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