Anatomy and physiology of a neural mechanism defining

Transcription

Anatomy and physiology of a neural mechanism defining
European Journal of Neuroscience, Vol. 12, pp. 4117±4130, 2000
ã Federation of European Neuroscience Societies
Anatomy and physiology of a neural mechanism de®ning
depth order and contrast polarity at illusory contours
B. Heider,* V. Meskenaite² and E. Peterhans
Department of Neurology, University Hospital Zurich, CH-8091 Zurich, Switzerland
Keywords: alert monkey, ®gure-ground segregation, occlusion cues, visual contour processing, V1 and V2
Abstract
We studied the anatomy and physiology of neurons in monkey visual cortex, which contribute to mechanisms segregating ®gure and
ground at contours based on information provided by occlusion cues. First, we de®ned the location of neurons sensitive to occluding
(illusory) contours. These neurons were found most frequently in the pale cytochrome oxidase stripes of area V2 but rarely in V1. In
area V2, they were found in all laminae and with similar frequencies. The few neurons recorded in area V1 concentrated in the upper
laminae. Second, we studied the properties and anatomical location of neurons sensitive to occlusion cues (dark and light line-ends,
corners). These neurons had end-stopped receptive ®elds and were found with similar frequencies in both areas. In area V1, they
concentrated in the upper laminae. In area V2, they were found in all laminae and cytochrome oxidase stripes. These neurons
responded to short stimuli of optimal length (bars, edges) and to stimuli terminating in their receptive ®eld (line-ends, corners).
Overall, about half of these neurons detected the direction of such terminations and about 60% were selective for certain types of
termination. In summary, our results suggest that in monkey visual cortex, occlusion cues are represented in areas V1 and V2,
whereas grouping mechanisms detecting occluding contours concentrate in area V2.
Introduction
Evidence of form perception suggests that ®gure-ground segregation
begins at contours, and that the neural mechanisms involved are
implemented early in visual processing (Nakayama et al., 1989). This
process is critical for the perception of object forms and for de®ning
their depth order in visual space. Figure-ground segregation is
particularly important in perception of cluttered visual scenes, which
produce incomplete images of objects on the retina due to spatial
occlusion. Monocular and binocular mechanisms contribute to this
process. Binocular mechanisms use the retinal disparity of image
elements as a cue; monocular mechanisms use discontinuities of
luminance, hue, texture, or motion. Images of cluttered visual scenes
include occlusion cues like line-ends, corners and junctions that
indicate the location of the occluding surface relative to ground.
Figure 1 shows an arti®cial example of such a scene. Here, the
occluding surfaces (triangles, squares) are of the same luminance as
the background, but are perceived as being either brighter (upper half)
or darker (lower half) than the background. The perception of these
surfaces is de®ned by the spatial arrangement, the contrast polarity
and the direction of the occlusion cues (dark or light line-ends,
corners). At sites of fading contrast, the occluding borders are
completed by illusory contours.
The role of cortical neurons in various aspects of scene
segmentation has been studied in single cell physiology. In the
Correspondence: Dr E. Peterhans, Wyderrain 7, CH-3012 Bern, Switzerland.
E-mail: [email protected]
*Present address: Yale University School of Medicine, Section in Neurobiology, 333 Cedar Street, SHM-I412, New Haven, CT 06510, USA.
²
Present address: Department of Biochemistry, University of Zurich,
Winterthurerstr. 190,CH-8057 Zurich, Switzerland.
Received 10 December 1999, revised 20 July 2000, accepted 24 August 2000
monkey for example, neurons sensitive to retinal disparity have been
found in striate and extrastriate cortex (Hubel & Wiesel, 1970;
Poggio & Fischer, 1977; Maunsell & Van Essen, 1983; Poggio et al.,
1985; Felleman & Van Essen, 1987; Roy et al., 1992; Uka et al.,
1998; Janssen et al., 1999) and similarly for neurons detecting objects
from motion cues (Allman et al., 1985; Tanaka et al., 1986; SaÂry
et al., 1993; Lamme et al., 1998). Further, Bradley & Andersen
(1998) showed that extrastriate neurons (middle temporal area, MT)
combine motion and disparity cues for segregating surfaces located in
different depth planes. Neurons sensitive to discontinuities of
luminance, hue or texture in images are common in both striate
and extrastriate cortex (Hubel & Wiesel, 1968; Hubel & Livingstone,
1987; Van Essen et al., 1989; Roe & Ts'o, 1995; Gegenfurter et al.,
1996). Although these neurons contribute to contour processing and
thus to the de®nition of object borders, they do not provide
information about the depth order of the surfaces associated with
such contours. Little is known about the neural mechanisms
segregating ®gure and ground at contours, as shown in Fig. 1. Only
recently, neurons were found in area V2 that showed selectivity for
the depth order that human observers perceive at contours (Baumann
et al., 1997; Chang et al., 1999; Zhou et al., 2000). In the present
paper, we identify the anatomical location of neurons as described by
Baumann et al. (1997) and provide a detailed analysis of the cortical
representation of occlusion cues. Preliminary results have been
reported (Heider et al., 1997; Heider & Peterhans, 1998).
Methods
Physiology
Animal preparation
Five rhesus monkeys (female, body weight: 4.5±6.2 kg) were trained
on a visual ®xation task that reinforced foveal viewing. The ®xation
4118 B. Heider et al.
under general anaesthesia, for accessing different regions of striate
and prestriate cortex (see also Peterhans & von der Heydt, 1993).
After several months of experiments, a second chamber was
implanted for recording in the other hemisphere. The Veterinary
Of®ce of the Kanton Zurich approved of all experimental procedures.
Animal housing and care corresponded to the standards of Swiss
federal law.
Visual stimulation and data recording
FIG. 1. Arti®cial ®gures illustrating ®gure-ground segregation from occlusion
cues. Occlusion cues (line-ends, corners) appear in the retinal image at points
of intersection between occluding surfaces (squares, triangles) and background
structures (striped, solid disks). The visual system uses these cues to de®ne the
contours of occluding surfaces by generating illusory contours at sites of
fading contrast, as well as the depth order and the brightness effects associated
with such contours.
target consisted of two small vertical lines (1 3 7 min arc, separated
by 5 min arc). The animals could initiate a trial by pulling a lever.
After an unpredictable time interval (0.5±5 s), the target turned by
90 ° and the animal had to release the lever within 0.4 s. Correct trials
were rewarded with a small drop of fruit juice or water. When the
animals reached a performance rate of >85%, a head-holder was
implanted. In the ®nal part of the training, the animals learned to
work with the head ®xed and with other stimuli presented besides the
®xation target. The training was completed when the animals
concentrated on this task and worked with a performance rate of
90±95%. Accuracy of visual ®xation was controlled using a TV
camera and regular checks from the dot displays of neuronal
responses (see von der Heydt & Peterhans, 1989). This method was
adopted from Motter & Poggio (1984), who showed that visual
®xation under these conditions varied randomly around the ®xation
target with standard deviations of 6±8 and 7±13 min arc for horizontal
and vertical components, respectively.
After completion of the training, we implanted a recording
chamber (diameter, 21 mm) onto the skull over the operculum of
one of the two hemispheres. All operations were performed under
general anaesthesia initiated by a combination of ketamine hydrochloride (Ketalarq, 5±10 mg/kg, i.m.) and diazepam (Valiumq,
0.05±0.1 mg/kg, i.m.), followed by atropine sulphate (0.05±0.1 mg/
kg, s.c.) and pentobarbital sodium (Nembutalq, 25±30 mg/kg, i.p.).
The anaesthesia was maintained using N2O : O2 (2 : 1) via a tracheal
tube and pentobarbital sodium as necessary (Nembutalq, 2±10 mg/kg,
i.v. or i.p. every 1±2 h). Pulse rate and blood oxygenation (SpO2)
were monitored continuously using a pulse oximeter (NONIN
Medical Inc., Plymouth, MN, USA) with a printout option for offline documentation. Body temperature was also monitored continuously and maintained via a feedback circuit connected to an electric
heating pad. Before each series of experiment, we made a small
trepanation (diameter, 3 mm) within the recording chamber, also
The ®xation target and the visual stimuli were generated using analog
and digital circuits and presented separately for each eye on a ¯atfaced, high-resolution oscilloscope (Ferranti A5, peak at 555 nm)
with a refresh rate of 100 Hz. The animals viewed the oscilloscope
screen via a stereoscope such that the plane of visual ®xation was
viewed at a distance of 40 cm. A uniform illumination was added to
this display by means of a half slivered mirror so that the background
luminance was 22 or 36 cd/m2 and that of the stimuli 51 or 72 cd/m2.
The activity of single neurons was recorded extracellularly during
the periods of active visual ®xation using glass-coated, platinumiridium microelectrodes, prepared according to Wolbarsht et al.
(1960) but without platinum-black coating. The signals were
ampli®ed and fed to earphones for listening to the responses during
qualitative testing, and to a Schmitt trigger for quantitative records on
computer for on-line displays and off-line analysis. Each neuron was
®rst studied qualitatively, then quantitatively by recording the most
relevant results.
Evaluation of neuronal properties
Each neuron was ®rst studied qualitatively. We determined the
preferred orientation and size and position of the minimum response
®eld using bars or edges that could be moved manually using a
joystick. Then, we tested the neuron's preference for stimulus type
(light or dark bar, edges or gratings) and length, and estimated its
preferred stereoscopic depth. The latter estimate was established
routinely since the majority of V1 and V2 neurons are sensitive to
binocular disparity (Poggio & Fischer, 1977). In the context of the
present paper, binocular disparity was used to ensure optimal
stimulus presentation. A separate analysis of this neuronal property
is in progress; preliminary results have been published (Peterhans
et al., 1995).
Following these initial tests, we analysed sensitivity to stimulus
length in more detail and de®ned two categories of neurons
depending on the presence or absence of end-inhibition in their
receptive ®eld. Neurons that preferred short stimuli of a certain length
and gave weaker responses or none to long stimuli (6±12 °) were
called `end-stopped cells'. (Subsequent comparison of qualitative and
quantitative classi®cation revealed that response reductions > 40%
were reliably detected by auditive discrimination.) These neurons
were further studied with different types (line-ends, corners) and
contrast polarities (light, dark) of terminations (for examples see
Fig. 13A). Neurons without end-inhibition, hereafter called `end-free
cells', were studied with illusory-contour stimuli that were either
ambiguous with regard to depth order (contours between abutting
line-gratings as shown in Fig. 9; see also von der Heydt & Peterhans,
1989) or induced a step in depth at the contour (illusory bar or edge
stimuli as shown in Fig. 4; see also Peterhans & von der Heydt, 1989;
Baumann et al., 1997). Following these qualitative tests, we
performed as many of these experiments as possible quantitatively
by recording the neuronal responses in series of stimulus conditions
repeatedly in a prede®ned, pseudorandom order. The stimuli were
usually moved back and forth over the receptive ®eld, orthogonal to
the neuron's preferred orientation with a sweep length that included
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
Figure-ground segregation in monkey area V2 4119
FIG. 2. (A) Reconstruction of a cytochrome oxidase pattern of area V2. Dashed lines indicate borders between thick and pale stripes, dotted lines borders between
thin and pale stripes. Symbols serve the identi®cation of the three patches shown in B. Head coordinates are indicated at the top left. The border to area V1 runs
approximately parallel to the bottom of the ®gure. (B) Densitometry. Three patches selected from the upper, middle and lower part of the pattern shown in A. Solid
curves indicate the mean luminance per pixel column along the horizontal axis (resolution: 300 columns per inch). Vertical axes range between 165 and 15 bits per
column for the brightest and darkest values, respectively. Horizontal lines mark the levels of 112, 122 and 125 bits per column used to de®ne the stripe borders in
the lower, middle and upper patch, respectively. Light and dark rectangles show the emerging pattern.
the entire response and also accounted for the ®xational eye
movements that occur under these conditions (discussed earlier).
All stimulus insets of the ®gures show the stimuli placed in the centre
of the sweep with amplitude and frequency indicated in the legend.
Anatomy
Histology
Histology was available for four animals that contributed to the
results of the present paper (Nissl stainings in three animals,
cytochrome oxidase stainings in two animals, Cat-301 immunoreactivity in one animal). For the ®fth animal, we include only
neurons that could be located either in area V1 or V2, based on
physiological criteria. The analysis of the correlation between
anatomy and physiology was restricted to the two animals for which
cytochrome oxidase staining was available. The general anatomical
procedures and the technique of reconstructing microelectrode tracks
were performed according to Peterhans & von der Heydt (1993).
In the last 5±7 days of the experiment, the microelectrode tracks
were marked with electrolytic lesions, usually three in a row
separated by 500 mm (8±10 mA, 10±30 s, tip negative). In general
anaesthesia (discussed earlier), we marked the area of brain studied
by inserting between seven and 12 tungsten pins (0.25 3 12 mm,
sharpened electrolytically) using our X/Y stage (Medic AG
Switzerland, after Toyama et al., 1981). Subsequently, we injected
a lethal dose of pentobarbital sodium (Nembutalq) and perfused the
brain through the heart with about 200 mL Ringer solution containing
5 U-USP heparin (Liqueminq, 1 mL), followed by 4% phosphatebuffered paraformaldehyde (+ 0.0025% glutaraldehyde in one animal,
none in the others). The blocks of brain were removed, ¯oated in
sucrose solutions of increasing concentrations (10±30%) until sunk
and cut on a vibratome at 100 mm after freeze-thawing. The plane of
sectioning, as de®ned by the marker pins, was approximately parallel
to the lunate sulcus and orthogonal to the cortical surface. For the two
animals with cytochrome oxidase staining available, we stained
alternate sections for cytochrome oxidase (Wong-Riley & Carroll,
1984) and Nissl substance or Cat-301 (DeYoe et al., 1990).
The sections, mounted and cover slipped, were enlarged photographically, digitized with a resolution of 1200 dots per inch, and
processed as grey-valued images with a resolution of 300 dots per
inch using Adobe Photoshopq software for image editing (Versions 4
and 5). The cytochrome oxidase and Cat-301 patterns were
reconstructed on the ¯at parts of area V2 by aligning successive
sections using the lesions of the marker pins for reference. Figure 2A
shows the result for the right hemisphere of one animal. It shows the
typical pattern of dark thin and thick stripes (hereafter called thin and
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
4120 B. Heider et al.
FIG. 3. Reconstruction of the laminar distribution of cortical neurons. Track
7BI as reconstructed on the appropriate section stained for cytochrome
oxidase. Horizontal lines indicate borders of cortical layers as determined
during the experiment by listening to the background activity. The dashed part
indicates white matter. Circles mark neurons recorded along the track. The
square indicates neuron 7BI5 that was sensitive to occluding contours.
thick stripes), separated by pale stripes that contain less of the
enzyme. This pattern was determined by eye and veri®ed by means of
densitometry (Image software, version 1.54, NIH, Bethesda, MD,
USA) as shown in Fig. 2B. It shows the density pro®les (solid curves)
across three selected patterns representing average grey values of
pixel columns. The periodicity of the patterns was de®ned by setting
an average grey level (horizontal lines) and de®ning the points of
intersection as borders between stripes. Figure 2B shows that the
reconstructed patterns (borders of light and dark rectangles)
correspond to the patterns determined by eye (dashed and dotted
lines).
The Cat-301 pattern was reconstructed by the same technique.
However, the staining was considerably patchier and stripe borders
were dif®cult to establish. The most consistent Cat-301 labelling was
found in regions corresponding to the thick cytochrome oxidase
stripes. This con®rms the ®ndings of previous studies (DeYoe et al.,
1990; Gegenfurter et al., 1996), suggesting Cat-301 as a good marker
for identifying thick cytochrome oxidase stripes.
Reconstruction of microelectrode tracks
The microelectrode tracks were reconstructed by projecting their
position onto a cortical surface map according to the marker pins and
the coordinate system of our X/Y stage. This allowed us to assign
each track to its appropriate section of the brain. We assessed the
accuracy of reconstruction from the distances of the calculated
positions to the lesion centres. The estimated standard error of
positioning was 247 mm (n = 23) in directions tangential to the cortical
surface (see also Peterhans & von der Heydt, 1993).
Depth assignments were made by ®tting the depth records of the
physiological parameters noticed while advancing the microelectrode
to the anatomical de®nition of cortical laminae, as shown in Fig. 3.
The parameters used in area V1 included the notice of cortex entry,
increased levels of background activity in laminae 4A and C,
monocular responses and the lack of orientation selectivity in lamina
FIG. 4. Anatomical distribution of neurons sensitive to occluding contours in
area V2. (A) Distribution with regard to the cytochrome oxidase pattern (thin
stripes, 3%; pale stripes, 44%; thick stripes, 12%). (B) Distribution with regard
to cortical laminae (2 + 3, 16%; 4, 20%; 5 + 6, 23%).
FIG. 5. The role of end-stopped cells in cortical representations of occlusion
cues. (A) Double-stopped neurons with inhibitory zones of similar strength
(hatched disks) at both ends of the excitatory zone (open ellipse) signal
terminations, but without indicating their direction. (B and C) Single-stopped
neurons signal the direction of terminations by giving stronger responses to
terminations pointing in one of the two possible directions (left or right) and
only weak responses or none to terminations pointing in the other direction.
4C, and the transition into white matter. Since less is known about
laminar properties in area V2, we used in this area only the ®rst
detection of cortical activity and the fading of this activity upon
leaving the area. Figure 3 shows a track in which the microelectrode
passed through a blob region of area V1 and entered area V2 after a
short passage through white matter (dashed section). The circles
indicate records of cortical neurons, the square the position of a
neuron sensitive to occluding contours (for the physiological
properties of this neuron, see Baumann et al., 1997; Figs 7 and 8).
Since lamina 4 was safest to identify in both areas, we combined the
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
Figure-ground segregation in monkey area V2 4121
FIG. 6. Responses of a double-stopped cell.
(A) Length-response function showing that the
optimal bar length was about 0.5 ° and that
long stimuli (> 2 °) failed to evoke a response.
Inset (a) shows this bar (®lled) and a 4 ° long
bar (open) in relation to the neuron's receptive
®eld. (B) Length-activity pro®les as mapped
with the short bar (solid curve) and a 2.7 °
long bar (dashed curve). The stimuli were
presented in different positions along the
length-axis of the receptive ®eld, as indicated
on the abscissa scale. Arrows mark peak
responses; insets (a, b and d) show the
corresponding positions of stimuli in relation
to the receptive ®eld. This neuron was
recorded in area V2 (thin stripe, laminae
2 + 3). Conventions: data points and vertical
lines indicate mean responses and standard
errors of eight stimulus presentations, where
one stimulus presentation corresponds to one
cycle of stimulus movement (amplitude, 1.5 °;
frequency, 1 Hz). Insets show excitatory (open
ellipse) and inhibitory zones (hatched disks) of
the receptive ®eld. The length of the excitatory
zone was determined from the activity pro®le
(solid curve shown in B), its width from dot
displays as shown in Figs 10±12. The size of
the inhibitory zones is arbitrary; equal hatching
indicates similar strength of end-inhibition
(Ei = 0.33, see Fig. 8).
cortical laminae into three groups hereafter called super®cial
(laminae 2 + 3), middle (laminae 4A, B and C) and deep laminae
(5 + 6).
For assigning individual neurons to the cytochrome oxidase pattern
of area V2, we copied the stripe pattern as shown in Fig. 2A onto
brain sections as shown in Fig. 3.
Results
In the present paper, we analyse the correlation between anatomy and
physiology of neurons that contribute to a mechanism that de®nes
occluding (illusory) contours based on information provided by
occlusion cues. First, we identi®ed the anatomical location of neurons
sensitive to the orientation of such contours and to the ®gure-ground
direction that human observers perceive at such contours. Second, we
analysed the anatomical location and the physiological properties of
neurons sensitive to occlusion cues (line-ends, corners).
Neurons detecting occluding contours
We studied a total of 224 neurons (V1, 73; V2, 151) with stimuli that
induce occluding contours in perception. Examples of stimuli are
shown in Fig. 4. These contours were moved over the neuron's
receptive ®eld such that they induced the perception of an illusory bar
(left stimulus) or edge (right stimulus) sliding back and forth over two
stationary rectangles (left stimulus) or a grating texture (right
stimulus) as a background. In response to the right stimulus, we
found neurons that were selective for one of the two ®gure-ground
directions that human observers perceive at such contours. Some
neurons preferred the occluding surface to the left of the contour as
shown in Fig. 4; others preferred it to the right of the contour. For
details of the physiological properties of these neurons, see Baumann
et al. (1997).
Anatomy
Neurons sensitive to illusory bars or edges were found most frequently
in area V2 (21%, 32/151) and only rarely in area V1 (5%, 4/73).
In area V2, we localized 110/151 neurons with respect to the
cytochrome oxidase pattern. Neurons that could not be localized
(n = 22) and neurons recorded at borders between stripes (n = 19) were
excluded. Figure 4A shows that neurons sensitive to occluding
contours were found most frequently in the pale stripes, rarely in
the thick, and apart from one exception not in the thin stripes
(c2 = 19.4, d.f. = 2, P < 0.001). A similar result was obtained when the
responses to each stimulus type were analysed separately (illusory
bar: c2 = 13.4, d.f. = 2, P < 0.01; illusory edge: c2 = 10.2, d.f. = 2,
P < 0.01). Figure 4B shows that we found these neurons with similar
frequencies in all laminae of area V2 (c2 = 0.6, d.f. = 2, P > 0.05). The
three neurons located in area V1 were found in the upper laminae
(2 + 3, 4; see Methods for identi®cation of laminae). They were of the
type that preferred a certain combination of ®gure-ground direction
and contrast polarity at the occluding contour (for details see
Baumann et al., 1997).
Eccentricity
The receptive ®elds of neurons studied with illusory bar or edge
stimuli were located within the central 10 ° of visual ®eld. The mean
eccentricity was 3.2 ° (range, 0.4±10.1 °; n = 128) for neurons
studied in area V2, and 2.9 ° (range, 0.7±7.5 °; n = 61) for neurons
studied in area V1. Fields of neurons sensitive to occluding contours
were evenly distributed among ®elds of neurons not showing this
property.
Model of a neural mechanism
Previous physiological ®ndings (Peterhans, 1997) and simulations of
neuronal responses (Heitger et al., 1998) suggest that end-stopped
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
4122 B. Heider et al.
FIG. 7. Responses of single-stopped cells.
(A) Length-activity pro®les of the responses to
a short bar of optimal length (solid curve) and
to a long bar (dashed curve) for a neuron
preferring upward pointing terminations (d).
(B) Same experiment for a neuron preferring
downward pointing terminations (b). Bar
lengths were 0.67 and 3.3 ° for neuron 7DH1,
and 0.08 and 2.0 ° for neuron 7EC1. The
frequency of stimulus movement was 1 Hz for
both neurons, the amplitude 0.6 and 0.8 ° for
neurons 7DH1 and 7EC1, respectively. Both
neurons were recorded in area V1 (laminae
2 + 3). The stimulus insets show the
experimental conditions for neuron 7EC1.
Hatched and open disks indicate strong and
weak (or absent) end-inhibition, respectively
(Ei = 0.83 and 0.96 for neuron 7DH1 and
7EC1, respectively, see Fig. 8). Conventions
otherwise as in Fig. 6.
cells do respond to terminations and detect positions and directions of
occlusion cues. Therefore, these neurons can provide the basic
information necessary for cortical representations of occluding
contours. Figure 5 shows schematic receptive ®elds of end-stopped
cells in the context of illusory-contour stimuli (A, double-stopped
®elds; B and C, single-stopped ®elds). While all ®elds are suitable for
detecting terminations, their directions can only be signalled by
neurons with single-stopped ®elds. Neurons with the inhibitory zone
(hatched disk) to the left of the excitatory zone (open ellipse) are
expected to respond to terminations pointing to the left and not to
terminations pointing to the right, and reverse for neurons with the
opposite arrangement of excitatory and inhibitory zones. Hence, only
mechanisms based on scheme (B) or (C) can detect the ®gure-ground
direction at such contours, whereas mechanisms based on scheme (A)
are ambiguous with respect to ®gure and ground, but still indicate the
illusory contour.
Baumann et al. (1997) found two types of neuron that were
sensitive to ®gure-ground direction at illusory contours. The ®rst
showed this sensitivity independent of the contrast polarity of the
occlusion cues, the second required a certain combination of ®gureground direction and contrast polarity. Peterhans et al. (2000) found
that grouping end-stopped operators with either complex- or simpletype excitatory ®elds could simulate the responses of these neurons.
Complex-type operators provide information about position and
direction of terminations; simple-type operators provide additional
information about type (line-end, corner) and contrast polarity of
occlusion cues.
Neurons detecting occlusion cues
In the light of this scheme we analysed the sensitivity of end-stopped
cells with regard to direction, type and contrast polarity of occlusion
cues and correlated these results with anatomy.
Symmetry of end-inhibition
We studied the symmetry of end-inhibition in a total of 86 endstopped cells (V1, 42; V2, 44). Figure 6 shows responses of a doublestopped cell of area V2. Figure 6A shows responses to light bars of
different lengths, as indicated on the abscissa scale. Bars longer than
2 ° failed to evoke a response. The optimal length was 0.5 °. Inset (a)
shows this bar in relation to the neuron's receptive ®eld. The open
ellipse indicates the response ®eld to this bar; the hatched disks
indicate inhibitory end-zones (size arbitrary). The dotted line marks
the axis of stimulus movement positioned in the centre of the ®eld.
Figure 6B shows responses of this neuron to the bar of optimal length
(solid line) and to a long bar (dashed line) placed at different
positions along the length-axis of the receptive ®eld. The width of the
response curve de®ned the length of the excitatory ®eld (ellipse), the
position of maximum response (a, zero on the abscissa scale) was
the centre of the ®eld. The long bar evoked two response peaks, one
when its upper end just covered the excitatory ®eld (b) and another
when the lower end was in a corresponding position (d). As expected
from experiment (A), the long bar failed to evoke a response when
centred in the ®eld (c).
Figure 7 shows the responses of two single-stopped cells of area V1
(A, 7DH1; B, 7EC1) that indicated the direction of terminations. The
receptive ®elds of the two neurons were scanned along the lengthaxis of the receptive ®eld, as described for the double-stopped cell of
Fig. 6. The solid curves show the responses to the bars of optimal
length that de®ned the length of the excitatory zone (open ellipses),
the dashed curves show the responses to long bars in different
positions of the receptive ®eld. As in the double-stopped cell of
Fig. 6, long bars failed to evoke a response when centred in the ®eld
(c). When they terminated in the receptive ®eld, the neurons
responded only when the termination pointed in one of the two
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
Figure-ground segregation in monkey area V2 4123
FIG. 8. Symmetry of end-inhibition. The histogram shows the distribution of
the index Ei.
possible directions, neuron 7EC1 only to downward directions (b),
neuron 7DH1 only to upward directions (d). These responses indicate
a strong inhibitory zone (hatched disks) at one end of the ®eld, and a
weak one or none at the other end (traces of a disk).
Neurons as shown in Figs 6 and 7 represent extremities of a
continuum of responses to terminations in our sample of end-stopped
cells. Neurons that responded twice as strong or stronger to
terminations pointing in one direction (Rmax) than to terminations
pointing in the other direction (Rmin) were called single-stopped, the
remainder double-stopped. For the 67 neurons (V1, 36; V2, 31) that
we studied quantitatively, we de®ned an index of symmetry of endinhibition (Ei = Rmax ± Rmin/Rmax) that is plotted in Fig. 8. In all
neurons with indices Ei > 0.5, the mean responses Rmax and Rmin
were also statistically different (Student's test: t > 3.0, d.f. = 14,
P < 0.01). These neurons were called single-stopped, the remainder
double-stopped. In a retrospective analysis, we found that this
criterion of classi®cation also agreed with our qualitative classi®cation, because a 50% difference in response strength was always
detected by listening to the responses. Thus, some neurons that gave
very clear results to qualitative testing were not studied quantitatively
in order to test their selectivity for types of termination (discussed
later). Overall, 48% (41/86) of the neurons were called singlestopped, the remainder 52% (45/86) double-stopped. These proportions were similar in areas V1 and V2 (c2 = 3.0, d.f. = 1, P > 0.05).
Orientation selectivity
Considering the function of end-stopped cells proposed above, it is
important that the orientation preference of these neurons remains
constant in different stimulus conditions. Therefore, we compared the
preferred orientation of end-stopped cells for short stimuli of optimal
length and terminations (line-ends, corners) and never found a neuron
that preferred signi®cantly different orientations for the two types of
stimulus. The preferred orientation also remained constant when
terminations were presented in the context of an illusory-contour
stimulus (abutting line-gratings, illusory bar stimuli). Figure 9 shows
this property for a double-stopped cell recorded in area V1. The
excitatory ®eld (open ellipse) was determined with a short bar of
optimal length and orientation (+22.5 °). Figure 9A shows the
responses to the short bar, (B) those to a line-end. The two response
peaks in Fig. 9B indicate that upward (orientation ±157.5 °) and
downward (orientation +22.5 °) pointing terminations evoked similar
responses. This suggests inhibitory zones of similar strength at both
ends of the ®eld (double-stopped cell). In the context of the illusorycontour stimulus (C, abutting line-gratings), the responses were
slightly weaker, but otherwise similar to those in Fig. 9B.
FIG. 9. Orientation selectivity of end-stopped cells. Responses to (A) a short
bar of optimal length (0.07 3 0.5 °), (B) a line-end (0.02 3 2.5 °) and (C) a
line-end in the context of an illusory-contour stimulus (lines: 0.02 3 2.5 °).
The frequency of stimulus movement was 1 Hz, the amplitude 0.7 °. Symmetry
of end-inhibition, Ei = 0.44. For illustration purposes, the critical (central) line
of the illusory-contour stimulus was drawn slightly wider than the others and
the surrounding circular aperture was reduced to a diameter of 2.6 °. This
neuron was recorded in area V1 (laminae 2 + 3). Conventions otherwise as in
Fig. 6.
Type and contrast polarity of terminations
We studied the responses of end-stopped cells to different types and
contrast polarities of stimuli of optimal length (bars, edges) and
terminations (line-ends, corners). Figure 10A±D shows an example of
a stimulus set (short stimuli of optimal length and corresponding
terminations shown in the left and right panels, respectively). A total
of 119 end-stopped cells were studied with such stimuli (V1, 42; V2,
77). For comparison, we also studied 154 end-free cells with bars and
edges of optimal length (V1, 54; V2, 100).
We found three types of selectivity in end-stopped cells:
(i) unselective neurons giving similar responses to all types of
stimuli (light and dark line-ends, corners), (ii) neurons selective for
stimulus pairs (usually a light or dark line-end and one type of
corner), and (iii) highly selective neurons preferring one stimulus
type (a light or dark line-end, or one type of corner). Figure 10 shows
an example of the responses of an unselective neuron. It shows that
end-stopped had the same selectivity for terminations (right panel) as
for bars and edges of optimal length (left panel). To both qualitative
and quantitative testing (see below), we never found a neuron
preferring different stimulus types for short stimuli and terminations.
Figure 11 shows an example of the responses of a neuron that was
selective for a stimulus pair (A, light line-end; B, light/dark corner). It
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
4124 B. Heider et al.
FIG. 10. Neuron unselective for type and contrast polarity of occlusion cues. Left panel: responses to stimuli of optimal length (A, light bar; B, light/dark edge; C,
dark bar; D, dark/light edge). Right panel: responses to the corresponding terminations (A, light line-end; B, light/dark corner; C, dark line-end; D, dark/light
corner). Spontaneous activity was 2.7 spikes/s (not shown). This neuron was recorded in area V1 (laminae 4). Selectivity indices: IS = 0.08, IB = 0.35, IE = ±0.22
(see Fig. 14). Conventions: the stimuli were moved back and forth over the receptive ®eld at a frequency of 1 Hz and sweep amplitude of 0.7 °. Each display shows
responses recorded during 24 cycles of stimulus movement (responses in the forth sweep of stimulus movement are shown in the left half, those in the back sweep
in the right half of the displays). Each dot represents an action potential; the ®gures on the right indicate mean numbers of spikes per stimulus cycle. Spontaneous
activity was recorded during corresponding time intervals.
gave only weak responses or none to the other stimulus pair (C, dark
line-end; D, dark/light corner). Figure 12 shows the responses of a
neuron selective for one stimulus type. It preferred dark/light corners
(D) and was hardly activated by light line-ends (A), light/dark corners
(B) or dark line-ends (C). Bars and edges of optimal length evoked
similar responses (A, 2.3; B, 1.2; C, 0.6; D, 30.2 spikes/stimulus
presentation, respectively).
Figure 13 shows histograms of the four most typical types of endstopped cells selective for stimulus pairs (B), and for one stimulus
type (C). One can see that pair-selective neurons usually preferred
one type of line-end and a corner. Selectivity for both types of lineend or corner was rare. Highly selective neurons were most
frequently selective for one line-end.
We developed a quantitative method for classifying the stimulus
selectivity of these neurons. Since bars and edges are basically
different stimuli, we did a two-step analysis, ®rst with regard to
stimulus type (corners, line-ends) and second with regard to the
contrast polarity of these stimuli (light, dark). In the ®rst step, we
de®ned an index (IS) comparing mean responses to line-ends (R1, R3)
and corners (R2, R4), as shown in Fig. 13A:
IS = [(R1 + R3) ± (R2 + R4)]/(R1 + R2 + R3 + R4)
To account for response variability in this measure, we compared the
mean responses to line-ends (R1 + R3) and corners (R2 + R4) and also
compared them statistically using Student's t-test, and used this
measure to select the critical IS-values separating selective from
unselective responses. Since the two measures were highly correlated,
as revealed by regression analysis (r = 0.88, P < 0.001), we de®ned the
critical IS-values as the crossing points of the linear regression line
with the levels of the t-values indicating signi®cant differences
between the two types of responses (6 2.04, d.f. = 31, P = 0.05).
Figure 14A shows this analysis for 114/119 end-stopped cells
(standard errors not recorded in ®ve neurons). Neurons with indices
beyond the critical IS-values were considered to be selective for lineends or corners, neurons with indices between these values were
considered unselective for stimulus type. In the second step of this
analysis, we de®ned the selectivity for contrast polarity. We used two
indices, one for line-ends (IB = R1 ± R3/R1 + R3) and another for
corners (IE = R2 ± R4/R2 + R4), and selected the critical values
separating selective from unselective neurons again on the critical
t-values, as described earlier for IS. The two indices were plotted
against each other, as shown in Fig. 14B. The result for neurons that
were considered selective for line-ends or corners is shown in (a).
Neurons with IB and/or IE beyond the critical values (triangles)
preferred either a dark or light line-end or one type of corner and were
called `selective for one stimulus type'. Neurons with indices IB and
IE between the critical values were rare (diamonds). They responded
to both line-ends or to both corners and were called `pair-selective'.
The plot for neurons considered unselective for stimulus type is
shown in (b). Neurons with IB and IE beyond the critical values (open
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
Figure-ground segregation in monkey area V2 4125
FIG. 11. Neuron selective for a stimulus pair. This neuron preferred light lineends (A) and light/dark corners (B). It gave much weaker responses to dark
line-ends (C) and dark/light corners (D). The amplitude of stimulus movement
was 1.3 °, the frequency 1 Hz; 32 cycles are shown for each stimulus.
Spontaneous activity was zero (not shown). This neuron was recorded in area
V2 (thick stripe, laminae 5 + 6). Selectivity indices: IS = 0.12, IB = 0.95,
IE = 0.55 (see Fig. 14). For illustration purposes, the lateral borders of the
corner stimuli were shortened as indicated by curved contours. Conventions
otherwise as in Fig. 10.
dots) responded to one type of bar and corner and were also called
pair-selective. The remaining neurons (®lled dots) were called
`unselective'. Based on this classi®cation, we found 29% (34/119)
of the end-stopped cells to be selective for one stimulus type, 29%
(35/119) for a stimulus pair and 42% (50/119) were unselective.
Since the mapping of end-stopped receptive ®elds is tedious and
time consuming, we tested selectivity for stimulus type and contrast
polarity ®rst qualitatively using bars and edges of optimal length and
terminations, and then quantitatively but only for one of the two
stimulus types. This seemed justi®ed because, in qualitative testing,
we never found a neuron that preferred different stimulus types for
short stimuli of optimal length and terminations. We con®rmed this
®nding in some neurons quantitatively by comparing the selectivity
index IS, as determined from the responses to stimuli of optimal
length and terminations. Figure 15 shows the result. The regression
analysis revealed a high correlation between the two indices (r = 0.91,
P < 0.001).
For comparison, we used the same method to analyse stimulus
selectivity for end-free cells. Of course, only bars and edges of
optimal length were used in these neurons. The regression analysis
between the indices IS and the t-values of the Student's test
comparing the mean responses to the two types of stimulus also
revealed a high correlation between the two measures (r = 0.86,
P < 0.001). Thus, the crossing points of the linear regression line with
the levels of the t-values indicating signi®cant differences between
FIG. 12. Neuron selective for one stimulus type. This neuron preferred dark/
light corners (D). The remaining stimuli (A, light line-ends; B, light/dark
corners; C, dark line-ends) failed to evoke a response. The amplitude of
stimulus movement was 1.5 °, the frequency 1 Hz; 32 cycles are shown for
each stimulus. Spontaneous activity was 0.36 spikes/s (not shown). This
neuron was recorded in area V2 (pale stripe, laminae 5 + 6). Selectivity
indices: IS = ±0.82, IB = 0.66, IE = ±0.93 (see Fig. 14). Conventions otherwise as
in Fig. 10.
these responses (6 2.04, d.f. = 30, P = 0.05) also de®ned the critical
IS-values separating selective neurons from unselective neurons. The
result of this analysis is shown in Fig. 16A for 149/154 neurons
studied (standard errors not recorded in ®ve neurons). Figure 16B
shows the second step of the analysis concerning the contrast polarity
of these stimuli. The result for neurons that were considered selective
for bars or edges is shown in (a). Neurons with IB and/or IE beyond
the critical values (triangles) preferred either a dark or light bar, or
one type of edge and were called `selective for one stimulus type'.
Neurons with IB and IE between the critical values were rare
(diamonds). They responded to either both bars or to both edges and
were called `pair-selective'. The plot for neurons that were
considered unselective for stimulus type is shown in (b). Neurons
with indices IB and IE beyond the critical values (open dots)
responded to one type of bar and an edge, and were all called pairselective. The remaining neurons (®lled dots) were called `unselective'. By this measure, we found 32% (50/154) of the end-free cells to
be selective for one stimulus type, 34% (53/154) for a stimulus pair
and 33% (51/154) were unselective.
Anatomy
In area V2, we found 25% (168/675) of the neurons to have endstopped receptive ®elds; 115 were localized with respect to the
cytochrome oxidase pattern. Neurons that could not be localized
(n = 19) and neurons recorded at borders between stripes (n = 34) were
excluded. End-stopped cells were recorded with similar frequencies
in all cytochrome oxidase stripes (c2 = 4.2, d.f. = 2, P > 0.05) and
cortical laminae (c2 = 2.6, d.f. = 2, P > 0.05). The distributions are
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
4126 B. Heider et al.
FIG. 13. Examples of different types of
selectivity. (A) Stimuli as indicated on the
abscissa scales. (B) Responses of pair-selective
neurons. (C) Responses of neurons selective
for one stimulus type. The values of IS
indicate selectivity for stimulus type, those of
IB and IE indicate selectivity for contrast
polarity of line-ends and corners, respectively
(see text). Anatomical location of these
neurons: 4FQ3: V2, pale stripe, laminae 4;
4FK3: V2, thin stripe, laminae 5 + 6; 7EA2:
V1, laminae 2 + 3; 7CL2: V1, laminae 2 + 3;
7BD8: V2, thin stripe, laminae 2 + 3; 4CC6:
V2, thick stripe, laminae 2 + 3; 4CC5: V2,
thick stripe, laminae 2 + 3; 7IF3: V2, pale
stripe, laminae 5 + 6. Conventions: bars and
vertical lines indicate mean responses and
standard errors of 24 cycles of stimulus
movement. Stimulus amplitude and frequency
used for each neuron: 4FQ3: 1 °, 1.5 Hz; 4FK3:
2.7 °, 1 Hz; 7EA2: 0.8 °, 1 Hz; 7CL2: 0.6 °,
1 Hz; 7BD8: 0.7 °, 1 Hz; 4CC6: 0.7 °, 1 Hz;
4CC5: 3.3 °, 1.5 Hz; 7IF3: 1.5 °, 1 Hz.
shown in Fig. 17. Also, neurons with single- and double-stopped
®elds were distributed evenly within the cytochrome oxidase pattern
(c2 = 1.2, d.f. = 2, P > 0.05) and the cortical laminae (c2 = 2.5, d.f. = 2,
P > 0.05).
In area V1, we found a similar proportion of neurons with endstopped receptive ®elds (21%, 100/466) as in area V2. However, here
we found end-stopped cells most frequently in the upper laminae
(2 + 3: 30%, 60/203; 4: 17%, 20/119) and rarely in the deep laminae
(5 + 6: 4%, 4/96) (c2 = 27.3, d.f. = 2, P < 0.001).
Areas V1 and V2 were similar with regard to neuronal selectivity
for stimulus type and contrast polarity. In area V2, 32% (25/77) of the
end-stopped cells were selective for one stimulus type, 32% (25/77)
for a stimulus pair and 35% (27/77) were unselective. Similarly, 37%
(37/100) of the end-free cells were selective for one stimulus type,
32% (32/100) for a stimulus pair and 31% (31/100) were unselective.
In area V1, we found 21% (9/42) of the end-stopped cells to be
selective for one stimulus type, 24% (10/42) for a stimulus pair and
55% (23/42) were unselective. Similarly, 24% (13/54) of the end-free
cells were selective for one stimulus type, 39% (21/54) for a stimulus
pair and 37% (20/54) were unselective. Statistically, no signi®cant
differences were found between the two areas, neither for endstopped cells (c2 = 4.4, d.f. = 2, P > 0.05) nor for end-free cells
(c2 = 2.7, d.f. = 2, P > 0.05).
Eccentricity
The majority of the receptive ®elds of neurons studied for selectivity
of stimulus type were located within the central 5 ° of visual ®eld. In
area V2, the mean eccentricity was 2.9 ° for end-stopped cells (range:
0.6±8.8 °, n = 77) and 3.8 ° for end-free cells (range: 0.9±8.5 °,
n = 100). A similar representation of the visual ®eld was studied in
area V1. The mean eccentricity was 2.1 ° for end-stopped cells
(range: 0.9±6.5 °, n = 42) and 2.6 ° for end-free cells (range 0.7±7.0 °,
n = 54). Fields of selective neurons were scattered among ®elds of
unselective neurons. No clustering was found.
Discussion
In the present paper, we show that grouping mechanisms for
segregating ®gure and ground at contours are mainly implemented
in area V2 (pale cytochrome oxidase stripes). Neurons in this part of
the visual cortex signal the properties of occluding contours from
information provided by occlusion cues (line-ends, corners). We
show that end-stopped cells sensitive to different types, directions and
contrast polarities of occlusion cues can signal this information. This
mechanism generates illusory contours at sites of fading contrast and
initiates the brightness perception and depth ordering associated with
such contours.
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
Figure-ground segregation in monkey area V2 4127
FIG. 14. Two-step analysis de®ning the
selectivity of end-stopped cells for
terminations. (A) Selectivity for stimulus type
(line-ends, corners). Relationship between
selectivity index IS and t-values of Student's
test comparing mean responses to line-ends
and corners. t-values beyond 6 2.04
(horizontal dotted lines) indicate signi®cant
differences between these responses. Crossing
points with the regression line mark the critical
values of IS (±0.39 and 0.36, vertical dotted
lines) which separate selective neurons
(triangles, diamonds) from unselective neurons
(open, ®lled dots). (B) Selectivity for contrast
polarity (light, dark). Relationship between
indices de®ning selectivity for dark or light
line-ends (IB; critical values ±0.31 and 0.32)
and corners (IE; critical values 6 0.41). Plot
(a) shows the result for neurons that were
selective, plot (b) for neurons that were
unselective for stimulus type, as de®ned in A.
Representations of occluding contours in areas V1
and V2
Our results suggest that grouping mechanisms for representing
occluding contours are mainly implemented in area V2 and only
rarely in area V1. This ®nding agrees with the results of Lamme et al.
(1998) who reported that multiunit activity related to stimulus
conditions separating ®gures from ground by differences in orientation or motion was lost when the animal was anaesthetized or the
extrastriate cortex lesioned, while activity related to contrast borders
persisted. They suggest that V1 responses are due to a feedback
projection from extrastriate cortex that was inactivated during
anaesthesia or by the lesions. A similar explanation may be invoked
for signals of occluding contours that we found in area V1. A
comparable function of feedback projections from area MT (V5) was
invoked by Hupe et al. (1998) for ®gure-ground segregation from
motion cues.
Peterhans & von der Heydt (1993) found neuronal signals of
illusory contours in the pale and thick cytochrome oxidase stripes.
The present study suggests that mechanisms de®ning the depth order
at such contours are mainly located in the pale stripes. This difference
in localization can be explained by the difference in function
(discussed later) and the recruitment of signals of different types of
end-stopped cells (single- vs. double-stopped cells). Both studies
report that mechanisms generating illusory contours are generally not
found in the thin stripes.
FIG. 15. Comparison of the selectivity indices IS, as calculated from the
responses to stimuli of optimal length (bars, edges) and the corresponding
terminations (line-ends, corners). The solid line represents unity. The diamond
indicates neuron 7CK1 of Fig. 10.
Links to human perception
In the human visual cortex, representations of illusory contours have
also been reported in area V2 (Hirsch et al., 1995; Fftyche & Zeki,
1996). Larsson et al. (1999) found activity in both areas V1 and V2,
and showed that most regions were activated by both real and illusory
contours. This result agrees with our ®nding that neurons sensitive to
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
4128 B. Heider et al.
FIG. 16. Two-step analysis de®ning the
selectivity of end-free cells for bars and edges.
(A) Selectivity for stimulus type (bars, edges).
Relationship between selectivity index IS and
t-values of Student's test comparing mean
responses to bars and edges. t-values beyond
6 2.04 (horizontal dotted lines) indicate a
signi®cant difference between these responses.
Crossing points with the regression line mark
the critical values of IS (±0.24 and 0.22,
vertical dotted lines) which separate selective
neurons (triangles, diamonds) from unselective
neurons (open, ®lled dots). (B) Selectivity for
contrast polarity (light, dark). Relationship
between indices de®ning selectivity for dark or
light bars (IB; critical values 6 0.17) and edges
(IE; critical values ±0.19 and 0.17). Plot (a)
shows the result for neurons that were
selective, plot (b) for neurons that were
unselective for stimulus type as de®ned in A.
illusory contours also detect contrast borders (bars, edges). Mendola
et al. (1999) found activity evoked by illusory-contour stimuli also in
higher cortical areas such as V3A, V4v, V7 and V8. Our anatomical
results also relate to the perceptual de®cits of certain patients
suffering from visual form agnosia (Heider, 2000). These patients had
lesions of extrastriate cortex (including area V2) caused by carbon
monoxide poisoning or degenerative disease. They were unable to
perceive illusory contours and were severely impaired in segmenting
cluttered visual scenes requiring the de®nition of occluding contours
and ®gure-ground segregation. These de®cits may be explained by
the fact that the pale stripes are less vascularized (Zheng et al., 1991)
and contain less cytochrome oxidase than the thin and thick stripes,
and may therefore be more easily damaged (e.g. by hypoxia) than the
cytochrome oxidase-rich stripes (see also Milner & Goodale, 1995;
Zeki, 1997).
Model of the grouping process
Neural sensitivity to depth order and contrast polarity at illusory
contours can be explained in terms of Peterhans & von der Heydt's
(1991) two-stage model which suggests that neurons with endstopped receptive ®elds detect occlusion cues (line-ends, corners).
This model has the advantage that occlusion cues are detected by
classical types of cortical neurons (end-stopped cells) that have been
studied in anaesthetized and awake animals (Peterhans, 1997).
Evidence of computer simulations suggests that these neurons can
FIG. 17. Anatomical distribution of end-stopped cells in area V2. (A)
Distribution with regard the cytochrome oxidase pattern (thin stripes, 25%;
pale stripes, 28%; thick stripes, 19%). (B) Distribution with regard to cortical
laminae (2 + 3, 23%; 4, 29%; 5 + 6, 22%).
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
Figure-ground segregation in monkey area V2 4129
provide the basic information necessary for cortical representations of
occluding contours (Heitger et al., 1992, 1998; Peterhans et al., 2000).
Representations of occlusion cues in areas V1 and V2
In the light of this model, we studied the receptive ®elds of
end-stopped cells with regard to symmetry of end-inhibition, and
selectivity for orientation, type and contrast polarity of terminations
(light and dark line-ends, corners).
Symmetry of end-inhibition
Hubel & Wiesel (1965, 1968) found two types of end-stopped cells,
namely `double-stopped cells' with inhibitory zones of similar
strength at either end of the ®eld and `single-stopped cells' with a
single inhibitory zone at only one end of the ®eld. Using a
quantitative measure for de®ning symmetry of end-inhibition, we
found that about half of the neurons in areas V1 and V2 had singlestopped ®elds. This result is similar to the earlier report of van der
Zwan et al. (1995), who also showed that about one-third of these
neurons actually gave stronger responses to terminations than to short
stimuli of optimal length.
Orientation selectivity
We recorded orientation response functions for end-stopped cells to
stimuli of optimal length and to terminations and found similar
preferred orientations for the two types of stimulus. This preference
was also similar in the context of an illusory-contour stimulus, which
con®rms that end-stopped cells signal occlusion cues in the context of
such ®gures.
Types and contrast polarity
The results of the present paper suggest that end-stopped cells have
simple or complex-type excitatory ®elds, as has been reported earlier
in striate cortex of anaesthetized cats (Bishop & Henry, 1972; Dreher,
1972; Gilbert, 1977; Rose, 1977; Kato et al., 1978; Walker et al., 2000)
and monkeys (Schiller et al., 1976). Schiller et al. (1976; their ®g. 25)
found 59% (77/130) of the end-stopped cells of area V1 (end-inhibition
> 40%) to have complex-type excitatory ®elds; the remainder had
simple-type ®elds. This result is similar to ours (55%, 23/42),
assuming that unselective neurons had complex-type excitatory ®elds.
To our knowledge, no comparable results are available for area V2.
Anatomy
End-stopped cells were found with similar frequencies in areas V1
and V2. However, the laminar distribution of the two populations was
different. In area V1, end-stopped cells were found most frequently in
the upper laminae, a result that agrees with studies of anaesthetized
monkeys (Hubel & Wiesel, 1968, their ®g. 13; Schiller et al., 1976,
their ®g. 29). In area V2, end-stopped cells were recorded with similar
frequencies in all laminae and cytochrome oxidase stripes. This
distribution is slightly different from results of the anaesthetized
monkey. Levitt et al. (1994, their ®g. 16) found end-stopped cells
most frequently in the deep laminae of the thin stripes. However, this
number of neurons was small (three out of four neurons studied) and
overall, with regard to the stripe pattern, the distribution was uniform
(c2 = 3.2, d.f. = 2, P > 0.05). Other studies reported that end-stopped
cells concentrate in the pale cytochrome oxidase stripes (Hubel &
Livingstone, 1987; Gegenfurter et al., 1996).
Conclusions
The results of the present paper show that end-stopped cells, as a
classical type of cortical neuron, can detect occlusion cues and thus
provide the basic information necessary for de®ning occluding
(illusory) contours. The grouping process involved de®nes the
position and orientation of such contours and initiates the brightness
perception and depth ordering associated with such contours. The
results further show that this mechanism is mainly implemented in
the pale cytochrome oxidase stripes of area V2 that project to area V4
and the inferotemporal cortex (form processing path). Thus, lesions of
this part of the visual cortex may lead to perceptual de®cits
concerning contour processing and ®gure-ground segregation, a
hypothesis that agrees with the visual impairments reported for
certain patients suffering from visual form agnosia.
Acknowledgements
We thank J. Lentjes and S. ElsaÈsser for technical assistance, M.R. DuÈrsteler
and F. Heitger for developing software for data acquisition, R. von der Heydt
for participating in some of these experiments, J. Weilenmann and J. MuÈller
for photography, K.A.C. Martin (Institute of Neuroinformatics, UZ/ETHZ) for
help with the histology and Susan Hock®eld (Yale University, CT, USA) for
providing the Cat-301 antibody. Supported by SNF-SPP grant number 5002044891.
References
Allman, J., Miezin, F. & McGuinness, E. (1985) Direction- and velocityspeci®c responses from beyond the classical receptive ®eld in the middle
temporal visual area (MT). Perception, 14, 105±126.
Baumann, R., van der Zwan, R. & Peterhans, E. (1997) Figure-ground
segregation at contours: a neural mechanism in the visual cortex of the alert
monkey. Eur. J. Neurosci., 9, 1290±1303.
Bishop, P.O. & Henry, G.H. (1972) Striate neurons: receptive ®eld concepts.
Invest. Ophthalmol., 11, 346±354.
Bradley, D.C. & Andersen, R.A. (1998) Center-surround antagonism based on
disparity in primate area MT. J. Neurosci., 18, 7552±7565.
Chang, G., Stoner, G.R. & Albright, T.D. (1999) Neuronal correlates for
depth-ordering in area V2. ARVO Abstr., 24, S640.
DeYoe, E.A., Hock®eld, S., Garran, H. & Van Essen, D.C. (1990) Antibody
labeling of functional subdivisions in visual cortex: Cat-301
immunoreactivity in striate and extrastriate cortex of the macaque
monkey. Vis. Neurosci., 5, 67±81.
Dreher, B. (1972) Hypercomplex cells in the cat's striate cortex. Invest.
Ophthalmol., 11, 355±356.
Felleman, D.J. & Van Essen, D.C. (1987) Receptive ®eld properties of neurons
in area V3 of macaque monkey extrastriate cortex. J. Neurophysiol., 57,
889±920.
Ffytche, D.H. & Zeki, S. (1996) Brain activity related to the perception of
illusory contours. Neuroimage, 3, 104±108.
Gegenfurter, K.R., Kiper, D.C. & Fenstemaker, S.B. (1996) Processing of
color, form, and motion in macaque area V2. Vis. Neurosci., 13, 161±172.
Gilbert, C.D. (1977) Laminar differences in receptive ®eld properties of cells
in cat primary visual cortex. J. Physiol. (Lond), 268, 391±421.
Heider, B. (2000) Visual form agnosia: neural mechanisms and anatomical
foundations. Neurocase, 6, 1±8.
Heider, B. & Peterhans, E. (1998) Neural sensitivity to occlusion cues in
monkey visual cortex. Soc. Neurosci. Abstr., 24, 1396.
Heider, B., Meskenaite, V. & Peterhans, E. (1997) Neural mechanisms of
®gure-ground segregation in monkey area V2. Soc. Neurosci. Abstr., 23,
1031.
Heitger, F., Rosenthaler, L., von der Heydt, R., Peterhans, E. & KuÈbler, O.
(1992) Simulation of neural contour mechanisms: from simple to endstopped cells. Vision Res., 32, 963±981.
Heitger, F., von der Heydt, R., Peterhans, E., Rosenthaler, L. & KuÈbler, O.
(1998) Simulation of neural contour mechanisms: representing anomalous
contours. Image Vision Comput., 16, 407±421.
Hirsch, J., DeLaPaz, R.L., Relkin, N.R., Victor, J., Kim, K., Li, T., Borden, P.,
Rubin, N. & Shapley, R. (1995) Illusory contours activate speci®c regions in
human visual cortex: evidence from functional magnetic resonance
imaging. Proc. Natl Acad. Sci. USA, 92, 6469±6473.
Hubel, D.H. & Livingstone, M.S. (1987) Segregation of form, color, and
stereopsis in primate area 18. J. Neurosci., 7, 3378±3415.
Hubel, D.H. & Wiesel, T.N. (1965) Receptive ®elds and functional
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130
4130 B. Heider et al.
architecture in two nonstriate visual areas (18 and 19) of the cat. J.
Neurophysiol., 28, 229±289.
Hubel, D.H. & Wiesel, T.N. (1968) Receptive ®elds and functional
architecture of monkey striate cortex. J. Physiol. (Lond), 195, 215±243.
Hubel, D.H. & Wiesel, T.N. (1970) Cells sensitive to binocular depth in area
18 of the macaque monkey cortex. Nature, 225, 41±42.
HupeÂ, J., James, A., Payne, B., Lomber, S., Girard, P. & Bullier, J. (1998)
Cortical feedback improves discrimination between ®gure and background
by V1, V2 and V3 neurons. Nature, 394, 784±787.
Janssen, P., Vogels, R. & Orban, G.A. (1999) Macaque inferior temporal
neurons are selective for disparity-de®ned three-dimensional shapes. Proc.
Natl Acad. Sci. USA, 96, 8217±8222.
Kato, H., Bishop, P.O. & Orban, G.A. (1978) Hypercomplex and simple/
complex cell classi®cations in cat striate cortex. J. Neurophysiol., 41,
1071±1095.
Lamme, V.A.F., SupeÁr, H. & Spekreijse, H. (1998) Feedforward, horizontal,
and feedback processing in the visual cortex. Curr. Opin. Neurobiol., 8,
529±535.
Larsson, J., Amunts, K., GulyaÂs, B., Malikovic, A., Zilles, K. & Roland, P.E.
(1999) Neuronal correlates of real and illusory contour perception:
functional anatomy with PET. Eur. J. Neurosci., 11, 4024±4036.
Levitt, J.B., Kiper, D.C. & Movshon, J.A. (1994) Receptive ®elds and
functional architecture of macaque V2. J. Neurophysiol., 71, 2517±2542.
Maunsell, J.H.R. & Van Essen, D.C. (1983) Functional properties of neurons
in middle temporal visual area of the macaque monkey. II. Binocular
interactions and sensitivity to binocular disparity. J. Neurophysiol., 49,
1148±1167.
Mendola, J.D., Dale, A.M., Fischl, B., Liu, A.K. & Tootell, R.B.H. (1999) The
representation of illusory and real contours in human cortical visual areas
revealed by functional magnetic resonance imaging. J. Neurosci., 19,
8560±8572.
Milner, A.D. & Goodale, M.A. (1995) The Visual Brain in Action. Oxford
University Press, Oxford.
Motter, B.C. & Poggio, G.F. (1984) Binocular ®xation in the rhesus monkey:
spatial and temporal characteristics. Exp. Brain Res., 54, 304±314.
Nakayama, K., Shimojo, S. & Silverman, G.H. (1989) Stereoscopic depth: its
relation to image segmentation, grouping, and the recognition of occluded
objects. Perception, 18, 55±68.
Peterhans, E. (1997) Functional organization of area V2 in the awake monkey.
In Rockland, K.S., Kaas, J.H., Peters, A. (eds), Cerebral Cortex, Vol. 12.
Plenum Press, New York, NY, pp. 335±357.
Peterhans, E. & von der Heydt, R. (1989) Mechanisms of contour perception
in monkey visual cortex. II. Contours bridging gaps. J. Neurosci., 9,
1749±1763.
Peterhans, E. & von der Heydt, R. (1991) Subjective contours ± bridging the
gap between psychophysics and physiology. Trends Neurosci., 14, 112±119.
Peterhans, E. & von der Heydt, R. (1993) Functional organization of area V2
in the alert macaque. Eur. J. Neurosci., 5, 509±524.
Peterhans, E., van der Zwan, R. & Baumann, R. (1995) Sensitivity to
stereoscopic depth of end-stopped cells in monkey visual cortex.
Perception, 24, 6.
Peterhans, E., van der Zwan, R., Heider, B. & Heitger, F. (2000) Figureground segregation and brightness perception at illusory contours: a
neuronal model. In van Hemmen, J.L. (ed.), Models of Neural Networks,
Vol. IV. Springer-Verlag, New York, pp. 197±225.
Poggio, G.F. & Fischer, B. (1977) Binocular interaction and depth sensitivity
in striate and prestriate cortex of behaving rhesus monkey. J. Neurophysiol.,
40, 392±1405.
Poggio, G.F., Motter, B.C., Squatrito, S. & Trotter, Y. (1985) Responses of
neurons in visual cortex (V1 and V2) of the alert macaque to dynamic
random-dot stereograms. Vision. Res., 25, 397±406.
Roe, A.W. & Ts'o, D.Y. (1995) Visual topography in primate V2: multiple
representation across functional stripes. J. Neurosci., 15, 3689±3715.
Rose, D. (1977) Responses of single units in cat visual cortex to moving bars
of light as a function of bar length. J. Physiol., 271, 1±23.
Roy, J.P., Komatsu, H. & Wurtz, R.H. (1992) Disparity sensitivity of neurons
in monkey extrastriate area MST. J. Neurosci., 12, 2478±2492.
SaÂry, G., Vogels, R. & Orban, G.A. (1993) Cue-invariant shape selectivity of
macaque inferior temporal neurons. Science, 260, 995±997.
Schiller, P.H., Finlay, B.L. & Volman, S.F. (1976) Quantitative studies of
single-cell properties in monkey striate cortex. I. Spatiotemporal
organization of receptive ®elds. J. Neurophysiol., 39, 1288±1319.
Tanaka, K., Hikosaka, H., Saito, H., Yukie, Y., Fukuda, Y. & Iwai, E. (1986)
Analysis of local and wide-®eld movements in the superior temporal visual
areas of the macaque monkey. J. Neurosci., 6, 134±144.
Toyama, K., Kimura, M. & Tanaka, K. (1981) Cross-correlation analysis of
interneuronal connectivity in cat visual cortex. J. Neurophysiol., 46,
191±201.
Uka, T., Tanaka, H., Kato, M. & Fujita, I. (1998) Segmentation of surfaces by
disparity or contours in monkey inferior temporal cortex. Soc. Neurosci.
Abstr., 24, 899.
van der Zwan, R., Baumann, R. & Peterhans, E. (1995) End-stopped cells in
the visual cortex of the alert monkey. Perception, 24, 43.
Van Essen, D.C., DeYoe, E.A., Olavarria, J.F., Knierim, J.J., Fox, J.M., Sagi,
D. & Julesz, B. (1989) Neural responses to static and moving texture
patterns in visual cortex of the macaque monkey. In Lam, D.M.-K., Gilbert,
C.D. (eds), Neural Mechanisms of Visual Perception. Portfolio Publishing
Company, The Woodlands, TX, pp. 137±154.
von der Heydt, R. & Peterhans, E. (1989) Mechanisms of contour perception
in monkey visual cortex. I. Lines of pattern discontinuity. J. Neurosci., 9,
1731±1748.
Walker, G.A., Ohzawa, I. & Freeman, R.D. (2000) Suppression outside the
classical cortical receptive ®eld. Vis. Neurosci., 17, 369±379.
Wolbarsht, M.L., MacNichol,E.F. Jr & Wagner, H.G. (1960) Glass insulated
platinum microelectrode. Science, 132, 1309±1310.
Wong-Riley, M.T.T. & Carroll, E.W. (1984) Quantitative light and electron
microscopic analysis of cytochrome-oxidase rich zones in V II prestriate
cortex of the squirrel monkey. J. Comp. Neurol., 222, 18±37.
Zeki, S. (1997) The color and motion systems as guides to conscious visual
perception. In Rockland, K.S., Kaas, J.H., Peters, A. (eds), Cerebral Cortex,
Vol. 12. Plenum Press, New York, NY, pp. 777±809.
Zheng, D., LaMantia, A.-S. & Purves, D. (1991) Specialized vascularization of
the primate visual cortex. J. Neurosci., 11, 2622±2629.
Zhou, H., Friedman, H.S. & von der Heydt, R. (2000) Coding of border
ownership in monkey visual cortex. J. Neurosci., 20, 6594±6611.
Ó 2000 Federation of European Neuroscience Societies, European Journal of Neuroscience, 12, 4117±4130