Long-range interactions in visual perception

REVIEW
L. Spillmann and J.S. Werner
– Long-range interactions
Long-range interactions in visual perception
Lothar Spillmann and John S. Werner
Classical
receptive-field
conceptshavebeenusedto explainlocalperceptualeffectssuchasborder
contrastand Machbands,but are not suficientto explainglobalperceptualeffects.Examplesare
the perceptionof illusorycontours,areacontrast,colorconstancy,
depthplanes,coherentmotion
and texture contrast.Thesediverseeffectsrequire neurophysiological
mechanismswithinthe
visualpathwayswith long-rangeinteractions.Candidatemechanismsare suggested,including
convergingfeedforwardprojectionto accountfor the emergenceof newresponsepropertiesat
higherlevels,recruitmentof lateralconnectionsto compensatefor lossof afferenceand explain
filling-in,andre-entrantprojectionsfrom higherlevelsusingsynchronization
of neuronalresponses
to accountfor binding.
Trends Neurosci. (1996) 19, 428-434
I
Lothar Spillmcmnis
at the Instituteof
Biophysicsand
RadiationBiology,
Brain Research
Unit,LJniversi~of
Freiburg,
Hansastrasse9,
D-79104 Freiburg,
Germany,and
John S. Werner
is at the
Deptof Psychology,
Universityof
Colorado,Boulder,
CO80309-0345,
USA.
428
N THEIR PIONEERINGSTUDIES of contrast
phenomena, Mach’ and Hering23in the last century
proposedthat each region of the retina might interact
with many other distant regions (’Wechselwirkung
der Sehfeldstellen’).Fiftyyears later, the Gesaltists, in
their attempt to understand phi motion (that is,
apparent motion between two successivestimuli presented in differentlocations) and figure-groundsegregation’, called for similar interactions in the realm
of form and motion perception. In many demonstrations they showedthat the appearanceof a given
part of the stimulus pattern depends on the context
within which it is embedded.It is only recently that
the anatomicaland physiologicalmechanismsfor these
figure-groundrelations(Wertheimer’s‘Querfunktionen’
or lateral functions) have come under scrutiny.
The classical receptive-field concept originating
with the work of Kuffler5and Barlow6provided the
basis for contemporary ideas about neural representations of visual form. Yet, correlations between perception and center-surround antagonism of retinal
receptive fields have been limited to short-range
effects such as Mach bands7and illusory spots in the
Hermann grid (for further examples, see Refs 8-10).
Such short-range interactions cannot explain more
complex aspectsof perception involving spatiallyseparated areas in the domains of illusory contours,
brightness, color, depth, motion and texture. Longrange interactions, primarily in the cortex, are
required.
It is now accepted that in many visual neurons,
stimuli presented outside the classical receptive field
exert a strong and selective influence on the response
to stimuli presented within the classical receptive
field”. Among the earliest examples of long-range
interactions was the peripheryeffect12,which showed
that the response of retinal ganglion cells in the cat
can be facilitated by moving a stimulus in the far
peripheryof the visual field. A similarinteraction was
demonstratedin retina and lateral geniculate nucleus
with a shifting grating surround13’14.
The perceptual
significance of these effects is unclear, although they
might play a role in visual attention and suppression
during saccadic eye movements15.The problems disTIM Vol. 19, No. 10, 1996
cussed here, however, are not with physiological
mechanisms in search of perceptual correlates, but
with perceptual phenomena in quest of neuronal
mechanisms.
In this paper, we present six phenomena requiring
an explanation in terms of long-rangeinteractions in
the visual field. The mechanisms proposedto account
for these interactions are: (1) converging feedforward
projectionsleadingto the generationof new receptivefield propertiesat higher levels; (2) horizontal intrinsic connectionsprovidingfor interactionwithina single
visual area; and (3) re-entrant feedback projections
divergingto cells at lower levels which respond selectively to specific properties of a stimulus. It has been
argued that the divergent feedback associated with
this latter mechanism might utilize synchronization
of neuronal responses as the basis for binding. The
six phenomena, all of which can be observedunder
naturalconditions,and their hypotheticalexplanations
by long-range interactions constitute a challenge for
neurophysiologists as they shift their attention
increasinglyfrom local to global mechanisms of visual
perception.
Illusorycontours
andbrightness
enhancement
In nature we rarely experience an unobstructed
viewof an object; most objects are seen only partially,
due to occlusion by other objects. Despiteincomplete
views, however, there is seldom confusion about
which parts belong together. A partially occluded
object is perceivedas unitary accordingto the Gestalt
factors of good continuation, closure and the principle of ‘Pragnanz’ (figural goodness). Similar principles applyto the perception of an illusoryfigurein a
seeminglyincomplete stimulus configuration such as
the Kanizsa triangle (Fig. 1), where an area Of uniformly enhanced brightnessbounded by illusorycontours is generated by the corners of a hypothetical
triangle.There is no luminance differencebetweenthe
inside and outside of the perceived figure, yet the
triangle appearsto be lighter than the background.
Although it is tempting to assign illusory contours
(and surfaces)a role in everydayperception, they are
in fact rarely if ever seen in a natural setting, Also,
Copyright 431996, Elsevier Science Ltd. All rights reserved. 0166-
2236/96/$15.00
PII: S0166-2236(96)1
OO38-2
L. Spillmann and J.S. Werner
unlike recognition of a partially hidden object which
will occur even if the occlusion is ‘jagged’, illusory
contours requiresmooth gapsand closely alignedsegments. Neurons with classical receptive fields cannot
account for such contours; long-range connections
within a larger‘responsefield’ able to mediate perceptual completion acrossgapsof severaldegreesof visual
angle are needed.
Peterhans, von der Heydt and Baumgartner16’17
found that approximately one third of the magnocells in area V2 of the macaque monkey, the second
largest cortical area for visual processing, are responsive to cues eliciting the perception of subjective
contours in human observers. End-stoppedreceptive
fields of these cells are hypothesizedto fill-in the gap
and restore the (incomplete) Gestalt by connecting
the parts with an illusory border. The parallel behavior between these cells and the percept suggeststhat
one is a neural substrate for the other. Related
phenomena implying long-distance interactions
might be similarly explained. For example, illusory
stripes (’phantoms’) can be observedmoving through
an empty horizontal gap in phase with two vertical
gratings on top and on the bottom’g. The uniform
brightness enhancement observed in the Kanizsa
triangle is an example of filling-in as discussedbelow.
REVIEW
– Long-range interactions
(1)
(2)
Areacontrast
andfilling-inof brightness
andcolor
The fundamental cues defining figure-ground segregation in a stationary stimulus configuration are
brightness, color, binocular disparity,motion and texture. In this section, we concentrate on the first two of
these cues. Areaspossessingthe same brightness and
color are usually seen as one, figure or ground. This
segregationis supportedby contrast mechanisms that
enhance the difference between adjacent regions of
the visual field. However,border contrast alone is not
sufficient to describeour visual experienceunder normal conditions; enhancement of surfacesby area contrast is equally important. For example, a grey square
of given luminance presented on different shades of
greywill be perceivedas having greatlydifferentlightnesses. Or, a yellow disk if surroundedby an achromatic annulus of variable luminance will turn brown
and ultimatelyblack as the luminance of the surround
is progressivelyincreased above the luminance of the
center (’Schwarzverhullung’
23’19).A striking example
of area contrast, known as colored shadows, was
describedby Goethezo. His illustration is presentedin
Fig. 2. Here, an area of broad-bandillumination, that
would appear white under ordinary viewing conditions, looks bluish when surrounded by yellow.
Unlikeborder contrast, which enhances the difference
between figure and ground, area contrast serves to
homogenize regions of different color and brightness
within the figure.
What might be the processes and mechanisms
responsiblefor brightnessand color perceptionwithin
uniformly stimulatedareasboundedby an edge?Most
neurons in areaVI and V2 do not respondto constant
illumination within their receptive fields. Absence of
response is ambiguous- it occurs in the presence of
many stimulusconditions. Yet we do not see outlines,
we see uniform surfaces bordered by contours. The
need for signalsfrom contours to prevent a perceptual
void becomes apparent when the image is stabilized
on the retinazl.Within seconds the entire perceptwill
Fig. 1. Kanizsa Triangle. This pattern gives rise to a subjective triangle (left), which is obo/ished when the inducing cuesare closedby thin curves(right). End-stopped cellsin area VI are
assumed to mediate the subjective contours based on receptive fields shown schematically by
an elongated excitatory region and an inhibitory end zone (depicted in gray). They are ideally
suited for detecting terminations of edges and lines, such as at corners. The bottom scheme
shows a hypothetical feedforward circuit to account for the illusion. The contour cell (2) in V2
is assumed to sum the signals of two para//e/ paths: (1) an edge-detecting path responsiveto
real contours of a given orientation; and (2) a grouping path integrating responsesto stimuli
oriented orthogonally to the contour. It is assumed that the receptive fields of the grouping
path are distributed along the receptive field of the edge-detecting mechanism and that their
inputs are mukiplied (X) before being summed (X). As this mechanism cannot distinguish
between signak from either path, we perceive a faint edge where in fact there is none.
Modified from Ref. 16.
Fig. 2. Coloredshadaws (simultaneous color contrast). A white light
is used to illuminate a surface from the left whi/ea yellowlight i//uminates it from the right. An object placed in the center will cast shadows
of the object that differ in color. In the area that receivesno white light,
the shadow is a saturated yellow, while the area receiving only white
light appears bluish. Colored shadows are frequently observed on the
snow and under intense spectral light sources. Modified from Ref. 20.
TINSVol. 19, NO. 10,1996
429
REVIEW
L. Spillmann and J.S. Werner
– Long-range interactions
disappearor fade (Troxler-effect;local adaptation). If,
however,the stimulus contours are displaced,as with
involuntary eye movements, the percept reappears.
We conclude that in order to sustain the brightness
and color of the central area, the signals corresponding to the edgesmust be constantly revived.
That these interactions dependon global, not local,
mechanismswasshownby Gerritsand Vendrik22,who
observed that colors in stabilized retinal images
encompassing the blind spot were perceived as uniform disks. This is a process known as filling-in. The
scotoma correspondingto the physiologicalblind spot
can be madevisible only with specialtechniques, such
as using small perimetrictargets. If a scotoma is mimicked by a large uniform disk presented on a colored
or textured background it will also tend to fill-in by
acquiring the spatio–temporal properties of the surround. For example, a largered diskshown on a green
background will rapidly disappearfrom vision to be
replacedby a uniformly green surface if the border is
blurred or stabilized on the retina23.Similarly, a uniformly grey target on a dynamic noise background
will temporarily fade from view to be filled-in by
noisez’z’.
Recent evidence shows a neurophysiologicalcorrelate of this adaptation in area V3 (and to a lesser
degree area V2) of the behaving monkey: within seconds of being presentedwith a textured stimuluscontaining an ‘artificial scotoma’ (producedby a white
square), the initially lowered activity of a cell will
recoverand approachthe activity elicited by the same
stimulus,but no scotoma26.The deficit of neural activity within the scotomatous area (and its presumed
compensationby lateralinteractions)is in a wayanalogous to filling-in of the blind spotz’.To explain these
percepts, long-range signals arising at the edge and
propagatedfrom the boundary to the silent neurons
representing the enclosed region are required. The
ambiguity associated with the absence of neuronal
response makes it possible for lateral interactions to
impart a signal to those neurons that is consistent
with the stimulusas encoded at the edge.
Colorconstancy
Color constancy refers to our ability to perceive a
given color as the same despite changes in ambient
illumination. This ability is essential for learning the
identity of objects. It has long been known that the
brightness and color of an area depend crucially on
the illumination of the surround, particularlyat the
edges as was discussedfor area contrast. In complex
scenes, overall increasesin illumination might be discounted by reciprocal lateral connections: the effects
of light in the center are offset by the effects of light
in the surroundsuch that the net effect is to promote
brightnessand color constancy23’28.
The importanceof
integrating information over large regions of space to
maintain color constancy was emphasizedby Landzg,
who showedthat spatiallycomplex stimuluspatterns
(patchwork of color called ‘Mondrians’ after the
works of the Dutch painter Piet Mondriaan) tend to
maintain their appearance despite large changes in
the intensity and spectral distribution of the light
source. Shown in isolation, individualregions of the
stimulus pattern would assume a different hue with
changes in the intensity or spectraldistributionof the
illumination.
430
TINS Vol. 19, No. 10, 1996
Land proposed an algorithm for computing colors
that wouldsupportconstancy. This algorithm is based
on a comparison of three receptor-specific lightness
values from each surface in the scene with those of
other surfaces. One way of implementing this algorithm would be to move a photosensitive ‘mouse’
along arbitrarytrajectories from the perimeter of the
Mondrian to the surface under consideration. By
crossing a number of borders, a comparison can be
madebetweenthe reflectanceratios for a given surface
relative to that of neighboring surfaces. Alternative
schemes have been proposed (for example, Ref. 30),
but most retain the important notion that constancy
depends on long-distance comparisons between different regionswithin a given pattern.
Long-rangecomputations involved in color induction and filling-in of large areas might be generated
alreadyat the level of the retina31or lateral geniculate
nucleu532,
but
the
global
computations required for
color constancy most likely involve cortical interactions between both hemispheres. The importance of
transcortical connections in color constancy was
demonstratedin a patient whose corpuscallosum had
been transected surgically to control his epileptic
seizuresjj. For this individual, color constancy for
stimuli falling on different hemifields was severely
impairedrelativeto normal observers.This case study
suggeststhat, given the appropriatestimuli, color constancy can be mediated by communication between
the two hemispheres. Where might these long-range
computationsbe carriedout in the visual system?The
answeris not known, but it is likely that they depend,
at least in part, on area V4, where cell responses are
modifiedby both local and global chromatic surround
information includinginformation coming from deep
inside the ipsilateral visual hemifield34.In primate
area V4, Zeki35has described‘perceptive’neurons that
respond in a context-dependent manner, and seemingly consistent with the perceived color of a stimulus, rather than its wavelength. The inputs from the
complex surroundsof these cells have not been quantified, but Zekinotes that they are long-rangeand defy
descriptionin terms of the classicalreceptivefield.
Theperception
ofdepthplanes
A phenomenon analogousto the uniform filling-in
of boundedsurfacesis the uniform induction of depth
from the edges onto an enclosed area. This is called
‘depth capture’. However,rather than by luminance
or color contrast, the perception of depth planes is
defined by the lateral disparities at the borders. For
example, an outline squarein which the vertical lines
for one eye are displaced laterally (so as to produce
crossed or uncrossed disparity) is perceived as uniformlyelevatedor recessedin depth in spiteof the fact
that the area between the lines providesno disparity
information. It appearsthat the entire enclosed uniform surface assumes a different depth plane based
only on the cues,providedby the edges. This ‘depth
capture’ is conceptually similar to the filling-in
processes discussed earli&. To explain these effects,
one has to assumelong-distanceinteractions.
This assumptionis also supportedby the occurrence
of depth contours in random-dotstereograms36.Here,
none of the monocular images contains contours
to define a figure. The figure emerges only after
binocular fusion has taken place (form-from-depth).
L. Spillmann and J.S. Werner
REVIEW
- Long-rangeinteractions
To extract depth from such a stimuluswould seem to
require a global comparison of the two monocular
imagess7.While there is evidence suggestingthat the
correspondence problem might alreadybe solved by
VI neurons within local regions of the random-dot
stereogram38, the contour separatingthe depth Planes
appearsto be made explicit only by cells in area V2
(Ref. 39). This contour almost certainly requires a
global mechanism as it does not connect individual
dots to make an irregular or jagged contour, but
instead follows a perfectly smooth straight or curved
line. Little is known about the algorithm used by the
brain to perform this smoothing operation.
Coherentmotion
Groupingof stimuli by coherent motion is a powerful effect to be attributedto binding. Figure3 servesto
illustratehow an invisible figurecomposedof dots on
a dotted background will ‘pop out’ at the slightest
movement by virtue of the Gestalt factor of common
fate. The figurewill also be perceived,but not as well,
when only the background dots move or when both
the dots representingthe figure and those representing the ground move in different directions or at different speeds.Despitethe coarsenessand irregulardistribution of the dots the word MOTION emerging
from the noise field tends to have crisp, well-defined
edges. It also is seen as lying slightly above the background.This is similarto the stratifiedsheets of noise
sliding past each other when two groups of random
dots moving in different directions are spatiallysuperimposed’”.The high spatial resolution needed for the
edge extrapolation and the low resolution needed for
the stratification require mechanisms analogous to
those that produce smoothing and filling-in of depth
planes in random-dot stereograms.Single-cell studies
in the macaque monkey have yielded neuronal correlates of motion segregationin areaV1 (Ref. 41) and of
motion transparency in the medial temporal area
(area MT)Q. Motion filling-in also OCCS.US when ‘ne
observesa large figure such as a homogeneous white
square moving over a black background. In this
example, motion signals originate only at the boundary of the figurewhile no signalsare generatedby the
interior. Yet, we see the whole figure moving instead
of just accretion at the leading edge and decretion at
the trailing edge. This might be called motion capture
by analogy to depth capture.
Using both psychophysical and electrophysiological methods, Niedeggenand Wist43showedthat only
a small percentageof spatiallydistributed,coherently
moving dots in a dynamic random-dotfield were sufficient to support figure-ground segregation. That
coherent motion does not require identical directions
and speeds for all elements in an array is demonstrated by biological motion such as observed when
small lights are attached to the main joints of the
body of a dancer in the dark44.One can easily group
the varyingtrajectories of the individuallights to perceive correctly the movements of the dancer. What
might be the cellular basis of motion coherence?
Britten and colleagues’sidentified cells in area MT of
the monkey that respondin a manner that is directly
parallel to the behavioral findings. These cells have
large receptive fields and are highly sensitive to the
coherent translation of dots within a random-dot
kinematogram. The ability of neurons from area MT
Fig. 3. Coherent motion. If one makes a transparency af the word
MOT/OIV in a photocopying machine and over/ays it onto the rcmdomdot background, one perceives figureqround segregation through
coherent motion. The individual letters will be invisible as long as the
foi/ is kept stationay, but will immediate/y pop-out when it is moved
relative to the background. This is an example of grouping by the
Gestalt factor of common fate and might be attributed to synchronization of neuronal responsesof movement-detecting cells in the medial
temporal area (MT), a process called binding.
and the medial superiortemporal (MST)area46to integrate motion information (including constriction,
expansion and rotation) across large portions of the
visual field requiressubstantialconvergenceof inputs
from earlier cortical levels, such as V1 and V2. The
generation of receptive fields that can mediate this
long-range integration is likely to be accomplished
through the convergenceof feedforwardconnections.
Convergingfeedforwardprocessingis also likely to
mediate the perception of apparent motion as
described by Wertheimer4. Thresholds for apparent
motion in humans and monkeys were measured by
Newsomeand colleagues47,and their psychophysical
resultswerecomparedwith cell recordingsin areasV1
and MT. The authors conclude that MT neurons are
responsiblefor the perception of fast apparentmovement, whereasboth VI and MT neurons are responsible for slow apparent movement. They suggestthat
the neuronal substratefor apparentmotion might be
distributedover multiple cortical areas, dependenton
the speedand the spatial interval of the stimulus.
Texturecontrast
There are severalstrikingexamplesof texture segregation that suggest the involvement of long-range
neuronal interactions across the visual field. The sudden emergence or ‘pop-out’ of a stimulus element
embedded within a matrix of elements differing in
orientation, color, polarity, size, shape and texture
requires fast long-distance comparisons without any
effort or conscious attention by the observer. These
processesare independentof the numberof distracters
and have been attributed to parallel (versus serial)
search. They are, therefore, called preattentive4&50.
It has recently been shown that neurons in area VI
respond dependingon the perceptualcontext within
TINSVO1. 19, No. 10,1996
431
REVIEW
L. Spillmann and J.S. Werner
- Long-rangeinteractions
A
B
Receptivefields
Corticalcells
Fig. 4. Filling-in of o retinal scotonxz (A) Shaded areos illustrate the receptive fields of cortical cellsA, B and C. The crrrowsrepresent intracortical connections from cellsA and C onto
cell B. The inputs provided by these /otera/ connections are assumed to be relatively weak and
not detectable under normal conditions ofihmrination. (B) Followingloss of primary afference
due too retinal lesion, cell B will cease to respond. However, after only a few minutes it can be
reactivated by stimulation of the shaded oreas surrounding the /esion. This enlargement of the
effective receptive field is mode possible through ‘recruitment’ of horizontal connections with
cc//s A and C (thick arrows). The perceptual consequences of the recruitment might be a
fi//ing-in of the scotoma from the surround such that a uniform field is perceived despite the
absence of stimulation within the /esioned area.
which the stimulus is placed. For example, the
responsesof many neurons were suppressedmarkedly
by line textures extending beyond the classicalreceptive field51-53.
These regions are normally silent, but
will inhibit or facilitate the neuronal response if
stimulatedin conjunction with the classicalreceptive
field. Accordingly, the response to an optimally
oriented bar was enhanced if the surroundingtexture
was oriented orthogonally. In other words, responses
of these cells were consistent with an increased perceptual salience, analogouslyto ‘pop-out’.Pop-outby
orientation contrast is paralleledby a similarenhancement due to motion contrast when a cell’s responseis
facilitated by antiphase movement in its receptivefield surroundSA,SS.
Such neurons might be inS.tmmental in mediating figure+groundsegregation.
Potential
mechanisms
Neurophysiological and anatomical studies have
provided evidence that the visual system processes
global information in at least three different ways:
(1) converging feedforwardprojections from lower to
higher levels; (2) recruitment of lateral connections
within the cortex to compensate for loss of afference
in deafferented cells; and (3) synchronization of
neuronal responses and ‘tagging’ of lower-level cell
activity by re-entrant signals.All of these mechanisms
are relevant to the understandingof the phenomena
describedhere.
Traditionally, hierarchical feedforward processing
has been assumedwhereby new receptive-fieldproperties evolve from convergent inputs from lower-level
neuronss~ss.The idea here is that widely separated
neurons at lower levels become interacting neighbors
at higher levels through remapping. We now know
that the projection from areas VI and V2 to area MT
and the inferotemporalcortex (IT) is not strictly topographic;spatially,the receptivefieldsof these areasare
quite large with a substantial overlap. Barlow has
arguedthat these non-topographicprojections are not
random, but occur in an orderlypattern accordingto
stimulus dimensions (see also Ref. 59). He assumed
that all information on one aspect of the stimulus(for
example, motion in one direction, one velocity) is
brought together from a wide region of the visual
432
TINS VO1. 19, No. 10, 1996
field. The large number of specializedpathways and
cortical areas with their anatomically identified patterns of connectivity known to servevision60,61
would
supportthis bottom-up approach.
Amongthe six phenomena described,the filling-in
of illusory contours and area brightness lends itself
most clearlyto an explanation in terms of converging
feedforward projections. Peterhans, von der Heydt
and Baumgartner16’17propose that multiplicative
inputs from end-stopped cells in area VI, tuned
orthogonally, are required for generating the illusory
contours of the Kanizsatriangle. A subjective contour
is signaledwhen a higher-ordercell in area V2 is activated concurrently by two or more of these distant
inputs. Since the same neuron might also respond to
a physical line in the same location as the subjective
contour, the output of the cell is similar for the two
types of stimuli, as is their appearance.Furthermore,
when the sectors inducing a subjective contour are
closed by thin curves, as illustrated in Fig. 1 (right),
the neuronal response breaks down and so does the
illusion. In the context of the model by Peterhansand
colleagues,this wouldbe expectedbecausethe closing
lines fall on the inhibitory end-zones of the endstoppedcells and thus reducetheir activation.
A second kind of neural processing to explain
filling-in involves horizontal intrinsic connections
within a single visual area. It is now known that
dramatic dynamic changes occur in the size and location of cortical receptivefields when retinal activity
is preventedfrom reachingits target areaby deafferentation. For example,when a scotoma is inducedin cat
retinae by photocoagulation, receptive fields of cells
in the lateralgeniculatenucleus62and striatecortex63’64
that had previouslyreceived input from the lesioned
areabecome displacedand enlarged.This is illustrated
in Fig.4. The finding that the initially silencedneuron
can be re-activated,within minutes, by stimuli falling
onto the edge of the lesion65)66
suggestsa mechanism
that mediates input through lateral connections. An
alternative explanation of short-term plasticity in
terms of an overall increase in cell responsiveness,
rather than a dynamic alteration of receptive-field
structure,has been proposed67.The functional potentiation resultingin either case wouldlead to a perceptual filling-in of a gap, such as a retinal scotoma,
although the much slower recovery in patients
suggeststhat sproutingmust also take place.
If deafferentationfollowinga lesion leads to fillingin by lateral interaction, it would also be expected to
occur when there is no patterned input due to a mask
covering a certain region of the retina (artificial scotoma). Indeed,in the cat it has been shown that when
the area from which a given neuron can be driven is
maskedby a black diskand a gratingpattern is moved
in the immediatesurround,the receptivefield expands
up to five times its original size, enabling cells to
become responsiveagain68.Similarly,followingpartial
occlusion of a dynamic noise stimulus,cells inarea V3
of the monkey will compensate rapidly for the
reduced retinal stimulation with an increase in
response,presumablydue to an unmasking(disinhibition) of previously ineffective excitation from well
outsidethe classicalreceptivefield26.
An even larger expansion has been reported by
Fiorani and colleagues69,who obtained responses in
area VI of the monkey when stimulating two regions
L. Spillmann and J.S. Werner
on either side of the optic disk that were 15 degrees
apart. These distances are up to IOtimes the lengths
of conventional receptivefields,implyinga functional
(and structural) convergence much larger than
hitherto thought. Although the blind spot is present
from birth and thus represents a special case of a
scotoma, the physiological findings suggestthat our
unawareness of it might be based on a filling-in
process that uses mechanisms similar to the intracortical connections underlying filling-in of other
kinds of scotomas.
Filling-in by horizontal interaction might also be
responsible for uniform brightness and color perception in extended areas. One possible manifestation of
this type of neural processingis illustratedin Fig. 5 for
the Craik–O’Brien-Cornsweet illusion. Contrary to
the luminance profile, the perceivedbrightnesswithin
the central area is uniformly low, whereas in the surround it is uniformly high. Clearly, these two brightness levels must be defined by the relative neural
activities at the border. Horizontalconnections of up
to 6mm between spatially separated hypercolumns
have been found”71 that could mediate propagation
of edge signals and thereby ‘assign’ different brightnesses and colors to regions of the visual field several
degreesaway. Polysynaptic cascades of local connections could carry these signals even further. It is
important to add that the distribution of neural activity measured by microelectrode recording is only
about 5% of that found by optical recording,in agreement with what might be needed to explain many
long-range perceptual effects’z. A similar interpretation applies to the segregation into smoothly delineated depth planes. Modelsassumingconnectionist
networks73and boundary-triggereddiffusion74have
been proposedto account for these effects.
A third neural process that supports global integration involveslong-rangefeedbackprojections from
higher areas to group cell responsesat lower levels or
across hemispheres” by virtue of synchronization of
neural activity among separateareas. These top-down
projections need not be confined to the cortex. It is
known, for example, that the feline cortex has massive
projections to the lateral geniculate nucleus”. It
should also be noted that top-down feedback from
higher areas does not necessarilyrequire synchronization, and conversely synchronization does not
necessarily involve feedback from higher areas, but
might be accomplishedby feedforwardor lateralinteractions in some yet unknown manner.
While binding by re-entrant signals might contribute to more than just one of the phenomena
described,it is most easilyunderstoodwith respectto
coherent motion. We know that spike activities
between remote brain areas can interact by way of
synchronization within a cell assembly, thereby producing a possibleneuronal basis for perceptualcoherence and connectivity7778.Such a scheme would serve
to enhance the salience of a figurewith a minimum of
neural connections: the significance of a neuron’s
activity would depend on the context of activity in
other neurons7g,a0.
For the multitude of random dots
comprisingthe wordMOTIONin Fig.3, the synchronization of activity in cells with separatereceptivefields
might provide the binding necessary to obtain
structure-from-motion. To confirm this hypothesis
an experiment combining single-cell recording and
REVIEW
– Long-rangeinteractions
Craik–
O’Brien–
Cornsweet
illusion
Luminance
profile
Receptive
fields
Cortical
cells
Fig. 5. Area contrast. The Craik-O’Brien–Cornsweet illusion (see
Ref. 70) is shown on the top with its corresponding luminance profile.
The Iuminances of the center and surround are identical, as can be
verified by placing thin strips of paper over the discontinuitiesindicated
by the luminance profile. Without the strips, the perceived brightness
within the central area is uniformly /ow while in the surround it is
uniformly high (center panel). It is assumed that the brightness in each
area is ‘assigned’ according to the brightness at the surrounding edges
with the gradual luminance change rectified. This homogenization of
brightness across a large surface might be attained in analogy to deafferentation by cells that propagate the edge signal across adjacent
areas where input is weak or lacking (cell B). The spread of uniform
brightness is hypothesized ta be due to recruitment of /ong-ronge /ateral connections from cellsA and C.
behavioraltesting is neededto be able to correlatethe
extent of synchronizationwith the perceptualsalience
of a stimulus.This experiment remains to be done.
What is the evidence for such a proposal?On average, each cortical area in monkey possesses connections t. 10 others81.These connections are between
areas at the same level as well as above and below in
the cortical hierarchy, giving cells in any tissue patch
distributedparallel access to information different in
both retinotopic location and sensory specialization.
Successful spike transmission to exploit these pathwaysrequiressynchronous dischargein widelyseparated areas. Striate and extrastriate neurons of both
cat82and monkef13 stimulated by coherent motion
show synchronizeddischarges(short bursts occurring
at 40-90 Hz), even though the individual stimulus
elements are spaced over areas much larger than
Hubel and Wiesel’s hypercolumns. This theoretical
framework might also account for the long-range
facilitation underlying the Gestalt factor of good
continuation84’85.
Global integration might sometimes be based on
more than one neural mechanism to produce a given
phenomenon. For example, in a neural-network
model, texture contrast has been attributedto feedforwardprocessingwith inhibitory interneuronsbetween
TINS Vol. 19, No. 10, 1996
433
REVIEW
L. Spillmann and J.S. Werner
– Long-rangeinteractions
orientation detectors8bas well as to lateral modulation
by orientationally tuned cells via horizontal connections8788.However,the same phenomenon could also
be interpretedin terms of binding through synchronization. Similarly,while coherent motion and motion
contrast were explained by synchronization’g, it
might equally be accounted for by convergent feedforwardprojections4b89.
To explain many of the phenomena of the Gestalt
school that have eludedneuroscientist for more than
50years, it appearsthat we must deal with the possibility that simple perceptsare the achievement of distributedprocessingby morethan one corticalarea.This
idea requirestwo tasksfrom neuroscience:to establish
mechanisms for the synchronization of information
and binding among multiple areas, and to give reciprocal projections a more central role in spike transmission. The real challenge, however,lies in the problem of demonstratingthat perceptualsalienceparallels
the pattern of cell responseswithin an assemblyin the
human brain. The perceptualphenomena discussedin
this paper require visual neurons that respond not
solelyto stimulusfeatureswithin a localizedarea,but,
equally importantly, to the context in which they
appear.This is consistent with the Gestalt credo that
the whole is different from the sum of its parts.
Selectedreferences
1 Mach, E. (1865) Sitzungsberichte der Wiener Akademie der
Wissenschaften, Mathematisch-Natrcrwissenschaftliche Classe,
ZweiteAbteilung, 52, 303-322
2 Hering, E. (1878) Grcmdziigeder Lehre vom Lichtsinn (Hurvich,
L.M. and Jameson, D., trans., 1964, HarvardUniversityPress),
Springer
3 Hering, E. (1907) in Graefe-Saemisch Handbuch der gesamterr
Augenheilkunde(Vol.3, 2nd edn) (Saemisch,Th., cd.), pp. 1-194,
W. Engelmann
4 Wertheimer, M. (1912) Zschr. Psychol. 61, 161-265
5 Kuffler,S.W. (1953)1. Neurophysiol.16, 37-68
6 Barlow, H.B. (19S3) J. PhysioL 119, 69-88
7 Ratliff, F. (1965) Mach Bands: Quantitative Studies on Neural
Networksin the Retina,HoldenDay
8 Jung, R. (1973) in Handbook of Sensory Physiology: Central
Processingof Visual Information (Vol. VII/3A)(Autrum,H. et aL,
eds), pp. 1-152, Springer-Verlag
9 Spillmann, L. and Werner, J. S., eds (1990) Visual Perception:
The Nercrophysiolog”cal
Foundations, AcademicPress
10 Spillmann, L. and Ehrenstein, W. (1996) in Comprehensive
Human Physiology. From Cellular Mechanisms to Integration
(Vol. 1) (Greger, R. and Windhorst, U., eds), pp. 861-893,
Springer-Verlag
11 Allman, J., Miezin, F. and McGuinness, E. (1985) Annu. Rev.
Neurosci. 8, 407-430
12 McIlwain, J.T. (1964) J. Neurophysio2.27, 1154-1173
Acknowledgements
13 Kriiger,J. and Fischer, B. (1973) Exp. Brain Res. 18, 316-318
We aregratefil for 14 Fischer, B., Barth, R. and Stemheim, C. (1978) Exp. Brain Res.
the valuable
COf?lr?WiltSby
H.B. Barlow,
R. Eclchorn,
A.K. Errgel,
C.D. Gilbert,
S. Lehar,
\.H.R.Maunsell,
[.1.Nelson,
P.H.SchilIerand
W. Singer.JSW is a
recipientof a Senior
ScientistAward
from the
Alexander-vonHumboldt
Foundation.
434
31, 235-248
Breitmeyer, B. and Valberg,A. (1979) Science203, 463-464
16 Peterhans, E. and von der Heydt, R. (1989) J. NeuroscL9,
1749-1763
17 Peterhans, E., von der Heydt, R. and Baumgartner, G. (1986)
in Visual Neuroscience (Pettigrew, J.D., Sanderson, K.J. and
Levick,W.R., eds), pp. 343–351, CambridgeUniversityPress
18 Tynan, P. and Sekuler,R. (1975) Science188, 951-952
981-986
19 Werner, J.S. et aL (1984) J Opt.Soc. Am. A 1,
20 von Goethe, J.W. (1810) Zur Farberdehre (J.G. Cotta, cd.),
Tiibingen
21 Riggs,L.A. et aL (1953) J. Opt. Soc. Am. 43, 495-501
22 Gerrits, H.J.M. and Vendrik, A.J.H. (1970) EXP.Brain Res. 11,
411-430
23 Krauskopf,J. (1963) J. Opt.Soc. Am. 53, 741-744
24 Ramachandran, V.S. and Gregory, R.L. (1991) Nature 350,
699-702
25 Spillmann, L. and Kurtenbach, A. (1992) Vis. Res. 32,
1941-1946
26 DeWeerd,P. et al. (1995) Nature 377, 731-734
27 Durgin, F.H., Tripathy, S.P. and Levi, D.M. (1995) Perception
24, 827-840
15
TINS Vol. 19, No. 10, 1996
28 Jameson, D. and Hurvich, L.M. (1961) Science133, 174–179
29 Land, E.H. (1959) Proc. Natl. Acad. Sci. U.S. A. 45, 115–129
30 Shapley, R. and Reid, R.C. (1985) Proc. NatL Acad. Sci. U. S. A.
82, 5983-5986
31 PCippel,E. (1986) Nature 320, 523-526
32 Creutzfeldt, O.D. et aL (1991) Exp. Brain Res. 87, 2245
33 Land, E.H. et al. (1983) Nature 303, 616-618
34 Schein, S.J. and Desimone, R. (1990) J. Neurosci. 10,3369-3389
35 Zeki, S.M. (1983) Neuroscience9, 767-781
36 Julesz, B. (1971) Foundations of Cyclopean Perception, University
of ChicagoPress
37 Nelson,J.L (1975) J. T’heor.Bio2.49, 1-88
38 Qian, N. (1994) Neural Computation 6, 390-404
39 Friedman, H. et aL (1996) Invest. Ophtha2moLVis. Sci. 37, S424
40 van Doom, A.J. and Koenderink,J.J. (1982) Exp. BrainRes.45,
179-188
41 Lamme, V.A.F. (1993) Nature 363, 541-543
42 Qian, N. and Andersen,R.A. (1994) J. Neurosci. 14, 7367-7380
43 Niedeggen,M. and Wist, E.R. (1992) Perception21 (Suppl.2), 32
44 Johansson, G. (1975) Sci. Am. 232, 76-88
45 Britten, K.H. et al. (1992) J. Neurosci.12, 4745-4765
46 Saito, H. et al. (1986) J. Neurosci. 6, 145-157
47 Newsome, W.T., Mikami, A. and Wurtz, R.H. (1986)
J. hJearophysioL55, 1340-1351
48 Beck, J. (1982) Textural Segmentation in Organization and
Representationin Perception(Beck,J., cd.), pp. 285-317, Erlbaum
49 Julesz, B. (1984) in SensoryExperience,Adaptation, and Perception
(Spillmann,L. and Wooten, B.R., eds),pp. 37-52, Erlbaum
50 Treisman, A. (1986) Sci.Am. 255, 114-125
51 Knierim, J.J. and van Essen, D.C. (1992) J. Neurophysiol. 67,
961-980
52 Sillito, A.M. et al. (1995) Nature 378, 492-496
53 Lamme, V.A.F. (1995) J. Neurosci. 15, 1605-1615
54 Hammond, P. and MacKay,D.M. (1981) J. Physiol.319,431442
55 Allman,J., Miezin,F. and McGuinness,E. (1985) Perception14,
105-126
56 Hubel, D.H. and Wiesel, T.N. (1962) J. Plrysio2.160, 106-154
57 Barlow, H.B. (1981) Proc.R. Soc.London Ser.B 212, 1-34
58 Barlow, H.B. (1985) Quart.J. Exp. PsychoL 37, 121-146
59 Nelson, J.L (1985) in Modek of the VisualCortex(Rose,D. and
Dobson,V., eds),pp. 108-122, Wiley
60 van Essen, D.C., Anderson, C.H. and Felleman, D.J. (1992)
Science255, 419-423
61 Maunsell,J.H.R. (1995) Science 270, 764-769
62 Eysel, U.Th. (1982) Nature 299, 442444
63 Gilbert, C.D. and Wiesel, T.N. (1992) Nature 356, 150-152
64 Chino, Y.M. et aL (1992) Vis.Res. 32, 789-796
65 Gilbert, C.D. and Wiesel, T.N. (1990) Vis.Res. 30, 1689-1701
66 Gilbert, C.D. (1992) Neuron9, 1-13
67 DeAngelis, G.C. et al. (1995) Proc. NatL Acad. Sci. U. S. A. 92,
9682-9686
68 Pettet, M.W. and Gilbert, C.D. (1992) Proc. NatL Acad. Sci.
U.S. A. 89, 8366-8370
69 Fiorani, M. et aJ. (1992) Proc. NatL Acad. Sci. U. S. A. 89,
8547-8551
70 Fiorentini, A. et aL (1990) in Visual Perception: The
Neurophysiologfca2Foundations (Spillmann, L. and Werner, J.S.,
eds),pp. 129-161, AcademicPress
71 Lund, J.S., Yoshioka, T. and Levitt, J.B. (1993) Cereb. Cortex3,
148-162
72 Das, A. and Gilbert, C.D. (1995) Nature 375, 735-736
73 Marr, D. and Poggio, T. (1979) Proc.R. Soc. London Ser. B 204,
301-328
74 Grossberg,S. and Todorovic, D. (1988) Percept.Psychophys.43,
241-277
75 Engel, A.K.et al. (1991) Science 252, 1177-1179
76 Sherman, S.M. and Koch, C. (1986) Exp. Brain Res. 63, 1-20
77 Eckhom, R. et aL (1988) Bio2.Cyberrr.60, 121-130
78 Gray, C.M. et al. (1989) Nature 338, 334–337
79 Singer,W. (1993) Annu. Rev. Physiol. 55, 349-374
80 Singer,W. (1995) Science 270, 758-764
81 Young, M.P. (1992) Nature 358, 152-155
82 Eckhom, R. et al. (1989) in Models of Brain Functioning
(Cotterill, R.M.J., cd.), pp. 255-272, CambridgeUniversityPress
83 Frien, A. et al. (1994) NeuroReport5, 2273-2277
84 Field, D.J., Hayes, A. and Hess, R.F. (1993) Vis. Res. 33,
173–193
85 Polat, U. and Sagi, D. (1994) Proc. Natl. Acad. Sci. U. S. A. 91,
1206-1209
86 Stemmler, M., Usher, M. and Niebuhr, E. (1995) Science 269,
1877-1880
87 Ts’o, D.Y., Gilbert, CD. and Wiesel, T.N. (1986) J. Neurosci. 6,
1160-1170
88 Kapadia,M.K. et al. (1995) Neuron 15, 843-856
89 Barlow, H. (1995) in Large Scale Neuronal Theories of the Brain
(Koch,C. and Davis,J.L., eds),pp. 1-22, MITPress