomy and Graduate Programme in Neuroscience. Our laboratory focuses
on elucidating cell diversity and the precise wiring of long-range projection neurons (LRPN) that monosynaptically link distant brain regions, and may thus be pivotal substrates of the widely distributed networks that
allow complex perception, cognition and action. We apply in electrophysiology and high-resolution single-cell
axonal tracing methods such as juxtacellular injections and single-cell transfection in vivo, standard and confocal
microscopy, stereology and 3D reconstruction methods.
Key Personnel
Prof. Francisco Clasca (male) graduated in Medicine from the Basque Country Univeristy (1993). Ph.D. in Neuroscience (1990) from the Autonoma University in Madrid. Did a postdoctoral training with Carlos Avendaño
Sensory Plasticuty lab in Madrid, and then joined Mriganka Sur’s laboratory (1992-1995) at the Dept of Brain &
Cognitive Sciences of the Massachusetts Institute of Technology. After returning to Spain, I became Associate
Professor (1997) and Full Professor (2007) at the Department of Anatomy and Graduate Program in Neuroscience of the Autónoma University of Madrid. The goal of my research is to elucidate the connectomics of highcentrality cortical and subcortical neuronal hubs that, by means of their long-range, divergent connections,
allow the forebrain to behave as a highly integrated, dynamic network. Over the past decade my work has
focused on high-resolution, quantitative studies of thalamocortical pathways. We apply high-resolution tracing
of small cell populations or single neuron in vivo, and analyze circuitry organization at the mesoscale (whole
cerebral hemisphere), microscale levels.
Prof. Lucia Prensa (female) obtained her B. Sc. degree in Veterinary Medicine from Complutense Univerisity and
her Ph.D. in Neuroscience from the Autonoma University of Madrid (1998) Her Ph.D thesis dealt with principally
the neurochemical organization of the striatum in the human brain. She then moved to the Centre de Recherche
Université Laval Robert-Giffard (CRULRG), in Québec, Canada (1998-2000), for a postdoc in Dr. André Parent’s
lab. Her work there was centered on the study of the trajectory and pattern of axonal arborization of the nigrostriatal pathway in rodents. In 2001, she returned to Spain under and was awarded a highly competitive “Ramon y
Cajal” fellowship from Spanish Science and Technology Ministry. She professor in Navarra University 2001-2004,
and then moved to the Autonoma Univerisy in Madrid as Associate Professor.
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P66 UCLM, Universidad de Castilla – La Mancha (Spain)
Laboratory Profile
Synaptic Structure Laboratory (Syslab). The Synaptic Structure Laboratory focuses on unravelling different
aspects of the neuronal functional structure, mainly by dissecting the molecular cytology of neurons through
the experimental analysis of regional distribution and cellular and subcellular localization of neurotransmitter
receptors and ion channels. This knowledge is crucially important to understand the basic mechanisms by which
the brain is working and, therefore, the consequences deriving from its dysfunction under pathological conditions. The laboratory has two major project areas: 1) To reveal the molecular, structural and functional heterogeneity of central excitatory and inhibitory synapses; and 2) To create a molecular map of the neuronal surface by
determining the location and density of neurotransmitter receptors and ion channel subunits in defined subcellular compartments of identified central neurons. Molecular, light- and electron microscopic immunolocalization
approaches are combined to address these issues. Furthermore, the laboratory also employs quantitative electron microscopic freeze-fracture replica immunogold localizations to reveal the molecular composition of structurally and functionally distinct subcellular compartments. The results shed new light on the structure-function
relationship of central synapses clearly demonstrated that those signaling molecules show different cell surface
distribution patterns in distinct neuron types (cell type-specific distributions), and that the ion channel content
of distinct subcellular compartments is highly specific (subcellular compartment-specific distributions).
Key Personnel
Dr. Rafael Luján (male) was born on 9th April 1967 in Almería, Spain. In 1985, he was admitted to the Biology
School, University of Granada, Spain, to study biological sciences. Following his graduation in 1990, he enrolled to
the Department of Cell Biology as a graduate student. His aim was to understand how administration of ethanol
affects the number and structure of thalamic nerve cells. He completed his thesis in 1993 and received Ph.D. From
1993 to 1997 he was a Postdoctoral Research Assistant in Peter Somogyi’s lab at University of Oxford, where he
learned high-resolution immunoelectron microscopy. His aim was to establish the molecular architecture of central
synapses. During these years, he developed novel quantitative, immunolabeling EM techniques to reveal the
precise subcellular location of neurotransmitter receptors and to tell how many of them are segregated in certain
synapses. In 1998, Dr Luján returned to Spain and he spent two years at the Instituto de Neurociencias, Alicante,
Spain. In 2000, he moved to Albacete to establish his independent research group in the Medicine School, Universidad de Castilla-La Mancha, where he setup the Laboratory of Synaptic Structure. In 2008 and 2010, he spent
several months in Shigemoto’s lab at NIPS, Japan, where he learned SDS-FRL techniques. His research interest
focuses on unravelling functional structure of neurons with particular emphasis in dissecting the molecular cytology of neurons through the analysis of cellular and subcellular localization of receptors and ion channels. From
the point of view of scientific standards and indicators, the PI presents an h index of 34, with about 5250 citations.
Dr. José Martínez-Hernández (male) was born on 20th July 1979 in Valencia, Spain. In 2002, he graduated at
the Biology School, University of Valencia, Spain. He completed his thesis in 2009 and received Ph.D. In 2010 he
was a postdoc in Shigemoto’s lab at NIPS, Japan, where he learned high-resolution immunoelectron microscopic
techniques. In 2010 he joined the laboratory of Dr. Rafael Luján as a postdoc, at the School of Medicine, UCLM,
Albacete, Spain. He has been working on the subcellular localization of neurotransmitter receptors and ion channels in the brain. He has published 11 articles in medium- high impact journals, 32 communications to international
meetings and has participated in six research grants. For the last two years he is working at the INSERN, Grenoble
Institut des Neurosciences, La Tronche, Grenoble, France. Dr. Martinez-Hernandez will contribute to perform the
complex quantitative analysis of the FIB/SEM immunogold experiments using appropriate software.
Dr. Joaquín Calixto Garcia-Martinez (male) found in 2010 the research group “Pharmaceutical Organic Chemistry” at the new Faculty of Pharmacy of Universidad de Castilla- La Mancha. Associate professor since 2009, at
Faculty of Chemistry, his research interest focuses on synthesis, functionalization, characterization and properties of macromolecules such hyperbranch polymers or dendrimers. The structures designed and prepared have
been used in a wide scope of applications: fluorescence properties, metal nanoparticles, supramolecular chemistry, or gene transfection. He has participated in seven funded research projects, two of them as principal investigator (PI), and published a total of 42 articles, within reviews, research articles, book chapters and a book. He is
also inventor of five patents and contributed in 30 international and national congresses. He has supervised two
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P66 UCLM, Universidad de Castilla – La Mancha (Spain)
thesis and two master projects. Overall, Dr. Garcia-Martinez has an h-index of 17. In 2009, he was granted with
“Luisa Sigea de Velasco” awards for young scientist. He is also member of American Chemical Society, Spanish
Royal Society of Chemistry, Spanish Society of Organic Chemistry, and Spanish Society of Medicinal Chemistry.
Founding partner of Spanish Young Chemist Society. Since 2010, he is Associate Dean of Faculty of Pharmacy.
Dr. Juan Tolosa-Barrilero (male) finished his Ph.D. in 2007 with a dissertation on “design of new dendritic architectures and multichromophoric systems”. Then, he started a postdoc career of five years –initially at Georgia
Institute of Technology (USA) and afterwards at the ‘Organische Chemie Institut’ in the University of Heidelberg
(Germany)–before becoming assistant professor in the group “Pharmaceutical Organic Chemistry” led by Dr.
García-Martínez at the Faculty of Pharmacy of Universidad de Castilla-La Mancha in 2012. He has published 15
material science articles on conjugated hyperbranched polymers, dendrimers and fluorescent sensors, including contributions to JACS and Angewandte Chemie (selected as V.I.P. paper), a cover in Journal of Organic
Chemistry and a highlighted article in Chemical and Engineering News. He has participated in 4 funded research
projects and his current interest focuses in the use of water- soluble dendrimers and hyperbranched polymers
as biocompatible tools in the study, control and/or manipulation of physiological processes. He is member of
American Chemical Society and Spanish Royal Society of Chemistry.
P67
UGR, Universidad de Granada (Spain)
Laboratory Profile
The Computational neuroscience and neurobotics Lab is part of the Computer Architecture and Technology
Department at the University of Granada. The lab focuses on developing efficient neural simulation engines for
real-time closed-loop experiments with brain-body models and has participated in three European projects
investigating these issues, as part of the FP5, FP6 and FP7 programmes. The lab’s main expertise is in simulating brain modules or neural subsystems such as the cerebellum, and interfacing with real or simulated robots
in behavioural experiments. Work at the lab concentrates on experiment-driven development, and most of the
tools it has created have been released under open source licenses. One of the best known is EDLUT (http://
code.google.com/p/edlut/ ) - an efficient neural simulator with a strong focus on real-time simulation. The lab’s
main equipment consists of local simulation clusters that it uses to run massive simulations for brain-body configuration studies.
Key Personnel
Prof. Eduardo Ros (male) of the University of Granada has more than 170 scientific publications (7058 SCI
journals, 110 international conferences) and has supervised thirteen Ph.D. theses. He has been the PI for six EU
grants in the FP5, FP6 and FP7 programmes, he and has also won five national grants, and led five industrial
projects. He is co-author of three international patents. In 2002, he was recognised as the best young researcher
in Andalucía. His main research interests are in computational neuroscience, biomedical engineering, computer
science and neuromorphic engineering, with a specific focus on efficient schemes for real-time simulation, and
embedded neural simulators in robotics.
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P68
UMINHO, Universidade do Minho (Portugal)
Laboratory Profile
The Neuroscience Research Domain at ICVS aims to create the conditions to produce high quality research
in the field of neuroscience. We cover the full spectrum of research (from basic to clinic) with a high degree of
inter-disciplinarity. We are focused on understanding the neurobiological mechanisms implicated in several neurodevelopmental and neurodegenerative disorders, as well as in evaluating the interplay between the nervous
and the immune systems. We benefit from a great logistic (labs and equipment) infrastructure and a vast team
that guarantees expertise in a vast technical platform; in this way we foster multimodal approach to the research
questions under study. The close interplay with the Clinical Academic Center allows to bridge, within the same
infrastructure, from the genetic, molecular and cellular approaches to the clinical applications. In this way, we
hope to take part of the fantastic challenge of contributing to better understanding the Nervous System in
health and in disease to improve its functioning.
Key Personnel
Prof. Nuno Sousa (male) is a MD, Full professor and Director of the Medical Degree at School of Health Sciences,
University of Minho and Director of the Clinical Academic Center in Hospital de Braga. He coordinates Neuroscience Research Domain at ICVS. He has published more than 150 peer-reviewed papers. His research main
interests are focused in the establishment of functional and structural correlations mediated by environmental
challenges (e.g. stress) and its implications in neuropsychiatric disorders. Detailed assessment of neuroplastic
events, incorporation of newly generated cells into neuronal networks, rearrangements of established dendritic
and synaptic contacts, combined with behavioural, neurochemical and electrophysiological, molecular biology
and bioimaging correlates have been established in his lab; the work from the lab covers from basic to clinical research and several modulatory interventions have also been described in order to promote recovery of
structure and function in neuronal tissues. He has been involved in several EU FP7 funded projects, including MC
training networks. He has received 6 awards and honours for his research accomplishments. He is Editor-in-Chief
of Frontiers in Behavioral Neuroscience and member of the Editorial Board of Molecular Neurodegeneration.
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P69
UPM, Universidad Politécnica de Madrid (Spain)
Laboratory Profile
The Laboratorio Cajal de Circuitos Corticales UPM-CSIC (CCCL) is led by Javier de Felipe. Located at the UPM
it was established in 2008 as a joint research laboratory between UPM and the Cajal Institute (IC-CSIC) with
the aim of combining experimental studies of the brain with computer science technologies. It brings together
neuroinformatic groups from across the UPM that provide expertise in statistics, informatics tools and image
analysis, and also includes expert researchers in neuroscience (neuroanatomy) from the IC-CSIC as well as
computer scientists. The CCCL has all of the latest equipment to carry out its ongoing research. It is currently
engaged in collaborations with research groups from EPFL (Switzerland), Columbia University (USA), Heidelberg University (Germany), University of Cambridge (England), the Royal College of Surgeons (Ireland), and the
Institute Pasteur (France).
Key Personnel
Prof. Javier DeFelipe (male) - SP 1 Leader / WP 1.2 Leader / WP 1.3 Leader / WP 1.6 Leader / WP 2.2 Leader /
Research Board Member - is a research professor, specialised in correlating morphological electron microscopy
data with data on synaptic connectivity generated through the use of functional markers, or by intracellular
labelling. He was the Spanish project leader for the NASA Neurolab project and is the Director of the Cajal Blue
Brain Project. A former associate editor of Brain Research and the chief editor of Frontiers in Neuroanatomy,
he serves on the editorial boards of several other journals, including the Journal of Chemical Neuroanatomy,
Experimental Neurology and Cerebral Cortex. A highly cited author, Professor DeFelipe has given more than
270 international lectures. He is the recipient of the Cortical Discoverer Award from the Cajal Club and Honorary
Member of the American Association of Anatomists (elected in 2013).
Dr. Ángel Merchán (male): Senior Researcher
Dr. Alberto Muñoz (male): Senior Researcher
Dr. Lidia Alonso-Nanclares (female): Postdoctoral Researcher
Dr. Ruth Benavides-Piccione (female): Postdoctoral Researcher
Dr. Pilar Flores-Romero (female): Project Manager
Laboratory Profile
The Computational Intelligence Group (CIG) was created in 2010 and is leaded by Prof. Pedro Larrañaga.
Research of CIG members, both theoretical and practical, is devoted to modelization (from a statistical and
machine learning perspectives), heuristic optimization, and neuroinformatics. The main issues in modelization
include: data streams, multi-dimensional supervised classification, multi-label classification, clustering in highdimensional spaces, feature subset selection using methods as Bayesian networks, and regularization. In heuristic optimization, we solve complex problems with e.g. multiple objectives with special emphasis on estimation
of distribution algorithms. In neuroinformatics we face neuroanatomy issues, like modelling and simulation of
dendritic trees, spines or somas; optimal dendritic wiring; spatial distribution of synapses and classification
of neuron types based on morphological features. Also, we deal with problems related to neurodegenerative
diseases, like predicting health-related quality of life in Parkinson’s disease and searching for genetic biomarkers in Alzheimer’s disease. Current collaborations include research groups from Columbia University (USA),
George Mason University (USA), Centro de Investigación y Estudios Avanzados del Instituto Politécnico Nacional (Mexico), Oxford University (UK), Radboud University Nijmegen (The Netherlands), Aalborg University
(Denmark) and King’s College Hospital (UK).
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P69 UPM, Universidad Politécnica de Madrid (Spain)
Key Personnel
Prof. Pedro Larrañaga (male): Prof. Pedro Larrañaga holds an MSc degree in Mathematics (Statistics) from
the University of Valladolid and a PhD degree in Computer Science from the University of the Basque Country
(excellence award) where he founded the Intelligent Systems research group, becoming full professor in 2004.
Then he moved to Technical University of Madrid in 2008. With almost 20 years of post-doctoral experience,
Prof. Larrañaga has supervised 21 PhD theses, and published 200+ peer-reviewed papers and held various
offices, most notably as Expert Manager of Computer Technology area, Deputy Directorate of research projects,
of the Spanish Ministry of Science and Innovation (2007-2010). In 2012, he was granted as an ECCAI fellow. In
2013, he was awarded as National Prize in Computer Science by the Spanish Scientific Society of Informatics.
Laboratory Profile
CeSViMa (Centro de Supercomputación and Visualización de Madrid = Madrid Supercomputing and Visualization Center). CeSViMa’s expertise ranges from high performance computing to GPU programming, massive
information storage, visualisation and optimisation. Led by Prof Vicente Martin, CeSViMa is located on the
Campus de Montegancedo and hosts Magerit, the second largest general-purpose supercomputer in Spain, as
well as a five-wall immersive visualisation cave that is unique in the country. The centre provides more than 45
million CPU hours to over 100 projects, yearly serving some 400 researchers. Its work with the Cajal Blue Brain
project and Alzheimer 3Pi has resulted in a line of activity devoted to interactive/immersive three-dimensional
visualisation for neuroscience applications. As part of this work, it has developed or co-developed the ESPINA,
RTNeuron and VCell programmes, which provide novel functionality for image segmentation, 3D volume reconstruction of synapses, cortical column visualisation and initial simulations of populations of cortical columns.
Key Personnel
Prof. Vicente Martin (male) is the director of CeSViMa, where he leads the UPM Quantum Information and Computation Group as well as the effort to prototype a metropolitan area QKD network. He is an associate professor
of computational science, with a Ph.D. on the numerical simulation of quantum systems from the Universidad
Autónoma de Madrid. He has taught scientific computing and parallel programming for more than ten years, has
directed or participated in more than twenty projects, has co-authored more than forty papers, holds several
patents and has contributed to standardisation. He is a member of the European Telecommunications Standards
Institute (ETSI) Industry Specification Group (ISG) on QKD.
Laboratory Profile
The UPM Autonomous Systems Laboratory (www.aslab.upm.es) is a research laboratory centred in the development of technology for the implementation of complex autonomous systems with a cross-domain approach
(control, robotics, cognitive science, neuroscience). Their focus of activity is in complex intelligent control,
autonomous robotics, software intensive control systems, distributed control systems, model-based engineering, and cognitive architectures. The approach is transdisciplinary and strongly based in the development of
autonomous systems theory to support the systematic engineering of artificial agents in different industrial
domains, esp. in robotics.
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P69 UPM, Universidad Politécnica de Madrid (Spain)
Key Personnel
Prof. Ricardo Sanz (male) is Electrical Engineer (1987), PhD in Robotics and Artificial Intelligence (1990), and
Professor in Automatic Control and Systems Engineering at the UPM. His research focuses in architectures for
software-intensive intelligent control systems. This work sits the frontier between control, computing and intelligence –automatic control, artificial intelligence, embedded systems, real-time distributed systems, software
engineering, and cognitive systems. He is the founder and coordinator of the Autonomous Systems Laboratory
of the UPM. He has been researcher (+25 years) and principal investigator in many national and international
projects (10+) in the fields of complex intelligent controllers, real-time distributed systems, cognitive systems
and robotics; most of them funded by the EU. He is associate editor of the new Journal on Biologically Inspired
Cognitive Architectures and the International Journal of Machine Consciousness.
Laboratory Profile
Grupo de Minería de Datos y Simulación (MIDAS). Co-led by Professors Ernestina Menasalvas and José María
Peña, MIDAS is affiliated with the Centre of Biomedical Technology and CeSViMa and has collaborated in more
than twenty projects in the fields of life sciences and medicine, where the group applies advanced data analysis
techniques and simulation methods to research in bioinformatics, neuroinformatics and pharmacoeconomics.
MIDAS collaborates with the Cajal Blue Brain project, conducting neuroinformatics research in database integration, modelling/simulation, image processing and data analysis. MIDAS group is part of the International Brain
Mechanics and Trauma Lab (coordinated by Prof. Antoine Jérusalem, University of Oxford) in which it collaborates in the coupling mechanical-electrophysiological simulations to model impulse transmission impairment
after brain trauma. MIDAS research focuses on the application of data mining techniques and interactive visual
analytics on Big Data for complex problems in science, engineering and the biomedical sector. Its work includes
the development of the ESPINA toolkit (http://cajalbbp.cesvima.upm.es/espina) a neuroscience-specific image
processing and analysis tool integrated with the HBP Neuroinformatics platform.
Key Personnel
Prof. José María Peña (male), is a professor at UPM and the scientific sub-director of the CeSViMa-UPM Supercomputing Center. After obtaining a Ph.D. in computer science from UPM, he has pursued a career in the field
of high-performance data analysis and modelling, focussing on applied problems in genomics, proteomics and
neuroscience. He has more than fifteen years of research experience and has participated in more than twenty
national and international projects, five of which he has led. He coordinated the UPM node in the computational
neuroscience part of the Cajal Blue Brain project. He is a member of the Intelligent Data Analysis (IDA) Council
and the associate editor of several journals. He has received the Best Young Researcher Award from FGUPM and
has published more than 100 peer-reviewed papers.
Prof. Ernestina Menasalvas (female) is a professor of databasing and data mining at UPM and belongs to the
CTB-MIDAS research group. Her research focuses on data mining project development and specifically the integration and preparation of data. She has participated in research and development projects in data integration
and mining on mobile devices and has published three books on web and text mining. Her many journal papers
include publications in the Data and Knowledge Engineering Journal, the International Journal on Information
Systems, and the International Journal of Intelligent Data Analysis. She has led several EU project on data mining
and Big Data technologies and is currently the academic representative of UPM in the Big Data PPP (PublicPrivate Partnership).
Prof. Ángel Rodríguez (male) is associate Professor at the Computer Science School in the UPM. He has participated in numerous national and international projects funded by both, public and private organizations (more
than 30). He is currently member of the Virtual Reality and Modelization Group (GMRV) and his research line is
focused on visual analytics. He has published more than 50 peer-review papers and supervised 4 PhD thesis.
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P70
URJC, Universidad Rey Juan Carlos (Spain)
Laboratory Profile
The Research Group on Modelling and Virtual Reality (GMRV) focuses its research on scientific visualisation,
interaction, physically-based simulation and animation, and virtual reality. It was created in 2000 with researchers from the URJC and UPM, and is led by Luis Pastor. The group is composed of one full professor, two associate
professors, six assistant professors, six post-doctoral fellows, two technical staff and fourteen Ph.D. students,
from both institutions. With an ERC starting grant, GMRV collaborates with numerous European, Spanish and
privately funded research programmes in the areas of computer graphics, VR and visualization, including the
Cajal Blue Brain and the HBP.
Key Personnel
Prof. Luis Pastor (male) holds a Ph.D. in Electrical Engineering from the Universidad Politécnica de Madrid and
is a professor of Computer Science/Engineering at the Universidad Rey Juan Carlos in Madrid, where he heads
the Research Group on Modelling and Virtual Reality. In recent years, he has worked on virtual reality, visualisation and interaction, in particular in neuroscience, having taken an active part in the Blue Brain and Cajal Blue
Brain projects. In addition, he has been working in high performance computing and its application to graphics
and imaging. He has led 33 European and Spanish-funded research projects and has co-authored some sixty
peer-reviewed publications. He holds several patents on imaging and VR-based surgical simulators, some of
which have been exploited commercially (Simbionix ARTHRO VR).
Dr. Pablo Toharia (male) holds a Ph.D. in Informatics from the Universidad Politécnica de Madrid(UPM) in the
fields of Content-based Retrieval and High Performance Computing. At the moment he has a postdoctoral
research position at the Universidad Rey Juan Carlos in Madrid. He has been teaching assistant for nine years
including postgraduate teaching in the field of Virtual Reality. For ten years he has carried out research work
inside the Virtual Reality and Modelling Group (GMRV). During his research experience he has taken part in
more than fifteen projects with both public and private funds. Also he has published more the twenty five peerreviewed publications and has an international patent which is being commercially exploited.
Engineer Francisco González de Quevedo (male) holds a Degree in Industrial Engineering from the Universidad Politécnica de Madrid and a Master in Quality Management from the Universidad Nacional de Educación
a Distancia. His professional career has been developed mostly in IBM (Madrid), IBM Eurocoordination (Paris)
and Banco Bilbao Vizcaya Argentaria (in the technology department). He has extensive experience in project
and program management, both in Spain and abroad. During the last 25 years he has carried out projects in
software development, software measurement, quality control and implementation of disaster recovery plans.
Currently, he is a project manager for the Human Brain Project and Regional Anaesthesia Simulator and Assistant (RASimAS).
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P71
UNIPV, Universita degli Studi di Pavia (Italy)
Laboratory Profile
Brain Connectivity Center. The Laboratory of Neurophysiology, led by Egidio D’Angelo, investigates plasticity and computation and generates advanced computational models of the cerebellar network. The group is
specialised in single-neuron and neural circuit physiology, single-neuron and neural circuit computation, electrophysiology and imaging, cerebellum and sensory-motor control. The laboratory belongs to and directs the
Brain Connectivity Center (BCC), a joint center of the University of Pavia and the IRCCS Neurological Institute
C. Mondino, which installs and operates facilities for fMRI, TMS, BCI, EEG studies. The laboratory coordinates the
Ph.D. in Biomedical Sciences, two EU projects (REALNET and CEREBNET) on basic cerebellar physiology and
computation and three projects on cerebro-cerebellar function and pathology in humans, for the Italian Ministry
of Health.
Key Personnel
Prof. Egidio D’Angelo (male) - WP5.4 Leader - has a degree in medicine from the IRCCS C. Mondino. He has
been a Fellow of the European Science Foundation, and was awarded the SIF prize for young physiologists by
the Società Italiana di Fisiologia. He has been a visiting professor at the Universities of Heidelberg and Jerusalem, and an associate professor at the University of Parma. A full professor of physiology at the University of
Pavia, where he teaches neuroscience, neurophysiopathology, and neuronal modelling, he also serves as director
of its Ph.D. programme in physiology and neuroscience. He directs the Brain Connectivity Center for neuroscience research, IRCCS C. Mondino, the European Projects CEREBNET (ITN), and REALNET (ICT). An associate
editor of the Journal of Physiology and of Functional Neurology, he is a member of the directors’ committee of
the Italian Society for Neuroscience.
Dr. Francesca Prestori (female) has degree in Biology and a PhD in Physiological Sciences. She is researcher at
the University of Pavia where she teaches Human Anatomy for the degree course in Pharmacy. The main scientific interest is in neuron biophysics and cellular and systems neurophysiology of the cerebellum concerning
neurotransmission and long-term synaptic plasticity, neuronal excitability and signal coding, with regard to cell
neuropathology. The techniques used for her studies are patch-clamp and imaging in brain slices and molecular
biology. She is a review editor of Frontiers in Cellular Neuroscience and member of Society of Neuroscience
(SfN).
Prof. Giorgio Sandrini (male) is Full Professor of Neurology and Chairman of the Department of Neurorehabilitation at the Institute of Neurology, “C. Mondino” Foundation, University of Pavia, in Pavia, Italy. He is Director
of Postgraduate School in Neurophysiopathology and the University Department of Neurological Sciences. He
is President of the Scientific Committee of the Research Consortium on Adaptive Disorders and Headache. He
is President of the Italian Society of Neurorehabilitation and Vice-president of the European Federation of the
Neurorehabilitation Societies. He is Chairman of the International Headache Society Italian Linguistic Special
Interest Group and Chairman of the European Federation of Neurological Societies Task Force on Neurophysiological Tests and Neuroimaging Procedures in Non-acute Headache. He is active member of several societies
and of the editorial Board in various scientific journals. He was Chief of Pavia Unit I of University Centre for
Adaptive Disorders and Headache (UCADH) and Executive Director of UCADH. His main fields of interest are:
Neurorehabilitation, pathogenetic mechanisms, classification and treatment of Headache and Neuropathic Pain;
neurophysiology of pain and autonomic system; movement disorders. Scientific Activity: he has published more
than 200 indexed papers. He has edited or co-edited several scientific books and Congress Proceedings. He has
organised numerous National and International Congresses.
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P72
UBERN, Universität Bern (Switzerland)
Laboratory Profile
Computational Neuroscience Lab, Department of Physiology (Senn Lab). The Senn Lab at the University of
Bern uses mathematical models of synapses, neurons and networks to explain aspects of perception and behavior. It particularly focuses on models of cortical pyramidal neurons and microcircuits that have been investigated
experimentally in vivo and in vitro. Other research at the lab focuses on the neuronal substrate for learning
and memory and the way the brain learns action sequences from an on-going stream of sensory inputs and a
delayed feedback signal. The lab has developed models of sensory processing and its interaction with cortical
top-down signals which can explain experimental recordings from the visual cortex, obtained during perceptual or classification tasks. These models highlight key mechanisms by which synapses and neurons enable our
brains to deal with learning and memory.
Key Personnel
Prof. Walter Senn (male) holds a Ph.D. in differential geometry and calculus of variation from the University of
Bern. After post-doctoral studies in Neural Computation at Hebrew University, Jerusalem, in the lab of Idan Segev,
and research at the National Institutes of Health and the Center for Neural Sciences (USA) with John Rinzel, he
joined the Medical Faculty at the University of Bern, where he is a full professor at the Department of Physiology
and co-Editor-in-Chief of Biological Cybernetics. His interests include the neuronal explanations of learning and
behavior using mathematical models of neurons and synapses. His current focus is on reward-based learning,
decision making and spatial map formation using spike-based models of neurons and synaptic plasticity.
P73
UNIBI, Universität Bielefeld (Germany)
Laboratory Profile
Cluster of Excellence Cognitive Interaction Technology (CITEC), Cognitronics and Sensor Systems (CSS).
The research group “Cognitronics and Sensor Systems”, (CSS), directed by Professor Ulrich Rückert and Dr.
Mario Porrmann, is part of the Cluster of Excellence Cognitive Interaction Technology (CITEC) at Bielefeld
University. Our common research goal is the systematic design and the demand-oriented implementation of
innovative microelectronic circuits and systems. In this field, we are developing microelectronic components
and systems in digital and analogue circuit technology with an emphasis on massively parallel and dynamically
reconfigurable system architectures. Particular attention is paid to the optimisation of the resource-efficiency
and robustness of respective implementations. The group comprises 28 Ph.D. students, funded by EU, DFG,
BMBF, ESA, and industry.
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P73 UNIBI, Universität Bielefeld (Germany)
Key Personnel
Prof. Ulrich Rückert (male) received the diploma degree (MSc), with honours in computer science, and a Dr.-Ing.
degree (PhD), with honours in electrical engineering, both from the University of Dortmund, Germany, in 1984
and 1989, respectively. He joined the Department of Electronic Components, University of Dortmund, in 1985,
where he developed the first VLSI implementations of artificial neural networks in Europe. In February 1990,
he accepted a position as Senior Researcher at the Department of Electronic Components, University of Dortmund. From 1993 to 1995, he was Associate Professor of microelectronics and CAD (computer aided design) at
the Research Centre for Information and Communication Technology of the Technical University of HamburgHarburg. From 1995 until 2009 he was Full Professor of Electrical Engineering at the University of Paderborn.
As a member of the Heinz Nixdorf Institute, he held the chair in “System and Circuit Technology”. Since 2009,
he is Full Professor at the Cognitive Interaction Technology Centre of Excellence at Bielefeld University heading
the research group Cognitronics and Sensor Systems. The group is working on innovative circuit design and
development of microelectronic systems for massively parallel and resource- efficient information processing.
Their main research interests are bio-inspired architectures for nanotechnologies, neural information processing, reconfigurable computing architectures, and cognitive robotics. Rückert was founding organizer of the
International Workshop on Microelectronics for Neural Networks: MicroNeuro, (Dortmund 1990, München 1991,
Edinburgh 1992, Granada 1995, Lausanne 1996, Dresden 1997). He is chairman of the national Special Interest
Group “Microelectronics for neural networks” of the ITG (German Information Technology Society) in Germany.
He has authored or co-authored more than 250 journal and conference publications and holds three patents.
Dr. Mario Porrmann (male) is senior post-doctoral researcher (Akademischer Direktor) in the research group
Cognitronics and Sensor Systems, Center of Excellence Cognitive Interaction Technology, Bielefeld University.
He graduated as “Diplom-Ingenieur” in Electrical Engineering at the University of Dortmund, Germany, in 1994.
In 2001 he received a PhD in Electrical Engineering from the University of Paderborn, Germany for his work on
performance evaluation of embedded neurocomputers. From 2001 to 2009 he was post-doctoral researcher
and from 2010 to March 2012 Acting Professor of the research group System and Circuit Technology at the
Heinz Nixdorf Institute, University of Paderborn. Mario Porrmann`s main scientific interests are in on-chip multiprocessor systems, dynamically reconfigurable computing and resource-efficient architectures for network
components. Mario Porrmann has published more than 150 peer-reviewed papers in scientific journals as well
as for international conferences.
145
P74 UKAACHEN, Universitätsklinikum Aachen (Germany)
Laboratory Profile
The Department of Psychiatry, Psychotherapy and Psychosomatics is one of the leading psychiatric research
institutions in Germany. It is part of the School of Medicine of RWTH Aachen University and provides healthcare
within the framework of the University Hospital Aachen. The department is headed by Professor Frank Schneider and currently comprises eleven professorships (comprising one senior professor and three joint professorships with Juelich) dedicated to characterizing the normal and in mental disorders deviant brain on subcellular,
cellular, structural and functional level. The research employs predominantly imaging methods (EEG, MEG, PET,
MRI) with a special focus on the combination of existing methods, like EEG and fMRI and the improvement of
data analyses. The department cooperates closely with Forschungszentrum Jülich within the framework of the
Juelich Aachen Research Alliance (JARA) and operates an International Research Training Group (IRTG 1328)
with Jülich and the University of Pennsylvania.
Key Personnel
Prof. Frank Schneider (male) performed studies in Psychology and Medicine and holds both a MD and PhD
degree. He is a specialist in Psychiatry and Psychotherapy and Psychological Psychotherapist. Following positions in Tübingen, Philadelphia and Düsseldorf he is head of the Department of Psychiatry, Psychotherapy and
Psychosomatics, University Hospital Aachen, since 2003. He is currently Vice Dean at the School of Medicine,
RWTH Aachen University and also Past President of the German Society for Psychiatry and Psychotherapy. Furthermore, he is managing director of the Jülich Aachen Research Alliance (JARA), director of the section “Translational Brain Research” within the Jülich-Aachen Research Alliance (JARA) and speaker of the International
Research Training Group “Schizophrenia and Autism” (funded by DFG). In 2013 he was listed as a Top-Physician
in Germany in the section „Psychiatry“ by the „focus” magazine.
P75
UKE, Universitätsklinikum Hamburg-Eppendorf (Germany)
Laboratory Profile
Work in the Department of Neurophysiology and Pathophysiology (led by Prof. Andreas K. Engel) focuses on
cognitive and sensorimotor functions, which are studied in humans and animal models using neurophysiological
and neuroimaging techniques. The group is addressing the neural mechanisms underlying perceptual integration,
sensorimotor integration, multisensory interactions, attentional control, response selection, perceptual decision
making, agency, social cognition and awareness. Further topics of interest include the role of synchrony in sensorimotor transformations (which convert signals from various sensory modalities into motor commands), establishing links between synchrony and perceptual states, cross-species comparison of synchronization phenomena,
and the study of synchronization mechanisms (carried out via recordings in transgenic mice). To understand the
mechanisms of cross-modal binding, the group has developed computational models of networks of coupled
oscillators. Research of the group also focuses on the pathophysiology of neuropsychiatric disorders such as
multiple sclerosis, Parkinson’s disease, schizophrenia and autism. Another key aim of the group is interdisciplinary
work linking neurophysiology, neuroimaging and technical applications (neuroprosthetics, brain-computer-interfaces, neurorobotics). Such links have successfully been established by the group as part of several EU-funded ICT
projects (Amouse, POP, eSMCs) and networks (Neuro-IT, NeuroVersIT, euCognition, euCogII, euCogIII).
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P75 UKE, Universitätsklinikum Hamburg-Eppendorf (Germany)
Key Personnel
Prof. Andreas K. Engel (male) - is full professor of physiology and director of the Dept. of Neurophysiology and
Pathophysiology. The focus of his research is the dynamics of neuronal populations and, specifically, temporal
correlations between different neurons leading to the formation of coherent cell assemblies. He has extensive
expertise in in-vivo multielectrode recording from humans, carnivores and rodents, and in EEG and MEG recordings in humans. He has authored over 200 publications in internationally renowned journals (including e.g. Nature,
Science, Nat Neurosci, Neuron, Curr Biol, Nat Rev Neurosci, Trends Cogn Sci), books and proceedings (for details,
see http://www.40hz.net). Current H-index: 54; cumulative impact of peer-reviewed publications >1.100; number of
citations >19.900 (http://scholar.google.de/citations?user=WreTMD0AAAAJ&hl=de&oi=ao). He has been awarded
more than 14 Mio € in research grants. He has acted as coordinator of several EU funded grants and is the coordinator of the Collaborative Research Centre SFB 936 funded by the DFG. In 2011, he received an ERC Advanced
Investigator Grant.
Dr. Alexander Maye (male) - leads the research group “Computational Modelling and BCI” at the Dept. of Neurophysiology. A computer scientist by education, the focus of his work is on the functional role of oscillatory neuronal activity in perception, cognition, and consciousness. He has experience in bio-inspired robotics, computer
vision and image processing. Currently he works on probabilistic computational models of sensorimotor contingencies for autonomous robot control. He has lead several projects with industry partners.
Dr. Dr. Guido Nolte (male) - is a theoretical physicist and head of the MEG group at the Dept. of Neurophysiology. He has worked on essentially all aspects of data analysis methods for MEG and EEG data including forward
and inverse calculations, nonlinear time series analysis and connectivity analysis. He has authored over 100 publications in internationally renowned journals, books and proceedings. Current H-index: 29; number of citations
>3,300 (http://scholar.google.de/citations?user=iDXuEAoAAAAJ&hl=de).
P76 UZH, Universität Zürich (Switzerland)
Laboratory Profile
The UZH Functional Imaging and Neurovascular Coupling group, headed by Bruno Weber, investigates the
mechanisms governing the regulation of blood flow and metabolism in the brain. Combining ex vivo and in vivo
experiments in the rodent somatosensory cortex, the group is working to close the gap between structural and
functional aspects of hemodynamic response. Other studies by the group use immunohistochemical methods and
synchrotron-based X-ray computed tomography to study cerebral microvasculature in rat and monkey tissue and
state-of-the-art optical methods to study the 2D and 3D dynamics of blood flow. The experimental data collected
in this work serves as a basis for numerical models, simulating the topology of cerebral blood flow.
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P76 UZH, Universität Zürich (Switzerland)
Key Personnel
Prof. Bruno Weber (male): Professor of Multimodal Experimental Imaging at the UZH Medical Faculty. Bruno
Weber has a Ph.D. from UZH, a habilitation from the UZH Medical Faculty, and has been a post-doctoral fellow
both at UZH and at the Max Planck Institute in Tübingen. His recent work involves the acquisition of highresolution angiography data from rodent and monkey cerebral cortex, using synchrotron radiation-based
x-ray tomographic microscopy (SRXTM). The data is post-processed to improve signal-to-noise ratio, correct
for sample deformation, and remove artificial vascular interrupts. The cerebral vasculature is then represented
in graph-format, making it possible to study its topological properties, hierarchical organisation, branching angles, segment length and diameter. Probability density functions for these parameters can be studied
across several cortical layers, potentially providing insights into the principles governing the development of
the cerebral microvascular network.
Dr. Matthias Schneider (male) received his PhD at the ETH Zurich at the Computer Vision Laboratory. He is
an expert in image segmentation with a special focus on vascular reconstruction. He works for the HBP since
May 2014.
Prof. Marco Stampanoni (male) for X-ray Imaging at ETH Zurich is a co-PI for the HBP and is instrumental for
the data collection of the mouse brain vascular system. He leads the tomography beam line at the synchrotron
(Swiss Light Source, Paul Scherrer Institute, Villigen, Switzerland).
P77
UB, Universitat de Barcelona (Spain)
Laboratory Profile
Experimental Virtual Environments for Neuroscience and Technology (EVENT Lab). This lab researches virtual
environments and computer graphics, with applications mainly in neuroscience and technology. It focuses on the
exploitation of virtual reality and robotics in investigating how the brain represents the body. Co-led by Mel Slater
and Maria V. Sanchez-Vires the EVENT Lab has a staff of approximately 25 full-time researchers and technicians. It
is funded mainly through European projects, including an ERC Senior research project granted to the lab director,
ICREA Professor Mel Slater. The lab has two advanced head-mounted display systems together with head-trackers
and full body motion capture, and physiological recording devices including EEG. It also has a state-of-the-art high
definition four-sided Cave system, and an emotionally expressive life-sized robot. The major research of the lab
in recent years has been the exploitation of body ownership in investigations of body representation and body
plasticity. This embodies people in virtual bodies or robotic bodies controlled by brain-computer interfaces.
Key Personnel
Prof. Mel Slater (male) - WP 9.6 Leader - has an ERC award for his TRAVERSE project (www.traversecr.org), leads
the FET consortium Virtual Embodiment and Robotic Re-Embodiment (www.vereproject.org) and is the scientific
manager of BEAMING (www.beaming-eu.org) - all projects focussing on concepts of body ownership and agency.
Since 2006, he has been a research professor at ICREA-University of Barcelona and part-time professor of virtual
environments at University College London.
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P78 UPF, Universitat Pompeu Fabra (Spain)
Laboratory Profile
The Computational and Theoretical Neuroscience Group at UPF, led by Prof Gustavo Deco, ICREA research
professor, investigates neuronal and cortical mechanisms of perception and cognition. This group developed a
theoretical framework to deepen our understanding of a great variety of mechanisms and computations underlying higher brain functions. The theoretical framework was obtained by developing explicit mathematical neurodynamic models of brain function at the level of neuronal spiking and synaptic activity. The analysis of networks
of integrate-and-fire neurons (including non-linearities) enables the study of many aspects of brain function from
the spiking activity of single neurons to the effects of pharmacological agents on synaptic currents. The group has
extensive experience in modelling cognitive functions such as attention and decision making with biologically realistic models. Indeed, they have highly cited publications in related theoretical, numerical and experimental work.
The group was also involved in numerous European projects of which: BrainNRG, Brain Network Recovery Group
(project number 220020255) funded by James S. McDonnell Foundation and in BRAINSYNC, Large scale interactions in brain networks and their breakdown in brain diseases (Project Number: 200728). Currently, the group is
participating in the ICT FP7 project BrainScaleS: Brain-Inspired Multiscale Computation in Neuromorphic Hybrid
Systems (Project Number: 269921) and CORONET: Choreographing Neural Networks: Coupling Activity Dynamics
Across Biomimetic Brain Interfaces with Neuromorphic VLSI, (Project Number: 269459). Gustavo Deco has been
also granted an ERC Advanced grant: The Dynamical and Structural Basis of Human Mind Complexity: Segregation and Integration of Information and Processing in the Brain (DYSTRUCTURE Project Number: 295129).
Key Personnel
Prof. Gustavo Deco (male) - WP3.4 Leader - is Research Professor at ICREA (Institució Catalana de Recerca i
Estudis Avançats) and Full Professor (Catedrático) at Pompeu Fabra University (Barcelona) where he is head of
the Computational and Theoretical Neuroscience Group and Director of the Center of Brain and Cognition. He
received his Ph.D. degree in Physics in 1987 (National University of Rosario, Argentina). In 1997, he obtained his
habilitation (maximal academical degree in Germany) in Computer Science (Dr. rer. nat. habil.) at the Technical
University of Munich for his thesis on Neural Learning. In 2001, he received his PhD in Psychology (Dr. phil.) for his
thesis on Visual Attention at the Ludwig-Maximilian-University of Munich. He headed Computational Neuroscience
Group at the Siemens Corporate Research Center in Munich from 1990 to 2003. He has published 4 books, more
than 170 papers in International Journals, 260 papers in International Conferences and 30 book chapters. He has
also 52 patents in Europe, USA, Canada and Japan. In 2012, he was awarded with the Advanced ERC grant.
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P79
AMU, Universite d’Aix Marseille (France)
Laboratory Profile
Institut des Neurosciences de Système (INS). The INS Institute is located on the medical campus of Aix-Marseille
University, the largest University in France. INS houses a high-performance computing cluster dedicated to neural
modelling, an MEG platform, a coupled EEG-TMS platform and an epileptic patient unit with stereotactic EEG (sEEG)
at the hospital La Timone (APHM). INS is directed by Patrick Chauvel and Viktor Jirsa (PI) and comprises 27 permanent faculty members and 70 institute members in total. INS combines expertise from computational, cognitive and
clinical neuroscience, as well as biomedical imaging and signal analysis. In 2011 INS has received the highest grade of
excellence (A+) during its four-year evaluation by the National Scientific Evaluation Agency (AERES).
Key Personnel
Dr. Viktor Jirsa (male) is Director of Research (CNRS) and Co-Director of the Institut de Neurosciences des
Systèmes (INS). He heads the Theoretical Neurosciences Laboratory (approx. 20 members), which has received
the highest grade of excellence (A+) during its four-year evaluation by the National Scientific Evaluation Agency
(AERES). 1999 to 2005 he was faculty member at the Center for Complex Systems and Brain Sciences, then he
joined the CNRS in France. Since the late 90s Dr. Jirsa has made pioneering contributions to the understanding of how network structure constrains the emergence of functional dynamics using methods from nonlinear
dynamic system theory and computational neuroscience. Together with Randy McIntosh, he is the project leader
of the neuroinformatics platform The Virtual Brain (www.thevirtualbrain.org) implicating 11 laboratories worldwide. Dr. Jirsa has been awarded several international and national awards for his research including the Prime of
Scientific Excellence (CNRS, 2011), the Early Career Distinguished Scholar Award by NASPSPA in 2004 and the
Francois Erbsmann Prize in 2001. He is invited regularly to major international conferences and has given more
than 100 invited lectures, including various keynote addresses and plenary lectures. Dr. Jirsa is Editor-in-chief
of the European Physical Journal (EPJ) Nonlinear Biomedical Physics, serves on various Editorial and Scientific
Advisory Boards, supervised 16 doctoral theses and has published more than 100 scientific articles and book
chapters (H-index 26, more than 2100 citations), as well as co-edited several books including the Handbook of
Brain Connectivity.
Dr. Andreas Spiegler (male) is a postdoctoral fellow at INS. He received his doctoral degree in Electrical Engineering in 2012 and is an expert in modelling of large-scale brain network dynamics.
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P80
UBO, Université de Bordeaux (France)
Laboratory Profile
Epidemiology and Neuropsychology of Brain Aging. This group’s main research topic is the epidemiology of
Alzheimer’s Disease and related disorders (ADRD). Led by Jean-François Dartigues, it conducts studies on population-based cohorts of elderly people living in the Bordeaux Area, with follow-up data collection lasting up to 25
years. The group also works in the organisation of non-drug trials for ADRD.
Key Personnel
Prof. Jean-Marc Orgogozo, (male) qualified as a neurologist in 1977 after training at La Salpêtrière Hospital in
Paris. He is a Professor of Neurology at the University of Bordeaux, Head of the Clinical Neurosciences Department at the University Hospital and Director of the Federation of the Bordeaux Neuroscience Institutes. He was
a member of the INSERM group on “Epidemiology of the Aging Brain and Dementia” under Jean-François Dartigues from its creation in 1993, and is now at the CRI-897. Orgogozo is past-Chairman of the European Stroke
Council (ESC) and of the European Union Affairs Committee of the European Federation of Neurological Societies
(EFNS), officer of the European Stroke Initiative and of the Dementia and the Cerebrovascular Research Groups
of the World Federation of Neurology, past member of the Membership Committee of the American Academy of
Neurology. He served for 20 years as an Expert in Neurology to the World Health Organization (WHO), for which
he was responsible for the Neurological Adaptation of the WHO International Classification of Diseases-10. He is
currently Chair of the International Working Group on Harmonization for Dementia Trials. He has published some
300 articles, co-authored three books, and serves or has served on the Editorial Boards of Stroke, Neuroepidemiology, Dementia, European Journal of Neurology, Evidence Based Medical Journal and Cerebrovascular Diseases.
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P81
UA, Universiteit Antwerpen (Belgium)
Laboratory Profile
The Theoretical Neurobiology unit is a research group affiliated with the University of Antwerp - UA (Belgium).
We study cortical and cerebellar function using a combination of technological, experimental and theoretical
approaches. These range from substrate arrays of microelectrodes to patch-clamp, from in vitro cellular electrophysiology to in vivo recordings, from the micro- and nanotechnologies for neural engineering applications to
the computer simulation of realistic models of neurons and neuronal networks. We also develop neural simulation
software. The images on our pages show simulated calcium images of a modelled cerebellar Purkinje cell.
Key Personnel
Prof. Michele Giugliano (male) is a principal investigator and a tenured Associate Professor (ZAP-BOF research
mandate, Hoofddocent) in the Department of Biomedical Sciences and at the University of Antwerp. He retains
a visiting academic appointment at the Department of Computer Science of the University of Sheffield (UK), and
an external collaboration appointment at the Brain Mind Institute of the Swiss Federal Institute of Technology of
Lausanne (Switzerland). Giugliano was born in 1974 in Italy, where he was trained as an Electronic Engineer specialising in Biomedical Engineering. He received a five-year laurea-degree summa cum laude from the University
in 1997. After developing a strong interest in biophysics and computational neuroscience, he earned a PhD in
Bioengineering in 2001 from the Politecnico di Milano. The late Prof. Massimo Grattarola, who pioneered the fields
of bioelectronics and neuroengineering, oversaw Giugliano’s PhD studies. Giugliano was awarded a long-term
postdoctoral fellowship from the Human Frontier Science Program Organization to pursue experimental research
on the nervous system, with emphasis on novel non-conventional experimental paradigms and techniques at the
cellular and microcircuit levels. He then moved to the Faculty of Medicine of the University of Bern (Switzerland)
as a member of the Department of Physiology, working on the team of Prof. Hans-Rudolf Luescher and collaborating with Prof. Stefano Fusi. Since 2008, Giugliano has been faculty member in the Department of Biomedical
Sciences at the University of Antwerp, and he is also the Director of the Laboratory of Theoretical Neurobiology
and Neuroengineering.
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P82 UiO, Universitetet i Oslo (Norway)
Laboratory Profile
Institute of Basic Medical Sciences, Neural Systems Laboratory. The Neural Systems Laboratory has three divisions: Experimental Neuroanatomy and Brain MRI Analysis; Preclinical PET/CT; and Neuroinformatics. Its main
areas of research include digital rodent brain atlasing, mapping of brain connectivity, the characterisation of
detailed architecture and organising principles in major brain pathways, structural and functional phenotyping
of disease models using small animal imaging and brain atlasing technologies, development of neuroinformatics
tools for viewing and 3D analysis of microscopic level data on neuronal architecture, and sharing of data and tools
through novel database applications. The laboratory hosts the Norwegian Node of the International Neuroinformatics Coordinating Facility.
Key Personnel
Prof. Jan Bjaalie (male) - WP4.2 Leader - is Head of the Institute of Basic Medical Sciences of the University of
Oslo and Chair of the Governing Board of the International Neuroinformatics Coordinating Facility. His research
group has been a partner in the Centre for Molecular Biology and Neuroscience, a Norwegian Centre of Excellence (2003-2012), and is currently a partner in the Scientific Excellence Research Thematic Area: Healthy Brain
Aging, at the University of Oslo. His laboratory has discovered fundamental principles of sensory map transformations in large projection systems of the brain and has performed novel regional and whole brain atlasing and
histological mapping. It uses anatomical and computerised methods for visualisation and quantitative analyses,
electrophysiology, and in vivo imaging, for studying systems-level organisation in the brain, and has developed
a variety of software, including tools for 3-D reconstruction and advanced visualisation of neuronal organisation as well as database applications for neuroanatomical image data made available via the Rodent Brain
Workbench. Jan Bjaalie has been a partner and coordinator of several EU-funded projects and has collaborated
extensively with leading laboratories worldwide. He serves on the board of several journals, was a member of
the Neuroinformatics Committee of the Society for Neuroscience, and served as founding Executive Director of
the International Neuroinformatics Coordinating Facility.
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P83
UCL, University College London (United Kingdom)
Laboratory Profile
The Alex M. Thomson Synaptic Circruit Group uses a variety of techniques. Cellular/molecular techniques allow
the group to study the interactions between the synaptic cleft-spanning proteins that underpin synapse-formation and specificity; multi-photon imaging combined with electrophysiology and uncaging is used to study
the contribution of voltage-gated ion channels to the shaping and integration of synaptic inputs in different
dendritic compartments; paired intracellular recordings combined with histological and immuno-cytochemical
processing and pharmacology form the basis for studies of the properties of cortical circuits and the synaptic
connections that form them.
Key Personnel
Prof. Alex Thomson (female) - Governance Oversight Committee Member - Following a BSc in Physiology at
Bedford College, University of London (1975), Alex moved to the Physiology Department in Bristol to study for
her PhD with Dr Tony Ridge. After two postdoctoral years in the Anatomy Department in Bristol, she moved to
the University Laboratory of Physiology in Oxford in 1980 with a Beit Memorial Fellowship, joining Somerville
College as a Fulford Junior Research Fellow in 1982. In 1985 Alex moved to the Physiology Department, University College Cardiff, as a Wellcome Lecturer. Here the paired intracellular recordings from synaptically connected
cortical neurones that have become the hallmark of the lab began. She moved to the Department of Physiology, Royal Free Hospital Medical School, in 1988, again as a Wellcome Lecturer, becoming Professor of Neurophysiology at the newly combined Royal Free and University College Medical School in 1998. In 2002, Professor
Thomson moved to The School of Pharmacy where she was Head of the Pharmacology Department until 2007
and Wellcome Professor of Pharmacology until 2014. She retired in 2014, taking emeritus status.
Dr Agota Biro (female) (postdoctoral research fellow) HBP-paid from June 1st 2014. Contributions made by
voltage-gated ion channels to shaping synaptic inputs in layer 3 pyramidal neurones.
Ms Joanne Falck (female) (histology technician) HBP-paid from June 1st 2014. Histological processing and
analysis, reconstructions, cell property archiving, neocortex and hippocampus.
Dr Sigrun Lange (female) (postdoctoral research fellow) HBP-paid from Oct 1st 2013. Competitive call management until February 2014, then histological processing and analysis, reconstructions, cell property archiving,
neocortex and hippocampus.
Dr Audrey Mercer (female) (Lecturer, HEFCE-funded and independent principal investigator) Electrophysiology, imaging, histological processing and analysis, 3-D neurone-reconstruction, cell property archiving, neocortex and hippocampus. Essential contributor to proposed hippocampal microcircuit model construction.
154
P83 UCL, University College London (United Kingdom)
Laboratory Profile
The Wellcome Trust Centre for Neuroimaging at UCL (incorporating the Leopold Muller Functional Imaging
Laboratory and the Wellcome Department of Imaging Neuroscience) is an interdisciplinary centre for neuroimaging excellence. It brings together clinicians and scientists who study higher cognitive function using
neuroimaging techniques. Its goal is to understand how thought and perception arise from brain activity, and
how such processes break down in neurological and psychiatric disease. Its research groups study all aspects
of higher cognitive function including vision, memory, language and reasoning, emotion, decision making and
motor control. Home to SPM, the world’s most popular tool for analysing neuroimaging data, the Centre seeks to
answer fundamental questions about how the brain works in order to improve human and animal health. It hosts
and trains over 100 clinicians, scientists and support staff, and interacts with over 200 collaborators both at UCL
and throughout the world. As well as conducting scientific research, it offers a wide range of educational and
training opportunities to support the development of imaging neuroscience both nationally and internationally,
and have an active public engagement agenda.
Key Personnel
Prof. John Ashburner (male) - SP2 Co-leader / Research Board Member - is a professor of imaging science at
the Wellcome Trust Centre for Neuroimaging. He has a Ph.D. in Neuroscience from University College London
(UK), where he held positions as a lecturer and a senior lecturer before taking his current job. Prof. Ashburner
is co-author (contributed about 45,000 lines of code) of SPM – a widely-used software package for modelling
functional and structural neuroimaging data. He has over 14,000 citations and an H-index of 60. His research is
primarily in imaging science, focusing on developing models for image registration, segmentation, computational
anatomy and pattern recognition.
Laboratory Profile
The Space and Memory lab in the UCL Institute of Cognitive Neuroscience (ICN), headed by Neil Burgess,
has strong expertise in computational neuroscience, functional neuroimaging, single-unit electrophysiology and
neuropsychology. The main focus of the lab is understanding the neural mechanisms of memory, and particularly spatial area, an area in which it is possible to compare results from humans and rodents.
Key Personnel
Prof. Neil Burgess (male) is professor of cognitive and computational neuroscience, a Wellcome Trust Principal
Research Fellow, and Deputy Director of the UCL Institute of Cognitive Neuroscience. His laboratory investigates
the neural mechanisms of memory using a combination of methods including computational modelling, human
neuropsychology and functional neuroimaging, and single unit recordings in freely moving rodents. His main goal
is to understand how the actions of networks of neurons in our brains allow us to remember events and the spatial
locations where they occurred. After studying math and physics at UCL he did a Ph.D. in theoretical physics in
Manchester and a research fellowship in Rome, before returning to UCL funded by a Royal Society University
Research Fellowship and the Medical Research Council (UK).
Dr Fabian Chersi (male) (postdoctoral research fellow) HBP-paid from Dec 1st 2013. Computational modelling of
the neural mechanisms of spatial navigation, with a focus on the hippocampal formation and striatum.
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P84
UU, Uppsala Universitet (Sweden)
Laboratory Profile
Centre for Research Ethics and Bioethics (CRB). CRB studies research ethics, bioethics, neuroethics and
medical law and has recently received a top-quality rating from Uppsala University as part of an overall evaluation of the institution’s research. Ethics is included in the curriculum for Uppsala University’s programmes in
nursing and medicine. In this setting, CRB offers a web-based course in neuroethics as well as an advanced
level course on ethics and public health. It also offers research ethics courses for postgraduate students at all
faculties. CRB participates in several bilateral and multilateral national and international research collaborations.
Key Personnel
Prof. Kathinka Evers, (female) - SP 10 Leader / WP 10.2 Leader / Research Board Member / Governance
Oversight Committee Member - is a senior researcher and professor of philosophy at the Centre for Research
Ethics and Bioethics (CRB) at Uppsala University. She has been an invited professor (Condorcet Chair) at the
Ecole Normale Supérieure in Paris, at the Collège de France, and at the Centro de Investigaciones Filosoficas,
in Buenos Aires (Argentina). She is honorary professor at Universidad Central, Santiago, Chile. Her research
focuses on philosophy of mind, neurophilosophy, bioethics and neuroethics. She directs Uppsala University’s
teaching and research on neuroethics and established its first courses in the subject. She is also interested in
the social responsibility of science, and served as the Executive Director for the Standing Committee for Ethics
and Responsibility in Science of the International Council for Science. She has been an expert in scientific review
panels at the ERC, covering the topic “The Human Mind and Its Complexity”. Kathinka Evers will co-direct the
Ethics and Society Program of the HBP.
Dr. Arleen Salles, (female) is the director of the Neuroethics Program at the Center of Philosophical Research
(CIF) in Buenos Aires, Argentina, and associated senior researcher at the Centre for Research Ethics & Bioethics
(CRB) at Uppsala University, Sweden. She studied philosophy in Universidad de Buenos Aires (Argentina) and
has a Doctorate and Master degree in Philosophy from the State University of New York at Buffalo. Salles taught
philosophy and ethics at Montclair State University, John Jay College of Criminal Justice (CUNY), and St John’s
University in USA and is currently teaching at Universidad Torcuato Di Tella and UADE in Argentina. Her area of
specialty is moral philosophy and moral psychology. Her current interest is on the intersection of neuroscience
and philosophy, specifically, the neuroscience of moral decision-making and the impact of neuroscientific findings on key ethical and metaphysical notions.
Dr. Michele Farisco, (male) holds a degree in Philosophy from University of Naples “L’Orientale” in 2003, a PhD
in “Ethics and Anthropology. History and Foundation” from University of Lecce in 2008 and a Master degree in
Biolaw from the University of Rome “Lumsa” in 2009. He spent time on an exchange grant from the European
Neuroscience and Society Network within the European Science Foundation joining the Coma Science Group of
the University of Liège (Belgium). He is the head of the “Science and society” research unit of Biogem Genetic
Research Centre in Ariano Irpino (Italy). In his HBP-related PhD project, supervised by K. Evers, M. Farisco will
study philosophical, ethical and legal issues emerging from neuroscientific investigation of Disorders of Consciousness and related technological applications.
Dr. Karl Sallin (male) is a paediatric resident at Astrid Lindgren Children’s Hospital, Karolinska University Hospital. He is on the hospital’s Ethics committee and he is also a member of the Swedish Society of Medicine’s Ethics
committee. Karl Sallin holds a degree in Philosophy from the University of Cambridge where his main foci were
on the philosophy of mind, language and mathematics. In his clinical work Karl Sallin has been involved with children suffering from Resignation Syndrome (RS). RS is a severe condition in asylum-seeking refugee adolescents
most notably resulting in a seemingly unconscious state. Karl Sallin’s HBP-related PhD project, supervised by K.
Evers, analyses what it is like to be unconscious with special regards to Resignation Syndrome.
156
P85 WIS, Weizmann Institute of Science (Israel)
Laboratory Profile
The Weizmann Institute’s Computational Neuroscience Lab, led by Dr Misha Tsodyks, adopts a theoretical
approach to modelling brain functions. It is part of the Neurobiology Department, and in this position collaborates
on the design of new experiments and the analysis of experimental data. The lab’s main activities are in the fields
of learning and memory, space representation in hippocampal formation, visual processing and synaptic transmission in the cortex. It includes one post-doctoral fellow, three PhD students and one research assistant. It is well
equipped with computer power and benefits from the services of the Weizmann Institute Computer Center.
Key Personnel
Prof. Misha Tsodyks (male) has a Ph.D. in theoretical physics from Landau Institute of Theoretical Physics,
Moscow (Russia). He has worked as a researcher in mathematical neuroscience at the Institute of Neurophysiology of the Soviet Union Academy of Science, and then as a senior lecturer at the Hebrew University of Jerusalem, where he researched neural networks theory. He was post-doctoral fellow at the Salk Institute (USA) in
computational neuroscience, after which he returned to Israel to take a faculty position at the Weizmann Institute of Science.
Laboratory Profile
The visual cognition laboratory studies the visual mechanisms and processes used by the brain to understand
the world in terms of objects, agents, and the interactions between them. Key topics include object recognition
and categorization, action recognition, and the use of vision to obtain information about agents, their goals, and
interactions. The main focus is on computational studies and modeling of brain processes that allow the brain to
attain these goals. The computational models are evaluated by their functional performance, and by their ability to
explain and predict empirical data at both the physiological and behavioral levels. A major aspect of the studies is
to include learning mechanisms that allow the models to learn on their own from visual experience.
Key Personnel
Prof. Shimon Ullman (male) obtained his Bs.C. with special distinction in Mathematics, physics, and an additional degree in biology, from the Hebrew University in Jerusalem. He did his Ph.D. at MIT in the Artificial Intelligence Laboratory. He remained on faculty at MIT, becoming an Associate and then Full Professor at the Brain
and Cognitive Department. He subsequently moved to the Weizmann Institute, the department of computer
science where he serves as the Samy and Ruth Professor of computer science. He has made fundamental contributions to the study of motion perception, object recognition and categorization, and the modelling of brain
processes combining bottom-up with top-down processing. He is the 2008 recipient of the Rumelhart award in
human cognition and a member of the Israeli Academy of Science and the Humanities.
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ETHICS & SAFETY
5. ETHICS AND SAFETY
5.1 Meeting National, Legal and Ethical
Requirements in Countries where
Research is Carried Out
5.1.1.5 Ethical Requirements: Spain
Experiments with Animals: For experimental procedures
needed to perform targeted mapping of neural morphologies, molecules types of synapses, cellular composition
of different brain regions, mapping of axonal projections
between modules within brain regions and mapping of projections between these regions we will use mice. Approval
will be requested from the local Animal Welfare Committee
of the institutions involved.
5.1.1 SP1 Targeted Mapping of the Mouse Brain
Many SP1 tasks involve handling or producing animalderived (and on occasion, human-derived) tissues, for
which local ethical approval is required.
5.1.1.6 Ethical Requirements: Switzerland
The members of the SP1 team have worked closely with
the secretariat of the HBP Research Ethics Committee to ensure that the EU is informed of each Partner’s
approval status, and to provide evidence of ethical
approval when received.
Experiments with Animals: For studies that focus on
targeted mapping of the neurovascular-glial-system of
themouse brain, written approval will be requested from
the local veterinary authorities (Local Veterinary and
Switzerland Offices).
We shall continue to work with the secretariat to
monitor work potentially requiring ethical approval,
requests for approval, requests for changes to planned
research and the final result of the approval process.
5.1.1.7 Ethical Requirements: United Kingdom
Experiments with Animals: Under the Animals (Scientific
Procedures) Act 1986, specific programmes of work have to
be approved and licenced by the Secretary of State, Home
Office. Local ethics approval will be also be sought from the
local Animal Welfare Board of the institutions involved.
Listed below are the ethical requirements of countries
where SP1 work is performed, the specific categories of
work that require ethical approval, and the processes
to obtain approval.
Human Biological Material: National Research Ethics Committee approval will be held by those Partners who may
handle material of human origin.
5.1.1.1 Ethical Requirements: China
Experiments with Animals: For the distribution and
reconstruction of neurons belonging to different morphological types, written approval will be requested
from the Animal Welfare Committee of our institution.
5.1.2 SP2 Targeted Mapping of the Human Brain
Listed below are the ethical requirements of the countries
where SP2 work will be performed, the specific tasks that
require ethical approval, and the status of approval process.
5.1.1.2 Ethical Requirements: Germany
5.1.2.1 Ethical Requirements: France
Experiments with Animals: For architectonic studies
on the cellular distribution and connectivity of the
mouse brain, additional ethical approvals under German
Animal Welfare Legislation (LANUV) are not required.
Experiments with adults
– Ethical approvals (May and June 2008) – Comité de
Protection de Persones.I.D.F. VII
5.1.1.3 Ethical Requirements: Hungary
Experiments with Animals: For the distribution and
reconstruction of neurons belonging to different morphological types, written approval will be requested
from the Animal Welfare Committee of the institution.
– Information sheet and informed consent form for a
person taking part in biomedical research (“Formulaire
d’information et consentement éclairé pour une
personne participant à une recherche biomédicale”)
5.1.1.4 Ethical Requirements: Italy
– Biomedical research protocol N° ID RCB 2008-A0024154/1 (“Protocole de Recherche Biomédicale” entitled
“Neuro-Imagerie Cognitive à Haute Résolution Spatiale
et Temporelle et Relation avec la Variabilité Génétique”,
with identification number (RCB) 2008-A00241-54 /1)
For targeted mapping of neural morphologies and the
cellular composition of different brain regions, we will
use fixed mouse brain tissue. For this, we will request
a formal notification from the Italian Ministry of Health.
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Ethics and Safety
tomes Project. For this, we must request approval from
the local ethics committee in a letter that provides a
detailed description of the work planned.
Experiments with babies/children
–C
onfirmation from AFSSAPS (French Agency
for the Safety of Health Product) that it received
our application for clinical trial authorisation for
non-health products (“Accusé de réception et de
recevabilité d’une demande d’autorisation d’essai
clinique ne portant pas sur un produit de santé”)
For post mortem studies, additional ethical approvals are
not necessary. All body donors have provided written
informed consent according to the regulations of the
ethical committees of the universities concerned.
5.1.2.3 Ethical Requirements: Netherlands
–E
thical approval (June 2011) – Comité de Protection
de Persones.I.D.F. VII
For microcircuitry studies on human brain tissue from
neurosurgery and autopsy, we will apply for approval from
the local Medical Ethical Committee of the institution.
– B iomedical research protocol N° ID RCB 2011A00058-33
5.1.2.4 Task Ethical Approval Status
–C
onsent form for parents or tutors of the
child taking part in the study (“Formulaire de
consentement destiné aux parents ou tuteurs de
l’enfant participant à la recherché”)
In France, the researchers responsible started the
application process in December 2013. All documents
relating to adults and children/babies, i.e., information
sheets, consent forms, protocols, insurance certificates,
etc. have been delivered and are on file with the HBP
Ethics Group.
–C
onsent form for parents or guardians of the child
taking part in the study – Optional genetic analysis
(“Formulaire de consentement destiné aux parents
ou tuteurs de l’enfant participant à la recherché –
Analyse génétique optionnelle”)
These documents cover the whole Ramp-Up Phase except
for the insurance certificate, which expires in July 2014.
CEA will apply for a new insurance certificate in May 2014.
– Information sheet about the optional genetic
analysis of saliva
– Information sheet for very young children
(3 to 6 years old) (“Notice d’Information enfant très
jeune (3 à 6 ans)”)
In Germany, the use of in vivo data from the US 1000
Connectomes Project has already been approved by the
local Ethics Committee. The associated documents have
been received and are on file at the HBP Ethics Group.
Post mortem work in human brains is being performed in
accordance with the local ethics committee at UDUS, and
does not need any additional approval.
– Information sheet for children (6 to 11 years old)
(“Notice d’Information enfant (6 à 11 ans)”)
– Information sheet for parents or guardians of the
child taking part in research (“Notice d’information
destinée aux parents ou tuteurs de l’enfant participant
à la recherché”)
In the Netherlands, the study has obtained the necessary
approval from the Medical Ethical Committee of VU University Amsterdam.
5.1.3 SP7 Medical Informatics
5.1.3.1 CHUV - Switzerland
The Medical Informatics Platform will use legacy data that
are routinely collected by the hospitals. In other terms, the
research team will not generate new data for the HBP.
Documents that are valid for experiments on adults and
babies/children
– Insurance certificate (“Attestation d’assurance de la
responsabilité civile professionnelle des personnes
vivées par la loi”)
The data are archived in several CHUV databases. To
access the data, researchers need to make a formal
request to the ‘Comité cantonal d’éthique de la recherche’ (local ethics committee). The request was formally
approved on Nov 20, 2013.
–R
eceipt of declaration of conformity to a standard
methodology (“Récépissé de déclaration de
conformité à une méthodologie de reference”)
CNIL (Commission nationale de l’informatique et
des libertés) is a French independent administrative
authority that operates in accordance with the data
protection legislationparticipant à la recherché”)
Should informed consent be required in the future, the
‘Commission cantonale d’éthique de la recherche’ must be
contacted to obtain approval for the research project.
The ethical arrangements made with the CHUV comply
with standard best practice and will be used as a model in
the phase of hospital and research database recruitment.
In line with EU Directive 2010/63/EU, the licensing of
animal research in France has been regulated on a project
basis since January 2013. Previously, it was regulated at
the individual researcher level.
Given that recruitment has not yet begun, it is not possible to detail the specific ethical provisions applying to
other hospitals contributing data to the Medical Informatics Platform. However, differences with CHUV practice are
expected to be modest.
5.1.2.2 Ethical Requirements: Germany
For the modelling of functional and anatomical connectivity in vivo, we will use data from the US 1000 Connec-
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Ethics and Safety
Adoption of best practices and compliance with national
and European regulations will be a requirement for all hospitals participating.
Application of the Three Rs in HBP Animal Experimentation
HBP animal experimentation will follow the principle of
the “Three Rs”: replacement, reduction and refinement.
5.2 General Approach to Ethical Issues
Replacement: All proposed experiments will involve laboratory animals bred specifically for research. In the kinds of
investigation the HBP requires (investigations of complex
brain structures and dynamics), there is currently no
alternative to the use of animals. However, experimental
approaches can be improved enormously by close interaction between experimental and computational approaches.
This is reflected in the present proposal, where some Partners already use brain modelling and simulation as their
principal research tool. Validated predictive methods have
the potential to vastly reduce the number of animal experiments the Project needs to perform.
5.2.1 Objectives
The HBP aims to achieve a unified understanding of the
human brain (and thus, indirectly, of what it means to be
human); to design a new generation of computing technologies using brain-like circuitry and computing principles; and to develop a radically new approach to the
classification, diagnosis and treatment of brain disease.
Anyone who accepts the overall goals of the scientific
enterprise will consider these outcomes as unquestionable ethical goods. However, this does not rule out
objections to the methods used or some of the Project’s
potential impacts. HBP Management and the Project’s
larde Ethics and Society Programme (see Appendix 1)
are already making and will continue to make every possible effort to pursue a policy of Responsible Research
Innovation and to mitigate unavoidable risks.
Reduction: Reduction of the use of animals and of potential
suffering will be achieved through an appropriate choice
of experimental techniques. The majority of mouse and
rat experiments will be carried out either under terminal
anaesthesia or using isolated tissue prepared at euthanasia.
According to the UK Home Office Guidance Notes (2002)
to the Animals (Scientific Procedures) Act 1986 (A(SP)A),
the severity of these experimental protocols therefore falls
in the category “Unclassified” (of low severity).
5.2.2 Research Methodology
5.2.2.1 Animal research
Overview
As a Project with a significant neuroscience component, the HBP will require many animal experiments.
Animal experiments in the CP will only use rodents.
In particular, SP1 will involve many experiments on
mice. Partnering Projects may also include research in
other species including non-human primates. Several
aspects of the Project will mitigate potential public
concern about this research.
Where in vivo experiments are necessary, pain and suffering will be avoided by non-recovery protocols; wherever
possible, experiments will be conducted under terminal
anaesthesia. Experiments to study behaviour in awake
animals will be performed following recovery from minimally invasive surgery under full surgical anaesthesia and
involving no more than mild pain. No pathological states
will be induced and no pharmacological testing will be
performed. No painful or psychologically distressing protocols will be used.
• The HBP’s effort in neuroinformatics, its support for
the INCF, and its collaboration with other international neuroscience initiatives will encourage a culture
of data sharing, making it easy for labs to identify
data that is already available and reducing duplicate
animal experiments.
Measures will be taken to maximise the chances of
obtaining useful data from each individual animal (e.g.,
sterile surgery conditions, healthy animals). State-ofthe-art electrophysiological and imaging methods make
it possible to obtain comprehensive detailed data from a
single animal. In particular, optogenetics and multi-electrode, multi-site, electrophysiological recording methods
enable researchers to collect data about neuronal activity in many cells simultaneously. In vivo imaging methods
for repeated monitoring of neural networks in the same
animal (longitudinally) and for data collection in awake,
behaving animals also help to maximise the information
gathered from individual animals.
• Predictive neuroinformatics can potentially predict
parameter values where experimental data are not
available. Animal experimentation is essential for
establishing and validating predictive methods and
will always be required where validated methods are
not available. However, predictive methods have the
long-run potential to make certain kinds of experiment unnecessary.
• The Project’s modelling and simulation capabilities
will be especially useful for preliminary drug screening. While this kind of screening cannot replace animal
testing, it will make testing more efficient, excluding
drugs with predicted poor efficacy or adverse effects.
The HBP will allow clinical researchers to gain a new
understanding of brain disease, design new diagnostic
tools and develop new treatments. The potential contribution to human wellbeing and the potential long-term
reductions in animal experimentation amply justify the
Project’s limited and responsible use of animals.
For behavioural experiments, extensive training of limited
numbers of animals will assure collection of high-quality
meaningful data. Given low inter-individual variability, firm
conclusions can usually be reached from small numbers
of animals. Animal numbers will also be further reduced
by conducting small-scale pilot experiments before proceeding to experiments using larger numbers of animals.
As indicated above, computational modelling will reduce the
number of animals needed for experiments by maximising
the data that can be extracted from individual data sets.
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Ethics and Safety
Refinement (animal welfare): Animals will be obtained from
animal housing facilities that are dedicated to institutional
research and whose work practice has been scrutinised and
authorised by an official homologation review led by local
veterinary services, as mandated by applicable law. HBP
research teams will ensure that animal houses offer the best
possible conditions. Laboratory staff are trained in the handling of laboratory animals, health is monitored daily, and all
participant laboratories have veterinary assistance.
Compliance with European and
National Data Protection Law
All clinical data made available through the Medical
Informatics Platform will be anonymised. As such, the
data appear to fall outside the remit of the European
Union Directive on Data Protection (Directive 95/46/
EC), which is limited to data referring to an “identified
or identifiable natural person”. However the directive
defines such a person as anyone who “can be identified, directly or indirectly, in particular by reference
to an identification number or by one or more factors
specific to his physical, physiological, mental, economic, cultural, or social identity”. In other words, a
formally anonymised patient record, which included
information on the patient’s age, zip code, clinical
diagnosis, genome, etc. could still be considered personal data. Theoretically, this risk can be avoided by
“de-identifying” the data, i.e., by removing any kind of
data that can be used to identify the patient. However,
this would reduce the value of the data for clinical
research, and make it practically impossible to test
“personalised” treatments.
Trained personnel with official authorisations for animal
experimentation perform all surgical operations under
anaesthesia and analgesia (as approved by ethical committees). Experimental procedures for behavioural experiments
are being steadily improved and refined to optimise the well
being of experimental animals – a prerequisite for collecting
high-quality data.
Benefits of the Proposed Animal Research
The HBP’s goal of simulating the human brain can provide
radically new insights into the functioning of the human
brain, opening the door to new computing technologies
and, most importantly, to better classification, diagnosis
and treatment of brain diseases. Rodent data will make a
direct contribution to modelling and simulating the mouse
brain. This work will yield tools and establish generally applicable principles of brain organisation that make it possible
to extract the maximum possible knowledge from available
human data (see below).
In some cases, researchers may wish to use pseudoanonymous data. In this case In this case, which is not
envisaged in current HBP plans, researchers will apply
for the appropriate authorisations.
The European Commission is currently in the process
of drafting a new Data Protection Regulation designed
to provide new protections for personal data, and to
remove ambiguities in the current directive. However,
the medical research community has expressed concerns that the regulation could have a negative impact
on the kind of research proposed by the HBP and has
proposed a number of modifications to the draft regulation. It is not yet known which, if any, of these changes
will be accepted in the final draft.
5.2.2.2 Research with Human Subjects
The HBP will collect large volumes of data from human volunteers. These data will help the Project to achieve a better
understanding of the relationship between brain structure
and function, and to leverage data from rodent studies. In
particular, SP2 will engage in non-invasive neuroimaging studies to collect data on human brain connectivity. A
second study will systematically scan the brains of ten volunteers over a period of several years. A third study conducted in SP2 will collect data on the developing infant brain.
In this situation, the policy of the HBP will be to comply
with existing European and national law and jurisprudence, deferring to the interpretation of the law
provided by the hospitals and other institutions contributing data to the HBP and their respective ethics
committees. Any requests for ethical approval will
go through these institutions. In the event that a user
wishes to analyse data from a specific patient for purposes of diagnosis, the HBP will apply relevant local
rules and regulations.
In all three cases, protocols for the studies follow practices
already well established in the partner organisations responsible, and include well-defined procedures for informed
consent (including parental consent for the scanning of
infant brains), handling of incidental findings, etc. All protocols will be submitted for approval to the appropriate IRB
prior to the start of the experiment.
5.2.2.3 Re-use of Clinical Data
Technical Measures to Protect Patient Data
The HBP’s in situ query technology will make it possible
to query data stored on local hospital servers without
moving them to a central location, reducing the risk of
unauthorised access. Access criteria will be configured
at the individual server level, ensuring compliance with
the national law in force in different countries, local regulations, the privacy policies of individual hospitals, and
additional restrictions on use requested by individual
patients (e.g., restrictions on the use of specific categories
of data). The novel security mechanisms introduced in the
Platform will help to meet these requirements.
The HBP Medical Informatics Platform (SP7) will federate
large volumes of anonymised data (genetic data, imaging
data, and other clinical data) originally generated for clinical
purposes, and make it available to the research community.
Data sources include hospitals, pharmaceutical companies and other organisations (e.g., large prospective trials). Partnering Projects will mine these data
for biological signatures of disease, which if found,
could provide important insights into disease mechanisms, contributing to the development of new
diagnostic tools and new treatments. The Project will
encourage community efforts to use Platform data and
tools for studies of a broad range of brain disorders.
Below we discuss the implications of this approach.
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Ethics and Safety
In some cases (e.g., studies requiring advanced image analysis), it may be necessary to move data to a central server for
advanced forms of analysis. In this case, the data will always
be anonymised prior to the transfer. Copies of data on the
Platform will be retained only for the time essential to complete the analysis and immediately destroyed. Where it is necessary to repeat an analysis, the data will be reconstructed
from the original sources using HBP provenance tracking.
carried out without prior written approval from the relevant IRB. In some cases, the groups concerned have
already applied for and received ethical approval.
5.2.3 Potential Impact of the Research
5.2.3.1 Clinical Outcomes
Some of the earliest results of HBP research will be in the
clinic. Contributing to the diagnosis and treatment of brain
disease is an obvious ethical good. It nonetheless has a
number of ethical, social and legal implications.
Informed Consent
The HBP intends to analyse anonymised historical data, collected for purposes of diagnosis or treatment, and during
clinical trials. Given that, in many cases patients have not
consented to the use of their data for research, this raises
ethical issues. Many members of the medical research
community have argued that denial of access to this kind
of data would prevent valuable research (e.g., retrospective epidemiological studies). However, current legislation
is ambiguous. As long as this situation remains unchanged,
the HBP will defer to the interpretation of the law provided
by the hospitals and other institutions contributing data to
the HBP and their respective ethics committees. Clinicians
and ethicists working in the HBP will participate in public
and academic debate to clarify open issues.
New HBP diagnostic tools will be part of a secular trend
toward early diagnosis of disease. In cases where early
diagnosis facilitates treatment and cure, this is ethically
unproblematic. However, in cases where there is no effective
treatment (e.g., Huntington’s disease), patients may demand
their right not to know. It is ethically important that society
finds ways of respecting this right.
Another key issue is the impact of effective early diagnosis
on insurance-based health services, the viability of which
depends on the unpredictability of a large proportion of
serious illness. Early diagnosis of highly prevalent brain diseases could seriously undermine current models of private
health insurance.
A second issue is how to reform models of informed
consent for future patients. Many ethicists and clinicians
would agree that data cannot be used unless patients
have given their consent. However, there is growing
recognition that it is not always possible to enumerate the
different ways in which future researchers may wish to
use specific classes of clinical data. This has led to suggestions for forms of “open consent” that cover a broad
range of possible uses. Clinicians and ethicists working in
the HBP are participating in public and academic debate
around this issue. In the meantime, they will work with
local hospital administrations and ethics committees
to develop informed consent procedures that provide
meaningful protection to patients, while simultaneously
enabling effective research.
Finally, there can be little doubt that many of the diagnostic tools and treatments derived from HBP research will
be expensive. Savings in the cost of care are likely to be
far higher than the cost of early diagnosis and treatment.
However, the introduction of new and expensive technologies could exacerbate inequalities in access to care. No one
would seriously argue that this is a reason to stop development of new medical technologies. It is nonetheless important that there should be an open debate on the way the new
technologies are deployed, used and paid for. The HBP will
participate actively in this debate.
5.2.3.2 Dual Use
None of the know-how or technologies developed in the
HBP have obvious or direct military applications. However,
the HBP recognises the risk that state or non-state actors
could use future research results for military purposes or for
other goals (e.g., mass surveillance) of ethical concern.
Brain Simulation
A significant proportion of modern neuroscience research
(but not the research conducted by the HBP Partners)
receives funding from sources associated with the military.
There is thus legitimate public concern that state or non-state
actors could use the results of neuroscience research for military purposes. Potential military applications of neuroscience
that have been discussed in the media include novel chemical weapons targeting the brain, novel techniques of “mind
reading” and “mind control”, and neuroscience-enhanced
techniques of torture/interrogation.
Requests for Ethical Approval
No clinical data will be made available through the Medical
Informatics Platform without the approval of the hospitals
or other organisations holding the data. These organisations will be responsible for requesting ethical approval
(where required) from the relevant Independent Review
Boards. In the early stages, it is expected that the majority of these organisations will be located in Switzerland.
At later stages, the Project will involve hospitals all over
Europe. Staff in the HBP Ethics and Society Programme
(SP10) and staff from the Medical Informatics SP will assist
hospitals in formulating their applications and in providing any information IRBs may require.
The goal of the Project is that all necessary applications
for ethical approval should be completed not later than
the end of Month 24, and that all requests should be
approved not later than Month 30.
Obviously, concerns about the applications of neuroscience
extend to HBP brain models and simulations. However, many
of the scenarios described in the press focus on applications
(mind-reading, mind control) that are unlikely to be feasible
in the short- to medium term future, or that would be
easier to develop with more conventional technologies
(toxins, new interrogation techniques, etc.).
5.2.2.4 Research with Human Tissues
Several studies proposed in SP2 will use human tissues
extracted during neurosurgical procedures performed
for clinical purposes or during autopsy. No study will be
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Ethics and Safety
5.2.3.3Legal and Extra-legal Surveillance
Of course, the Consortium cannot exclude the possibility
of unexpected discoveries with potential for abuse. Measures to manage such discoveries are described below.
Other questionable applications might include deployment of cognitive technologies for automated mass surveillance (e.g., analysis of images from CCTV cameras,
automated transcription, translation and interpretation
of phone calls, automated analysis of e-mails).
Neuromorphic Computing and Neurorobotics
We believe that the sectors of HBP research that are most
likely to give rise to military applications are neuromorphic
computing and neurorobotics. These have obvious applications in autonomous or semi-autonomous weapons
systems, and especially as controllers for such systems.
As has been pointed out in debates on military drones,
the deployment of such systems raises delicate issues of
morality and of international criminal law.
5.2.3.4 Impact on Employment
The HBP’s work in neuromorphic computing and neurorobotics will lay the foundations for a new generation of
computing systems and machines with cognitive capabilities absent in current technology, including a degree
of autonomy and an ability to learn. This raises the issue
of legal liability when a neuromorphic or a neurorobotic
system damages humans or their property – a topic
already raised by the advent of autonomous vehicles.
The HBP Ethics and Society Programme will contribute
to this debate.
Of course, nearly all ICT (including consumer devices and
systems) has potential military applications. Ethically, this
is insufficient grounds to halt the development and commercialisation of new technology. However, it is more than
sufficient grounds to try and identify these applications in
advance to make the public aware of potential abuses and
to debate the way new technologies should be regulated.
The Citizen Conventions and other forms of public awareness-building organised by the HBP Ethics and Society
Programme (SP10) will contribute to this goal (see paragraph 2.2.2.3).
A larger, longer-term risk is that the impact of the new
technologies on employment. In some cases, neuromorphic and neurorobotic technologies could replace
humans in tasks that are dirty, dangerous or unpleasant.
It is possible, furthermore, that the new machines will
provide citizens with services (e.g., help with domestic
chores) that are currently unavailable or unaffordable.
Non-state Actors
Any technology suitable for use by the armed forces of
a nation state could also be used to further the military
goals of non-state actors. However, non-state actors
face severe barriers to entry, and so far have lacked the
know-how and financial resources to deploy advanced
weaponry (e.g., nuclear weapons) that is not freely available on the market.
However, the widespread use of the new technologies will also imply a major shift in current patterns of
employment and there is no guarantee that the creation
of new jobs in some sectors of the economy will be sufficient to counterbalance losses in other sectors. As in the
case of medical innovation, it will not be ethically justifiable to abandon technical innovation because of the risk
of disruption to current economic and social structures.
Again, these changes will need to be governed. This will
be another area for debate in SP10.
At the time of writing, none of the scientific or technological developments planned in the HBP appear to be accessible to non-state actors. However, the Project recognises
the risk that future developments could create unforeseen
opportunities for abuse. To mitigate these risks, the Project
will take the measures described in the following section.
5.2.3.5 Ownership and Public Access
to Knowledge
Neuroscience data, clinical data and basic research tools
developed by the HBP will become community resources,
freely accessible to scientists around the world.
Mitigation Measures
The HBP Consortium Agreement for the Ramp-Up phase
contains a formal commitment that the Partners will not
collaborate or accept funding from the armed forces,
defence-related funding agencies or the defence industry.
The HBP will maintain this commitment for the duration of
the HBP Flagship Initiative.
At the same time, the HBP Partners will protect and commercially exploit specific technologies, tools, and applications. This strategy will be similar to the approach
adopted by other large-scale science projects, and we
do not expect that it will give rise to fundamental ethical
or policy objections.
Additionally, the HBP Foresight Lab (part of SP10) will continuously monitor HBP for results with potential for misuse.
Where the risks are long-term and strategic, SP11 will bring
the risks to the attention of the public and lead a public
debate on how they should be managed. In the unlikely
event that the HBP makes a discovery that poses an imminent danger, the Partners concerned will immediately notify
the Consortium Management and the appropriate authorities, halting the research (and related publications) until
the RB has decided on an appropriate course of action.
5.2.3.6 Allocation of Public Resources
In a period of financial crisis and cuts in research
funding, any research proposal has an ethical obligation to demonstrate that it is better to invest in this way
than to spend the money outside science, or on other
forms of research. The Partners in the HBP believe
that investment in the HBP will be fully justified by the
potential benefits for European society and the European economy.
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APPENDIX 1
APPENDIX 1: OVERVIEW OF THE FLAGSHIP OBJECTIVES
AND STRATEGIC RESEARCH ROADMAP
1. CONCEPT AND STRATEGY
ciated with the development of CNS drugs have led
many pharmaceutical companies to cut back on their
research. Effective diagnosis and treatment of neurological and psychiatric diseases require a shift away
from symptom and syndrome-based classifications
of disease toward objective, biologically grounded
classifications. As a first step, we need to identify the
biological changes associated with disease at different levels of brain organisation: the “biological signatures” of disease. Ultimately, we have to understand
the causal mechanisms that give rise to these changes
and their effects.
Integration (HBP)
¤50 million
Experimental Mapping
¤500 million
Individual Research
¤7 billion
Until recently these challenges were intractable. The HBP
Flagship Initiative proposes a new strategy that exploits
the possibilities opened up by modern ICT. In neuroscience, the HBP uses state-of-the-art supercomputers to
build high-fidelity reconstructions of the brain from sparse
experimental data, exploiting interdependencies in the
data to predictively fill in gaps where no data is available
and steadily improving the accuracy of the reconstructions as more data become available. In the first five years
of the HBP, the Project will reconstruct and simulate the
mouse brain. In the second five years, it will produce first
draft reconstructions and simulations of the human brain.
Simulations will be linked to virtual robots interacting with
a virtual environment, creating a closed loop. simulation
experiments using these systems will make it possible to
dissect the basic biological mechanisms underlying cognition and behaviour.
Figure 28: Funding perspective in neuroscience
Every year, the world spends more than EUR 7 billion on
brain research, producing rapidly growing volumes of data
and knowledge. To date, however, the scientific, social and
economic returns have been disappointing. Neuroscience is
still far from achieving a unified understanding of the multilevel mechanisms that give rise to cognition and behaviour.
Our steadily improving understanding of the brain has yet to
give rise to new computing technologies. Most importantly
of all, brain research has had very little impact on the way
we understand, diagnose and treat brain disorders – diseases that already cost the European economy more than
EUR 800 billion per year [11, 12]. This is a burden expected
to grow with the aging of European population. To make
progress, there are three critical challenges to overcome.
In computing, the HBP is building the machinery and
methods to translate high-fidelity reconstructions into simplified models of the brain, and to implement these models
in neuromorphic and neurorobotic devices and systems.
The Project will explore potential applications for industry,
transport, health-care, the home, high performance computing etc. Much of the work performed in the Project also
requires new developments in High Performance Computing (new architectures, new methods for interactive visualisation, new techniques of multi-scale simulation). The
potential applications go far beyond brain simulation.
The first challenge is in neuroscience. Despite decades
of effort, we still do not fully understand the brains of
very simple animals, let alone the human brain, with its
approximately 100 billion neurons and 100 trillion synapses. Modern experimental research produces massive
volumes of data, but has only generated a tiny fraction
of the data that would be needed to create a complete
map of the brain. To achieve a unified understanding of
the brain, we need is a new strategy that makes it possible to integrate the data coming from research, and to
fill in the huge gaps where data are not available.
In medicine, the HBP is federating hospital archives and
other sources of anonymised clinical data, and building the
analytical tools to extract “biological signatures of disease”
from very large volumes of heterogeneous data (genetics,
blood chemistry, structural data from imaging, EEG, clinical
signs, treatment response etc.) and mapping the similarities
and differences between different disorders. This work will
allow more effective diagnosis and treatment of patients,
better identification of potential drug targets, and better
selection of participants for clinical trials. Ultimately, the
Project will develop the capability to simulate brain disorders, reconfiguring reconstructions of the healthy brain to
reflect biological signatures of disease. Disease simulation
will make it possible to investigate the causal mechanisms
responsible for disease and to screen potential treatments,
accelerating the drug development process.
The second challenge is in computing. Current computing technologies cannot match the brain’s reliability,
fault-tolerance, energy, or ability to process complex
data streams in real-time and to learn without explicit
programming. Some of the hardware needed to build
brain-like devices and systems is on the horizon. But to
use this hardware effectively, we have to understand
the basic computational principles and circuit designs
that give the brain its capabilities, and build the tools to
translate this understanding into practical technology.
The third challenge is in medicine. Today there are few
disorders of the brain whose causes are fully understood, and few effective treatments. The high risks asso-
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Appendix 1
Platforms v4, Multi-level Human Brain Atlas, first draft model of the whole human brain, Exascale HBP
supercomputer, first MI tools for personalized medicine, PM-NCS with 5 billion neurons and 13,000 billion
synapses, and on-board plasticity processor; Neurorobotics support for human brain models.
M120
Platforms v3, Initial multi-level Human Brain Atlas, multi-level model of whole
mouse brain, upgrade of HBP supercomputer to 100 PFLOPs, tools for large-scale
data mining, PM-NCS with 500 million neurons and 130 billion synapses and onboard plasticity processor; published behavioural experiments using cellular level
reconstructions of the mouse brain with inbuilt plasticity.
Overall HBP
Milestones
M90
Platforms v2, Multi-level Mouse Brain Atlas, cellular-level models of whole mouse
brain with closed-loop support, pre-exascale HBP supercomputer. (up to 50 PFLOPs),
community access to Europe-wide network of clinical data, PM-NCS with 4 million
neurons and 0.9 billion synapses and on-board plasticity processor, MC-NCS with 1
billion neurons and 10 billion synapses; first pilot experiments using cellular level
reconstructions of the mouse brain.
M60
Start of operational phase (Core Project). Platforms v1, network models of whole mouse brain, MI Platform offers
access to first federated data, PM-NCS with 4 million neurons and 0.9 billion synapses, MC-NCS with 100 million
neurons and 100 billion synapses; first pilot experiments with neurorobotics platform.
M30
M30
M60
M90
M120
Figure 29: Timeline for important project outputs
Computing, Medical Informatics, Neuromorphic Computing and Neurorobotics. The first versions of the Platforms,
accessible via a single Unified Portal, will open for community use in Month 30. The Platforms will be regularly
updated at 30-month intervals, and are likely to include
novel tools and technologies proposed and contributed by
Partnering Projects.
ICT platforms for Neuroinformatics,
Brain Simulation, High Performance
Computing, Medical Informatics,
Neuromorphics Computing,
and Neurorobotics
The HBP Platforms will enable members of the community
to perform research and collaborate on a very broad range
of topics in neuroscience, computing and medicine. It is this
research, enabled by the Platform that will enable the Project
to achieve its Strategic Objectives. The Research Roadmap
identifies many possible themes but is deliberately formulated
in such a way as to be open to new ideas and contributions.
The HBP’s approaches to neuroscience, computing and
medicine require technological know-how and infrastructure that are currently available only to very few research
groups. One of the first goals of the HBP Core Project is
thus to make these capabilities available to members of the
relevant scientific communities. To achieve this, the Project
is developing six ICT Platforms dedicated respectively to
Neuroinformatics, Brain Simulation, High Performance
In sum, the HBP Flagship Initiative will drive a completely
new mode of organising collaborative, transdisciplinary
research, of accelerating basic science, and of translating
results from basic research into products and services that
benefit the European economy and European citizens.
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Appendix 1
2. STRATEGIC FLAGSHIP OBJECTIVES (SFOS)
SFO1 Future Neuroscience
Achieve a unified, multi-level understanding of the human
brain that integrates data and knowledge about the
healthy and diseased brain across all levels of biological organisation, from genes to behaviour; establish in
silico experimentation as a foundational methodology for
understanding the brain.
supercomputing technologies for brain simulation, robot
and autonomous systems control and other data intensive
applications.
SFO3 Future Medicine
Develop an objective, biologically grounded map of neurological and psychiatric diseases based on multi-level clinical data;
use the map to classify and diagnose brain diseases and to
configure models of these diseases; use in silico experimentation to understand the causes of brain diseases and to develop
drugs and other treatments; establish personalised medicine
for neurology and psychiatry.
SFO2 Future Computing
Develop novel neuromorphic and neurorobotic technologies based on the brain’s circuitry and computing principles; explore their potential applications; develop novel
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Appendix 1
3. RESEARCH ROADMAP
3.1 Overview
European and International initiatives, building synergies
and avoiding duplication of effort.
The Research Roadmap defines the research that the HBP
Flagship Initiative will perform over the duration of the
Project. Some of the planned Actions contribute directly
to the SFO – as when the Project produces an important
new scientific insight, a new computing technology, or
a new clinical application of its results. Others contribute indirectly, for instance by contributing data, methods,
algorithms and tools, or by enabling the Project to follow
a policy of Responsible Research Innovation.
The Research Roadmap groups planned Actions into 10
research Subprojects, (see Figure 30). The eleventh Subproject (Management and Coordination) is described elsewhere. The Roadmap defines each Subproject’s general
and operational objectives, going on to describe the relevant state of the art, planned advances beyond the state
of the art, planned Actions, output targets and Milestones,
risks and contingency plans, and potential impacts.
The research and development performed by the Project
can be roughly divided into two categories: research
contributing to the Project’s scientific and technical
capabilities (made available to the scientific community
through the HBP Platforms) and research using these
capabilities for work in future neuroscience, future computing and future medicine.
Subprojects are divided into Work Packages, each implementing a specific set of Actions. Many use intermediate
results and services from other subprojects, as described.
The Roadmap distinguishes between Work Packages
implemented in the Core Project and those implemented
by Partnering Projects, and specifies work to be carried
out in external collaborations. All stages of the Project are
designed to make meaningful contributions to the SFOs.
Success will be measured, not just in terms of its final results
but also in terms of intermediate outputs. Major Milestones are planned for Month 30 (the end of the Ramp-Up
Phase), Month 60, Month 90 and Month 120. More detailed
Milestones will be fixed in successive SGAs (for the Core
Project) and in Descriptions of Work or equivalent documentation (for Partnering Projects). Figure 28: provides an
estimated timeline for key outputs already planned. Other
outputs (especially from the Partnering Projects) will be
defined over the duration of the Project.
Research and development critical to the HBP’s technical capabilities will be conducted by the Core Project.
Additional contributions to the Platforms and research
using HBP capabilities will come from the Partnering Projects. The detailed allocation of Actions to the
Core Project and the Partnering Projects is described
in the paragraphs below. The Roadmap also shows
areas of research, some of great importance for the
HBP, where the Project will rely on collaborations with
other national,
Figure 30: HBP subprojects
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Appendix 1
3.2 Subproject 1: Targeted Mapping of
the Mouse Brain
MB4 – Multi-level map of the mouse brain including
cognition and behaviour
M120
MB3 –Structural and functional map from genes
to cognition and behaviour
SP1
Milestones
M90
MB2 –Structural, multi-level map from genes to the whole brain
M60
MB1 –Structural, cellular–level map from cells to the whole brain
M30
M30
M60
M90
M120
Figure 31: Output Targets and Milestones for SP1: Targeted Mapping of the Mouse Brain (MB)
3.2.1 General and Operational Objectives
in single neurons or the way proteins are targeted in
neurons. At the cellular anatomy and connectivity levels,
we still do not have complete data for a single species.
Even in C. elegans – the only animal whose neuronal
circuitry has been completely deciphered – essential
information such as data on neural morphologies is still
missing. At the physiological level, we do not have a clear,
quantitatively accurate picture of physiological response
in different types of synapse, cell and circuit. Data on
long-range connections between different brain regions
is also sparse. Above all, we still do not have a clear
picture of the brain as an integrated system. Without a
systematic programme of research in a single species, it
will be extremely difficult to understand the relationships
between different levels of brain organisation; e.g., how
a variant in a specific gene affects the architecture of
an animal’s neural circuitry and its subsequent behaviour.
The vertebrate species for which we have the most data
and the best techniques of data generation is mouse.
SP1 will perform targeted mapping of the adult mouse
brain, generating data required to constrain and validate high-fidelity reconstructions. Specifically, the Core
Project will generate systematic, standardised structural data for key levels of biological organisation (the
genome, the transcriptome, the proteome, cells, synapses, and connectomics). The Partnering Projects will
generate complementary data sets documenting brain
function and links from structure to cognition and behaviour. These data are unlikely to come from other research
in progress or planned.
Current techniques make it possible to obtain data
for every level of biological organisation of the mouse
brain. No other species can provide similar coverage.
Mouse data will thus make a vital contribution to the
HBP’s reconstruction and validation processes. Comparison with human datasets will facilitate translation to the human brain, which has many features not
present in mouse. The data generated will contribute
to the Mouse Brain Atlas generated in SP4, and to the
high-fidelity reconstructions of the mouse brain generated by SP5. Ultimately, it will contribute to high-fidelity reconstructions of the human brain. To maximise
compatibility with on going work, SP1 will focus on the
adult mouse and will use the same strain of mouse used
by the Allen Institute.
Although an enormous amount of work remains to be done,
new technologies are making it easier to generate data on
the mouse brain, and to relate them to data for humans.
At the molecular level, we already have a large volume of
quantitative data on DNA sequences and modifications,
[13] RNA [14] and proteins [15] [16]. The last three years
have seen the release of the first molecular-level atlas of
the mouse [15] and human brain transcriptomes [17]. In
principle, these atlases, combined with RNA and protein
profiles for different cell and synapse types, could make
it possible to estimate the numbers of different types
of cells in different brain regions and to relate the data
for the two species. The Human Brain Project will fully
exploit these possibilities.
3.2.2 State of the Art
Current neuroscience research comprises many disciplines and communities, each focusing on a specific
level of biological organisation and on the brain regions,
species and methods best adapted to its specific goals.
Progress is rapid at all levels. However, our current
knowledge has many gaps. At the molecular level, we
lack a complete description of the genes expressed
At higher levels of organisation, breakthroughs in scalable
methods—particularly in optogenetics [18] and MRI—are
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cells: characterise micro projections (e.g. synaptic connections between neighbouring neurons);
measure the density and distributions of excitatory
and inhibitory synapses, and numbers and distributions of organelles (e.g., mitochondria); identify synaptic selectivity principles; capture the morphologies of
neurons and glial cells; characterise structural relationships between neurons, glia and the vascular system.
paving the way for comprehensive studies comparable
to work being done in molecular biology and proteomics.
In particular, there has been considerable progress in
connectomics. Molecular tracer methods now make it
possible to trace connections between different types of
cells and their synapses. Data from these studies can be
correlated with results from behavioural studies, which
were traditionally performed in low-throughput settings,
but which are now complemented by high-throughput
methods using touchscreen-based perception and
learning tasks [19]. These methods make it possible to
measure thousands of animals and compare the data
with data from human subjects.
WP1.3 Circuit Architecture: characterise afferent
maps using transparent brains; characterise tract
structure (fibre composition and distribution, topographical organisation).
3.2.3 Advances over State of the Art
Work in SP1 has the potential to produce the most complete multi-level map of a vertebrate brain ever produced - spanning all levels of biological organisation
from molecules to large-scale brain architecture.
WP1.4 Theory and informatics: identify principles for
use in predictive neuroinformatics, mouse-human comparisons and multi-scale theory; identify principles governing the spatial architecture of brain regions, neuronal
populations and synapse types; develop a theory of
structural-functional relationships; develop techniques
to characterise cognitive architectures, developmental
models and variability; develop techniques for big data
management and links to HBP Brain Atlases; develop
validation tests for brains models and simulations.
At the molecular level, SP1 will generate profiles of the
molecular components of individual cells (neurons and
glia) with an emphasis on the genome (DNA and epigenome), the transcriptome (RNA), the proteome (proteins), and the metabolome (metabolites). This will be
the first time these data are collected.
SP1 will go on to characterise the dendritic, axonal and
synaptic architecture of neurons at the molecular scale,
identifying hierarchies of organisation and regulation,
including transcriptional and RNA regulatory networks,
protein complexes and organelles.
WP1.5 Integrative map: develop an integrative,
multi-level map of the whole mouse brain including
expression (e.g. ion channels, receptors, synapses),
and single-cell transcriptomes; identify topographical and metabolic relationships between blood
vessels, neurons and glial cells; identify principles
of structural segregation (cortical areas and nuclei);
visualise cells and fibres in the whole brain; develop
whole brain reconstructions from transparent brains;
identify principles of functional segregation.
Equivalent information will be collected for different
types of brain cells in different regions of the brain.
These molecular maps will provide vital information for
the reconstruction and simulation of the healthy brain,
and for the exploration and simulation of hundreds of
brain diseases.
Molecular maps will be integrated with the cellular scale
maps. This second series of maps will catalogue and
profile the synapses, axonal projections and dendritic
morphologies that characterise different cell types.
Combining the molecular and morphological maps will
make it possible to systematically assign cells to different cell types.
WP1.6 Scientific coordination: coordinate scientific activities within the SP and with other SPs,
Partnering Projects and international collaborations; coordinate quality assurance, organisation of
meetings and workshops and reporting.
Molecular and cellular levels will be integrated with
maps of the short and long-range connections within
and between brain regions and nuclei to create the first
multi-level map of the whole mouse brain. The map will
enable the first high-fidelity reconstructions and simulations of the whole mouse brain.
3.2.4.2 Partnering Projects
WP1.7 Physiological data: generate targeted physiological data going beyond the data sets generated in the Core Project; candidate data sets include
data on whole brain dynamics, neuroendocrinology
and neuroimmunology, metabolism and energetics,
the physiology of neurons and synapses, receptor and
channel biophysics, and gene expression.
3.2.4 Actions
3.2.4.1 Core Research Projects
WP1.1 Genetic and molecular architecture: characterise inter-individual genetic variation; generate single
cell transcriptomes, together with data on epigenetics,
genetic regulatory networks, proteome composition
and organisation, and the distribution of transporters,
ion channels, receptors and complexes.
WP1.8 From genes to cognition: perform experimental and informatics studies on the link between
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M120: MB4 - Fully integrated multi-level map of the
mouse brain including data from the Core Project,
Partnering Projects and collaboration.
genes and cognition and the impact of normal genetic
variations and mutations; develop links to human brain
disease signatures established in SP7 and to human
work in SP2.
3.2.6 Risk Analysis
WP1.9 Functional architectures of cognition: generate data on functional architectures of cognition
in mouse; possible themes include multi-modal perception and action, motivation, reward and decision making, synaptic plasticity, learning, memory
and goal-oriented behaviour, representations of
space time and quality in planning and navigation,
and the architecture of gene-behaviour-environment interactions.
R1.1 Risk of delay in cell-type transcriptomics
(Probability: medium; Impact: moderate).
Risk: Cell-type transcriptomics is a new frontier in
research. Extensive work on method development
has been in progress for the past five years, exploring
a broad range of strategies.
The HBP will consolidate best practices into a single
high-throughput strategy. However, there is a risk that
the markers used to isolate cell types in initial transgenics will not be sufficiently specific. Cell-type transcriptomes could therefore be incomplete.
WP1.10 Comparative studies: perform research comparing structural and physiological data in mouse,
humans and other animals (research performed in
conjunction with SP2).
3.2.4.3 Collaborations with other National, European
and International Initiatives
Impact: In the Ramp-Up Phase, model building can
proceed with existing high-quality data from microdissected regions. However, the single-cell data will be
essential in the Operational Phase for the prediction of
morphological and physiological properties of neurons
that cannot be measured directly, such as most neurons
in the human brain.
The HBP will work closely with existing and future
initiatives that generate structural and functional
data about the mouse brain or comparable data for
other species (non-human primates, simpler animals,
etc.). Other collaborations will focus on comparisons
between the mouse brain and the brains of other
species, on studies of genotype/phenotype relationships, and on the adaptation of techniques used in
mouse for application to humans. Especially important
will be collaboration with the Allen Brain Institute and
with the US BRAIN Initiative.
Contingency plans: Other organisations (e.g., the Allen
Brain Institute and the Wellcome Trust Sanger Institute)
are working intensely in this area. The risk that no group
will produce key data over the course of the Project is
low. New predictive informatics strategies help to minimise the amount of data required to predict complete
cell-type transcriptomes.
The Project may also develop collaborations with initiatives addressing related themes, such as prenatal alterations in gene expression and postnatal environmental
influences, brain development, aging, and inter-individual
variations. One example is an agreement currently under
negotiation with the Florey Institute of Neuroscience and
Mental Health, University of Melbourne, Australia (http://
www.florey.edu.au), which is performing experiments
complementary to those performed in SP1.
End of risk: This risk will be cleared when the Project
generates enough transcriptomic data to accurately
predict neuron morphologies and electrophysiology.
The quantity of data required is not known. This risk
will only be cleared in the Operational Phase.
R1.2 Failure to generate sufficient volumes of data
owing to technical and/or organisational problems
3.2.5 Output Targets and Milestones
M30: MB1 - Maps of the vasculature of the whole
mouse brain, cellular distributions, long-range axonal
projections, and synaptic proteins; reconstructed
morphologies of major neuron types.
Risk: The HBP requires the generation of significant
volumes of data in relatively little time. Although the
data generation effort will use established techniques,
there is always a risk of delay due to technical and/or
organisational factors.
M60: MB2 - Single-cell transcriptome classification of cell-types; reconstructed morphologies of neurons and glia; data for neuron-glial ratios,
excitatory-inhibitory ratios; neuron-glia-vascular structural relationships, projections between brain regions,
projections of single neurons, synaptic connectivity
between identified neurons, whole brain density and
distributions of excitatory and inhibitory synapses,
ultrastructure properties of neurons and glia.
Impact: In the Ramp-Up Phase, model building will rely
on existing high-quality data and on data generated
outside the HBP. However, the data generated in the
Ramp-Up Phase is essential for model building in the
Operational Phase.
Contingency plans: If the volumes of data generated during the Ramp-Up Phase are below target, the
Project will rely on lower fidelity reconstructions until
the necessary data becomes available.
M90: MB3 - Incorporation of data from Partnering Projects and external collaborations; refocused
experimental mapping guided by reconstruction;
initial integrated multi-level map of the mouse brain.
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End of risk: This risk will fall gradually as the volume of
available data increases, allowing the construction of
steadily more accurate models. It will only be cleared in
the Operational Phase.
IMP1.3 The data generated in SP1 will provide the initial
reconstructions and simulations of the mouse
3.2.7 Impact and Innovation Potential
3.2.7.1 Scientific impact
IMP1.4 Comparative assessment of the data generated
in SP1 and SP2 will identify principles allowing
the use of mouse data to predict features of the
human brain for which experimental data are
not available.
IMP1.1 The data generated in SP1 will make a vital contribution to the Mouse Brain Atlas, created in SP4.
IMP1.2 The data generated in SP1 will enable the use of
gene expression data to predict features of the
brain that have not been measured experimentally,
drastically reducing the number of experiments
necessary to build high-fidelity reconstructions.
3.2.7.2 Social impact and Innovation Potential
The social impact of SP1 will be indirect, through its
contribution to other Subprojects.
Figure 32: Spatial and time scales for the human brain and for different classes of brain model
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3.3 Subproject 2: Targeted Mapping of
the Human Brain
HB4 – Multi-level map of the human brain including
cognition and behaviour
HB3 – Structural, multi-level map from genes
to the whole brain
M120
SP2
Milestones
M90
HB2 –Structural, cellular-level map from cells
to the whole brain
M60
HB1 – Initial multi-level datasets
M30
M30
M60
M90
M120
Figure 33: Output Targets and Milestones for SP2: Targeted Mapping of the Human Brain (HB)
#2849;Hawrylycz, 2012 #4306], these approaches make
it possible to build and test complex systems models
where every trait, at every level and scale, can be linked
to specific gene loci and regulatory sequences [16]
The recent introduction of computerised touchscreen
approaches has made it possible to compare a subset of
human cognitive functions with equivalent functions in
mouse [22]. Despite the limitations of mouse models for
predicting complex behaviour and cognition in humans,
comparative studies of mice and humans can provide
valuable information about putative mechanisms. Functions amenable to this approach include attentional
processing, visual and auditory memory, as well as cognitive flexibility and response inhibition. These methods
provide a valuable tool for studies of normal human
genetic variation.
The objective of SP2 is to generate a core data set that can
be used to constrain and validate a first draft reconstruction
and simulation of the human brain.
SP2 work in the Core Project will generate structural data
sets equivalent to the mouse data sets generated in SP1, and
evaluate differences and similarities between the mouse
and human data for different levels of biological organisation. This will make it possible to use transformed versions
of data for mouse genes, transcripts, proteins, neuron morphologies, etc. to fill in gaps in the human data, which will be
much less dense. Comparisons between mouse and human
data will facilitate systematic comparisons between mouse
data and data for simpler animals, and between data for
humans and non-human primates. These comparisons will
facilitate efforts to fill in gaps in our knowledge of the structural organisation of the human brain.
Human mutations as a major cause of brain disease.
Studies have identified over two hundred single gene
mutations affecting human postsynaptic proteins and
over a hundred and thirty brain diseases in which they are
believed to play a role. Regulatory sequences may also
play an important role [20]. Studies of individuals with
these mutations can provide useful insights into the way
variation in specific proteins contributes to differences in
cognitive, behavioural and emotional phenotypes, while
simultaneously providing valuable information on mechanisms of disease causation. Particularly interesting are
studies of affected individuals who display no overt signs
of disease.
The Partnering Projects will obtain functional datasets and
identify anatomical correlates for specific cognitive and
behavioural capabilities.
3.3.2 State of the art
Genetics and gene sequencing. Genetics is the method
of choice for understanding genome-to-phenome
linkage at the molecular, cellular and behavioural levels.
Two genetic strategies have proven particularly valuable.
The first compares phenotypes produced by point mutations against controls; the second examines small populations of individuals and assesses the role of endogenous
genetic variation (natural polymorphisms).
Molecular systems biology. Molecular systems biology
uses mathematical and computational methods to understand the molecular basis of information processing in
the brain. For example, multi-scalar analysis of genomic
variation data and quantitative phenotype data make it
Combined with massive “-omic” data sets, such as
ENCODE [20] and the recently released atlas of the
adult human brain transcriptome [21] [Hawrylycz, 2012
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Appendix 1
Imaging. Structural and functional imaging of the living
human brain provide a valuable supplement to highresolution data from post mortem studies [26]. Maps of
the density of the main types of neurons in post mortem
brains can link functional imaging data to underlying brain
anatomy [27]. Recent in vivo imaging techniques, particularly diffusion and resting state imaging, have made
it possible to map large-scale patterns of structural connectivity [28] [29] [30]. Polarised Light Imaging (PLI),
detecting the myelin surrounding axons, makes it possible
to link DTI data to the microscopic level and to verify data
from in vivo experiments [31]. Intra- and subcortical connection profiles for individual areas are likely to provide
new insights into the structure and function of the brain.
For the human brain, PLI is one of the few methods that
can bridge the gap between macroscopic organisation
and more detailed knowledge about long and short fibre
tracts. Given that most current information on human
brain connectivity is extrapolated from animal and developmental studies, this is a crucial step. Another imaging
technique involves neuronal recordings from healthy neocortical and hippocampal tissue that has been surgically
resected to gain access to deep epileptic foci or tumours.
This method provides 3D neuronal reconstructions in conjunction with functional connectivity, synaptic and neuronal physiology data. Finally, functional neuroimaging
makes it possible to localise regions specific to sensory,
motor or cognitive effects of interest. A key topic for
research is between-subject variability, which has thus far
hampered the creation of functional atlases of the brain.
possible to map patterns of gene and protein expression
to specific neuronal and synapse types. Massive, wellstructured molecular data sets for key brain cell and
synapse types make it possible to build rich quantitative
models of synapses, cells, neuronal ensembles and brain
areas, and to link these models to precisely matched anatomical, functional, and behavioural datasets, a precondition for predictive modelling.
Cataloguing cell types using transcriptomic data. Largescale mapping of gene expression patterns in the mouse
brain [23] [24] has confirmed that morphologically distinct cells express different combinations of the same
genes. The Allen Institute is now conducting similar
studies on human brain material [25]. Combined with
data from single cell transcriptomics – not yet available
but on the horizon – these data will make it possible to
predict cell types composition of different regions of the
brain. In principle, the data could also enable prediction
of the proteins present in different types of cells.
Cataloguing synapse types using proteomic data. Proteomics studies of human synapses have demonstrated
that human synapses contain over a thousand different proteins [26]. Certain patterns of synaptic protein
are typical of specific cell types and brain regions [27].
Array Tomography, a new technique, makes it possible
to map synapse diversity at the single synapse level [28].
Recently developed optogenetic methods for labelling
synaptic proteins allow rapid, highly efficient mapping
of individual synapse types, characterisation of the synapses present in different regions of the brain, and identification of their role in neuronal information processing.
Post mortem studies provide useful information about
the distribution of different types of transmitter receptor
in different regions of the brain [32]. Receptors play a
key role in neurotransmission and are highly relevant for
understanding neurological and psychiatric diseases and
the effect of drugs. So far, however, most of this work
has been based on static interaction representations
that do not capture the full dynamics of the nervous
system at the molecular level. This will require models
that exploit HBP high performance computing capabili-
Living human neurons from stem cells. It is now possible to study living human neurons derived from
human-induced Pluripotent Stem Cells (iPSCs) [29]. The
combination of iPSCs with developmental neurobiology
makes it possible to model human cortical function in a
dish [30] and to generate human neurons carrying specific disease mutations [31].
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ties to describe the time evolution of molecular species.
There is evidence that many diseases (e.g., epilepsy,
schizophrenia, major depression) depend on equilibrium among multiple receptors. Modelling and simulation provide an essential tool for understanding these
complex mechanisms.
Such a model is a prerequisite for the analysis and integration of top-down and bottom-up processes.
3.3.4 Operational Objectives and Related Actions
WP2.1 Genetic and molecular architecture: characterise inter-individual genetic variation; obtain
single cell transcriptomes, together with data on
epigenetics, genetic regulatory networks, proteome
composition and organisation, and the distribution of
transporters, ion channels, receptors and complexes.
Brain models require precise data on the cellular organisation of different brain areas (e.g., cortical layers and
columns) and their intrinsic connectivity at micro- and
meso-scales including neuron type-specific connections such as clustered connections. Unravelling the
intrinsic wiring rules of identified human cortical areas
will pave the raod to high fidelity large-scale modelling.
Recent studies have combined post mortem studies of
laminar cell distributions with in vivo diffusion techniques
to measure the distribution of cell and fibre diameters,
opening the road to in vivo studies of human cytoarchitecture and connectivity.
cells: characterise micro projections (e.g. synaptic connections between neighbouring neurons);
measure the density and distributions of excitatory
and inhibitory synapses, and numbers and distributions of organelles (e.g. mitochondria); identify synaptic selectivity principles; characterise the structural
relationships between neurons, glial cells and the vascular system; capture the morphologies of neurons
and glial cells.
Techniques introduced by SP2 will make it possible to
generate new data sets of critical importance for reconstruction of the human brain.
WP2.3 Circuit architecture: characterise afferent
maps using transparent brains and PLI; characterise
tract structure (fibre composition and distribution,
topographical organisation); characterise inter-subject variability in circuit architecture.
Multiplying the diffusion MRI acquisition time on a 7T
magnet with a powerful gradient system over 5 to 10 sessions will make it possible to perform imaging protocols
with varying water diffusion time, and thus to estimate
the distributions of axon diameters in each fibre bundle.
These distributions will be used to count the number of
axons in each bundle — a key parameter for simulation.
Data will be validated against PLI data from post mortem
specimens. The same dMRI acquisition protocol may
make it possible to distinguish boundaries cortical architectural in vivo, and to link them to the functional maps.
WP2.4 Theory and informatics: identify principles
comparisons and multi-scale theory; identify principles
governing the spatial architecture of brain regions, of
neuronal populations and of synapse types; develop a
theory of structural-functional relationships; develop
techniques to characterise cognitive architectures;
develop techniques of big data management, and link
to HBP Atlases; develop benchmarks for modelling and
simulation.
PLI will provide information about connectivity of the
human brain that is far beyond existing knowledge, offering excellent spatial resolution at the micrometre scale
and allowing the identification of currently unknown fibre
tracts. This will have important implications both for basic
research and for clinical applications (e.g., studies of diseases such as stroke, multiple sclerosis, and schizophrenia, that are characterised by changes in connectivity).
WP2.5 Integrative map: develop an integrative,
multi-level map of the whole mouse brain including data on cell numbers and distributions, neuron-glial ratios, excitatory-inhibitory ratios, cellular
composition (location-dependent composition
in terms of morphological, electrical, projection,
molecular and genetic subtypes of neurons), gene
and protein expression (e.g. ion channels, receptors, synapses), and single-cell transcriptomes;
identify topographical and metabolic relationships between blood vessels, neurons and glial
cells; characterise inter-subject variability; identify
principles of structural segregation (cortical areas
and nuclei); visualise cells and fibres in the whole
brain; develop whole brain maps from transparent
brains; identify principles of functional segregation; develop and apply advanced topographical
and image fusion methods.
SP2 will develop a microstructural model of the whole
human brain on the cellular scale. The model will serve
as a reference brain with ultra-high resolution, and as
a source of morphometric data. The Subproject is collaborating with the Netherlands Brain Bank Amsterdam
(http://www.brainbank.nl) to record and label neurons
from post mortem specimens. This work will yield 3D
morphological reconstructions of neurons from different areas of the brain together with single cell-type
transcriptome (SCT) data. These data are critically
important for reconstructions of the brain.
SP2 will also perform a systematic analysis of the
receptor architecture of transmitter systems, providing a “gold standard” for in vivo receptor PET studies
of normal subjects and patients. The results will make
it possible to identify hierarchies of areas, and thus to
develop a theoretical model of cortical organisation.
WP2.6 Scientific coordination: coordinate scientific activities within the SP, and with other SPs,
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Appendix 1
Partnering Projects and international collaborations,
coordinate quality assurance, organisation of
jects recruited and ethical approval received for in
vivo connectomics and functional neuroimaging;
initial datasets generated for neuronal and glial cell
compositions and genetic architecture; initial data
uploaded to human brain atlas on the Neuroinformatics Platform.
3.3.4.2Partnering Projects
WP2.7 Physiological data: generate targeted physiological data going beyond the data sets collected
in the Core Project; possible data sets include but
are not limited to data on whole brain dynamics
neuroendocrinology and neuroimmunology, metabolism and energetics, microcircuit dynamics and
information processing, the physiology of neurons
and synapses, receptor and channel biophysics, and
gene expression.
M60: HB2 - Initial multi-level targeted mapping of the
human brain; datasets generated for synapses, channels, neuronal network and behaviour, as well as neuronal and glial cell morphologies obtained and uploaded
to human brain atlas on the Neuroinformatics Platform; transcriptome and epigenetics data connected
to cell morphology and connectomics; neuro-vascular
relationships; updated cortex parcellation.
WP2.8 From genes to cognition: perform experimental and informatics studies on the link between genes
and cognition and the impact of normal genetic variations and mutations; develop links to human brain
disease signatures established in SP7 and to humanrelated work in SP1.
M90: HB3 - Initial multi-level map of the human brain
incorporating data from Core Project, Partnering Projects and collaborations; predictive reconstructions and
refocused experimental mapping; synaptic properties;
neuron and glial morphologies; whole brain cognitive
and genetic maps, initial integrated atlas.
WP2.9 Functional architectures of cognition: generate data on functional architectures of cognition in
humans; possible themes include multi-modal perception and action; motivation, reward and decision
making; synaptic plasticity, learning, memory and
goal-oriented behaviour; representations of space
time and quality in planning and navigation; the architecture of gene-behaviour-environment interactions.
M120: HB4 - Draft multi-level map of the human
brain including brain regions, cellular distributions,
cell-types, connectivity between and within brain
regions, connectivity between local neurons, cellular protein and receptor distribution and their
gene expression, synaptic proteins; comprehensive
models of human specific mental processes established and their relationship to structural, genetic
and epigenetics described; concepts of multi-level
brain organisation.
WP2.10 Comparative studies: perform research comparing structural and physiological data in mouse,
humans, non-human primates, and other animals (joint
work package with SP1).
3.3.6 Risk Analysis
R2.1 Failure to generate sufficient volumes of data
owing to technical and/or organisational problems
The HBP will work closely with existing and future initiatives that generate structural and functional data
about the human brain or comparable data for other
species (non-human primates, simpler animals, etc.).
This risk has the same characteristics as R1.2,
described in paragraph 3.2.6.
3.3.7.1 Scientific impact
Other collaborations will focus on comparisons
between the human brain and the brains of other
species, and on genotype/phenotype relationships.
Especially important will be collaboration with the
Allen Brain Institute and with the US BRAIN Initiative.
IMP2.1 The data generated in SP2 will make a vital contribution to the multi-level Atlas of the Human
Brain, created in SP4.
IMP2.2 The data generated in SP2 will provide the initial
reconstructions and simulations of the human
The Project may also develop collaborations with initiatives addressing related themes. Examples include
the role of the prenatal alterations in gene expression
and postnatal environmental influences, brain development, aging, and inter-individual variations.
3.3.7.2 Social Impact and Innovation Potential
M30: HB1 - Protocols established for post mortem
connectomics and multi-level architecture; sub-
The social impact of SP2 and its contribution to innovation
will be indirect, through its contribution to other Subprojects.
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Appendix 1
3.4 Subproject 3: Theoretical and
Mathematical Foundations of
Neuroscience
TF4 - A multi-scale theory of brain structure and function
SP3
M120
Milestones
TF3 - Theory-driven brain models of
cognitive processes
M90
TF2 – Large-scale brain models for
neuromorphic implementation
M60
TF1 – Theoretical and mathematical foundations for the HBP
M30
M30
M60
M90
M120
Figure 34: Output Targets and Milestones for SP3: Theoretical and Mathematical Foundations (TF)
and inhibition [36] [37]. In most cases, the output has
consisted of “toy models”, amenable to mathematical
analysis and to simulation on small personal computers.
What is not clear is how to connect the insights from
these models, or how to ground them in detailed biophysical observations.
The overall objective of SP3 is to provide solid theoretical
and mathematical foundations for work performed in the
other SPs.
The Core Project has four goals. The first is to enable horizontal collaboration among in which researchers from
different SPs work together to develop strategies and These are key themes in the work of the theoretical neualgorithims for the comparative assessment of brain data roscientists who have contributed to the preparation of
and data from different model approaches. The second the HBP proposal. For example W. Gerstner has shown
goal is to develop theoretically grounded methods how to extract parameters for simple neuron models
that reduce high-fidelity models to their simplest form, directly from experimental data, and from detailed bioenabling comparisons between bottom-up and top-down physical models [38] [39]. M. Tsodyks, W. Gerstner, N.
models. The third is to integrate top-down models with Brunel, A. Destexhe, and W. Senn have produced models
advanced learning algorithms that replicate the learning of synaptic plasticity suitable for integration in models
and cognitive behaviour observed in non-human animals of large-scale neuronal circuitry [40] [41] [42] [43];
and ultimately in humans.
W. Gerstner, D. Wierstra, and W. Maass have explored
models in which plasticity is modulated by a reward
The final goal is to operate the European Institute for The- signal [23] [24] [44], a basic requirement for so-called
oretical Neuroscience, set up in the Ramp-Up Phase. The reinforcement learning. N. Brunel has produced models
Institute provides a forum where independent neurosci- of population dynamics using networks of randomly
entists following different approaches can work together connected simple neurons [37] an approach exploited
to understand the fundamental computational principles by G. Deco to construct models of decision-making
underlying brain function and to work towards a unify- [45]. A. Destexhe [46] [47] has investigated the inteing theory. This work will be implemented through Part- grative properties of neurons and networks, while W.
nering Projects and in collaborations with other regional, Maass has studied their underlying computational prinnational, European and International Initiatives.
ciples [25] [22].
3.4.3 Advances over the State of the Art
Understood as mathematical modelling, theoretical neuroscience has a history of at least a hundred years. In
general, theoreticians have focused on models addressing
specific levels of brain organisation, for instance, the relation of Hebbian learning to cortical development [33], the
recall of associative memories [34], the link of temporal
codes and Spike Timing-Dependent Plasticity [35] and the
dynamics of neuronal networks with balanced excitation
SP3 aims to develop a multi-scale theory of the brain,
creating a synthesis between top-down and data-driven
bottom-up approaches. A second goal is to unify theories
of learning, memory, attention and goal-oriented behaviour, gaining insights into the way function emerges from
structure, and identifying the data and computing principles required to model specific brain functions in neuromorphic computing systems.
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Other expected theoretical advances include the identification of bridges linking the multiple temporal and spatial
scales implicated in brain activity and in the signals captured by imaging and other technologies; progress in
understanding plasticity, learning and memory, and the
way they shape neuronal circuits; and a better understanding of complex functions such as spatial navigation,
recursion, and symbolic processing. A key advance will
be the development of models, suitable for implementation in neuromorphic and neurorobotic systems and in
large-scale, top-down simulations of the brain.
tation on the Brain Simulation, Neuromorphic
Computing or Neurorobotics Platforms; use the
Platforms for in silico experiments validating and
refining the models; possible themes include but
will not be restricted to perception-action, surprise,
novelty, multi-sensory integration, decision making,
goal-oriented behaviour, reward, wakefulness, sleep,
dreams and the wake-sleep cycle, learning and
memory, working memory, declarative memory,
skills and habits, symbols and language (joint work
package with SP8 and SP9).
3.4.4 Operational Objectives and
Related Actions
WP3.8 Novel brain-inspired architectures for information processing: develop HPC architectures inspired by
theoretical and experimental insights into the structure
and function of the brain (joint work package with WP6
and WP7).
WP3.1 Theory across SP boundaries: develop strategies, principles, and algorithms enabling comparative
assessment of data from the mouse and human brains,
and different modelling approaches; develop theoretical frameworks to predict brain function from structure
and its clinically relevant dysfunctions, compare brain
models with implementations in Neuromorphic Computing Systems, and neurorobotic closed-loop experiments.
WP3.9 Disease modelling: develop theory-driven
models of disease from the biological signatures of
disease and the disease classifications identified by
researchers using the Medical Informatics Platform
(joint work package with SP5 and SP7).
3.4.4.3Collaborations with other National,
European and international Initiatives
WP3.2 Bridging scales: develop simplification strategies
and simplified models from the single cell to the circuit and
higher levels; derive mean field and point neuron models
from morphologically detailed models; investigate multiscale aspects of neural computation, from single cells to
circuits; characterise the biophysical mechanisms underlying brain signals at different scales, from single units to LFP,
EEG, MEG and fMRI.
The European Institute for Theoretical Neuroscience
(EITN), will initiate as many collaborations as possible
with the theoretical neuroscience and mathematicalcommunity outside the HBP. This will be done essentially
through the visiting scientist programme, and by inviting external speakers to participate in HBP workshops.
A long-term goal is to integrate the EITN within a European network of theory institutes. Finally, SP3 will establish collaborations with experimental neuroscientists,
and brain-science related initiatives around the world.
(including the US BRAIN initiative).
WP3.3 Learning and memory: develop plasticity algorithms; develop models for supervised and unsupervised
learning, reward and punishment, and goal-oriented
behavioural learning, suitable for implementation in Neuromorphic Computing Systems.
WP3.4 Models of cognitive processes: develop simplified top-down models single and multiple brain areas,
their dynamics and cognitive functions, for implementation in Neuromorphic Computing Systems; contribute to a multi-scale theory of the brain.
M30: TF1 - Develop theoretical frameworks for comparative assessment of mouse and human brain data;
link the temporal and spatial scales implicated in
brain activity to the signals captured by imaging and
other technologies; develop theories linking plasticity,
learning, memory, neuronal circuits, and behaviour;
model complex functions involving different scales
and plasticity mechanisms.
WP3.5 Large-scale brain models: Brain-scale
network models: develop theoretical frameworks making
it possible to construct and simulate multilayer network
models based on connectivity rules; compare the
behaviour of detailed and models with the approaches
developed in WP3.2, contributing to a multi-scale theory
of the brain; provide a complimentary substrate for topdown modelling in WP3.4; link concepts developed in
SP3 to bottom-up models developed in SP5.
M60: TF2 - Develop theoretical and mathematical strategies for comparative assessment of brain
data and different modelling approaches (analytical
models, large-scale network models, neuromorphic
computing systems, neurorobotics experiments).
M90: TF3 - Develop theory-driven models of cognitive processes at the level of neurons and synapses,
which are implementable by software simulation and
neuromorphic hardware to obtain microscopically
parallel, top-down simulations of brain functions.
WP3.6 Scientific coordination: operate the European
Institute for Theoretical Neuroscience and its visiting
scientists programme, coordinate scientific activities
within the SP, and with other SPs, Partnering Projects
and international collaborations; coordinate quality
assurance, organisation of meetings and reporting.
M120: TF4 - Develop a multi-scale theory of brain
structure and function that creates a synthesis
between top-down and data-driven bottom-up
approaches, and which should help to unify theories of learning, memory, attention and goal-oriented
WP3.7 Model development: develop theory-driven
models of brain function suitable for implemenHBP Framework Partnership Agreement Proposal
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behaviour, leading to a new understanding of the way
function emerges from structure.
neurons, plasticity mechanisms and their impact,
network dynamics and the mechanisms underlying specific cognitive functions.
3.4.6 Risk analysis
IMP3.2 SP3 will implement theoretical insights in highlevel operational models, suitable for implementation in neuromorphic computing.
IMP3.1 SP3 will generate new theoretical insights into
the link between different levels of biological
organisation in the brain, the dynamics of single
The social impact of SP3 and its contribution to innovation will be indirect, through its contribution to other
Subprojects.
No major risks are foreseen for this Subproject.
3.4.7.1 Scientific Impact
Global Collaboration
Mouse Brain
Functional Data
Other Animal Brain
Functional Data
Multi-level
constraints
Data driven model
building
Virtual specimens
Underlying rules
Predicting missing
data algorithms
In-silico
experiments
Complexity
of the data
Multi-constraint
algorithms
Biological
comparisons
Statistical
relationships
Structural
principles
Biological
predictions
Mouse Brain
Structural Data
Human Brain
Functional Data
Other Animal Brain
Structural Data
Theoretical
foundations of
cognition
Predictive
reverse
engineering
Virtual cognition &
behavior
Human Brain
Structural Data
Top down
Principles
of
cognition
Mechanisms
of
cognition
Bottom up
Figure 50. The HBP Vision; future neuroscience, future medicine, future computing
Figure 35: The HBP Vision; future neuroscience, future medicine, future computing
The Human Brain Project | October 2012
1 /1
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3.5 Subproject 4: Neuroinformatics
NI4 – Multi-level atlases for the brain of
selected other species
M120
SP4
Milestones
NI3 – First draft multi-level atlas of the human brain
M90
NI2 – First draft multi-level atlas of the mouse brain
M60
NI1 - Public launch of the Neuroinformatics Platform
M30
M30
M60
M90
M120
Figure 36: Output Targets and Milestones for SP4: Neuroinformatics (NI)
SP4 has two objectives. The first is to build and operate
a Neuroinformatics Platform that makes it easier for neuroscientists to organise and access the massive volumes
of heterogeneous data, knowledge and tools produced
by the international neuroscience community. The first
version will be released at the end of the Ramp-Up Phase,
providing a single source of curated, high-quality data for
the HBP’s brain modelling effort and for the wider international neuroscience community. The second objective
is to develop multi-level atlases of the mouse brain and
the human brain and integrate them into the Platform.
NIMH, to create its own Human Brain Project, an effort
that lasted until 2004. The work produced many important neuroscience databases. However, it never created a
standard interface for accessing the data and provided no
specific tools for relating and integrating the data.
Soon after the NIMH project ended, the OECD launched
the International Neuroinformatics Coordinating Facility
(INCF) [49]. Since 2005, the INCF has driven international
efforts to develop neuroscience ontologies, Brain Atlases,
model descriptions and data sharing, and has played an
important role in coordinating international neuroscience
research and setting up standards. Other initiatives such as
the US-based Neuroscience Information Framework (NIF)
[29], and the Biomedical Informatics Research Network
(BIRN) [50] are collaborating with INCF.
SP4 work in the Core Project will coordinate tool development (e.g., viewers for specific classes of data), promote
the population of the mouse and human Brain Atlases,
and operate the Platform for the benefit of the community. A key goal will be to provide users with effective Another important initiative was the foundation of The
training, mentoring, documentation, helplines, etc. Part- Allen Brain Institute, which, since 2003, has become a
nering Projects will contribute additional tools and data, world leader in industrial-scale data acquisition for neuas described below. SP4 will collaborate closely with roscience. The Institute has recently developed a Brain
other organisations and initiatives with similar objectives, Atlases including the recently published Allen Mouse Brain
in particular, the INCF [26] and the Allen Institute’s Brain Connectivity Atlas [51]. This work contributes directly to
Atlas projects (http://www.brain-map.org).
the HBP brain reconstruction process.
3.5.3 Advances Beyond the State of the Art
World neuroscience research generates an enormous The Neuroinformatics Platform and the Brain Atlases
amount of data. However, there is no plan for organising developed in SP4 will allow neuroscientists to collaband sharing this data, much of which is lost due to inad- oratively curate, analyse, share, and publish large-scale
equate data preservation [48], or is available is often in neuroscience data. SP4 is collaborating with INCF, the
non-standard formats.
Allen Institute and other international partners to develop
a global data registry and knowledge base where data,
The first attempts to provide easy access to high quality, models and literature are registered and annotated with
well-curated data in standard formats date back to high-level metadata, allowing their use in multi-level Brain
1989, when the Institute of Medicine at the US National Atlases. This represents a major step forward.
Academy of Sciences received funding to examine how
information technology could create the tools needed to Brain Atlases will be constructed by curating data , deposithandle the growing volume and diversity of neuroscien- ing them in the data registry and linking them to established
tific data. The study report, published in 1991 [27] enabled atlas ontologies and coordinates for rodent and human
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brains. Central to the goal of curating the data analysis will
be the development of tools for large-scale data analysis
and data mining. The atlases and related tools will be an
important tool for neuroscientists working on predictive
and computational models.
possible tools include but are not limited to tools and
methods for the analysis of large volumes of structural brain data (e.g., image stacks) and for the analysis of large volumes of functional data.
WP4.8 Sensory organs, the spinal cord and the
peripheral nervous system: expand the mouse and
the human brain atlases to accommodate data on
sensory organs, the spinal cord and the peripheral
nervous system in mouse and in humans; generate
initial data sets to populate the expanded atlases.
Related Actions
3.5.4.1 Core Partner Projects
WP4.1 Brain atlas tools, ontologies and shared data
space: develop a shared data space and navigation
tools, a generic atlas builder and tools for a “KnowledgeSpace” (a wiki of multi-level knowledge about
the brain); develop agreed ontologies.
WP4.9 Atlases for other species: create multi-level
atlases for the brains of species not covered by the
HBP Mouse Brain and Human Brain Atlases on the
Neuroinformatics Platform; integrate the atlases
with the HBP Mouse Brain and Human Brain atlases,
enabling cross-species comparisons
WP4.2 Mouse Brain Atlas: develop and maintain a
bring together targeted data from SP2, biological
signatures of disease from SP7, large-scale brainmapping data from the Allen Institute Human Brain
Atlas, the US BRAIN Initiative and others, predicted
data from SP5, theoretical insights from SP3 and knowledge from the literature (via the KnowledgeSpace).
SP4 will collaborate with other existing and future initiatives
to develop global policies and standards for data, ontologies, nomenclature, data preservation and data sharing.
Particularly important will be collaboration with the International Neuroinformatics Coordinating Facility (INCF).
WP4.3 Human Brain Atlas: develop and maintain a
bring together targeted data from SP2, biological signatures of disease from SP7, large-scale brain-mapping data from the Allen Institute Human Brain Atlas,
the US BRAIN Initiative and others, predicted data
from SP5, theoretical insights from SP3 and knowledge from the literature (via the KnowledgeSpace).
Other planned collaborations include the Allen Brain
Institute, Seattle Washington, USA; the US BRAIN initiative funded by NIH, NSF and DARPA; the Visible Brainwide Networks Project of the Britton Chance Center
for Biomedical Photonics in Wuhan China; the Australian Research Center of Excellence for Integrative Brain
Function, led by Monash University; the Kavli Foundation
Neurodata without borders initiatives; and the CENTERTBI, International Traumatic Brain Injury Study.
WP4.4 Theory and big data engineering: develop
theory-driven methods for predictive neuroinformatics, feature extraction, and data clustering; develop
tools, models and data-management technology for
efficient, large-scale provenance tracking, data analysis,
data mining and management of exascale data; develop
algorithms for large-scale predictive data analytics and
for the generation, maintenance, and mining of provenance links.
M30: NI1 - First version of Neuroinformatics Platform,
including service APIs for data federation, publication, discovery, access and navigation; interfaces for
uploading and annotating data with high-level metadata, including contributor, experimental protocol,
organism, location, data type; initial tools for navigation and data upload.
WP4.5 Neuroinformatics Platform: design, implement and operate an ICT Platform providing community access to the Atlases and related tools. Provide
documentation, training and support for users of
the Platform. Integrate the Platform with the HBP
Unified Portal.
M60: NI2 - Initial multi-level Mouse Brain Atlas
including data for whole brain structure, brain
region parcellation, nuclei, layers/modules, vasculature, cellular distributions, single cell transcriptomebased cell types, morphologies, electrical behaviour,
protein and gene expression, synaptic density and
types, neuron and glia morphologies, axonal projections between and within brain regions, synaptic
connectivity between neurons.
activities within the SP and with other SPs, Partnering
Projects and international collaborations; coordinate
M90: NI3 - Initial multi-level Human Brain Atlas including data for whole brain structure, brain region parcellation, nuclei, layers/modules, vasculature, cellular
distributions, single cell transcriptome-based cell types,
morphologies, electrical behaviour, protein and gene
expression, synaptic density and type, neuron and glial
morphologies, axonal projections between and within
WP4.7 Methods and tools: develop methods and
tools expanding the functionality of the Neuroinformatics Platform and integrate them into the Platform;
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Appendix 1
Contingency plans: If necessary, the Project will
seek funds from outside the Project for running and
operating the Platform.
brain regions, synaptic connectivity between neurons.
M120: NI4 - Detailed multi-level and mouse and human
brain atlases incorporating structural and functional
data from Core Project, Partnering Projects and collaborations; data covers molecular, subcellular, cellular,
microcircuit, brain region and whole brain level; relationships between genetics and epigenetics, structure, cognition and behaviour; data management tools for the
analysis, mining and tracking of exascale data.
End of risk: For specific SGA cycles the risk will be
cleared when the Project demonstrates it can operate
the Platform for a satisfactory number of users. However,
funding risks will persist for the whole duration of
the Project.
3.5.6 Risk Analysis
R4.3 Lack of community uptake (Probability: high;
Impact: moderate).
R4.1 Risk of delay in cell-type transcriptomics (Probability:
medium; Impact: moderate).
Risk: The HBP Brain Atlases need to be populated
with experimental data, only a small proportion of
which will come from within the Project.
Risk: A large part of the planned work in SP4 consists of
software development and thus involves an un-eliminable
risk of delay and technical failure.
Impact: If the atlases are not sufficiently populated,
they will not provide the data required for brain
modelling and will not offer a useful service to the
community. This issue is most urgent for mouse data.
Impact: A delay in the release of a specific version of a
specific module will lead to the loss or downgrading of
the functionality it provides, but will not compromise the
release or the performance of the other modules. The
development plan can accommodate delays without
endangering key Milestones or Deliverables.
Contingency plans: The subproject is already investing significant resources to recruit and engage
potential users. If uptake is low it will most probably be because the tools are not tailored to Use
Cases that the users care most about. This will
be addressed by iteratively refining the Platform
development goals to focus on the most valuable
Use Cases. The Platform team is following an iterative release strategy that expects and encourages
regular refinement of development goals.
Contingency plans: SP4 and the other SPs developing
Platforms have mitigated this risk by adopting a modular,
incremental development process in which no module
depends on a specific version of another module. This
minimises the risk that a single technical problem or delay
will compromise the overall development schedule.
End of risk: The risk for specific versions of the Platform
will be cleared with the releases planned in M30, M60,
M90 and M120. However, the general risk of delay will
persist for the whole duration of the Project.
End of risk: The risk will only be cleared one or two
years into the operational phase when the Platform
has been open to the community for sufficient time
to become well-known
R4.2 Insufficient financial resources for effective
operation of Platform (Probability: moderate; Impact:
moderate).
Risk: Operating the Neuroinformatics Platform
from M30 onwards will require significant financial
resources for the purchase and maintenance of hardware, connectivity, technical support and education, etc.
IMP4.1: SP4 will facilitate neuroscience research,
inside and outside the HBP, by creating and maintaining multi-level atlases of the mouse and human brain
and related atlasing tools, and by making them available through the HBP Neuroinformatics Platform.
The resources required go beyond the resources available in the CP budget. It will thus be necessary to obtain
alternative sources of funding. There is a risk that such
funding may not be available.
IMP4.2: By creating a major public data resource,
SP4 will strengthen Europe’s position as leader in
international neuroscience research.
Impact: The CP budget contains sufficient funds to
support operation of the different versions of the Platform.
However, lack of funds would limit the number of users the
Platform could serve and the quality of services.
The social impact of SP4 and its contribution to innovation will be indirect, through its contribution to
other Subprojects.
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Appendix 1
3.6 Subproject 5: Brain Simulation
BS4 - Draft multi-level reconstruction and simulation
of the human brain
M120
SP5
Milestones
BS3 - Draft multi-level reconstruction and
simulation of the mouse brain
M90
BS2 – Draft cellular-level reconstruction and
simulation of the mouse brain
M60
BS1 – Initial cellular-level reconstructions of brain regions and systems
M30
M30
M60
M90
M120
Figure 37: Output Targets and Milestones for SP5: Brain Simulation (BS)
Traub [55] [56] used an IBM 3090 mainframe computer
to simulate 10,000 neurons, each with about twenty
compartments. Since then, rapid improvements in supercomputer performance have made it possible to simulate ever-larger models. In 2007, Djurfeldt et al. reported
a large-scale simulation of a columnar cortex with 107
detailed multi-compartment neurons and 1010 synaptic
connections [57]. In the same year, Morrison reported the
simulation of a network with 109 synapses and spike-timing dependent plasticity (STDP) [58]. In 2009, the Modha
group at the IBM Almaden Research Centre reported the
simulation of a network, with roughly the same numbers
of neurons and synapses as the brain of a cat (109 neurons
and 1013 synapses) [59] [60]. In 2012 Potjans and Diesmann [61] carried out a simulation of a cubic millimetre
of cortex using single compartment model neurons that
accounted for 8 neuronal populations. This simulation
was full-scale in the sense that all local synapses were
represented. Recently, Jülich and RIKEN reported the
simulation of a generic random network of single compartment neurons with synaptic plasticity and a total of
1.73 109 billion nerve cells connected by 1.04 1013 synapses
orchestrating about a petabyte of main memory [62].
SP5 has two objectives. The first is to establish a generic
strategy to reconstruct and simulate the multi-level
organisation of brain. The second is to use this strategy
to build high-fidelity reconstructions, first of the mouse
brain and ultimately of the human brain. As the Project
proceeds, the Core Project will integrate the tools and
workflows it develops in a Brain Simulation Platform,
which it will make available to the Community for collaborative reconstruction and simulation.
In the first five years of the Project, the Core Project
will develop and validate the reconstruction process in
mouse—the species for which the most data are available. In the following five years, it will produce a first draft
reconstruction of the human brain. This work will involve
the integration of sparse data from the human brain
with data inferred from non-human primates, mouse,
and simpler animals. Partnering Projects will enrich the
Platform with new capabilities (e.g., data-driven models
of sensory organs and spinal cords, new algorithms and
workflows, and new techniques of data analysis and visualisation). Users of the Platform will perform novel forms
of in silico experimentation (e.g., experiments investigating the multi-level mechanisms leading from genes to
behaviour, disease simulation and drug simulations).
In parallel with this work on very large-scale networks,
other groups have developed general-purpose simulators allowing simulation of the brain at different levels
of biological detail. For example, NEURON [63] makes
it possible to simulate morphologically complex neurons
and networks of neurons,. STEPS [64] MCELL [65] and
Brownian Dynamics simulations bridge the gap between
NEURON’s compartment electrical model and the
molecular-scale processes of diffusion in complex fluid
environments and reaction mechanisms such as ligand
binding to receptors. To date, however, there have been
relatively few attempts to integrate models and simulations across multiple levels of biological organisation.
This is one of the aims of EPFL’s Blue Brain Project [66],
which has developed software and workflows [67] [68]
to reconstruct the neural microcircuit of juvenile rat,
Early models of the brain explained brain functions, such
as learning and memory, in terms of the behaviour of
neurons and neuron populations, thus giving rise to the
fields of Artificial Neural Networks and Machine Learning
[52]. In parallel, other researchers developed mechanistic models. In particular, Hodgkin and Huxley’s seminal
model of the generation of neuronal action potentials
[53] and Rall’s application of cable theory to signal
propagation in dendrites [54] made it possible to build
models of the brain from its basic components. Other
models cast light on the dynamics of large networks of
excitatory and inhibitory neurons. In the 1980s, Roger
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Appendix 1
from detailed anatomical and electrophysiological data.
This work continues in the HBP.
from the Neuroinformatics Platform; develop methods
for provenance tracking and validation of brain models.
WP5.2 Multi-scale simulation software: develop,
update and maintain brain simulation engines for molecular dynamics, reaction-diffusion dynamics, cellular-level
simulation and point neuron network simulation.
SP5 is developing a generic strategy to reconstruct and
simulate the multi-level organisation of the brain. Topdown models have been established for several decades.
SP5 offers a complementary, bottom-up approach that
makes it possible, for the first time, to achieve a mechanistic understanding of brain function.
WP5.3 Molecular models and simulations: build and
simulate molecular-level models of neurons, synapses,
glia and vasculature; develop multi-scale (atomistic and
coarse-grained) molecular modelling and simulation to
characterise molecular interactions (notably, proteinprotein and protein-drug interactions) and to obtain
thermodynamic and kinetic parameters, filling gaps in
experimental knowledge.
With current technology, there is no practical way to
measure every aspect of the brain experimentally, and it
is extremely unlikely that this will become possible at any
time in the foreseeable future. SP5 offers a novel solution
to this seemingly intractable problem, leveraging interdependencies within and between levels, thereby avoiding
the need to measure everything. This implies a change in
the criteria for what to measure. Classical neuroscience
assesses data according to the light it throws on specific
hypotheses. In contrast, the HBP prioritises data that
are constrained by, and that constrain other data. Implemented in multi-constraint algorithms, these interdependencies make it possible to reconstruct the brain from
sparse datasets, and to predict the data points needed to
fill gaps in our knowledge.
WP5.4 Mouse brain models: develop models of the
mouse brain at the subcellular, cellular, micro (column/
brain) levels.
WP5.5 Human brain models: develop models of the
human brain at the subcellular, cellular, micro (column/
brain) levels.
WP5.6 Theory: understand the relationship between
brain structure and function, contribute to a multi-scale
theory of the brain; generate simplified models for implementation in Neuromorphic Computing Systems.
The strategy proposed by the HBP is generic. In principle,
it can be used to reconstruct and simulate the whole brain
or any part of the brain of any healthy or diseased animal,
of any species or gender, at any age. In silico experiments
based on high-fidelity reconstructions and simulations
will allow researchers to perform experiments that would
not be possible in the laboratory. Examples include experiments to dissect the role of different levels of biological
organisation in cognition and behaviour, and simulations
of brain disorders to test hypotheses of disease causation,
candidate treatments and their mechanisms of action. The
HBP Brain Simulation Platform will give researchers the
tools to perform such experiments. This is an enormous
step beyond the current state of the art, and represents a
phase-shift for neuroscience.
WP5.7 Brain Simulation Platform: design, implement
and operate an ICT Platform, enabling researchers to collaboratively reconstruct and simulate the brain; provide
documentation, training and support for users of the Platform; integrate with the HBP Unified Portal.
activities within the SP and with other SPs, Partnering
SP5 will develop a novel multi-scale simulation approach
that makes it possible to link scales from molecules to brain
activity, and to run simulations in which different regions
of the brain are simulated at different levels of detail, at
different points during the simulation. This will require
major advances in supercomputer simulation technology
enabling dynamic coupling of different simulation engines,
and the use of advanced techniques in data management
and load balancing.
WP5.9 Tools, methods and workflows: develop tools,
methods and workflows expanding the functional
capabilities of the Brain Simulation Platform; possible
topics include but are not limited to new techniques
for multi-scale simulation, new simulation engines and
enhancements to existing engines, new tools for data
analysis and visualisation, and virtual instruments (in
silico molecular imaging, large-scale synaptic imaging,
whole-brain in silico electrical recording, in silico optogenetics, virtual MRI, DTI, and PET).
Related Actions
WP5.1 Algorithmic reconstruction of the brain: develop
algorithms for multi-level (molecular, sub-cellular and cellular level) reconstruction of neurons, synapses, glia and
vasculature, microcircuits, meso-circuits (brain regions),
and macro-circuits (the whole brain); implement theoretical insights from SP3 in algorithms for synaptic plasticity, re-wiring, axon remodelling and neuromodulation;
develop tools enabling automated integration of data
WP5.10 Brain reconstruction: develop high-fidelity
reconstructions of specific regions of the mouse or
human brain, or of specific levels of biological organisation not fully covered by HBP models; create high-fidelity
reconstructions of the brains of species not covered by
the HBP; create data-driven models of sensory organs or
the spinal cord.
WP5.11 In silico neuroscience: use the Brain Simula-
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Appendix 1
tion Platform (where necessary, in combination with the
Neuromorphic Computing or Neurorobotics Platforms)
for in silico experiments in basic neuroscience, cognition
and behaviour.
and behaviour experiments in Partnering Projects.
M120: BS4 - Algorithms and workflows for predictive multi-level reconstruction and simulation of the
mouse brain; first draft multi-level reconstruction
and simulation of the human brain; in silico validation
experiments for human brain models; in silico neuroscience, cognition and behaviour experiments; first
publications of in silico neuroscience, cognition and
behaviour experiments in Partnering Projects.
WP5.12 Disease and drug simulation: use biological
signatures of disease from the Medical Informatics
Platform and simulation capabilities from the Brain
Simulation Platform to gain new clinical insight; possible themes include mechanisms of disease causation, mechanisms of action of known therapeutic
agents, and screening of drug candidates (joint work
package with SP7).
3.6.6 Risk Analysis
R5.1 Delays in deployment of required supercomputing power (Probability: high; Impact: moderate).
WP5.13 Other Applications of Brain Simulation:
Develop other applications of brain simulation of
commercial and/or clinical value; examples include
fast prototyping of new experimental methods; fast
prototyping of neuroprosthetic devices, etc.
Risk: Molecular-level reconstructions of small areas of
the brain and cellular-level reconstruction of the whole
mouse and the human brains will require multi-petaflop and ultimately exascale supercomputing capabilities. Delays in deployment would delay the Project.
Possible causes of delay include technical difficulties
in building or deploying exascale machines, difficulties in negotiating agreements with Partners providing supercomputing capabilities and difficulties in the
procurement process.
European and International Initiatives
SP6 will collaborate with other existing and future initiatives to jointly develop large-scale brain models. Particularly important will be collaboration with the Allen
Brain Institute, Seattle Washington, USA on models of
the visual and motor systems of the mouse ultimately
leading to models of visuomotor behaviour in mouse.
Collaboration with CENTER-TBI will provide data on specific traumatic brain injury lesions and multi-level data including electrophysiology, imaging and cognitive measures
that could be used to build models of brain injury.
Impact: Delays would impact plans to reconstruct
and simulate the whole mouse brain and ultimately
the whole human brain. However, work on key tools,
models and workflows would continue. Delays would
thus cause a shift in the Project roadmap but would
not prevent progress towards its scientific objectives.
The Project’s multi-scale modelling strategy means that
large-scale simulations would still be possible but with
a lower level of granularity than originally planned.
M30: BS1 - Initial version of Brain Simulation Platform
incorporating algorithms and workflows for predictive reconstruction of subcellular, cellular, microcircuit, and meso-circuit (brain region/system) levels;
tools and protocols for image analysis and for in silico
experimentation and model validation; initial models
of molecular-level cortical neurons, cellular-level
reconstructions of mouse brain regions, and networklevel models of the whole mouse brain; simplified
models exported for implementation in neuromorphic computing systems.
Contingency plans: Discussions with possible Partners
have begun. If deployment of large supercomputing
resources is delayed, the Project will use the resources
it has already acquired.
End of risk: The risk with respect to multi-petaflop
capabilities will be cleared with the installation of a
multi-petaflop machine at Jülich, planned for late 2018.
The risk with respect to exascale capabilities will be
cleared in the last years of the Project.
M60: BS2 - Algorithms and workflows for predictive
reconstructions and simulations of the whole mouse
brain at the cellular level; first draft reconstruction
and simulation of the mouse brain at the cellular level;
tools and protocols for image analysis and for interactive in silico experimentation and model validation;
predictive reconstruction of molecular level neurons,
synapses and glia; first publications of in silico neuroscience experiments in Partnering Projects.
R5.2 Delays in generation of data required for modelling (Probability: medium; Impact: medium).
Risk: The HBP’s reconstruction strategy is designed to
extract the maximum possible value from sparse data.
However the work planned for SP1 and SP2 is critical.
Delays in data generation would cause delays in reconstruction. Possible causes of delay include technical/
scientific difficulties in the generation of new data sets
and managerial/organisational/financial issues.
M90: BS3 - Algorithms and workflows for predictive
multi-level reconstruction and simulation of the mouse
brain; first draft multi-level reconstruction and simulation of the mouse brain; first draft reconstruction of the
human brain at the cellular level; predictive reconstruction
of reactants and reaction kinetics, protein-protein interactions, ion channels, and receptors involved in the action of
drugs; first publications of in silico neuroscience cognition
Impact: In the Ramp-Up Phase, model building will rely
on existing high quality data and on data generated
outside the HBP. However, the data generated in the
Ramp-Up Phase and later phases of the Project are
essential for subsequent model building.
Contingency plans: If volumes of data are insufficient,
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Appendix 1
the Project will build lower fidelity reconstructions until
the necessary data becomes available. If necessary
the RB may decide to reallocate some of the Project’s
financial resources to SP1 and SP2, and/or to bring in
new research groups.
This risk will only be cleared at the end of the Project
End of risk: This risk will fall gradually as the volume
of available data increases, allowing the construction
of steadily more accurate models. The risk will only be
completely cleared towards the end of the Project.
This risk, common to all the Platforms, is described in
paragraph 3.5.6.
R5.6 Delays in software development/insufficient financial resources for operation of Platform/insufficient
community uptake.
R5.3 Failure of predictive strategy (Probability: low;
Impact: very high).
IMP5.1: SP5 will establish high-fidelity reconstructions
and simulations of the brain as an essential tool for integrating and curating multi-level experimental data.
Risk: The HBP proposes a novel predictive strategy that
uses interactions among multiple constraints to generate high-fidelity reconstructions of the brain from
sparse data. Although many prediction methods (e.g.,
prediction of connections from neuron morphology)
are already validated, others have yet to be tested.
Failure of specific prediction methods is probable.
However, complete failure of the strategic approach
seems very unlikely.
IMP5.2: SP5 will establish in silico experimentation as
a powerful method for addressing scientific questions
that cannot be addressed experimentally.
IMP5.3: SP5 will establish brain simulation as an effective technique for understanding the cascades of biological events implicated in brain disorders.
Impact: Failure of a specific predictive method would not
endanger the Project, though it would delay progress.
Failure of the overall Project’s predictive strategy would make
it impossible to build high-fidelity reconstructions, and
prevent the Project from achieving its strategic objectives.
IMP5.4: The Brain Simulation Platform will make it
possible for the first time for academic researchers
to use reconstructions and simulations of the brain in
their research.
Contingency plans: The Project is already exploring
multiple predictive methods. This strategy reduces
dependency on any specific method.
IMP5.5: SP5 will generate fundamental new insights
into the basic computational mechanisms underlying
human and animal cognition and behaviour.
End of risk: The first high-fidelity reconstructions of
the mouse brain, planned for M60 will demonstrate the
general validity of the Project’s approach and reduce
risk. However, the sparse data available for the human
brain poses additional issues. This risk will completely
cleared only at the end of the Project.
IMP5.6: Simplified reconstructions of the brain will
serve as the basis for novel neuromorphic computing
systems and devices.
IMP5.7: SP5 will establish European scientific
leadership in high-fidelity reconstructions and
simulations of the brain and their technological and
clinical applications.
R5.4 Technical/scientific problems in the reconstruction process (Probability: high; Impact: moderate).
Risk: The HBP represents the first attempt to build
high-fidelity reconstructions of the brain. This implies a
high risk of scientific/technical problems.
The social and economic impact of SP5 will be indirect,
through the Subproject’s contribution to the development
of new services for disease and drug simulation in SP5
and new neuromorphic and neurorobotic technologies in
SP8 and SP9.
Impact: In the Partners’ experience, technical/scientific
problems have caused delays but have not had a major
impact on the Project’s ability to achieve its strategic
goals. Future problems are likely to have a similar effect.
3.6.7.3 Innovation Potential
Contingency plans: SP5 adopts a modular, incremental reconstruction process in which many activities are
carried out in parallel. This minimises the risk that a
single technical problem or delay will compromise the
overall schedule.
IMP5.8: The research conducted in SP5 will make it
possible to create brain simulation services for commercial researchers in neuroscience, computing,
medicine, and pharmacology.
IMP5.9: Tools for brain reconstruction and simulation have the potential to generate licensing revenues
from commercial users in the pharmaceutical and
computing industries.
IMP5.10: Models of specific diseases have the poten-
End of risk: The first high-fidelity reconstructions of
the mouse brain, planned for M60 will demonstrate the
general validity of the Project’s approach and reduce
risk. However, the human brain poses additional issues.
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Appendix 1
tial to generate licensing revenues from users in clinical and pharmacological research.
to generate licensing revenues from technology
developers wishing to develop their own Neuromorphic Computing Systems.
IMP5.11: Simplified brain models have the potential
Electrical, biochemical
and pharmacological
properties
Structural
framework
For molecules
Synthesize neuronal
morphologies &
ultrasctructure
Geometrical
Constraints for
connectivity
Identify structural
connectivity, form
functional connectivity &
activate plasticity
Protein & biochemical
Kinetics, biophysics &
interactions
Local & global
constraints
Synapses counts,
shapes, positions &
selectivity rules
Protein life cycles,
biochemical networks &
metabolism
Gene-morphology
correlations
Pairwise transcriptomes
to predict synaptic
proteins
Cellular
proteomics
Morphology exemplars
& characteristic
morphometric statistics
Synaptic proteomics
The Interactome
Predicting the numbers,
distributions, kinetics, and
interacions of proteins
The Connectome
Gene Expression
Patterns
In Single Cells
Synthesizing projecting
axons according to global
connectivity data constraints
Protein translation rules
Cell counts &
cell ratios
Gene expression rules &
activity dependence
Whole Brain proteomics &
protein distributions
Gene expression
clustering
Whole brain protein and
gene expression maps
The Cellome
Classify cell types
in terms of gene
expression patterns
Converge local & global
constraints
Derive cellular
composition of the brain
Figure 38: The HBP Generalisation Strategy. Reading gene expression patterns.
Figure 13. The HBP Generalization Strategy: Reading gene expression patterns
The Human Brain Project | October 2012
1 /1
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Appendix 1
3.7 Subproject 6: High Performance
Computing
HPC4 – Exascale data-centric, interactive multi-scale
supercomputer
M120
SP6
Milestones
HPC3 - Pre-exascale, data-centric, interactive
supercomputer
M90
HPC2 – Pre-exascale data-centric supercomputer
M60
HPC1 – Seamless access to supercomputing resources
M30
M30
M60
M90
M120
Figure 39: Output Targets and Milestones for SP6: High Performance Computing (HPC)
The Partnering Projects will extend the Platform with new
HPC technologies and architectures and will study ways
of integrating neuromorphic technologies in HPC systems.
The goal of SP6 is to provide the HBP Flagship Initiative and the wider community with the supercomputing
capabilities, systems and middleware necessary to simulate multi-scale models of a complete human brain.
Since the introduction of the first supercomputers in the
1960/70s, trends in computer performance and memory
have followed “Moore’s Law”, doubling the number of
transistors on a computer chip approximately every eighteen months. According to the International Technology
Roadmap for Semiconductors (ITRS) [69] this trend will
continue for several processor generations to come.
The first objective of the Core Project is to design and
operate the HBP High Performance Computing Platform. This will consist of a central HBP supercomputer
complemented by three satellite facilities dedicated
to software development, molecular dynamics simulations, and massive data analytics, respectively. The first
version of the Platform will be operational at the end of
the Ramp-Up Phase. Over the duration of the Project,
it will gradually evolve toward exascale performance
and data management capabilities, complementing the
capabilities provided by the Partnership for Advanced
Computing in Europe (PRACE) and others. The hardware capabilities required will be based on innovative,
energy efficient technologies including multi and manycore processors, and possibly neuromorphic acceleration. The system will include hierarchical memory and I/O
sub-systems with multi-petabytes of capacity and data
rates of many terabits per second, as well as hardwareintegrated optical communication technologies with the
lowest possible latencies, possibly complemented by
brain-inspired communication sub-systems.
Since the introduction of the Cray-1 in 1976, improvements
in supercomputer performance have outstripped Moore’s
Law, increasing by roughly a thousand fold every ten
years - an improvement primarily due to ever increasing
numbers of processors. Achieving exaflop performance
by 2020 – a thousand-fold increase with respect to 2010
– will require further massive increases – a goal that poses
severe technical challenges [70] [71]. For environmental
and business reasons, vendors have set themselves the
task of containing energy consumption to a maximum of
20 megawatts per exaflop/s, driving processor design in
the direction of power-efficient many-core CPUs, similar
to today’s GPUs but with greater autonomy. Issues of
resilience combined with memory and I/O constraints
present additional obstacles, including problems with
end-to-end data integrity. With present technology, it is
unlikely that memory capacity and bandwidth will keep
up with the expected increase in compute performance.
The second objective is to design, implement and deploy
the novel software capabilities and algorithms required
for brain simulation. These include enhancements to
existing simulator software, allowing it to make efficient
use of HBP hardware capabilities; novel capabilities for
multi-scale simulation (simulations in which different
areas of the brain are simulated at different levels of
detail); and novel capabilities for interactive visualisation
of reconstructions and simulations.
International supercomputer vendors are making intense
efforts to solve these problems [72] [73]. IBM is exploring the use of storage-class memory technologies, as
in its highly innovative BGAS project. Cray focuses on
the exploitation of parallelism, at all levels. In Europe,
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Appendix 1
CRESTA [74], coordinated by the University of Edinburgh, is working with Cray and others to explore potential applications of exascale computing and to develop
appropriate system software. DEEP [75], led by Jülich,
aims to achieve very high scalability using many-core
X86 technology from Intel and the very low latency
EXTOLL network. DEEP-ER [76]will extend the ClusterBooster architecture of the DEEP project with a highly
scalable I/O system and implement an efficient mechanism to recover application tasks that fail due to hardware errors. Mont-Blanc [77], led by BSC, is working with
Bull to study energy efficiency using Arm embedded
system cores.
included the design and implementation of “integrated
problem solving environments” as one major challenge
[82]. Despite these early, specific requirements, only
limited progress has been made in this direction until
recently. Two popular visualisation systems, Paraview
and VisIt, now include libraries that enable the direct
integration of visualisation capabilities into running simulations [83] [84], either to perform in situ visualisation
and analysis or to present simulation results to the user
at runtime. These capabilities may ultimately lead to the
realisation of interactive steering capabilities.
The “Interactive Supercomputing” capabilities envisaged
by the HBP require changes to HPC hardware architecture, run-time systems and resource management, as
well as novel techniques of visualisation, analysis, and
steering. The HBP supercomputer must allow large
amounts of data to be held within the system, support
dynamic management of all relevant system resources,
and provide in situ visualisation and data analysis. In
addition, new techniques of numerical computing are
needed to achieve the necessary effectiveness.
Since the work of Gerstein and Mandelbrot in the 1960s
[98], brain simulation has always used the latest computing hardware. This tendency continues as teams in the
USA, Europe, and Japan work to increase the power of
simulation technology. In the USA, many of these efforts
are coordinated by the DARPA SyNAPSE programme
[78]. In Japan, efforts to simulate the whole brain are
funded by the MEXT “Next Generation Supercomputer”
project [79]. In 2013, a German-Japanese team led by
researchers from Forschungszentrum Jülich succeeded
in simulating a neuronal network consisting of 1.73 billion
nerve cells connected by 10.4 trillion synapses using the
simulation software NEST on the Japanese K supercomputer [62]. However, even this very large network represents only 1% of the neurons in the human brain.
Dynamic resource management. Complex workflows
including interactive visualisation and data analysis require dynamic management of relevant system
resources (including memory). The HBP will develop
mechanisms to support scenarios in which users launch
long lasting simulations that may request further simulations at different scales to provide parameters at
different points during the simulation process. The
mechanisms provided will allow users to launch analytics computational workflows and visualisation pipelines at any point during a long simulation. Each of the
components will constitute a different application run
within the context of a “session”. Each job will consist
of potentially multiple MPI processes, each potentially
multi-threaded. The relative computational demands of
the different jobs (components of the multi-scale simulation, visualisation and analysis) are likely to change
with time.
Most of the brain simulation projects just described focus
on models with large numbers of neurons and synapses
but with relatively little or no detail at lower levels of biological organisation. By contrast, EPFL’s on-going Blue
Brain Project (BBP) [80], builds and simulate biologically
realistic models. The Blue Brain team has produced a
parallel version of the NEURON code, running on an IBM
Blue Gene/P supercomputer with a peak performance
of 56 Teraflops. The Project has demonstrated that this
capability is sufficient to run cellular-level models with
up to one million detailed, multi-compartment neurons.
A simple extrapolation suggests that after optimisation,
a large system such as the 6 Petaflop Blue Gene/Qsupercomputer at the Jülich Supercomputing Centre
would provide enough computing power and memory to
simulate up to five hundred million neurons. Cellular-level
simulation of the 100 billion neurons of the human brain
will require compute power at the exascale (1018 flops,
100 Petabytes of memory).
Interactive visualisation and steering. Steering of simulations requires novel forms of interactivity that today’s
HPC environments do not usually provide. A key priority
is to reduce data movement. To achieve this, the HBP
will develop software capabilities to filter and visualise
data in situ. This includes streaming data primitives that
extract and efficiently compress the current state of the
simulation before it is shipped to the user for (immersive) visualisation in real time. Further improvements
in performance will be achieved by developing highlyscalable, parallel visualisation and rendering algorithms
as well as by extracting only an approximate state of
the simulation.
A unique requirement of the HBP is that supercomputers should act as flexible interactive scientific instruments,
enabling in silico experiments on virtual brains by providing researchers with visual feedback and allowing them to
“steer” simulations while they are underway. The fundamental idea behind interactive supercomputing was outlined
by McCormick et al. in their landmark report on scientific
visualisation as early as 1987 [81] They state that: “Scientists (sic.) not only want to analyze (sic.) data that results
from super-computations; they also want to interpret what
is happening to the data during super-computations.”
Data-intensive supercomputing. Simulations of detailed
biophysical and multi-scale brain models require large
overall memory capacity and memory bandwidth. For
economic reasons, it is likely that this memory will be
realized as a hierarchy of different technologies. This
requires explicit management of the data distribution
and flow that takes account of these novel memory
Johnson re-iterated this point in his 2006 article on top
challenges for scientific visualisation research where he
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Appendix 1
meetings and workshops and reporting; coordinate
supercomputer procurement and the PPI (Public Procurement of Innovation) process.
technologies. Data-locality aware programming models
and compute offloading will provide means to perform
computation across different levels in the memory hierarchy in a way that is transparent to applications.
New techniques of numerical computing. Real time
demands in steering and accuracy demands in simulation can only be met with substantial progress in numerical methods. Optimal complexity will be achieved by
developing new multi-level algorithms for all different
scales of human brain modelling. The new numerical methods will respect the design of the simulation
software developed by the neuroscientific simulation
community, as well as the architecture of current and
upcoming supercomputers. Further, communicationavoidance will be integrated, resulting in highly efficient
massively parallel numerical algorithms tailored for the
specific needs of brain simulation.
WP6.8 Technologies and architectures: develop
supercomputing technologies and architectures
meeting the specific requirements of brain simulation
and expanding the capabilities of the High Performance
Computing Platform; possible themes for research
include novel solutions for multi-scale simulation, novel
solutions for resiliency, fault tolerance and self repair;
new hardware/software solutions for memory and I/O
hierarchies, new interconnect architectures. Joint work
with WP6.9 for HW/SW co-design.
Related Actions
WP 6.9 Soft ware, alg orit hms and num eri ca l
methods: develop software, algorithms and numerical
methods that meet the specific requirements of brain
simulation and expand the capabilities of the High Performance Computing Platform: joint work with WP 6.8
for HW/SW co-design.
WP6.1 Simulation technology components: develop
specialised methods and libraries for the data structures, algorithms and numerical methods used in
brain simulator software; develop domain-specific
languages and tools for code generation.
WP6.10
Hybrid
HPC-neuromorphic
architectures: develop conceptual designs for hybrid
HPC-neuromorphic computing systems for energy
efficient, accelerated simulations in neuroscience;
demonstrate feasibility using the Neuromorphic
Computing Platform and the HBP Platform; possible
architectures include hybrid systems linked across
networks, on-board hybrids, on-chip hybrids (Neuromorphic cores) (joint work package with SP8).
WP6.2 Data-intensive supercomputing: develop
programming models, middleware, libraries, algorithms and data stores to exploit data locality and
avoid data movement on supercomputing systems.
WP6.3 Interactive visualisation software: develop
middleware and functionality for large-scale visual
data analysis, including semantic linking; develop
software for large-scale, interactive and immersive
visualisation environments.
WP6.11 Novel brain-inspired concepts for information processing: develop HPC concepts inspired by
theoretical and experimental insights into the structure and function of the brain (joint work package
with SP3 and SP5).
WP6.4 Dynamic resource management: develop
libraries, APIs, and scheduler software enabling
applications to dynamically change their use of
resources; develop middleware and libraries for in
situ and co-scheduled execution of analysis and
visualisation filters on heterogeneous hardware.
3.7.4.3 Collaborations with other National,
SP6 will work closely with industry and with existing
and future research projects and relevant research
communities engaged in the development of High Performance Computing Technologies and related software. Possible themes for collaboration include next
generation compilers and runtime systems, debugging
and virtualisation techniques for supercomputing, and
fault tolerance.
WP6.5 Performance modelling and hardware/software co-design: develop tools, models, description
languages, and simulation frameworks to model software performance on different machine architectures.
WP6.6 High Performance Computing Platform: design,
implement and operate an ICT Platform providing
access to the tools, models and simulations developed
in SP5; support industry-strength software deployment
through software development processes, continuous
integration, continuous deployment, and Platform
as a Service (PaaS); support performance tools and
auto-tuning for efficient user-driven analysis; provide
documentation, training and support for users of the
Platform; integrate with the HBP Unified Portal.
M30: HPC1 - First version of High Performance Computing Platform; fully operational Platform based
on HBP supercomputer (Jülich), HBP development
system (CSCS), HBP supercomputer for molecular
dynamics (BSC), HBP supercomputer for big data
analytics (Cineca), Cloud storage (KIT), and high-fidelity visualisation systems (RWTH, EPFL); high speed
network connecting HPC sites; web-enabled Platform
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Appendix 1
components integrated into the Unified Portal.
M60: HPC2 - Pre-exascale, data-centric HBP supercomputer with up to 50 PFlops; basic hardware and
software support for interactive supercomputing
(large memory capacity, dynamic resource management, visualisation and steering capabilities tightly
coupled to simulations, visual analysis algorithms for
basic multi-level post-processing).
resources for cellular-level simulation of the whole
mouse brain (planned for M60). The main impact of
delays would thus be on reconstructions of the human
brain. The HBP’s multi-scale computing strategy allows
the Project to make optimal use of available computing
resources. Delays in the deployment of exascale capabilities, would not block the reconstruction process, but
would constrain the granularity of simulations and limit
the accuracy attainable.
M90: HPC3 - Continued operation of pre-exascale, datacentric HBP supercomputer, advanced hardware and software support for interactive supercomputing (advanced
in-situ visualisation methods for multi-scale and steerable simulations, supported by session management and
annotation).
Contingency plans: In the event of delays, the HBP will
continue to use the Jülich pre-exascale machine and
the additional machines deployed by the other
HPC Partners.
End of risk: This risk will be cleared with the deployment of exascale computing capabilities, expected only
in M120.
M120: HPC4 - HPC4 - Exascale HBP supercomputer;
visualisation and analysis of brain models up to the
scale of the whole human brain; full multi-scale visual
brain analysis at the exascale.
R6.3 Delays in software development/poor community take-up (Probability: high; impact: moderate).
3.7.6 Risks and Contingencies
R6.1 Lack of financial resources/partnerships for the
deployment and operation of multi-petaflop and
exascale supercomputing infrastructures (Probability:
high; Impact: moderate).
These risks, common to all the Platforms, are described
in paragraph 3.5.6.
Risk: Deploying and operating the planned HBP hardware infrastructure will require financial resources
beyond those available in the budget. This creates
the risk that the Project will not be able to access the
capabilities it requires.
IMP6.1: The High Performance Computing Platform
will provide neuroscientists and developers with
unprecedented access to sub-exascale and exascale
supercomputing capabilities.
Impact: Failure to deploy the planned multi-petaflop
supercomputer would limit the granularity and accuracy of the planned reconstruction and simulation of
the mouse brain (planned for M60) and severely limit
efforts to reconstruct the human brain. Failure to deploy
the exascale supercomputer would limit the accuracy
and granularity of human brain models.
IMP6.2: SP6 will establish completely new technologies for interactive steering, visualisation and analytics. The new technologies will facilitate the adoption
of simulation-based research in neuroscience, and
other domains.
IMP6.3: SP6 will establish the use of low-power neuromorphic technologies in High Performance Computing.
Contingency plans: SP6 is working with national and
European Partners to allow joint deployment and operation of expensive computational infrastructures. In the
event of delays the HBP will continue to use its current
supercomputing capabilities.
3.7.7.2 Social and economic impact
The social and economic impact of SP6 will be indirect
through the services it provides to brain simulation (SP5),
neuromorphic computing (SP8) and neurorobotics (SP9).
End of risk: This risk will be cleared with the introduction of the Jülich multi-petaflop machine, currently
planned for M60 and with the deployment of the exascale machine (M120).
3.7.7.3 Innovation potential
IMP6.4: New technologies for remote interactive simulation, visualisation and analytics generated by SP6
have the potential to generate significant licensing
revenue.
R6.2 Delays in manufacturer deployment of exascale computing technology (Probability: moderate;
Impact: moderate).
IMP6.5: Novel HPC hardware based on low-power
neuromorphic technologies also have the potential to
generate licensing revenue.
Risk: The development of exascale computing poses
severe technical. These issues could delay the commercial availability of exascale computing beyond the timeframe of the HBP.
However, the last three years have already seen major progress. The risk of major delays thus appears to be falling.
Impact: The multi-petaflop HBP supercomputer
planned by Jülich (see above) will have sufficient
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Appendix 1
3.8 Subproject 7: Medical Informatics
MI4 – Draft map and models of brain diseases based
on biological signatures
M120
SP7
Milestones
MI3 – Europe-wide federated querying
of clinical data
M90
MI1 – First disease signatures
M60
MI1 – Pilot federated querying of distributed clinical data
M30
M30
M60
M90
M120
Figure 40: Output Targets and Milestones for SP7: Medical Informatics (MI)
damage.
The general objective of SP7 is to achieve a multilevel understanding of the similarities and differences
among brain diseases, and to use this knowledge to
improve the classification, diagnosis and treatment of
these diseases.
This means that most psychiatric and neurological diseases cannot be identified through a simple biomarker
and cannot be treated by modulating a single drug target.
The HBP Medical Informatics Platform is based on the
premise that the best way of identifying more complex
disease signatures and exploring new treatment options is
to explore very large volumes of multivariate patient data,
using methods from bioinformatics. Under the impulse of
the Human Genome Project, bioinformatics has already
developed extremely effective tools for exploring and
annotating genetic data. To date, however, there has been
relatively little work on other classes of clinical data.
The Core Project will design and operate a Medical
Informatics Platform that federates clinical data stored
in hospitals and research archives (clinical records,
imaging data, genetic data and other data from laboratory tests), makes them available to researchers, and
provides the tools to analyse the data and identify “biological signatures of disease”. The Platform will include
tools to anonymise, search, query, analyse and mine
patient data while simultaneously providing technical
guarantees that researchers cannot link the data to individual patients except under strict medical control and
legal supervision. It will use these tools and methods
to identify Biological Signatures of diseases and to
produce a draft map of the similarities and differences
among diseases. Partnering Projects will use them to
identify additional “biological signatures of disease”
and, on this basis, to develop a new, comprehensive
classification of brain diseases, new biologically based
diagnostics and new tools for personalised medicine.
The need for large volumes of data poses technical, cultural and organisational issues. On the technical side, it has
long been recognised that that the needs of researchers
seeking to store, query and manipulate scientific data are
profoundly different from the commercial needs that have
driven the development of relational database technology [85] [86]. In the case of medical informatics, these
issues are especially acute, leaving many gaps between
the requirements of research and the capabilities of the
technology. Despite intensive research, this requirements
gap has yet to be adequately filled.
Traditional epidemiology and drug development rely on a
univariate model in which a single outcome is linked to a
small set of risk factors (epidemiology) or the modulation
of a single drug target (drug development). This model fails
to take account of the complexity of biological systems, in
which multiple redundancies can stabilise the functioning
of the system even when a particular pathway is blocked
[64]. This is particularly true of the brain, whose intrinsic
plasticity gives it the ability to adapt to major changes in
the external environment and even to significant internal
A crucial issue is how to provide scientists with quick
access to raw medical data, such as data from imaging
[87]. Loading these large datasets into a database is a
time consuming process, particularly when it is not known
what parts of it will actually be used. The development
such functionality will require extensive research on how
to execute queries on different raw data formats [88].
On the organisational side, sharing of data is less common
among clinical scientists than in other scientific communi-
195
Appendix 1
ties. According to Visscher et al. [89] the reasons include
the need for standardisation, the time required to transfer
data to repositories, the need to protect clinical confidentiality, the perceived risk of jeopardising publications, and
difficulties in assessing the accuracy of results. All these
problems are soluble in principle, and have already been
solved by other scientific communities.
high dimensionality, high heterogeneity and high
noise due to missing values. However, the more data
that becomes available, the greater will be the discriminatory power of the analysis. As new hospitals
are recruited and hospitals already in the network
contribute data from new patients, the resulting
data will be incorporated into this dynamic, continuous, background process. The result will be a constantly optimised constellation of disease signatures
defining a new biologically based disease nosology.
Disease signatures will make it possible to derive
causal models of diseases and treatments. Inferences
based on these models and further interaction with
brain simulation results will enable major advances
in the diagnosis, classification, understand and treatment of brain diseases, preparing the way for new
Imaging presents an illustration of the challenges and
potential solutions. European hospitals and research establishments generate an enormous number of brain images,
most of which are only viewed once before being archived
on hospital or laboratory servers. Several attempts to
exploit such data are already in progress. Preliminary international data generation initiatives, such as the ADNI database [90] have demonstrated practicability and value for
money, The ENIGMA Consortium (http://enigma.loni.ucla.
edu), has recently brought together 125 institutions in a
very large brain imaging study, analysing brain images and
genome-wide scan data from 21,151 subjects.
Related Actions
As a result of these and similar studies, grant-awarding
institutions such as the NIH and Wellcome Trust require
that studies they fund make their databases available on
the Internet, facilitating data sharing. Switzerland, among
other countries, already allows hospital data mining by
health economists and insurance companies. Pilot studies
by the HBP Partners are profiting from this situation to
mine anonymised patient data generated by pharmaceutical firms, including data from failed clinical trials.
WP7.1 Clinical data infrastructure: develop tools to
harmonise heterogeneous clinical databases, and
for data anonymisation; develop interfaces for ontology-based querying; develop methods for federated
search and intensive distributed analysis of clinical
data; coordinate implementation of these tools in the
HBP Unified Portal.
WP7.2 Hospital recruitment and data gathering: recruit hospitals, clinics and other sources of
data (large-scale clinical studies, pharmaceutical
companies, biobanks, etc.); formalise agreements
with these organisations; provide required installation
services, demonstrations and training.
Federating hospital data requires systems with scalable storage, high availability, and effective mechanisms
to protect patient data when they are queried over the
network. The traditional approach is to copy the data into
a distributed store, which ensures high availability through
redundancy. However, this strategy does not provide security for patient data, which is no longer stored at the hospital.
WP7.3 Data models and features of disease: develop
and apply tools for data curation, and descriptive statistical analysis; extract brain morphology, genomic
and proteomic features from clinical and research
databases; extract patterns of variation in brain morphology, genes and proteins associated with neurological and psychiatric diseases; identify biological
signatures of disease; develop a map of brain diseases; contribute data and biological signatures of
disease to the Human Brain Atlas developed in SP4.
To preserve hospital ownership and control, the HBP will
develop a federated query engine that leaves patient data
in its original location and format. Compared to traditional
schemes in which data are moved to accommodate the
needs of the query engine, this a fundamental change.
To protect patient data, the HBP will introduce novel
methods of anonymisation that can precisely quantify
and control the amount of information disclosed, and
techniques to ensure that it is impossible to infer personal information about patients from query results.
WP7.4 Biological signatures of disease, theory, and
disease models: develop new techniques for big data
analysis; develop tools for data curation, and descriptive statistical analysis; introduce novel mathematical methods for clustering multi-level clinical data,
enabling the identification of biological signtaures of
disease; develop predictive and prescriptive medical
informatics, enabling the identification of biological
signatures of disease; develop generative models of
causal mechanisms and resilience.
An important goal for the HBP is to characterise
complete disease pathways, from the molecular
level, up to observable disorders of cognition and
behaviour, and to identify unique combinations of
biological and clinical signals associated with specific pathways. To pursue this goal, SP7 will use continuous dynamic data mining to identify biological
signatures of disease—constellations of biological,
anatomical, physiological and clinical variables that
define homogeneous populations. . The data mining
will be based on state of the art machine learning
algorithms. The HBP will extend current methods
to take into account the specificity of clinical data,
WP7.5 The Medical Informatics Platform: design,
single point of access to clinical data from hospitals and
other sources and advanced analysis tools; integrate the
Platform with the Unified Portal; provide support, training, maintenance and coordination; enable medical and
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pharmaceutical researchers to address novel research
questions; enable clinicians to use and advance new
different countries and different geographical regions).
workshops and reporting.
WP7.7 Clinical studies: use the data and analysis tools
provided by the Platforms to gain new insights into
the diagnosis, and classification of brain disorders
and to identify potential targets for treatment; studies
may include cluster analysis of data from retrospective studies, analysis of changes in disease signatures
at different stages in disease progression, re-analysis
of data from clinical trials and epidemiological studies
(e.g. measure impact of common genetic and/or environmental risk factors).
WP7.8 Disease and drug simulation: use data from
the Medical Informatics Platform and simulation capabilities from the Brain Simulation Platform to gain new
clinical insights; possible themes for research mechanisms of disease causation, mechanisms of action of
known therapeutic agents, and screening of drug candidates (development in conjunction with SP5).
WP7.9 Services for personalised medicine: use the
capabilities of the Medical Informatics Platform to
develop and trial new services for personalised medicine: personalised diagnosis and quantitative prognosis, personalised treatment, etc.
WP7.10 Methods and tools: develop and integrate new
tools and methods contributing to the capabilities of
the Medical Informatics Platform; possible tools and
methods include integrated machine learning, data
mining, and data intensive analysis for the identification of clusters in large volume of data.
SP7 will collaborate closely with industry, international
organisations and research consortia. Possible themes
include data sharing and related technologies and standards,
exploitation of data from large longitudinal and crosssectional databases, and epidemiological applications of the
Medical Informatics Platform (e.g., compilations of statistics
showing associations between disease prevalence and
geographical, social and economic data, and development
of a Mental Health Index allowing comparisons between
197
M30: MI1 - First version of Medical Informatics Platform; access for academic researchers, epidemiologists and clinicians; federation nodes in 5 hospital
nodes for in situ querying of anonymised data; webbased services for neuro-epidemiological studies,
interactive analysis and exploration of the biological
signatures of Alzheimer’s disease; initial publications
demonstrating the value of the Platform.
M60: MI2 - Federation extended to >10 hospital nodes
across Europe; refined tools for analysing medical data
at Federation level, enriched user-interaction functionalities, real-time automated data workflows; foundations for distributed mining of medical data; tools for
identification of homogeneous, disease-related biological constructs; publications demonstrating the value of
the platform and first disease signatures.
M90: MI3 - Federation extended with hospital nodes
world-wide; graph-based mathematical models for
interactive analysis; tools for large-scale mining of
medical data, using complex features; sophisticated
disease models with variables from in silico experimentation; tools for identification of homogeneous
disease-related biological constructs; external validation of disease models using post-hoc clinical phenotyping; interactions with brain simulation results and
tuning of brain disease signatures.
M120: MI4 - Federation further extended; graph-based
mathematical models; tools for large-scale mining
of medical data; predictive and prescriptive disease
models; disease simulation, with a generative model
of disease comorbidities and resilience; unified model
of brain diseases, generating a biologically grounded
classification of brain disorders; evaluations and crossanalyses using brain simulation; medical guidelines
based on disease models; extension of Platform use
into personalised medicine and patient selection for
clinical trials.
3.8.6 Risk Analysis
R7.1 Failure to recruit hospitals and other data sources
(Probability: medium; Impact: high).
Risk: The success of SP7 depends on its ability to detect
biological signatures of disease in very large volumes of
patient data. To achieve this goal, the Subproject will federate data from hospitals and other data sources (long
Appendix 1
term prospective studies, etc.). Success thus depends
on the willingness of these data sources to contribute
their data. Potential obstacles include concerns about
data protection, patient consent, and cross-border
access to patient data, technical difficulties and cost,
disagreement with the Subproject’s objectives and/or
strategy, and lack of interest on the part of physicians
and/or hospital management.
(e.g., stripping of data on age/gender/locations of
origin and residency/genetics) that would drastically
reduce the value of the data for analysis. The contingency plans described below would allow the Subproject to continue. However, there would inevitably be
severe delays.
Contingency plans: Informed consent procedures would
be amended to obtain explicit consent from patients
entering the system, allowing the use of the data.
Impact: Failure to accumulate a sufficient volume of clinical data would prevent the Project from achieving its goals.
End of risk: This risk will last for the whole duration of
the Project.
Contingency plans: If recruitment does not reach the
targets set by the work package, SP7 will extend its
recruitment effort to organizations and countries not
included in its original plan. As targets are very conservative, it is highly unlikely that this will be necessary.
R7.3 Novel rule-based clustering algorithms fail to
generate unique biological signatures of disease
(Probability: high; Impact: moderate).
End of risk: The Project has set itself goal of recruiting
five hospitals by the end of the Ramp-Up Phase.
Achieving this would be strong evidence that it can
also achieve its longer-term goals. The risk will only be
completely ended only when SP7 is regularly recruiting
new data sources from many different countries. We
expect that this will be fully achieved only towards the
end of the Project.
Risk: SP8 intends to develop novel rule-based clustering algorithms to detect unique biological signatures
of disease in large volumes of noisy clinical data. This is
novel research. There is thus a significant risk that this
work will fail to achieve its objectives.
Impact: In the short run, failure to develop new algorithms would force the use of existing clustering algorithms, which are computationally expensive and may
miss clinically significant signals present in the data. This
would have an impact on the efficiency of the Platform
and on the quality of the results it could deliver. However
current algorithms can produce extremely useful data
and methods that can be used to combine weaker classifiers into better performing ones. A failure in this area
would not, therefore be critical for the Project.
R7.2 Changes in regulations for data protection, limiting the use of anonymised data for research (Probability: high; impact: high:).
Risk: Regional, national or European regulators amend
current regulations in such a way as to prevent use of
anonymised clinical data in the way currently envisaged; national or European courts impose restrictive
interpretations of current regulations.
Contingency plans: SP8 has used the Ramp Up Phase
Competitive Call to diversify its portfolio of candidate
algorithms, improving its chances of success.
Impact: More restrictive regulation could make it
impossible to use the huge volumes of data generated
in the past, or impose de-identification procedures
End of risk: This risk can be considered cleared with
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the delivery of efficient algorithms and their incorporation into the Medical Informatics Platform, planned
for Month 30.
IMP7.4: “Biological signatures of disease”, identified
in SP7, will provide the data required for high-fidelity reconstructions and simulations of disease and
possible treatments. Simulations will provide a novel
tool for understanding the causes of brain disease,
and simulating the effects of drug candidates and
other treatments.
R7.6 Delays in software development/insufficient
financial resources for effective operation of Platform/poor community uptake (Probability: moderate;
Impact: moderate).
3.8.7.2 Social Impact
in paragraph 3.5.6.
IMP7.5: Biologically grounded classifications of brain
disorders established by SP7 will allow more effective
diagnosis and treatment of brain disorders, and more
effective selection of participants for clinical trials.
IMP7.1: SP7 will establish novel techniques and practices for the extraction of clinically valuable information from large volumes of patient data, exploiting
the competitive advantage offered by European
National Health Systems, and establishing European
leadership in a broad field of medical research. The
techniques established by the Subproject will have
a major impact on medical research outside the HBP.
IMP7.6: Disease and drug simulations will facilitate
the development of drug and other treatments.
IMP7.7: The data and tools made available by the
Medical Informatics Platform will facilitate the development of personalised treatments.
IMP7.8: Better understanding, diagnosis and treatment of brain disease will reduce costs for National
Health Services and insurance companies and reduce
the burden on patients and their families.
IMP7.2: The Medical Informatics Platform will offer
researchers unprecedented access to large volumes
of anonymised patient data, creating new opportunities for basic and applied research. The federation
and querying methods at the core of the Platform
will make it possible to leave personally sensitive
data in the systems and formats where they were
originally stored, without moving them to a central
system. Tools and methods supporting this strategy will have a substantial impact on future medical
research.
IMP7.9: SP7 will enable commercial services allowing
clinicians and pharmaceutical researchers to query
and analyse anonymised patient data.
IMP7.10: SP7 will enable commercial services allowing clinicians and pharmaceutical researchers to simulate brain diseases and candidate treatments.
IMP7.3: SP7 will contribute to establishing objective,
biologically grounded classifications of neurological
and psychiatric disease. This represents a major step
forward, compared to current symptom and syndrome-based methods of diagnosis.
IMP7.11: SP7 will enable commercial services for personalised medicine (diagnosis, prognosis, selection of
optimal treatment).
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Appendix 1
3.9 Subproject 8: Neuromorphic
computing
NM4 – NM-PM-3 (500M / 5B structured neurons, 130B /
1300B synapses, NM-MC-2 (10B Neurons, 1T synapses)
NM3 – PM: 100+ platform users, 1000+ users on
dissemination system; NM: 30+ platform users,
100+ users on dissemination system
M120
SP8
Milestones
M90
NM2 – NM-PM-2 (4M neurons, 1B synapses,
plasticity processor); NM-MC-1 (250M neurons,
100B plastic synapses)
M60
NM1 – NM-PM-1 (4M neurons, 1B synapses),
NM-MC-1 (100M neurons, 100B synapses)
M30
M30
M60
M90
M120
Figure 41: Output Targets and Milestones for SP8: Neuromorphic Computing (NM)
The distinguishing feature of the HBP’s strategy for
neuromorphic computing is that neural architectures will
be derived from detailed multi-level brain models, developed on the Brain Simulation Platform. The HBP will
systematically study the relationship between different
features of the models and their computational performance, identifying and implementing strategies to reduce
complexity while preserving functionality.
The overall goal of SP8 is to establish Neuromorphic
Computing as a new paradigm of computing, complementary to current designs, and to explore potential
applications. To achieve this goal, SP8 will design, implement and operate a Neuromorphic Computing Platform
that allows non-expert neuroscientists and engineers to
perform experiments with highly configurable Neuromorphic Computing Systems (NCS) implementing simplified
versions of brain models developed on the Brain Simulation Platform as well as generic circuit models based on
theoretical approaches. The Platform will also provide
software simulations for circuit verification of NCS and
software support for configuring, running and analysing
experiments. The first version of the Platform, accessible
to researchers inside and outside the HBP Flagship Initiative, will be released to the community at the end of the
Ramp-Up Phase and will be continuously updated over
the lifetime of the Project.
The Core Project will design, implement and deploy the
planned Neuromorphic Computing Systems (three versions of the NM-PM system, two versions of the NM-MC
system) and integrate them in the Neuromorphic Computing Platform, which it will open to the community at the
end of the Ramp-Up Phase.
The Partnering Projects will explore novel applications of
the technology. Potential application areas include pattern
detection in spatio-temporal data streams, finding causal
relations in big data, data mining, temporal sequence
learning, and approximate computing. Other themes for
investigation in the Partnering Projects include new hardware devices incorporating Neuromorphic Technology,
new device technologies (resistive memories, magnetic
memories, organic devices, 3D Integration, distributed
powering, etc.) and hybrid HPC-neuromorphic computing
systems for accelerated, energy efficient brain simulations.
The Neuromorphic Computing Systems developed by
SP8 are hardware devices incorporating the developing
state-of-the-art electronic component and circuit technologies as well as knowledge arising from other areas of
HBP research (experimental neuroscience, theory, brain
modelling). The Platform will allow researchers to use
two distinct categories of NCS: (1) Physical (analogue
or mixed-signal) emulations of brain models (NM-PM),
running in time-accelerated mode, and (2) Digital Multicore systems implementing numerical models running
(NM-MC), as well as hybrid systems, integrating NCS with
conventional computing technologies.
The primary technological challenges for traditional computing are energy consumption, software complexity and component reliability. One strategy to address these challenges is
to use neuromorphic technologies inspired by the architecture
of the brain. Some approaches have focused on physical emulation of brain circuits. These approaches have the potential
to exploit the characteristics of inherently noisy and unreliable
micro- or nanoscale components with feature sizes approaching the atomic structure of matter, and with an energy cost
per neural operation six orders of magnitude lower than that of
equivalent brain models running on conventional supercomput-
NCS will be tightly integrated with the High Performance
Computing Platform, which will provide essential services
for mapping and routing circuits to neuromorphic substrates, benchmarking and simulation-based verification
of hardware specifications.
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Appendix 1
ers. Other approaches use massively parallel many-core architectures that simulate neural models on digital processors. In both
strategies, communications among model neurons use clockless,
inherently asynchronous “spiking neural networks”– a “brain-like”
feature that offers major savings in energy consumption. Other
advantages include support for plasticity and learning and (in the
case physical emulation) the ability to run at speeds from 1,000
to 10,000 times faster than biological real time. This capability
allows model systems to emulate real world learning processes
and physical dynamics lasting weeks, months and even years.
local 128M byte RAM, and allows real-time simulation
of networks implementing complex, non-linear neuron
models. A single chip can simulate 16000 neurons with
eight million plastic synapses running in real time with an
energy budget of 1W.
SP8 will allow users of the Neuromorphic Computing
Platform to experiment with three versions of Neuromorphic Computing System based on the PM model,
and two versions based on the MC model. The first versions of these systems, which are now under construction, will be supported, maintained and moderately
upgraded until the next generations come into operation in M60 (NM-PM) and M120 (NM-PM and NM-MC).
The main scientific challenge for neuromorphic computing
is the choice of the computational paradigm to be implemented on the electronic substrate. This requires basic
research into the way the brain stores and processes information, the way it accommodates and even exploits the variability of its components, and the role of stochastic neuronal
behaviour.
The Neuromorphic Computing Platform will be based
on functional, large-scale architectures and proven
device technologies. The most important goal is to
provide the best possible neuromorphic processing
performance in term of system size and accessibility with the goal to study and understand the circuit
architectures and their use for information processing.
Planned advances beyond the state of the art include
the following.
Neuromorphic computing with modern microelectronics
was pioneered by the group of Carver Mead [102] at Caltech,
the first to integrate inspired electronic sensors with analogue circuits and to introduce an address-event-based
asynchronous, continuous time communications protocol.
Today, many groups follow the Mead approach, notably the
Institute for Neuroinformatics at ETH Zürich (Switzerland)
[103].
Scaling up. Researchers will scale up the current NM-MC-1
and NM-PM-1 in line with the development roadmaps
defined in Table 4 and Table 5. Final numbers in terms
of synaptic connections will reach 1300 billion for the
NM-PM system and 10000 billion for the NM-MC system.
The increase will allow more users to share the system,
and allow for larger network sizes.
The Mead work focuses on the demonstration of basic highlevel computational principles. IBM’s SyNAPSE (Systems of
Neuromorphic Adaptive Plastic Scalable Electronics) project,
by contrast, aims to reproduce large systems that abstract
away from the biological details of the brain. Proponents
argue that the inherent scalability of this approach allows
them to build systems that match the computing efficiency,
size and power consumption of the brain and its ability to
operate without programming [78].
Moving to advanced process nodes. The test chips
from advanced process nodes being designed for both
systems will be used as basic components for the next
generation systems, with a construction time scale of
approximately five years.
The European FACETS project has pioneered a different
approach that combines local analogue computation in
neurons and synapses with binary, asynchronous, continuous time spike communication [104] [105] [106]. FACETS
systems can incorporate 50*106 plastic synapses on a single
8-inch silicon wafer. In the near future, advances in CMOS
feature size, connection technologies and packaging will
make it possible to build multi-wafer systems with 1013 plastic
synapses operating at acceleration factors of 10.000 compared to biological real-time. The FACETS group has also
pioneered a network description language (PyNN) that provides Platform independent access to software simulators
and neuromorphic systems [107]. BrainScaleS – a follow-up
project – is pioneering the use of the technology to replicate
behaviour and learning over periods of up to a year while
simultaneously emulating the millisecond-scale dynamics of
the system.
Integrating recent neurobiological knowledge. As the
Project proceeds, SP8 will integrate more structured,
multi-compartment neuron models. Future systems will
make it possible to model plasticity, supervised and unsupervised learning, and developmental processes and a far
more flexible and user controllable way than this is done
with the current systems.
Integrating next generation chips into next generation
systems. This advance is described in the Roadmap below.
Related Actions
3.9.4.1 Core Project
WP8.1 Physical model implementation: design, build
and operate three versions of a physical model Neuromorphic Computing System (NM-PM-1, 2, 3), enabling
the scientific community to perform large-scale neuromorphic computing with physical emulation of brain
models; design required chips and boards, manufacture, assemble and commission neuromorphic computer systems; carry out targeted R&D on connection
Another strategy is to implement brain models in classical many-core architectures. This is the approach
adopted by the UK SpiNNaker group [108] [109]. The
group, which has a strong grounding in the ARM architecture, has recently completed the integration of a SpiNNaker chip into an operational system and is now running
experiments. Each chip has eighteen cores and a shared
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Appendix 1
WP8.8 Portable hardware systems for neuromorphic
computing: use the NM-PM and NM-MC systems to derive
specialised and resource efficient neuromorphic circuit
architectures for custom, special purpose low-power,
compact, low-cost hardware implementations as neuromorphic cores or complete stand-alone systems; application areas include robotics, automotive, manufacturing,
telecommunication.
technologies, in particular wafer-board interconnects
required for the construction of NM-PM-3; develop
and implement low-level software and firmware.
WP8.2 Digital model implementation: design, build
and operate two versions of a many-core neuromorphic computing system (NM-MC-1, 2), enabling
the scientific community to perform neuromorphic
computing with digital many-core simulations of
brain models; design required chips and boards;
manufacture, assemble and commission Neuromorphic Systems; carry out targeted R+D on 3D
memory integration as required for the construction
of NM-MC-2; develop and implement the low-level
software required.
WP8.9 Devices for neuromorphic computing: develop
and evaluate new device technologies for neuromorphic computing; simulate, construct and evaluate
small- scale demonstrator systems; evaluate integration into the HBP Neuromorphic Platform systems;
possible themes for development work include resistive memories, magnetic memories, organic devices,
3D Integration, and distributed powering.
WP8.3 Tools: develop and implement high level
software tools for the operation of the neuromorphic
systems developed in WP8.1 and WP 8.2; integrate
the Neuromorphic Computing Platform into the HBP
Unified Portal; integrate available HPC resources into
the neuromorphic computing workflow; develop and
carry out performance benchmarks for neuromorphic computing.
WP8.10 Hybrid HBP-neuromorphic architectures: develop conceptual designs for hybrid HPCneuromorphic computing systems for energy efficient,
accelerated simulations in neuroscience; demonstrate
feasibility using the Neuromorphic Computing Platform
and the HBP Platform; possible architectures include
hybrid systems linked across networks, on-board
hybrids, and on-chip hybrids with Neuromorphic cores.
WP8.4 Theory - principles of brain computation: extract principles of brain computation and
learning from experimental data in neuroscience and
cognitive science and simulations; use these principles to provide desired functional properties to neuromorphic systems, neurorobotic systems and other
applications; investigate and address systematic
problems that arise in specific application domains.
and international Initiatives
SP8 plans to engage in joint technology development
with major European players including Fraunhofer FhG
(Germany), CEA-Leti (France), and IMEC (Belgium).
Possible themes for joint projects include new
devices, connection technologies, and software tools.
The European electronics design and manufacturing
industry will play a key role in the development and
construction of neuromorphic systems. SP8 plans to
develop national technology nodes for a neuromorphic
applications, with a focus on robotics, automotive,
manufacturing and telecommunication systems. The
planned Global Network of Brain Initiatives will enable
SP8 to exchange information with other international
initiatives. Plans for collaboration include bi-annual
EU-US workshops on neuromorphic computing, and
joint workshops to develop a global strategy for
future development.
WP8.5 Neuromorphic Computing Platform: design,
single point of access to the software and hardware
infrastructure developed in SP8; provide documentation,
training and support for users of the neuromorphic Platform; integrate with the Unified Portal; enable researchers, technology and applications developers to design,
implement and test a spectrum of Neuromorphic Computing Systems and to develop products and services.
M30: NM1 – Physical Model System NM-PM-1 with 4
million neurons and 1 billion synapses, x10,000 acceleration. Many-Core System NM-MC-1 with 100 million
neurons and 100 billion synapses; smaller scale dissemination systems for both system types.
WP8.7 Applications for neuromorphic computing: use the
NM-PM and NM-MC systems to demonstrate applications
of Neuromorphic Computing Systems; potential application areas include pattern detection in spatio-temporal data streams, finding causal relations in big data, data
mining, temporal sequence learning, and approximate computing; feed back the results for further development and
feature upgrades of the Neuromorphic Platform systems.
M60: NM2 - Physical Model System NM-PM-2 transferred to advanced process node, plasticity processor system, 4 million neurons and 1 billion synapses;
Many-Core System NM-MC-1 expanded to 250 million
neurons and 1 billion synapses. Smaller 100 billion
plastic synapses; smaller scale dissemination systems
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Appendix 1
for both system types.
will only be available at the end of the Project. Therefore, some risk will persist for the whole duration.
M90: NM3 - Physical Model System NM-PM-3 100+
users for platform system, 1,000+ users for dissemination systems; Multi-core System 30+ users for platform system; 100+ users for dissemination systems.
financial resources for operation of Platform/insufficient community uptake.
M120: NM4 – Physical Model System NM-PM-3 with 500
million (a) or 5 billion (b) structured neurons and 130
billion (a) or 1,300 billion (b) synapses, x10.000 acceleration. Many-Core system NM-MC-2 with 2.5 billion neurons
and 1,000 billion synapses.
in paragraph 3.5.6
IMP8.1: SP8 will establish designs and technologies
for large-scale neuromorphic devices and systems
with novel learning capabilities, low energy consumption and high reliability.
(Note: The choice between options (a) and (b) will depend
on basic research and development in WP8.1.)
3.9.6 Risk Analysis
IMP8.2: The Neuromorphic Computing Platform will
offer academic researchers and technology developers the possibility to experiment with and test stateof-the-art neuromorphic devices and systems.
R8.1 Delays in hardware development (Probability:
moderate; Impact: moderate).
Risk: SP8 includes a large component of hardware
development. This activity is associated with an uneliminable risk of delay, and technical failure.
3.9.6.2Social and Economic Impact
IMP8.3: The technologies and systems developed
in SP8 have the potential to revolutionise computing technology, enabling a very broad range of completely novel applications.
Impact: Delay in production of a particular Neuromorphic Computing System would delay a specific Platform
version and any experiments or applications development work that relies on it.
IMP8.4: The services offered by the Neuromorphic Computing Platform will facilitate the emergence of a rich ecosystem of academic and industrial researchers, exploring
and ultimately commercialising novel applications.
Contingency plans: Experiments are routinely planned
using software simulations of neurocomputing hardware.
This strategy minimises the consequences of delays in
hardware development.
End of risk: The risk for specific versions of the Platform will be cleared with the Platform releases planned
in M30, M60, M90 and M120. The general risk of delay in
hardware development will persist for the whole duration of the Project.
IMP8.5: SP8 will establish European leadership
in an area of research of vital importance to the
European computing industry and to applications
developers.
3.9.6.3Innovation Potential
R8.3 Delay in production of simplified or theory-driven
brain models (Probability: moderate; Impact: moderate).
IMP8.6: SP8 has the potential to develop commercial
services offering researchers and technology developers the possibility to experiment with and test
applications based on state-of-the-art neuromorphic
devices and systems.
Risk: in experiments and applications development,
Neuromorphic Computing Systems will be configured
using simplified versions of the high-fidelity reconstructions generated by SP5 and/or theory-driven
models developed by SP3. Delays in production of
these models would create a risk of delay.
IMP8.7: Neuromorphic designs and technologies
developed in SP8 have the potential to generate licensing revenues from industry and applications developers.
Impact: The PM and the MC Neuromorphic Systems
are both configurable systems. Delays in production
of brain models will not therefore affect the design or
implementation of critical hardware or software components. They could however lead to delays in experimental and application development work.
IMP8.8: Neuromorphic technologies developed in
SP8 have the potential to generate commerciallyvaluable applications for manufacturing, transport,
healthcare, and consumer electronics.
Contingency plans: SP8 will obtain brain models both
from SP3 (theory-driven models) and SP5 (simplified
models derived from high fidelity reconstructions). The
use of two alternative sources significantly reduces risk.
End of risk: This risk will reduce gradually over the duration of the Project, as more and better models become
availability. However models of the whole human brain
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Appendix 1
System Version
Unit
Numbers
NM-PM-1
Ramp-up phase
M30 Deliverable
March 2015
Dissemination
System
180nm CMOS
20 cm Wafers
Wafer-on-PCB
5+2 Rack Architecture
FPGA digital links
3 TFlop local cluster
LIF neuron chip
Analogue and Digital I/O
FPGA processing
USB Board
20 Wafers
4M Neurons
1B Synapses
Adex Point Neurons
Up to 16000 syn. inputs
6-bit synapses
STP, STDP
Plasticity Processor
x1.000-x10.000 acc.
65nm CMOS
20 cm Wafers
Wafer-on-PCB
NM-PM-1 compatible
FPGA digital links
Adex neuron chip
FPGA processing
USB Board
Stand alone, Integrated PC
500 Wafers
500M Neurons
130B Synapses
Structured Neurons
6-bit synapses
STP,STDP
x1.000-x10.000 acc.
65nm CMOS
30 cm Wafers
Wafer-on-PCB
FPGA-less
Torus Architecture
On-wafer digital links
Multiple Adex neuron chips
FPGA processing
USB Board
5000 Wafers
SB Neurons
1300B Synapses
Structured Neurons
6-bit synapses
STP,STDP
x1.000-x10.000 acc.
65nm CMOS
30 cm Wafers
Wafer-in-PCB
FPGA-less
PCB embedding
Torus Architecture
On-wafer digital links
Adex neuron wafer
FPGA processing
USB Board
NM-PM-3
Option b (*)
M120 Milestone
September 2022
Infrastructure
Adex Point Neurons
4-bit synapses
STP, STDP
x1000-x10.000 acc.
NM-PM-3
Option a (*)
M120 Milestone
September 2022
Technologies
20 Wafers
4M Neurons
0.9B Synapses
NM-PM-2
M60 Milestone
September 2017
Neuroscience
Features
Table 4: Development roadmap for Physical Model Neuromorphic Computing Systems (PM-NCS)
(*) The choice between options a and b will depend on the result of technology R+D on wafer-PCB embedding carried out in WP8.1
Key novel features for new versions are indicated in bold
System Version
Unit
Numbers
NM-MC-1
Ramp-up phase
M30 Deliverable
Infrastructure
Dissemination
System
Any Point Neuron
1000 16-32 bit fixed or
plastic synapses per
neuron
Real-time
130nm CMOS
co-packaged 1 Gb
DDR2 DRAM
Rack Architecture
Chip and FPGA digital
links
Small cluster for
routing/job queuing
4-chip board USB board
1200 Boards
1B Neurons
10,000B Synapses
Multi-compartment
Neurons
10,000 16-32 bit fixed
or plastic synapses per
neuron.
Real-time
28nm CMOS
flip-chip DDR4
16 Gb DRAM
Rack Architecture
links
Small cluster for
routing/job queuing
2-4 chip board USB board
FPGA processing
USB Board
1200 Boards
1B Neurons
10,000B Synapses
Multi-compartment
Neurons
10,000 syn. inputs
16-32 bit fixed or plastic
synapses per neuron
Real-time.
14nm FIN-FET CMOS
flip-chip DDR4
16 Gb DRAM
Rack Architecture
links
Small cluster for
routing/job queuing
2-4 chip board USB board
FPGA processing
USB Board
NM-MC-2
Option b (*)
M120 Milestone
Technologies
600 Boards
100M Neurons
100B Synapses
NM-MC-2
Option a (*)
M120 Milestone
Neuroscience
Features
Table 5: Development for Many Core Neuromorphic Computing Systems (MC-MCS)
(*) The choice between options a (28nm) and b (14nm) will depend on the result of technology R+D on test chips carried out in WP8.2
Key novel features for new versions are indicated in bold
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3.10 Subproject 9: Neurorobotics
NR4 – First in silico human cognition
and behaviour experiments
M120
SP9
Milestones
NR3 - First in silico mouse cognition
and behaviour experiments
M90
NR2 - First simulations of robots and
devices coupled to brain models
M60
NR1 - Initial closed loop systems
M30
M30
M60
M90
M120
Figure 42: Output Targets and Milestones for SP9: Neurorobotics (NR)
both in neuroscience research (in silico behavioural experiments) and for potentially valuable commercial applications. Partnering Projects may also extend the Platform
to enable experiments involving multiple neurorobotic
systems and their interactions.
3.10.1 General Objectives
The overall objective of SP9 is to provide tools allowing
researchers to test the cognitive and behavioural capabilities of the brain models developed in SP5, and the neuromorphic implementations of these models from SP8. Even
with the high-performance computers of the HBP, it will
initially not be possible to simulate HBP brain models in
real time. Thus, SP9 will initially rely on simulated robots
and simulated environments. The Neurorobotics Platform
will provide researchers with access to detailed brain
models on the Brain Simulation Platform running slower
than real time, and to emulated models on the Neuromorphic Computing Platform running faster than real time. It
will also allow them to use mixed models in which some
areas of the brain are represented in full biological detail,
while others are represented by phenomenological models.
The tools provided by the Platform will allow researchers
to operate robots remotely, to repeat experiments as often
as they need, and to visualise the behaviour of the robots
as if they were running in real time.
Neurorobotics can be defined as the science and technology of robots which are controlled by a simulated nervous
system that reflects, at some level, the architecture and
dynamics of the brain [99]. Such robots can are situated
in a real-world environment, sense environmental cues,
and act upon their environment. Robots with these properties make it possible to study brain models in closedloop experiments.
Probably the first researcher to develop a robot that fulfilled these criteria was Thomas Ross, who in 1933 devised
a mobile robot with a small electromechanical brain, which
could navigate through a maze in real time [100]. Today,
there are two main strands in neurorobotic research, the
first focusing on biologically inspired robots, the second
on brain-inspired control architectures.
The Core Project will design and implement the tools, incorporating them in the HBP Neurorobotics Platform. The
first version of the Neurorobotics Platform will be released
at the end of the Ramp-Up Phase. The Platform allows
researchers to design simulated robot bodies, connect
these bodies to brain models, embed the bodies in rich
simulated environments, and calibrate the brain models to
match the specific characteristics of the robot’s sensors
and “muscles”. The resulting set-ups will allow researchers to replicate classical animal and human experiments in
silico, and ultimately to perform experiments that would
not be possible in the lab. During the Operational Phase,
the Platform will also provide access to physical robots
controlled by brain-models that can be executed in real
time, on analogue or digital neuromorphic hardware
provided by the Neuromorphic Computing Subproject.
Partnering Projects will enhance the methods and technologies used in the Platform and explore their applications,
Historically, biologically inspired robots have mainly come
from academic research. However, recent advances in
humanoid and four-legged robots have lead to a renewed
interest in applications for the military (BigDog, BostonDynamics.com), aeronautics (NASA Robonaut2), and
entertainment (Honda ASIMO, Sony AIBO). Biologically
inspired robots are adaptable and can display rich perceptual and behavioural capabilities. In contrast to industrial
robots, they often use compliant materials, which make
their mechanics intrinsically flexible. Researchers have
also developed a large number of robots, Three of are
iCub (a humanoid robot “child”) [101], Kojiro (a humanoid robot with about 100 “muscles” [102] and ECCE (a
humanoid upper torso that attempts to replicate the
inner structure and mechanisms of the human body
[103]. Brain-inspired control architectures are robotic
control systems, which at some level reflect properties
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Appendix 1
of animal nervous systems. In general, they are tailor
made for a specific set of tasks, often using a combination of Artificial Neural Networks, Computer Vision/
Audition, Machine Learning algorithms, and recently
Spiking Neural Networks [104] [105] [106] [107]. A
typical experiment might involve the emulation of a
rat as it navigates through a maze. In this case, the
control architecture for the simulated rat could comprise sensory areas, a hippocampus, and a motor area
to generate movements.
Robot and Environment Designer, and a World Simulation Engine; construct virtual robots and virtual environments from reusable parts; build and curate databases
of sensors, motors and other parts for robots and
environments; develop HPC-based physics engines for
high-fidelity simulation of sensory-rich, physically realistic worlds with multiple interacting robots and agents.
WP9.2 Virtual neurorobotics laboratory: develop
capabilities to plan, run and analyse in silico experiments with Neurorobotics Systems and test them
in pilot experiments; develop tools for immersive
high-fidelity rendering and real-time user interaction,
enabling life-like neurorobotics experiments with
users in the loop.
SP9 will deviate radically from brain-inspired control architectures. Rather than designing specific neural control
architectures for each experiment, HBP neurorobots will
be controlled by generic brain models provided by the
Brain Simulation Platform. To design a robot for use in an
experiment, researchers will connect models of sensors
(vision, audition, touch, balance) and actuators to a brain
model, calibrate the robot brain so that it can process the
relevant signals, and translate the model’s neural activity
into control signals for the robot. Researchers will then
use classical techniques (lesion studies, manipulations of
neurons, etc.) to identify the control architecture for specific tasks. This approach allows researchers to monitor and
control all states and parameters of the experiment (brain,
body, and environment) – something technically impossible to achieve in the laboratory. Since there is a clear trend
in general robotics towards the use of modular building
blocks and since the NRP control structures can also be
assembled from building blocks, the defining theme for
SP9 is “Building modular brains for modular bodies”.
WP9.3 Brain-body integration: build models of
spinal cord, sensory, motor and vestibular systems;
close the sensory-motor loop with the CNS, PNS and
body; establish reflexive control and motor primitives;
establish basic motor control; establish basic drives,
value-systems and motivations for autonomy.
WP9.4 Bridging the reality gap: develop technology
to construct and calibrate virtual robots, and virtual
physics to match real-world physics.
WP9.5 Neurorobotics models: develop and test a prototype of a complete closed-loop system with a brain, a
body and an environment sufficiently rich and accurate
for use in cognitive and behavioural research.
WP9.6 In silico behaviour, cognition and social interaction: run in silico experiments in which neurorobotic systems are coupled to models of the healthy
and the diseased brain; run experiments with multiagent neurorobotic systems, investigating the role
of social interaction in the development of cognitive
systems.
In terms of the development tool chain, the NRP aims
to build an open source software solution. Software
modules will be derived from established tools with a
strong developer community and from softwa re already
developed in the Blue Brain Project. Developers from
the robotics and open source communities are encouraged to take part in this continuous effort. The current
understanding of neurorobotics is largely bound to the
idea that the environment in which the robot interacts
must be the real world, but the gap between simulation
and reality is decreasing. A well-designed simulation
environment would make it possible to perform studies
much faster than would ever be possible with physical
robots, which need to be designed, built, programmed,
and re-designed, etc. in a never-ending cycle.
WP9.7 Technology bridge: translate virtual robots
and brain-derived controllers to physical prototypes;
transfer controllers to state-of-the-art embedded
systems.
WP9.8 Neurorobotics Platform: design, implement
access to Neurorobotics capabilities; provide documentation, training and support for users; integrate
with the Unified Portal. Enable a new paradigm of in
silico research for investigations of the links between
the multi-level structure of the brain, cognition and
behaviour; enable industry to develop new Neurorobotic applications.
activities within the SP, and with other SPs, Partnering
quality assurance, organization of meetings and workshops and reporting.
So while current neurorobotics research focuses on
physical robots, SP9 will focus on virtual robots and
environments. Simulation experiments using virtual
robots and environments will allow researchers to
perform completely novel in silico experiments investigating the link between brain circuitry and high-level
cognitive and behavioural functions. Insights gained
from this work will facilitate the development of new
types of robot controller.
3.10.4 Operational Objectives
and Related Actions
WP9.10 Software, tools and technologies: develop
software, tools and technologies that expand the capabilities of the Neurorobotics Platform; possible themes
WP9.1 Virtual robots and environments: develop a
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Appendix 1
include the high-performance, high-fidelity simulation
technologies for robots and their environments.
level reconstructions of the mouse brain; comprehensive
library of simulated robots and devices, environments
and experimental conditions for customisation.
WP9.11 Embodied neurorobotics: perform research
on the physics and function of bodies (bones, muscles,
tissue), sensors (vision, audition, touch, balance) and
peripheral nervous system (spinal cord) and integrate
the results into the Neurorobotics Platform.
M120: NR4 - Closed-loop support for human brain
models; pilot studies in human behaviour and cognition; finalised services for customisation of robots and
devices, environments and experimental conditions.
3.10.6 Risk Analysis
WP9.12 Social neurorobotics: expand the Neurorobotics Platform to enable experiments involving interactions among multiple neurorobotic systems.
financial resources for operation of Platform/insufficient
community uptake.
WP9.13 Neurorobotics as a tool for in silico neuroscience: use neurorobotic systems to perform in silico
experiments investigating fundamental issues in basic
neuroscience, cognition and behaviour.
These risks, common to all the Platforms, are described in
paragraph 3.5.6.
3.10.7 Impact and Innovation
WP9.14 Applications: use the Neurorobotics Platform to develop applications of commercial or clinical value; possible applications include applications
in manufacturing and mechanical engineering, personalised neuro-prosthetics and neuro-muscular controllers, robots for healthcare, robotic vehicles, and
robots for domestic applications.
3.10.7.1Scientific Impact
IMP9.1: SP9 will establish neurorobotics as a valid
technique for exploring the causal relationships
between the multi-level structure of the brain, cognition and behaviour.
3.10.4.3 Collaborations with National, Regional,
European and International Projects and Initiatives
IMP9.2: The HBP Neurorobotics Platform will make it
possible, for the first time, for researchers to design
and perform behavioural and cognitive experiments
using virtual robots connected to HBP brain simulations and inhabiting virtual experimental set-ups.
SP9 will collaborate with academic and industry researchers
on a broad range of themes including basic robotic
technologies, user interface/simulator technology, and
possible medical applications. Collaboration with industry
will focus on the translation of virtual models into physical
robots, the commercialisation of simulation, visualisation
and robotics technologies and specialised neuro-controllers.
SP9 will also work closely with open source organisations
that are building tools of strategic importance for the
Subproject. These include the Open Robotics Foundation,
the Blender Foundation, and the Open Dynamics Engine
(ODE).
IMP9.3: Research in SP9 will contribute to creating
a new multi-level understanding of the relationships
between brain structure, cognition and behaviour.
IMP9.4: SP9 will create the first prototype applications
exploiting the novel cognitive and behavioural capabilities of physical robots with neuromorphic controllers.
3.10.7.2 Social and Economic Impact
3.10.5 Output Targets and Outcomes
IMP9.5: Physical robots with neuromorphic controllers will have functional capabilities (e.g., learning, effective handling of multimodal real-time
input) not present in current robotic technologies.
These capabilities will have a major impact over a
broad range of domains from manufacturing to transport, healthcare, and the home.
M30: NR1 - Initial version of Neurorobotic Computing Platform; capabilities to design virtual robots,
environments and experiments and to link them to
existing brain simulations; pilot experiments using
Platform capabilities.
M60: NR2 - Enhanced user access and control;
enhancements to simulated robots, environments
and experiments; closed-loop support for simplified
brain models; first published experiments using Platform capabilities; pilot experiments using high-level
simulations with in-built plasticity; pilot experiments
using cellular level reconstructions of the mouse
brain; links to Brain Simulation, High Performance
Computing and Neuromorphic Computing Platforms;
first simulated robots and devices, environments and
experimental conditions.
IMP9.6: The Neurorobotics Platform will enable the
HBP to realise commercial services allowing industry to
experiment with state-of-the-art neurorobotics setups.
IMP9.7: HBP neurorobotic technology has the potential to generate significant licensing revenues.
IMP9.8: Applications developed based on neurorobotic technology have the potential to generate significant licensing revenues.
M90: NR3 - Closed-loop support for in silico mouse brain
experiments; first published behavioural experiments
using brain reconstructions with plasticity and cellular
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Appendix 1
3.11 Subproject 10: Ethics and Society
and benefits, responsibility and accountability, equity and
justice [115]. Foresight exercises play a central role in responsible innovation as they enable ‘anticipatory’ action to shape
the pathways of development in desired ways and to assess
and manage risks in a timely manner.
The overall objective of SP10 is to assist the HBP in pursuing a policy of Responsible Research and Innovation (RRI).
SP10 will monitor science and technological results as they
emerge, analyse their social and philosophical implications,
and work to involve researchers decision-makers, and the
general public in a far-reaching conversation about future
directions of research. SP10’s strategy involves: anticipation, through the work of the Foresight Laboratory, which
will produce scenarios of potential developments and their
implications and feed them back to HBP researchers; reflection to encourage ethical reflection among researchers of
the HBP to increase their capacity to consider the social
and ethical implications of their work; engagement involving
public dialogues with stakeholders and citizens; and action
(feeding the results back to HBP Management).
Conceptual and philosophical issues. Since the 1960s, scientific and technical advances [116] have made it ever
easier to anatomise the brain at the molecular, cellular
and circuit levels, encouraging claims that neuroscience is
close to identifying the physical basis of mind. Such claims
have major implications not only for medicine but also for
policies and practices dealing with normal and abnormal
human conduct, and for conceptions of personhood. The
significance and consequences of these developments are
strongly debated, with some authors arguing that we now
know enough to understand the neural bases of human
selfhood and higher mental functions [117] [118], while for
others, the neuroreductionist model attributes capacities
to brains that can only properly be attributed to persons
[119] [120]. Some have suggested that progress in neuroscience will lead to radical improvements in our ability
to treat psychiatric disease [121] [122]; others are more
doubtful [123] [124]. Although functional imaging has been
crucial in the development of new conceptualisations of
human mental states, many leading researchers remain
highly critical [125].
A central aim is to identify potential ethical and social concerns at an early stage and to address them in an open and
transparent manner, providing HBP scientists with opportunities to gauge public reaction to their work, and to hone
their research objectives and processes accordingly.
The Core Project will manage a major Ethics and Society Programme, which will explore the Project’s social, ethical and
philosophical implications, promote engagement with decision-makers and the general public, work to raise social and
ethical awareness among Project participants, and ensure
that the Project is governed in a way that ensures full compliance with relevant legal and ethical norms. The programme
will draw on the methods developed during empirical investigations of emerging technologies in genomics, neuroscience,
synthetic biology, nanotechnology and information and
communication technologies [108]. It will also draw on the
biomedical tradition of engaging with ethical issues through
the application of formal principles [109] – now usually
implemented through ethical review processes. Partnering
Projects will encourage research and outreach beyond the
scope of the Core Project, offering new perspectives and
new approaches, and involving new target populations.
Meanwhile, studies of the neural basis of higher brain functions have fed scientific and semi-popular debates about
ideas of personhood [126] [127] [128] and free will [129]
[130] [131] while studies combining psychophysics and brain
imaging (e.g., [132] have encouraged philosophers to readdress the eternal mystery of conscious awareness. The capabilities developed by the HBP will provide new material for
these debates.
The public, dialogue and engagement. Attempts to achieve
public dialogue and engagement during the development of
new technologies [133] [134] have used a range of methods
and approaches [135] including consensus conferences,
citizen juries, stakeholder workshops, deliberative polling,
focus groups and various forms of public dialogue. The
motivations for such exercises [111] [136] [137] are sometimes
normative – citizens affected by research have a right to participate in crucial decision-making – sometimes instrumental.
Many authors have argued, for instance, that dialogue can
reduce conflict, help to build trust and smooth the introduction of innovative technology. The strongest conclusion from
these debates is that not even the best prepared exercises
can comprehensively represent the positions of all parts
of society or resolve the issue of which groups or opinions
should have most weight in a particular decision. It is important, therefore, that such exercises respect scientists’ legitimate desire to inform the public about their research, while
avoiding self-conscious attempts to steer public opinion in a
particular direction. Experience from other areas of emerging technology research shows that this requires a sensitive
approach [138]. Public engagement exercises are successful
only if participants are convinced that they can genuinely
influence the course of events [139].
Forecasting innovation and its social and economic impact.
HBP research entails high expectations of social and economic benefits. However, the impact of basic research results
on society often depends not so much on the research
itself as on developments in apparently unconnected areas
of science and technology or on social, political and legal
factors external to science [110] [111] [112].
Current approaches to forecasting development pathways
use one of two strategies. The first studies the views, attitudes and strategies of key stakeholders with methods
from the empirical social sciences [113] [114]. The second,
which has reached its highest stage of development in the
UK (http://www.bis.gov.uk/foresight), uses systematic foresight techniques such as modelling, horizon scanning and
scenario planning. The goals of these exercises are, on the
one hand, to identify new developments and assess their
potential impact over the short, medium and longer term;
on the other to assess key ethical concerns such as privacy,
autonomy, transparency, the appropriate balance of risks
Methods such as consensus conferences, scenario workshops
and citizen’s hearings have developed and spread since the
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Appendix 1
late 1980s, allowing for technology assessment institutions
to act as ‘knowledge brokers’ among science, society and
policymakers [140]. One motivation for using participatory
methods concerns normativity in science-based policy advice.
Expert methods to support decision-making, often overlook
or simplify complex contextual factors such as policy trends
and societal values [141] [142]. The “laws of progress” built into
scientific forecasting methods presuppose a linear societal
development and cannot embrace the complexity of factors
influencing a society over time [143]. To gain relevance, objective scientific knowledge must be “contaminated” by normative evaluations, incorporating the complexity at stake [144].
The import of norms into science must happen in a transparent and socially responsible way. Including citizens in the evaluation of societal development means that scientific advice
is supplemented by the tacit knowledge of those affected by
political decisions [134]. This tacit knowledge often reveals
blind angles in science-based scenarios and administrative
thinking. Today, inclusion of citizens’ perspectives is often
seen as necessary for maintaining the legitimacy of science in
society and science-based policy [145].
tional projects, by the need to take account of different
national jurisdictions.
Foresight as anticipatory knowledge and capacity building. The HBP Foresight Lab is testing new approaches
for integrating responsible research and innovation with
emerging biotechnologies. The Foresight Lab will begin
a multi-institutional process of capacity building, both
within the HBP and with relevant constituencies outside.
It will consider questions of institutions, research and
innovation systems, business and investment strategies
and their implications, public values (including those of
consumers and patients), and challenges for governance.
The Foresight Lab will use an iterative process in which
the views and priorities of different communities interact with one another in an expanding dialogue, and feed
back into the direction, management, and priorities of
HBP researchers. This represents a significant advance
beyond the current state of the art.
Conceptual and philosophical issues. SP10 applies neuroscientific and medical analysis to the philosophical analysis of core concepts such as the mind-brain relationship,
consciousness, self-awareness, human identity and
simulation, enhancing the explanatory power of these
concepts. This approach is already producing results
of strong theoretical, societal and clinical relevance;
one example is an assessment of the role of simulation
as a scientific method in neuroscience and of the way
simulation can increase our understanding of residual
conscious function in patients with disorders of consciousness. Conceptual and philosophical analyses will
help the HBP to interpret the results of neuroscientific
experiments and models. They will also draw attention
to the implications, e.g., changes in our understanding of
human identity, self-hood, personhood, and the relationship between mind and body.
Researcher awareness. Ethical issues cannot be reduced
to algorithms or prescriptions; moral statements and
positions always require higher-level ethical reflection
and justification. From an ethical point of view, this reflection will come not just from external “ethical experts”,
but also from researchers and their leaders. This kind
of general reflexivity is currently not the norm and is
likely to meet resistance. It is nevertheless a key component of Responsible Research and Innovation [146].
Studies suggest that the best way to achieve it is to raise
researcher awareness in governance structures [147]—a
technique already applied in other areas of cutting-edge
technical research, notably nanotechnology (http://www.
nanocode.eu) [148] and synthetic biology.
Governance and regulation. Today’s science regulatory
environment is a result of past research that provoked
a vigorous social and governmental response [149]. One
example is animal research, in which the response took
the form of The Council of Europe’s Convention for the
Protection of Vertebrate Animals used for Experimental
and other Scientific Purposes (ETS 123) (1985), and the
EU Directive for the Protection of Vertebrate Animals
used for Experimental and other Scientific Purposes
[150] – documents that have set European standards
for the laboratory use of mice and other vertebrates.
Another more recent example is synthetic biology. In this
case, the reaction came only after a private institution
had created the first self-replicating bacterial cell from a
completely synthetic genome [108].
Public, dialogue and engagement. The HBP will adapt its
stakeholder and citizen involvement activities to specific
issues that arise during the Project. Rather than having
stakeholders debate HBP from afar, SP10 will facilitate
direct interaction between citizens and HBP researchers.
The results will be concrete enough to directly impact
the work of the Project.
Researcher Awareness. Researcher awareness and reflection is recognised as a key component in all responsible innovation activities. SP10 will tailor methodologies
proposed in contemporary discussions if Responsible
Research and Innovation (RRI), to the needs of the HBP.
Increased awareness of RRI will facilitate communication
related to individual and collaborative research interests,
and will contribute significantly to the HBP’s success.
Modern governance of innovation in biotechnology
involves a variety of actors, including research organisations, national and supranational regulators, governmental or quasi-governmental organisations, professional
bodies, publishers of science journals, and representatives of the mass media and public opinion. As Gottweis [151] noted for the case of transnational research
on embryonic stem cells, decision-making takes place
“… at the fuzzy intersection between science, society,
and politics”. This is complicated, in the case of interna-
Related Actions
WP10.1 Foresight: conduct systematic surveys of the
technological and clinical potential of HBP research
in neuroscience, computing and medicine, and assess
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Appendix 1
their economic, social and ethical implications.
WP10.2 Conceptual and philosophical issues: assess
the conceptual and philosophical implications of HBP
research with special reference to concepts of personhood, consciousness, the relationship between the
brain, the mind and the environment, and simulation.
WP10.3 Public dialogue and engagement: create a constructive dialogue with private and public stakeholders and
with the general public; create and manage Online Deliberations, Citizens’ Forums and Stakeholder/Expert Forums.
WP10.4 Researcher awareness: systematically investigate
researcher perceptions of ethical and social issues arising
from HBP research; organise special sessions in summer
schools and workshops to raise awareness (especially
among young scientists) and to involve researchers in
ethically important decisions.
WP10.5 Governance and regulation: support HBP decision-making on issues with significant ethical, legal or
social implications; manage an independent secretariat
for the ELSA (see paragraph 3.1.10.2) and the REC (see
paragraph 3.1.10.3).
activities within the SP, coordination with other SPs, Partnering Projects and international collaborations, coordinate quality assurance, organisation of meetings and
workshops and reporting.
WP10.7 Ethical, conceptual and philosophical issues:
perform research on ethical, conceptual and philosophical
issues, going beyond the research already planned within
the Core Project.
WP10.8 Public outreach: organise outreach activities to
promote public debate and participation on issues related
to HBP research.
SP10 is already in contact with groups studying ethical
and social issues, on behalf of other large brain initiatives, in particular the US BRAIN initiative and is
working to expand these contacts.
The HBP Ethics and Society Programme will run continuously for the duration of the Project. The work plan for
the Ramp-Up Phase defines specific Milestones for the
set-up of the programme. The HBP Consortium does not
believe it is appropriate to fix detailed Milestones for the
full duration of the Project.
IMP10.1: SP10’s Foresight Lab will inform the debate
on the social and economic implications of HBP
research helping to allay groundless fears, while identifying areas of genuine concern.
3.11.6 Risk Analysis
No major risks are foreseen for this Subproject.
IMP10.2: SP10 will have an important impact
on the emerging academic debate around the
conceptual and ethical implications of recent neuroscience research, in particular of brain simulation.
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3.11.7.2Social and Economic Impact
Brain Facts
IMP10.3: SP10 will build public awareness of the
economic and social potential of HBP research and
encourage public participation in priority setting and
decision-making. Public acceptance of and participation in the Project is a pre-condition for effective
commercial exploitation of Project results.
Whole Brain: The human brain receives
~15% of the cardiac output and accounts for
~20% of total body oxygen consumption,
~25% of the total glucose used in the body,
and consumes ~20% of the power (20 W)
3.11.7.3Innovation Potential
Connectivity: The neurons in a human
brain are connected by ~3 million km of
fibers.
IMP10.4: SP10 will contribute to the Project’s innovation potential indirectly, by making the public aware
of the potential of new computing technologies and
new approaches to the diagnosis and treatment of
brain disease.
Brain Regions: The cerebral cortex
occupies ~77% of the total volume of the
human brain and only ~31% of the total
rodent brain
As a first step, all incoming projects will be checked for legal,
ethical, financial, IP, and data protection criteria, involving
HBP advisory bodies where necessary. Given that most PPs
will be funded from outside sources, the HBP will establish interfaces to the funders in the evaluation process. In
principle, the HBP will not evaluate “scientific excellence”.
This evaluation will be performed by the external funding
organisation. In the case of HBP-issued calls, the “scientific excellence” evaluation will be performed by external
reviewers, using established methods of peer review.
Microcircuits: The smallest cluster of
neurons in the rodent neocortex contains
~31’000 neurons connected by ~180 million
synapses
Cells: The human brain contains ~86
billion neurons and virtually all the genes
in the genome are used to create vast
spectrum of different cell-types
For successful projects, the process will result in a signed
Partnering Project Agreement (HBP) and a positive
funding decision (funding body).
Synapses: The human brain contains ~86
billion neurons and virtually all the genes
in the genome are used to create vast
spectrum of different cell-types
The more influence HBP has on the call text and procedure,
the less pressure there is on the internal evaluation process,
resulting in simplified processes. The most rigorous internal
evaluation is going to be necessary for the existing, already
funded projects seeking to partner. As a principle, integration and evaluation processes will be standardised according to project type. Custom processes may be established
for non-standard PPs on a case-by-case basis.
Vasculature: There are ~!640 km of blood
capillaries in the human brain
Proteome: A single mammalian synapse
is a fraction of a micron in size and is
constructed with ~1000 different types of
proteins.
When a project successfully completes the evaluation
process and the funding decision is confirmed, HBP Management will ensure its smooth integration into the HBP.
The key steps in the process involve the following: signature of a Partnering Project Agreement (PPA) including
provisions for conflict resolution and contract termination, administrative integration (assignment of access
rights on HBP systems, EMDESK integration, legal, data
security, etc.); information to the EC Project Officer, the
RB, the ExCo, and the management team in the new PPs;
public announcement on the HBP Portal; information
from the SP Leader concerned to relevant WP and Task
Leaders; implementation of an Integration Plan for the
SP and the PP; monitoring every three months of integration by the PP integration manager together with the
STO; showcasing of new PPs through the Annual Summit
and through other dissemination channels.
Transcriptome: Most of the ~ 25,000
different genes that make up the human
genome are actively expressed in the
brain and 20-50% may be expressed in a
single neuron
Genome: There are ~ 25,000 genes in the
human genome, and the human genome
is made up of 3 billion bases of DNA.
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4. PARTNERING PROJECTS
Integrating Partnering Projects is of central importance
for the HBP, enabling the HBP to take on board the latest
advances in science and technology as the Core Project
moves forward, and keeping the project open to Partners
across Europe for the entire duration of the Project.
require. Where necessary the Partnering Projects Committees and the Partnering Projects will negotiate adjustments to ensure the maximum mutual benefit. At the end
of this process, the PPC will formulate a recommendation to the RB, which will be formally responsible for the
approval of new Partnering Projects
The key idea underlying Partnering Projects is mutual
benefit: Partnering Projects should benefit from the Platforms and the other capabilities made available by the
HBP; the HBP should benefit from the novel know-how,
technologies and ideas brought in by the Partnering
Projects.
The HBP will make a concerted effort to generate new
Partnering Projects and to give them optimal support.
Planned measures include the nomination of an HBP
call/project integration manager; support for FLAGERA and similar initiatives generating transnational
calls, communication to NFROs, prospective project
consortia and researchers; promotion of PPs to other
relevant European initiatives such as IMI, to pan-European R&D consortia such as EUREKA, and to programmes such as Eurostars; promotion of PPs to HBP
SP Leaders; and measures to give visibility to new and
existing PPs.
In many cases, Partnering Projects will be projects that
have already been evaluated and already have funding
from national funding agencies or other sources. In these
cases, the funding agency or the project itself will request
that the HBP gives the project the status of a Partnering
Project, and integrate its work in the HBP subprojects.
The HBP will also work with FLAG-ERA and successor
projects, national research funding agencies (NRFOs)
and JTCs, to develop Calls for Proposals and other mechanisms to generate new project proposals, directly targeting Actions listed in the HBP Research Roadmap.
Once Partnering Projects have been approved, HBP
Management will ensure their smooth integration into
the HBP. Key steps include the negotiation and signature of a Partnering Project Agreement (PPA), administrative integration (assignment of access rights on HBP
systems, EMDESK integration, legal, data security, etc.);
information to the EC Project Officer, the RB, the ExCo,
and the management team in the PP; a public announcement on the HBP Portal; information to relevant WP and
Task Leaders; implementation of a plan for the integration of the PP in the HBP; showcasing of PPs through the
Annual HBP Summit and through other dissemination
channels. Partnering Projects that are highly successful
in a particular phase of the CP will be invited to become
members of the FPA in the next phase.
Finally, the HBP will provide support to individual scientists and research institutions in the Member States and
the Associated Countries who wish to develop independent proposals for submission to national, EU, national or
other potential sources of funding.
In all three cases, administrative formalities will be kept to
a minimum. Partnering Projects Committees will examine
proposals and assess the benefits offer the HBP, and the
HBP’s ability to provide them with the capabilities they
212
Appendix 1
5. GLOSSARY
Action Potential A short-lasting electrical event in which the
membrane potential of a cell rapidly rises and
falls, following a consistent trajectory of depolarisation and hyperpolarisation.
Axon
A long projection of a neuron that conducts electrical impulsets away from the principle cell body.
Blue Brain Project
An EPFL project launched in 2005 with the goal
of creating the workflows and tools necessary
to build and simulate brain models. As proof of
concept, the project has successfully built and
simulated a cellular-level model of the rat cortical column.
BlueGene
An IBM supercomputer. The BlueGene/P used in
the EPFL Blue Brain Project is a massively parallel, tightly interconnected machine with 16,384
processors, 56 Teraflops of peak performance,
16 Terabytes of distributed memory and a 1 Petabyte file system. The Blue Brain team provides
enough computing power to simulate at least 60
rat cortical columns.
Brain atlas A work of reference (e.g., the Allen Mouse Atlas),
often available as an online public resource
showing how one or more data sets (e.g., gene
expression data) map to specific regions and
sub-regions of the brain.
BrainScaleS
An EU-funded research project that integrates in
vivo experimentation with computational analysis to investigate how the brain processes information on multiple spatial and temporal scales,
and to implement these capabilities in neuromorphic technology.
Cable Theory
Mathematical models making it possible to calculate the flow of electric current (and accompanying voltage), assuming passive neuronal
fibres such as axons and dendrites are cylindrical
cable-like structures.
Connectome
The complete connectivity map between
neurons, including the locations of all synapses.
COORD
Flagship Coordinator.
Core Project (CP) The component of the HBP FET Flagship Initiative responsible for coordinated research and
development critical to building and operating
the HBP Platforms, and for the overall governance and coordination of the Flagship Initiative.
The Core Project will be governed by the Framework (FPA), executed by the partners listed in
the FPA, and funded by the European Commission through the FET Flagship Programme. The
Core Project will be articulated in several (probably three) phases, each regulated by a Specific
Grant Agreement between the Partners and the
European Commission.
The
Core
Project General
Assembly(CP-GA)
The Core Project General Assembly is the
supreme governing body for the CP with respect
to the activities defined for a particular SGA. Its
membership at any one time will be composed
of the FPA Partners contributing to the current
phase of the Project.
Core
Project
Objective (CPO)
One of the 12 objectives of the Core Project,
defined in the Research Roadmap.
CP
Core Project.
CP-GA
Core Project General Assembly.
CPO
Core Project Objective.
Dendrite
The branched projections of a neuron that
conduct electrochemical signals received from
other neurons to the soma of the principal neuron.
Diffusion Tensor
Imaging (DTI)
A technique that enables the measurement
of the restricted diffusion of water in tissue to
produce neural tract images. It also provides
useful structural information.
ECOG
Intracranial electro-corticogram. A technique in
which electrodes are placed directly on the exposed
surface of the brain to record electrical activity.
EEG
Electroencephalography. The recording of electrical activity on the surface of the scalp. EEG
measures voltage fluctuations resulting from ionic
current flows within the neurons of the brain.
Electrophysiology
The study of the electrical properties of excitable biological cells and tissues.
ELSA
Ethics, Legal and Social Aspects Committee.
ESS
Executable System Specification.
Ethics,
Legal
and Social Aspects
Committee (ELSA)
The ELSA is responsible for strategic oversight
of ethical, legal and social issues. The ELSA acts
in an advisory capacity to the RB and the ExCo.
Exascale
Refers to a supercomputer with a performance
of 1018 flops. The first computers with this level
of performance are expected to become available during the second half of this decade.
ExCo
Executive Committee.
Executable Systems
Specification (ESS)
An engineering approach to large-scale system
design in which specifications are implemented
as a complete software model of the device
under construction. The ESS approach makes it
possible to verify the hardware design without
building a physical system.
Executive
Committee (ExCo)
The Executive Committee executes the decisions of the RB and oversees implementation
of the HBP Research Roadmap. The ExCo leads
and supervises the HBP’s internal management
and support structures as well as the Project’s
national, European and international collaborations. The ExCo, established in the Ramp-Up
Phase, has three members (including the Coordinator), each representing one of the three
Strategic Flagship Objectives: future neuroscience (SFO1) future computing (SFO2), and
future medicine (SFO3).
FACETS
A European research project (2005-2010) that
pioneered an integrated workflow for neuromorphic computing, leading from neurobiology and
brain modelling to neuromorphic hardware.
FGF
Flagship Governance Forum.
Flagship Coordinator
(COORD)
The Flagship Coordinator is the legal entity that
acts as the intermediary between the HBP Flagship Initiative and the European Commission.
Flagship Governance
Forum (FGF)
The Flagship Governance Forum (FGF) will
promote openness and contribute to the development of a common European effort based on
the Research Roadmaps defined by the two FET
Flagships. It will support the Flagships’ evolution,
creating synergies between the Core Project
of each Flagship and related activities that its
members are funding at the regional, national,
transnational or European level. The FGF will
be composed of representatives of the Member
States and Associated States of Horizon 2020,
the European Commission, and up to four representatives from each of the Flagship Consortia.
Flagship Partnership
Board (FPB)
The Flagship Partnership Board will maintain a
dialogue among the participants, monitor the
Research Roadmap, and provide input to the
H2020 Work Programme. The FPB will be a
small, operational steering mechanism convened
by the European Commission and co-chaired by
the Commission and the Flagship. A member of
the HBP ExCo will represent the HBP Flagship
Initiative on the Board.
Flop/s
Floating Point Operations Per Second. A
measure of computer performance. The largest
current supercomputers have a performance
in the order of Petaflops (1015 flops). Exascale
supercomputers planned for the end of the
decade would have a performance in the order
of Exaflops (1018 flops).
fMRI
Functional Magnetic Resonance Imaging.
HBP Foundation
The HBP Foundation will be a not-for-profit
foundation under Swiss law. Its purpose will be to
perpetuate and sustain the activities of the HBP;
ensure the evolution of the HBP’s status to that
of a permanent organisation; own and protect
the identity of the Project; establish mechanisms
to facilitate the protection, administration and
commercial exploitation of intellectual property
for the benefit of the HBP; create a network of
partner organisations; and cooperate with other
organisations whose activities are conducive to
these purposes. FPA Framework Partnership
Agreement. FPB Flagship Partnership Board.
Framework
Partnership
Agreement (FPA)
The agreement between the Commission and
the other signatories regulating the execution
of the Core Project in the FET Flagship Initiative, and defining the Research Roadmap for the
whole Initiative.
213
Appendix 1
Functional
Magnetic
Resonance Imaging
(fMRI)
An MRI procedure that measures brain activity
by detecting functional changes associated with
changing blood flow.
Microcircuit
A neural circuit lying within the dimensions of
the local arborisations of neurons (typically
200–500 μm).
Glia
Non-neuronal cells that maintain homeostasis,
form myelin, and provide support and protection
for neurons in the nervous system.
Molecular Dynamics
A form of computer simulation using approximations of known physics to estimate the motion of
atoms and molecules.
HBP
Human Brain Project.
MRI
Magnetic Resonance Imaging.
Multi-level
Refers to a description of the brain that takes
account of its different levels of organisation.
Multi-scale
Refers to a simulation technique that reproduces
the different levels of organisation of a complex
phenomenon, switching dynamically between
different levels of detail according to the needs
of the simulation.
Neuroinformatics
The academic discipline concerned with the use
of computational tools to federate, organise and
analyse neuroscience data.
HBP Flagship Initiative One of the two Flagship Initiatives launched and
managed by the EU FET Flagship Programme.
The HBP Flagship Initiative will be responsible
for implementing the Action Plan and Research
Roadmap defined in this document. It will consist
of a Core Project and Partnering Projects.
High
Performance
The use of parallel processing to run an applications programme efficiently, reliably and quickly.
Computing (HPC)
The term HPC is sometimes used as a synonym
for supercomputing.
Hodgkin
and
Huxley Model
A set of differential equations describing an electricalcircuit model for the non-linear dynamics of
ion channels and the cell membrane of neurons.
Neuromorphic
Refers to a method for emulating the structure
and function of neurons and neuronal circuits in
electronics.
Human
Brain Project
(HBP)
Short name of the HBP Flagship Initiative.
Neuromorphic
Computing System
In silico
A process or an experiment performed on a
computer or via computer simulation.
A computing system comprising a neuromorphic computing device, a software environment
for configuration and control, and the capability
to receive input and to generate output.
In vitro
Studies in experimental biology conducted using
components of an organism that have been isolated from their usual biological context.
Neuron
An electrically excitable cell that processes
and transmits information by electrical and
chemical signalling.
In vivo
Studies using a whole, living organism as
opposed to a partial or dead organism.
NEURON
INCF
Innovation
and
Technology Transfer
Committee (ITTC)
International Neuroinformatics Coordinating Facility.
A well-established environment for the empirically based simulations of neurons and networks
of neurons. Developed by Michael Hines, Yale
University, USA.
Neurorobotic System
A robotic system comprised of a controller, a
body, actuators and sensors, whose controller
architecture is derived from a model of the brain.
Operational Phase
The remaining 7 1/2 years of the HBP, following
the conclusion of the Ramp-Up phase.
International
Neuroinformatics
Coordinating Facility
(INCF)
An international science organisation, the
purpose of whichis to facilitate worldwide cooperation of activities and infrastructures in neuroinformatics-related fields.
Optogenetics
The combination of genetic and optical methods
to control specific events in targeted cells of
living tissue.
Optogenetics
Ion channel
Proteins controlling the passage of ions through
the cell membrane. Ion channels are targets for
neuromodulatory systems and for drugs. The
distribution of ion channels determines the electrical behaviour of the cell.
provides the temporal precision (millisecondtimescale) needed to keep pace with functioning
intact biological systems.
Organelles
Specialised subunits performing a specialised
function within a cell.
iPSC
ITTC
Knowledge
Space
The Innovation and Technology Transfer Committee is responsible for defining and implementing HBP policies on issues related to
intellectual property, acting in an advisory body
to the RB and the ExCo.
Partnering Project (PP)The component of the HBP FET Flagship Initiative responsible for developing new ideas,
approaches and technologies that are proposed
spontaneously by independent research groups,
adding novel capabilities to the Platforms
and using the Platforms to address questions
beyond the capabilities of any individual laboratory. Funding for the Partnering Projects will
come from outside the FET Flagship Programme
(e.g., from regional and national sources, other
sources of EU funding, and industry).
Induced Pluripotent Stem Cell, a type of stem
cell that can be used to generate neurons and
other kinds of cell for use in research.
Innovation and Technology Transfer Committee.
A community-driven wiki integrated in the HBP
Neuroinformatics Platform. The Knowledge
Space provides an encyclopaedic view of the
latest data, models and literature for all levels of
brain organisation.
Localiser
A (usually simple) task used in conjunction
with fMRI to characterise the neuronal circuitry
responsible for a specific cognitive or behavioural capability.
Magnetic
Resonance
Imaging
A medical imaging technique allowing the visualisation detailed internal structures. Nuclear
magnetic resonance (NMR) is used to image
nuclei of atoms inside the body.
Management
Key Performance
Indicators (M-KPIs)
Resource metrics, organisational evolution
metrics, and financial performance indicators used
to track the HBP’s performance on gender and
diversity targets, to show the European and international dimensions of the project, and to track
the overall performance of the project over time.
MCELL
A widely used simulator from the Computational
Neurobiology Lab, SALK Institute, USA. Mcell is
used in reaction diffusion simulations of molecular interactions.
Mechanistic
Refers to an explanation that identifies the causal
chain of physical or chemical events leading from
an initial cause (e.g., a gene defect) to its consequences (e.g., a change in behaviour). In clinical
research, knowledge of such cascades is a precondition for rational drug design.
M-KPIs
Management Key Performance Indicators.
214
Partnering
Projects
Committees (PPCs)
Partnering Projects Committees (one per Subproject) will be responsible for screening candidate Partnering Projects as described in
Appendix 1, Chapter 4. Each committee will be
composed of the leaders of the WPs contributing to the Subproject.
PET
An imaging technique that produces a threedimensional image of functional processes in the
body, using pairs of gamma rays emitted indirectly
by a positron-emitting radionuclide (tracer).
Petascale
of 1015 flops. In November 2011, the Japanese K
computer became the first machine to achieve a
peak performance of more than 10 Petaflops.
Plasticity
The ability of a synapse, a neuron or a neuronal
circuit to change its properties in response to
stimuli or the absence of stimuli.
PLI
Polarised Light Imaging.
Polarised
Light
Imaging (PLI)
An imaging technique making it possible to
identify the orientation of fibres in histological
sections of the brain. Often used for imaging
post mortem samples from the human brain.
PP
Partnering Project.
PPC
Partnering Projects Committees.
Appendix 1
The use of computational techniques to discover statistical regularities in the relationships
between two neuroscience data sets, and the
exploitation of these regularities to predict
parameter values where experimental measurements are not available.
Subproject
Committees (SPCs)
The Subproject Committees plan, supervise
and monitor the Subproject activities defined in
the Research Roadmap. SPCs are composed of
the WP Leaders and Task Leaders contributing
to the Subproject. They are chaired by the SP
leader, assisted by the co-Leader.
Proteome
The set of all the proteins expressed by a cell.
Supercomputer
Ramp-Up Phase
The first 2 1/2 years of the HBP.
A computer with performance close to the
highest performance attainable at a given time.
RB
Research Board.
Synapse
A structure between two neurons allowing them
to communicate via chemical or electrical signals.
REC
Research Ethics Committee.
SyNAPSE
Receptor
A protein molecule that receives and transmits
chemical information across membranes.
Reconstruction
A computer model of the brain or of parts of
the brain derived from sparse data by exploiting
interdependencies between data sets spanning
different levels of biological organisation.
A research project funded by the US agency
DARPA with the aim of building energy efficient, compact neuromorphic systems based on
modern component technologies.
Terascale
of 1012 flops.
Transcriptome
Research Board (RB)
The strategic decision-making body for the HBP
Flagship Initiative. The RB is composed of one
representative per SP (the Leader of the SP)
with an alternate (the SP co-Leader) who can
stand in if the SP-leader is unable to attend a
meeting.
The set of information required to fully represent
all cDNA expressed by a cell during translation
of the genome.
Very
Large Scale
Integration (VLSI)
The integration of very large numbers of transistors on a single silicon chip. VLSI devices were
initially defined as chips with more than 10,000
transistors. Current systems may contain more
than 2,000,000.
Predictive
Neuroinformatics
Research
Ethics
Committee (REC)
The Research Ethics Committee, helps the Partners to ensure that HBP research meets the
highest possible ethical standards, and that it
complies with all relevant European, national
and regional laws, as well as with the deontological standards imposed by relevant professional
bodies.
SAB
Strategic Advisory Board.
Simulation
The imitation or replication of a complex realworld process.
Numerical indicators that show the progress of
Scientific
Key
Performance Indicators individual tasks or tasks components over time.
(S-KPIs)
S-KPIs
Scientific Key Performance Indicators.
Soma
The cell body or the compartment in a cell that
houses the nucleus.
Specific
Grant
Agreement (SGA)
An agreement between the European Commission and the signatories regulating a specific
phase of the Core Project.
SGA
Specific Grant Agreement.
SpiNNaker
A UK-funded research project, the goal of which
is to build neuromorphic computing systems
based on many-core chips with efficient bidirectional links for asynchronous spikebased
communication.
Steering
Refers to interactive control of a simulation
using real-time (usually visual) feedback from
the simulation.
STEPS
A simulator for stochastic reaction-diffusion
systems in realistic morphologies, from the
Theoretical Neurobiology group, University of
Antwerp, Belgium.
Strategic Advisory
Board (SAB)
The Strategic Advisory Board is an independent
body composed of internationally recognised
leaders in neuroscience, computing, and medicine. The SAB provides advice to the RB and the
ExCo.
Strategic Flagship
Objective (SFO)
One of the three strategic objectives of the
whole Flagship Initiative. The Research Roadmap
defines SFOs for future neuroscience, future
computing, and future medicine.
SFO
Strategic Flagship Objective.
SP
Subproject.
SPCs
Subproject Committees.
Subproject (SP)
A component of the HBP Flagship Initiative
charged with coordinating the Initiative’s activities in a given area of scientific, technical or managerial work. The HBP Flagship Initiative consists
of 10 Subprojects dedicated to research, and one
dedicated to management and coordination.
Subprojects bring together work performed by
the Core Project, by Partnering Projects and by
collaborations with other national, European or
international projects and initiatives.
VLSI
Very Large Scale Integration.
Workflow
Term used in management engineering and in
computer science to describe a sequence of
steps leading to a welldefined outcome.
Work Package (WP)
A component of a Subproject covering a specific
area of scientific, technical or managerial work.
Work Package Deliverables and Milestones for a
given phase of the HBP will be defined in the
SGA for that phase.
WP
Work Package.w
215
Appendix 1
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