Abstract

It is known that neurons in area V2 (the second visual area) can signal the orientation of illusory contours in the primate. Whether area V1 (primary visual cortex) can signal illusory contour orientation is more controversial. While some electrophysiology studies have ruled out illusory signaling in V1, other reports suggest that V1 shows some illusory-specific response. Here, using optical imaging and single unit electrophysiology, we report that primate V1 does show an orientation-specific response to the ‘abutting line grating’ illusory contour. However, this response does not signal an illusory contour in the conventional sense. Rather, we find that illusory contour stimulation leads to an activation map that, after appropriate subtraction of real line signal, is inversely related to the real orientation map. The illusory contour orientation is thus negatively signaled or de-emphasized in V1. This ‘activation reversal’ is robust, is not due merely to presence of line ends, is not dependent on inducer orientation, and is not due to precise position of line end stimulation of V1 cells. These data suggest a resolution for previous apparently contradictory experimental findings. We propose that the de-emphasis of illusory contour orientation in V1 may be an important signal of contour identity and may, together with illusory signal from V2, provide a unique signature for illusory contour representation.

Introduction

Visual contours abound in natural scenes. Some visual contours are clearly defined by luminance contrast (e.g. Fig. 1a, river bank, lower circle). Other contours (e.g. Fig. 1a, canyon wall detail) are defined in a less direct manner, often inferred by local visual cues, e.g. texture (Julesz, 1984; Leventhal et al., 1998), motion (Marcar et al., 1995) and occlusion (Baumann et al., 1997). How does the visual system encode these inferred or ‘higher order’ contours?

Here, we have addressed this question by studying the cortical processing of one type of higher order contour, the ‘abutting line grating’ illusory contour (Fig. 1b) (Kanisza, 1974; Soriano et al., 1996). In this contour type, displaced line gratings induce the perception of orientation even in the absence of luminance contrast across the contour. Previous studies have drawn different conclusions regarding how visual cortex processes this type of illusory contour. Electrophysiological studies in the primate have shown that orientation-selective cells in area V1 (primary visual cortex) are well activated by real (luminance defined) contours (Hubel and Wiesel, 1968). In area V2 (the second visual area), however, cells are activated by both real and illusory contours of the same orientation (von der Heydt and Peterhans, 1989). The possible existence of such ‘illusory contour’ cells in V1 is more controversial. In the primate, electrophysiological studies have concluded that illusory contour cells are virtually absent in V1 (Peterhans and von der Heydt, 1989; von der Heydt and Peterhans, 1989). Grosof and co-workers suggested that primate V1 cells can respond to illusory contours defined by displaced grating stimuli (although their ‘illusory’ contour stimuli also comprised real luminance contrast edges) (Grosof et al., 1993). In the cat, Sheth et al. (Sheth et al., 1996) reported an illusory contour response in area 17 (the cat primary visual area), thus concluding that illusory contour processing indeed commences in the first rather than second visual area (Sheth et al., 1996). Lower resolution functional imaging studies of humans suggest, too, that V1 may play some role in illusory contour signaling (Hirsch et al., 1995; Mendola et al., 1999; Seghier et al., 2000). Whether these different conclusions are due to species differences or to differences in experimental method needs further examination.

Regardless of whether primary visual cortex encodes illusory contours or not, the encoding of real and illusory orientation by single V2 neurons raises significant questions. Since illusory contour cells in V2 respond to both real and illusory contours of the same orientation, their signal can be ambiguous. How, then, are real and illusory contours sufficiently differentiated by the visual system? One possible way in which real and illusory contours may be distinguished by V1 and V2 is by some integration of their respective responses.

In this paper, using optical imaging and electrophysiological methods, we investigate the processing of the abutting line grating illusory contour by V1 and V2 in the anesthetized primate. In particular, we examine whether V1 shows evidence of any illusory-specific activations and, if so, what role these activations play in illusory contour processing. We find that V1 does demonstrate orientation-selective response to illusory contours but, surprisingly, one that is complementary to that shown by V2. We propose that this signal in V1, together with the illusory signal in V2, serves to distinguish the real versus illusory nature of visual contours.

Materials and Methods

Surgical Preparation

Experiments were performed under protocols approved by Yale Animal Care and Use Committee. Five adult cynomologus macaque monkeys and one adult rhesus macaque monkey were administered ketamine (10 mg/kg i.m.) and atropine sulfate (0.05 mg/kg) and prepared for surgery. Following intubation and catheterization for intravenous drug administration, animals were anesthetized with thiopental sodium (Abbott Laboratories, North Chicago, IL; induction 10 mg/kg, maintenance 1–2 mg/kg per h), paralyzed with vercuronium bromide (Organon, West Orange, NJ; induction 0.1 mg/kg, maintenance 100 μg/kg per h), and artificially respirated. Anesthetic depth was assessed continuously via implanted wire EEG electrodes, end-tidal CO2, oximetry and heart rate monitoring, and by regular testing for response to toe pinch. Eyelids were retracted with specula. Pupils were dilated with atropine and eyes were focused with customized primate contact lenses (Danker Laboratories Inc., Sarasota, FL) onto a computer screen (Barco Calibrator PCD-321, Belgium) at 145 cm distance. Eyes were aligned by converging the receptive fields (RFs) of a V1 binocular cell with a Risley prism over one eye. Under aseptic surgical conditions, a craniotomy (in most instances 10 × 6 mm, 5–15 mm lateral to midline, 14–20 mm rostral to occipital cranial ridge) and durotomy were performed to expose cortex posterior to the lunate sulcus. Such exposures, from which all our recordings were obtained, gave us access to cortical areas representing eccentricities of 2–5° below the horizontal meridian and along the vertical meridian.

Optical Imaging

An optical chamber was adhered to the skull, filled with sterile silicone oil and sealed with a glass window. Images were acquired using an Imager 2000 system (Optical Imaging Inc., Germantown, NY) with 630 nm illumination. Image data was binned to yield response map dimensions of 324 × 240 pixels. Each stimulus condition was presented in randomized order for 3 s with a 10–15 s interstimulus interval (Bonhoeffer and Grinvald, 1996). For each stimulus condition, we collected 15 consecutive 200 ms image frames after stimulus onset and these were stored for subsequent analysis. Signal-to-noise ratio was enhanced by trial averaging (40–100 trials per stimulus condition), and by synchronization of acquisition with heart rate and respiration. Animals were positioned on a floating bench (Newport, Irvine, CA) to minimize motion artifacts. For ocular dominance maps, electromechanical shutters (Uniblitz, Rochester, NY) were placed in front of the eyes for monocular stimulation.

Visual Stimuli

Illusory contour stimuli were created using a custom-made C-language program and were presented binocularly to the animal. These achromatic illusory contour gratings were composed of short acute (45°, e.g. Fig. 2a) or short obtuse (135°) lines (bright lines against a dark background, 1 pixel wide, 0.03° width) spaced 0.25° apart, a spacing which has been shown to be effective for illusory contour cells in V2 [(von der Heydt and Peterhans, 1989); at 2–5° eccentricity V2 receptive fields typically have receptive field sizes of 1–2° and V1 0.2–0.5° (Hubel and Wiesel, 1974; Dow et al., 1981; Gattass et al., 1981; Roe and Ts'o, 1995)]. These inducing elements were aligned, with a column spacing of 1.25 cycles/degree, to produce a percept of either horizontal (Fig. 2a, left) or vertical (Fig. 2a, right) illusory contours. To minimize response to real inducer orientation, these rows of aligned inducers were together drifted back and forth [0.8°/s, drift range two cycles, three second presentation time, screen dimensions 13° (w) × 10° (h)] in the direction along the orientation of inducing lines, producing the percept of illusory contour motion orthogonal to the illusory contour orientation (see Fig. 2a). Thus, since element size, orientation, spacing and motion were identical for both illusory horizontal and illusory vertical stimuli, the only difference between these two conditions was the arrangement of the inducing lines, i.e. the orientation of the illusory contour. Responses to illusory contour gratings were compared with responses to identically spaced (1.25 cycles/degree) and drifting real line gratings [see Fig. 2b; 1 pixel width, 0.8°/s, drift range two cycles, 3 s presentation time, screen dimensions 13° (w) × 10° (h)] presented binocularly at four primary orientations (horizontal, acute, vertical and obtuse). Luminance values were measured using a calibrated photometer (Minolta Chromameter CS-100, Ramsey, NJ) and were constant across stimuli (background luminance 0.1 cd/m2, line luminance 40.0 cd/m2, global stimulus luminance 8.0 cd/m2).

Electrophysiology

Subsequent to imaging, the glass window and silicone oil were removed and the cortex was stabilized with agar. Glass-coated tungsten electrodes (Ainsworth, Northampton, UK) were inserted into superficial layers of V1 cortex. Response characteristics and RFs of single units were determined using a hand-held visual projection lamp. Units were selected for quantitative study only if they exhibited clear orientation selectivity as determined from an audio monitor. Single units were isolated and spike activity was collected (Spike2, Cambridge Electronic Design Ltd, Cambridge, UK) in response to sequences of oriented real and illusory small-field stimuli (see Figs 7a and 9). As for full field gratings, different illusory stimuli differed only in their illusory contour orientation and were composed of identical inducing lines with 0.25° line spacing. For each real or illusory orientation condition, a single real or illusory contour was swept back and forth (0.8°/s) across a static 2° aperture centered on the receptive field center. In the illusory stimulus conditions, there was no motion of the real lines, only coherent sweeping of the line end positions, producing a percept of a moving oriented illusory contour. Spontaneous activity levels were collected during blank screen presentation. Modulation indices were calculated for real (modr) and illusory (modi) contour stimulation at preferred and non-preferred orientations (see Fig. 7c):  

formula
and  
formula
where r1 is the mean spike count for epochs with real stimuli at preferred real orientations, r2 is the mean spike count for epochs with real stimuli at non-preferred real orientations, i1 is the mean spike count for epochs with illusory stimuli at preferred real orientations and i2 is the mean spike count for epochs with illusory stimuli at non-preferred real orientations. To ensure that modulations were not merely related to spontaneous variations in background spike firing, we also calculated a modulation index (mods) for the sequential epochs in which blank stimuli were shown:  
formula
where s1 and s2 are the mean spike counts during the alternating epochs of spontaneous activity recording. Common denominators were chosen for all indices so that calculated modulations were always relative to real response levels.

Image Analysis

Optical imaging maps shown in this paper are either ‘difference’ maps (responses to one stimulus condition subtracted from responses to another stimulus condition) or ‘single condition’ maps (responses show specific activations associated with one stimulus condition only). Single condition maps provide the most reliable indication of stimulus-specific activations, but this may occur at the expense of signal-to-noise ratio. Difference maps yield better overall signal quality, but activations common to both stimulus conditions are eliminated. In our image analysis design, we have taken advantage of this latter limitation. Single condition illusory contour responses contain intrinsically significant real orientation signal component (due to the orientation of real inducing elements). Thus, location of illusory specific responses can only be revealed by canceling out common real contributions via a difference map derivation (e.g. horizontal illusory minus vertical illusory) (Sheth et al., 1996).

Difference Maps

Difference maps were obtained for pairs of stimulus conditions by subtracting summed frames acquired within 3 s of stimulus onset. (Intrinsic cortical responses have relatively slow time-courses peaking 2–4 s after stimulus onset.) These maps (pixel values 0–255) indicate the relative preference of each location in the image for one (darker pixels) or other (lighter pixels) of a pair of conditions (e.g. horizontal or vertical). Gray values indicate equal preference for either stimulus.

Single Condition Maps

Single condition responses were obtained by first summing frames acquired within 3 s of stimulus onset. Single condition maps were subsequently derived relative to a reference ‘blank’ condition. For illusory contour condition maps, and for real oriented stimulus condition maps in some control experiments, we used a blank screen (null orientation stimulus, luminance 8.0 cd/m2) to generate the reference blank response. For all other real oriented stimulus condition maps we used a ‘cocktail blank’ reference, constructed by summing the responses to all four cardinal orientations (Bartfeld and Grinvald, 1992; Bonhoeffer and Grinvald, 1993). Such cocktail blanks are ‘activated’ blanks that serve to average out biological artifacts such as those due to blood vessels (Bartfeld and Grinvald, 1992). In contrast to difference maps, single condition maps indicate the response magnitude at each location in the image for a particular stimulus condition. Thus, darker pixels indicate strongest responses and lighter pixels indicate weakest responses.

First Frame Subtraction

In all quantitative image processing and analyses in this paper, the method of ‘first frame subtraction’ (Bonhoeffer and Grinvald, 1996) was used to remove blood vessel artifact. Since blood vessel artifacts tend to persist throughout the 3 s period of imaging, subtraction of the first frame (in our case 200 ms frame) from each of the subsequent 200 ms frames can reduce these image contributions. (Since the intrinsic signal has a slow onset, there is virtually no stimulus-specific response in the first few hundred milliseconds.) While this method is effective in removing blood vessel artifact, this image enhancement occurs at the expense of overall signal-to-noise ratio (e.g. increased ‘shot’ noise in image). Thus, the appearance of images can be qualitatively different depending on method of image calculation [e.g. compare Fig. 4a (without first-frame subtraction) with Fig. 5b (with first-frame subtraction)]. In this paper, we chose to use first-frame subtraction for all our automated quantitative analyses to reduce the likelihood of vessel artifacts confounding the determination of map correlations.

Thresholding

To compare the locations of imaged illusory domains with real orientation domains, we generated thresholded maps (80th percentile, pixel histogram distribution) of each of the real single condition (horizontal, acute, vertical and obtuse) orientation maps. Illusory contour difference maps were thresholded at the 80th percentile and above for horizontal illusory domains, and at the 20th percentile and below for vertical illusory domains. We have used these cut-off levels as a rule of thumb because they are in qualitative agreement with visual inspection of the image. The conclusions drawn from our statistical comparisons of image maps (see spatial correlation methods, below) are not affected by the precise cut-off. Prior to thresholding, images were spatially filtered using a 9 × 9 pixel moving window low pass filter.

Elimination of Small Activation Domains

We presumed that if an activated group of pixels was too small, then it was less likely to be a true orientation domain and more likely to be due to noise. Thus, although infrequent, thresholded pixel clusters (defined as groups of adjacent pixels) containing less than 10 pixels (i.e. less than 50 μm breadth) were excluded from analysis.

Test of Spatial Correlation

To test for the presence of spatial correlation between a pair of thresholded maps (e.g. mapA and mapB), we used a non-parametric statistical method (Cole, 1949; Sorenson, 1976). This method tests for the degree of spatial correlation and does not address the issue of relative signal magnitude. The presence or absence of suprathreshold activation for every pixel in each map pair was tabulated in 2 × 2 contingency tables. For each comparison, we calculated a χ2 statistic (Cole, 1949) to test for statistical significance:  

(1)
formula
where w is the pixel count for condition mapA = ON and mapB = ON; x is the pixel count for condition mapA = OFF and mapB = ON; y is the pixel count for condition mapA = ON and mapB = OFF; z is the pixel count for condition mapA = OFF and mapB = OFF; and n = w + x + y + z. The null hypothesis (that no significant spatial correlation occurred between map pairs) was rejected if the χ2 statistic (d.f. = 1) exceeded the 0.001 significance level. Where spatial correlation was deemed significant, coefficients of spatial correlation, c, were calculated (–1.0 < c < +1.0) (Cole, 1949):  
(2)
formula

Coefficients within the range 0.2 < c < 1.0 indicated a significant degree of domain overlap, and coefficients within the range –1.0 < c < –0.2 indicated a significant degree of domain segregation. Coefficients within the range –0.2 < c < 0.2 were deemed neither significantly overlapped nor segregated (Cole, 1949). We considered that coefficients could vary with changes in threshold criteria. We therefore tried different threshold levels (90th/10th and 70th/30th percentile, cf. 80th/20th percentile criteria) in some cases. We determined that although the precise coefficient value can vary with different cut-offs, the sign of the coefficient value remains robust.

Results

We used conventional intrinsic optical imaging methods to map the spatial distribution of cortical activity in area V1 of five anesthetized adult macaque monkeys. For comparison, we mapped area V2 activity in two of these five cases, and in one additional adult macaque monkey. In each case, a portion of areas V1 and V2 posterior to the lunate sulcus was exposed, and the V1/V2 border location was determined via ocular dominance column mapping (e.g. Figs 3c, 6a). We obtained and then compared cortical orientation maps in response to presentation of drifting real and illusory contour stimuli (Fig. 2).

To investigate the spatial relationships between real and illusory maps, we first derived high resolution spatial maps for real orientation preference (Fig. 3). Single condition maps were obtained for each of the four cardinal orientations (real lines were 1 pixel wide full screen length oriented at 0, 45, 90 or 135°) (Fig. 3a). Difference maps (Fig. 3b) were obtained by subtracting orthogonal conditions. In some cases, orientation maps were supported by electrophysiological sampling (Fig. 3d). The spatial locations of orientation domains were then determined by low-pass filtering and thresholding (Fig. 3a, colored outlines to right of each single condition map).

Illusory contour orientation maps (e.g. Figs 4b and 5c) were then obtained by subtracting image responses to orthogonal illusory stimuli composed of identical inducers. Such subtraction removes signal common to both stimulation conditions — that is, the contribution by real oblique contour activation (Sheth et al., 1996). Any remaining differential signal can then be attributed to differential illusory contour activation.

We have organized the paper in the following manner. Our observations regarding real and illusory responses in V1 and V2 are presented in Figures 4–7. Control data are presented in Figures 8–10. For control conditions, we used randomly positioned oblique short line stimuli with the same motion as illusory contour stimuli (no illusory contour percept) (see Fig. 10), and also blank screen stimuli with a global luminance equivalent to the real and illusory contour stimuli. Our interpretation of this differential signal as due to illusory contour activation was further controlled by examining dependence of this signal on inducer orientation and position (see Figs 8 and 9). Additional data that serve to aid in the interpretation of our observations (single condition maps) are presented in Figures 11–12. Our summary and speculations regarding these observations are presented in Figure 13.

Reversed Alignment of Illusory and Real Domains in Area V1

Previous studies had suggested that primate V1 cells exhibit little or no response to illusory contours (Peterhans and von der Heydt, 1989; von der Heydt and Peterhans, 1989). We were thus surprised to find that optical images from area V1 in response to illusory contour stimuli revealed orientation-dependent response domains. Figure 4 shows a typical V1 cortex case where illusory response domains are evident. These illusory response domains (Fig. 4b) were comparable in size and spacing to real line orientation domains (Fig. 4a) in V1, although overall differential signal amplitudes were reduced relative to real response maps (imaging activation typically 20–50% in magnitude). We were further intrigued when we compared real and illusory response maps and did not observe overlap between real and illusory domain maps of the same orientation preference. Rather, in V1, horizontal real domains tended to overlie vertical illusory domains and vertical real domains tended to overlie horizontal illusory domains (compare lower panels of Fig. 4a and b). Orange circles demarcate strongest (darkest) horizontal real domains in Figure 4a, but these same domain locations tend to coincide with strongest (lightest) vertical illusory domains in Figure 4b. Thus, when the illusory activation map is compared with the real activation map in V1, we find an apparent inversion in response, i.e. an ‘activation reversal’ map.

We then quantified these impressions. We uniformly applied low-pass and threshold criteria to images in order to delineate the locations and extents of activation domains, and then examined statistically the spatial overlap (i.e. spatial correlation) of these illusory contour and real line domains. As mentioned above, the illusory mapping signal is relatively small and thus susceptible to noise. To increase our confidence in our analysis, we therefore designed an analysis method that was conservative in two ways. First, we confined the test of correlation to only the strongest horizontal/vertical (either real or illusory) signal domains by thresholding the maps. Secondly, we used a non-parametric statistical analysis that (unlike parametric methods) does not require the assumption of image pixel normal distribution. With this approach, our statistic indicates primarily the presence or absence of spatial overlap of domains, rather than pixel-for-pixel correlation across unthresholded signal range. Indeed, because of the constraints associated with this approach, the extent of spatial correlation across conditions may sometimes be underestimated.

Figure 5 shows an example of how we quantitatively compared our V1 orientation maps. Strongest domain locations were obtained first by low-pass filtering and then thresholding each real response map (Figs 5a and b). Illusory response maps (Fig. 5c, top) were similarly low-pass filtered (Fig. 5c, middle) and thresholded (Fig. 5c, bottom). We then overlaid these strongest domain responses in one color-coded map (Fig. 5d) The presence of significant spatial correlation between these strongest domains in the illusory and real maps was tested using a χ2 statistic (see Material and Methods). For correlations that are significant, this method yields a numerical correlation index (c) that ranges from –1 (completely non-overlapped) to 0 (neither clearly overlapping or non-overlapping) to +1 (completely overlapping). Although, with this approach, the significance levels and the correlation indices can change with different low-pass and threshold parameters, we find that both the sign and approximate magnitude of the correlation index are persistent and robust over multiple low-pass and threshold parameters.

We applied these analysis procedures to image data from five cases of V1. Analysis results are summarized in Table 1. Two of the cases are shown in detail in Figure 5d and e. Consistent with our previous qualitative observations, horizontal illusory domains (red outline) tend to overlie vertical real domains (blue), and vertical illusory domains (black outline) tend to overlie horizontal real domains (orange). In all five cases of V1 studied, statistically significant spatial correlations (P < 0.001, χ2 test) were found between horizontal illusory and vertical real maps, and between vertical illusory and horizontal real maps (Table 1, area V1, orthogonal orientation data, positive indices). Between co-oriented real and illusory domains, significant inverse correlations (P < 0.001, χ2 test) were found (Table 1, area V1, matching orientation data, negative indices) in all five cases.

To test whether illusory activation maps may be related to the orientation of the inducing lines, we compared the distribution of illusory domains with real acute orientation domains (the inducing line orientation). Of the 10 such comparisons made in V1 (Table 1, 10 comparisons in last two columns), there were no instances of significant positive spatial correlation between illusory contour domains and real oblique orientation domains. Thus it is unlikely that illusory component maps were an artifactual consequence of insufficient ‘nulling’ of contributions from real inducing lines. In addition, maps obtained from subtraction of different randomly positioned oblique line segments did not produce significant differential response, demonstrating that the illusory contour signal did not result merely from the presence of line ends (see also Fig. 10). Neither were these signals due to differential motion since line segments were moved along the inducing real line orientation in both illusory conditions. We therefore attribute these activations as responses to illusory contours.

These data thus suggest that the activation pattern in V1 during illusory contour stimulation is reversed relative to that during real line stimulation, a pattern we term ‘activation reversal’. We will examine in a later part of this paper whether this reversal constitutes an absolute inversion in response or a relative inversion in response.

Alignment of Real and Illusory Orientation Domains in Area V2

For comparison, we also examined responses in area V2. In the macaque monkey, area V2 is located anterior to V1 on the lip and in the depths of the lunate sulcus. The portion of V2 available for imaging varies between 0 and 2 mm in antero-posterior extent. V2 cortex was sufficiently exposed for imaging in only three of six cases studied. We found a pattern of response in area V2 (Fig. 6) that was distinct from that of area V1. The orientation images obtained in response to real line stimulation in V2 were similar to those obtained previously with domain sizes of ~500 μm (Fig. 6b), larger in size than those in V1 (Ts'o et al., 1990; Roe and Ts'o, 1995; Roe and Ts'o 1997). When we imaged V2 during illusory contour stimulation (Fig. 6c), we also observed a clustering of cortical activation in difference maps. Although the magnitude of illusory response signal was smaller in general, these orientation-dependent response domains were comparable in size and spacing to real line orientation domains in V2 (Fig. 6b). Consistent with and further supporting previous electrophysiological findings in V2, we find that areas of dense activation often showed alignments between real and illusory contour domains with the same orientation preference (compare Fig. 6b with Fig. 6c, lower panels). These instances of domain alignment were accompanied by some spatial differences between real and illusory maps in V2 (e.g. Fig 6c, gray areas outside circled zones), perhaps related to the orientation of inducing real line components (Ramsden et al., 1999b).

As done for V1 analyses, we quantified the spatial overlap in V2 by calculating the statistical relationship between thresholded real and illusory maps. Of the three cases of V2 cortex studied, all exhibited a significant positive spatial correlation (P<0.001, χ2 test) between real and illusory domain maps of same orientation preference (Table 1, area V2, matching orientations data, positive indices). In the case shown in Figure 6 (Table 1, case F), the correlation index between horizontal real and horizontal illusory maps is +0.34 and between vertical real and vertical illusory maps is +0.27. As shown in Table 1, correlation indices in V2 ranged from +0.26 to +0.39, confirming significant overlap of real and illusory domains of the same orientation preference. Note that correlation indices in V2 tend to be somewhat lower than in V1 (see text below and Table 1). This may reflect a more complex organization for contour processing in V2 (Ramsden et al., 1999b). An orientation-matched correlation between real and illusory domains in V2 is consistent with (although not necessarily predicted by) previous electrophysiological findings showing that more than one-third of oriented V2 cells can have similar orientation tuning preference for oriented real line and higher order contour stimuli (Peterhans and von der Heydt, 1989; von der Heydt and Peterhans, 1989). Overall correlations between real and illusory orientation maps have been reported in area 18 of the anesthetized cat, although specific domain alignments were not compared (Sheth et al., 1996). This is the first report of such domain correlations in primate V2.

In sum (Fig. 6d), our optical imaging data demonstrate that differential illusory responses are evident in primate V2 and V1. These responses show characteristic and distinct alignments with real orientation domains. We find that horizontal illusory stimuli produce strongest activation in the horizontal real domains of V2. In contrast, the same horizontal illusory stimulus produces weakest activation in the horizontal real domains of V1.

Activation Reversal in V1 is Confirmed by Single Unit Electrophysiology

Given the surprising results we obtained in V1, we chose to further examine the responses of single V1 neurons to real and illusory contour stimulation using electrophysiological methods. As with our imaging recordings, we presented sequences of preferred and non-preferred (i.e. orthogonal) oriented drifting real lines or illusory contours (see Materials and Methods). Only cells with clearly oriented responses (n = 25) were considered for study. Figure 7 illustrates responses from a V1 cell with a 135° orientation preference (Fig. 7b). This cell exhibited a much stronger response to a 135° oriented line than a 45° oriented line (Fig. 7a, middle section). However, when alternating sequences of 45°/135° illusory contours were presented (Fig. 7a, left section), we obtained the opposite response pattern. The cell exhibited a greater response to a 45° illusory contour than a 135° illusory contour. Thus, when real line orientations were presented to illusory responsive cells (Fig. 7a, middle section) the strongest responses occurred at the preferred orientation. When illusory contour orientations were presented, we observed the weakest responses at the preferred orientation: i.e. an ‘activation reversal’ response pattern. These modulations were compared with spontaneous firing (Fig. 7a, right section; solid line = mean, dotted lines = ±1 SD). Indeed, when stimulated by illusory contours at the preferred real line orientation, responses could in some cases be less than mean spontaneous firing (Fig. 7a, left section). These activation patterns were observed using both small and full screen stimuli.

To quantify these observed modulatory effects, we calculated real (modr) and illusory (modi) modulation indices (Fig. 7c) for each cell when stimulated by preferred and non-preferred orientation sequences. Modulation indices range from –1 (strong activation reversal) to 0 (no modulation) to +1 (strong in-phase activation). In addition, we determined modulation indices for spontaneous activity (similarly calculated for alternating epochs, see Fig. 7a, right section) of all cells sampled, and used the mean index ± 2 SD (Fig. 7e, dotted lines) as a significance criterion. Three possible distributions are depicted in Figure 7d for real versus illusory modulation indices: uncorrelated activation (left), in-phase activation (middle) and activation reversal (right). As shown in Figure 7e, our data support the latter. Of 25 cells, 12 (48%) had illusory modulation indices exceeding those of spontaneous conditions (Fig. 7e, dotted line, mean spontaneous modulation – 2 SD). Modulation indices were negative for all of these 12 cells, demonstrating the presence of activation reversal at the level of single units. Considered as a population, these data also support the imaging results. The mean illusory modulation index was significantly below zero (i.e. the mean spontaneous index) (P = 0.01, paired t-test). The overall distribution of illusory modulation indices (mean –0.20, median –0.25, SD 0.23, range –0.68 to +0.19) tended towards negative values. Such a skewed distribution is consistent with a population response demonstrated by our imaging maps showing an activation reversal response in V1 (Fig. 7d, right).

Control Experiments

Area V1 map reversals occurred consistently across five different animal preparations during illusory processing. This suggests that they do not arise due to some chance consequence of a specific stimulus configuration selectively influencing a specific portion of cortical retinotopy. Nevertheless, we considered the possibility that the apparent illusory contour response map in V1 arose not from the higher order contour per se but rather from configurational aspects of the inducer elements themselves. For example, perhaps there was some specific interaction between the real and illusory orientation signaling that might lead to activation patterns dependent on a specific inducer angle (i.e. an inducer orientation dependence). Alternatively, due to the small size of some V1 RFs, perhaps there is an imbalance in the number of lines entering the RF during vertical versus horizontal illusory stimulation (i.e. an inducer position dependence). To investigate these possibilities we performed further control experiments.

Control Study 1: Inducer Orientation Independence

To investigate whether these illusory maps might be dependent on inducer element orientation, in three experiments we compared illusory orientation images obtained with inducing elements of different orientations (acute and obtuse). These experiments gave similar results. Figure 8 illustrates such a comparison (same case as shown in Fig. 3). Single condition orientation reference maps were first derived in response to horizontal, acute, vertical and obtuse oriented lines (cf. Fig. 3a). In Figure 8a we show illusory orientation maps obtained from the same cortex using either acute inducers (left) or obtuse inducers (right). The illusory horizontal and vertical activation zones are circled in red and black, respectively, for the acute induction condition (left); and in pink and brown, respectively, for the obtuse induction condition (right). Each illusory activation pattern bears the predicted reversed relationship with the real orientation map. When acute inducers are used, the horizontal illusory map (red outline) overlaps with the vertical real domains (blue from Fig. 3a) (Fig. 8b, top left panel). When obtuse inducers are used, the horizontal illusory domains (pink outline) also overlap with the vertical real domains (blue) (Fig. 8b, top right panel). When horizontal illusory maps obtained with acute or obtuse induction are compared directly, there is a high degree of overlap (Fig. 8b, bottom left panel, red and pink are overlapped). Figure 8c illustrates a similar relationship between the vertical illusory (black outline, acute inducers; brown outline, obtuse inducers) and horizontal real domains (orange). Thus, regions most strongly activated by real vertical are most weakly activated by illusory vertical; those most strongly activated by real horizontal are most weakly activated by illusory horizontal. These qualitative observations are also supported by spatial correlation indices (Table 2). Positive indices are obtained between orthogonal real and illusory maps, for both acute and obtuse inducers. Negative indices are obtained between matching real and illusory maps, for both acute and obtuse inducers. Thus, when inducer orientation is varied, we see no evidence of consistent change or shift of the map away from or towards the inducer orientation domains in V1. These results illustrate that the activation reversal pattern observed in V1 is predicted by the illusory contour orientation and is obtained independent of the inducer orientation.

Control Study 2: Inducer Position Independence

The interpretation of V1 responses may be complicated by the small receptive field size of V1 neurons. V2 responsiveness is more easily related to the alignment of line ends because the stimuli are designed so that each receptive field [typically 0.5–2° in size (Roe and Ts'o, 1995)] is stimulated by at least two or three sets of line ends (Peterhans and von der Heydt, 1989). At the eccentricity at which we record, the sizes of V1 cell classical receptive fields can be as small as 0.25° or less. Thus, it could be argued that some of the response modulation may be due to small differences in the precise geometry of line end positions. To examine this issue, we have studied how small shifts in the position of the illusory contour stimulus affects the response of V1 neurons.

Figure 9a illustrates a V1 cell (RF size ~0.2°) located in an obtuse orientation domain that is selective for 135° orientation. Figure 9b schematizes stimulation of this cell by acute (left panel) and obtuse (right panel) illusory contour stimuli. With this stimulus geometry, the receptive field is stimulated by two to four line ends of the illusory contour stimulus. To assess the effect of different positions of these line ends on the response of this V1 cell, we shifted the illusory contour stimulus (in four pixel offsets) such that the center of the stimulus was positioned at one of nine locations relative to the RF (Fig. 9c). Although we do not have the ability to know precisely what part of the receptive field each line end is entering, we can be sure that the cell is experiencing a slightly different stimulus geometry with each of the nine stimulus positions. Furthermore, our choice of offset and range of positions ensures that a full ‘cycle’ of inducer spacing has been sampled.

Using this approach, we repeated the experiment described in Figure 7, using alternating 45° and 135° real lines and illusory contours (Fig. 9d). The centers of both real and illusory line stimuli were similarly shifted in 4 pixel offsets. With the center of the stimulus at position 1 (Fig. 9d, top row, left), this V1 cell responds robustly to the 135° real line stimulus (unshaded epoch) and is relatively quiescent during 45° real line (shaded epoch) stimulation. Consistent with previous examples, this response pattern is reversed for illusory line stimuli (top row, right), such that a better response is obtained with 45° illusory line stimulus (shaded epoch) than with 135° illusory line stimulus (unshaded epoch). When the stimulus is moved to a different position (e.g. position 2) the response to 135° real line is slightly reduced (row 2, left), perhaps due to imprecise centering of the receptive field or to substructure within the receptive field. However, the response to illusory contours still shows a reversal at this position (row 2, right). Indeed, such a reversal is present in the remaining seven of the nine stimulus positions (lines 3–9). Differences in response magnitude are observed at different stimulus positions, both in terms of absolute response magnitude and relative preferred/non-preferred response ratio. Thus, there may be some effect of the precise stimulus geometry on the cell's response. However, in all positions the cell's orientation-selective response reverses with illusory contour stimulation. Although only one cell was mapped in such detail, these results strengthen our findings by showing that while the magnitude of response may be modulated by details of stimulation geometry, the pattern of activation reversal is not. That is, the activation reversal pattern observed in V1 is predicted by the illusory contour orientation and is obtained regardless of relative inducer position. These observations further support the activation reversals obtained with imaging.

Control Study 3: Random Line Control

Although illusory difference maps are ideal for revealing preference for one illusory stimulus over another (relative change), they are less useful for revealing the changes of activation associated with a given illusory stimulus condition (absolute change). For example, do strong illusory difference signals result from an increase in vertical domain activation, a decrease in horizontal domain activation, or a combination of both? To address this issue, we devised a difference map paradigm involving only one rather than two illusory contour stimuli. This paradigm involves subtraction of a random line stimulus from an illusory contour stimulus. At the top right of Figure 10a, we illustrate a random line stimulus where constituent real lines share the same size and orientation as the horizontal illusory stimulus and thus has identical overall line density and luminance. These random lines are also moved with identical motion along their axis of orientation. The random line stimulus differs from the illusory line stimulus only in its lack of line end alignment, and therefore lack of illusory contour percept. Thus, akin to subtracting blank from horizontal real, subtracting randomly positioned lines from horizontal illusory (Fig. 10a, right) eliminates the real component of the signal (due to orientation and motion of real line elements), leaving illusory-specific signal. In effect, this produces a difference map that discriminates signal changes associated with only one illusory contour condition.

Two random line experiments were conducted, both with similar results. One example of such a subtraction is shown in Figure 10a. Subtraction of random line response from horizontal illusory response evoked a differential map (right) that is qualitatively similar to that associated with the subtraction of vertical illusory responses from horizontal illusory response (left). Although not identical (see below), spatial overlap of these activation regions is high (compare alignment of red outlines). In both maps, dark regions (outlined in red) are associated with preferred horizontal illusory activation.

We next compared these random line subtracted maps with real orientation maps. Figure 10b illustrates that, consistent with the observations shown in Figures 3–5, horizontal illusory domains tend to overlie real vertical orientation domains (red outlines overlie blue domains) and vertical illusory domains tend to overlie real horizontal domains (black outlines overlie orange domains). Such alignments were not evident for either real acute domains (green regions in Fig. 10c) or for real obtuse domains (pink regions in Fig. 10c).

These results clarify the source of signal differences in our illusory contour maps, directly linking specific activation reversal response maps with the presence of a single illusory contour orientation. This exemplifies how the subtle rearrangement of identical oriented lines from random (‘no context’) to aligned (‘higher order context’) configurations can have a substantial and specific effect on activity distribution in V1. Indeed, absolute indices of the activation changes (–ΔR/R) following horizontal illusory stimulation (Fig. 10d) support the notion that (compared with random line responses) vertical domain activations increase in magnitude (compare blue bars, Fig. 10d) while horizontal domain activations decrease in magnitude (compare orange bars, Fig. 10d). Thus, a single illusory contour orientation can alter the balance of orientation domain response in V1, such that activity in the matching real orientation domain is relatively suppressed while activity in the orthogonal real domain is relatively enhanced.

What is the Signal? Single Condition versus Subtracted Maps

To better understand the relative changes in orientation domain activation during the processing of real and illusory contours, we next sought to compare the absolute activation levels of different stimuli (i.e. ‘single condition’ maps). Such comparisons are technically difficult because our illusory signal modulations are small relative to real orientation responses, and because single condition analyses render images more susceptible to blood vessel artifact. (In conventional orientation imaging, vessel artifacts can be reduced via ‘cocktail’ referencing methods, but this method is only appropriate for real orientation mapping, where aggregate cocktail stimulation is likely to evoke both an even and complete stimulation of the cortex in question.) To maximize the power of our single condition analysis, we therefore chose to analyze in detail the case (Case E) that gave the strongest illusory difference maps in these experiments.

To better isolate single condition illusory modulatory responses in V1, we chose a relatively vessel-free area that exhibited strong illusory difference signals (Table 1, Case E). We show single condition responses (referenced to blank stimulus) for this V1 portion in response to a range of real and illusory stimuli in the upper panels of Figure 11a. In the lower panels of Figure 11a, we show these same maps overlaid with green circles. These green circles indicate locations of real acute orientation domains (see reference maps, in bottom right insert, Fig. 11). On inspection, these single condition responses are comparable for stimuli containing acute oriented lines (illusory horizontal, illusory vertical, real acute, random lines, i.e. the first four response maps in Fig. 11a), but are not comparable for stimuli involving other orientations (last three response maps Fig. 11a). The similarity of the left four maps indicate that regardless of whether the stimulus is real or illusory, the principal response in V1 is that of real stimulus content. Although the locations of activations are largely the same in the first four conditions, we stress that there are nevertheless small differences in their relative magnitudes. We suggest that these differences comprise the components of the response which are specific to other features of the stimulus, such as illusory contour response components or line end response. These small differences are only revealed by image subtraction analyses that remove common real components.

Figure 11b shows how alignments with acute domains (green circles) change following image subtraction. At the left of this figure, we show horizontal illusory minus vertical illusory, and at the right we show horizontal illusory minus random acute lines. Instead of alignment with green circles, we find a new alignment pattern. Weakest map signals are now aligned with horizontal domains (orange) circles. Strongest map signals are now aligned with vertical domains (blue circles). This illustrates how, by canceling out real line contributions, image subtraction reveals the illusory contour modulations that are superimposed on underlying real orientation response.

Together, these single condition and difference maps show that, during the processing of the abutting line grating illusory contour, the overall balance of orientation activation in V1 is altered. The differences observed in V1 during real versus illusory contour activation comprise a shift in relative activations between different orientation domains (shown schematically in Fig. 12). To describe these shifts in relative activations, we use the terms ‘emphasis’ and ‘de-emphasis’ of particular orientation signaling. Thus, during horizontal real line stimulation, horizontal features are ‘emphasized’ because the horizontal domains are the most strongly activated. In contrast, during horizontal illusory contour stimulation, horizontal features are ‘deemphasized’ because horizontal domain activation is weakened relative to other orientation domain activations. These terms thus refer to relative activation levels and should not be confused with absolute activation or suppression.

Discussion

Our imaging and electrophysiological results show that the abutting line grating illusory contour evokes an ‘activation reversal’ response in area V1 of the macaque monkey. During real contour stimulation, the orientation of the real contour is emphasized in V1. However, during illusory contour stimulation, the orientation of the contour is de-emphasized in V1. These activation patterns are distinct from those found in V2. They persist with different inducer orientations and with different precise line end positions, and are not due merely to the presence of line ends. Our single condition analyses demonstrate that these illusory contour responses comprise a modulation of the real orientation signal in V1.

Is There an Illusory Response in Primate Area V1?

That an activation reversal response occurs in V1 is surprising. Previous electrophysiological studies report that cells co-responsive to the same real and illusory orientation are very sparse (1 of 60) in macaque V1 (von der Heydt and Peterhans, 1989). [Note that V1 cells have been shown to respond to abutting sine-wave luminance gratings, but these stimuli have luminance contrast at contour borders and are therefore not illusory by our definition (Grosof et al., 1993).] Such a sparse occurrence of illusory response cells in V1 predicts a flat activation map for illusory stimulus subtraction. That we can evoke a V1 illusory map is not, however, inconsistent with a predicted lack of illusory contour cells. We find that V1 cells can be relatively suppressed by illusory contours presented at their preferred (real) orientation. Indeed, they can also exhibit relative firing enhancements when illusory stimuli are orthogonal to their preferred orientation (e.g. Figs 7 and 9). We suggest that it is these orientation-specific modulations that evoke an activation reversal map instead of a predicted flat activation map.

Our results are not necessarily in contradiction with those of Sheth et al. (Sheth et al., 1996). However, our results lead us to draw different conclusions about the role of V1 in illusory contour processing. Using optical imaging, they demonstrated that illusory contour response maps are present in cat areas 17 and 18. Inspection of these maps do not clearly reveal activation reversals, possibly because of species differences or because of stimulus design confounds [their illusory maps may contain orthogonal real line components; see Sheth et al.'s Fig. 3 (Sheth et al., 1996)]. In cases in which real components were appropriately subtracted out [Sheth et al.'s Fig. 4 (Sheth et al., 1996)], comparisons of real and illusory maps were not made. Questions of alignment (and therefore of potential activation reversal in area 17) were not sufficiently addressed by their study, and therefore their conclusion differs significantly from ours. They suggest that illusory contour processing occurs in cat area 17 (V1), although to a weaker degree than found in area 18 (V2). Our data, recorded in anesthetized primates, also suggest the presence of illusory contour response in V1, but one that is quite different from (indeed opposite in sign to) that in V2.

Is there an illusory response in primate V1? The answer to this question rests upon the issue of what constitutes a response. Our results do show an illusory response in V1 but not one that reflects illusory orientation signaling per se. Rather, the response consists of a change in the balance between different orientation response populations in V1. We show that the balance of activation shifts away rather than towards the illusory contour orientation. The orientation of the illusory contour is thus not explicitly signaled in V1, but is instead ‘de-emphasized’.

Context-dependent V1–V2 Cooperativity

Our findings emphasize that cooperativity between and within cortical areas depends on stimulus context. When a horizontal real line is processed, horizontal domains are co-activated in V1 and V2 (Fig. 13a, upper). When a horizontal illusory contour is processed, horizontal domains are activated in V2 but are relatively suppressed in V1 (Fig. 13a, lower). In effect, illusory processing leads to a co-activation of orthogonal orientation domains in V1 and V2. That V1–V2 co-activation changes from matched to unmatched orientations suggests that the functional connectivity between these V1–V2 cell pairs also must change, either in sign or in strength. Precedence for such stimulus dependent interactions in macaque monkey has been reported (Ts'o et al., 1993; Nowak et al., 1999; Roe and Ts'o, 1999).

Our findings support the notion, already proposed from larger-scale PET and fMRI imaging, that the cortical areas operate as a distributed multi-nodal network where functional connectivity is constantly ‘reconfigured’ depending on task demands (Friston, 1998; Mesulam, 1998; Ungerleider et al., 1998). Here we show that context-dependent functional reconfigurations may also occur in very selective (orientation-specific) ways and at a finer spatial scale (sub-millimeter or columnar) than has been previously evident using fMRI or PET [but see other authors (Menon et al., 1997; Logothetis et al., 1999; Kim et al., 2000)]. Imaging at sub-millimeter resolution may thus reveal activation patterns not seen at lower spatial resolutions and may therefore be essential for proper interpretation of some multi-areal activation data. Furthermore, we have shown that de-emphasis should not be overlooked as a potential and significant signal in such functional reconfigurations (Sawaguchi, 1994; Shulman et al., 1997; Raichle, 1998; Tsunoda et al., 1999; Lewis et al., 2000).

How is the Balance of Orientation Signals in Area V1 Changed?

A change in the balance of orientation signaling could occur by a selective increase in activation of other orientation domains, by a selective decrease in activation of domains signaling that orientation, or a combination of both of these mechanisms. Our data suggests both mechanisms are at play (e.g. see Figs 7 and 10b), but the details of how this may occur in primate V1 remains unclear.

Could geniculate input and cortical circuitry within V1 alone give rise to the activation reversal map? We believe that this is unlikely. The illusory contour stimulus contains no explicit orientations orthogonal to the illusory contour. It is possible that some V1 complex cells might selectively respond to very specific configurations of line ends [e.g. via a particular sub-unit geometry (Spitzer and Hochstein, 1985; Grosof et al., 1993)]. However, such cells would suggest a mix of activation reversal and in-phase responses, which we did not observe. It is possible that V1 circuitry could collectively signal an alignment of line ends (e.g. via integration of end-stopped cell responses, via horizontal connections) and hence provide an orientation-dependent signal. However such explicit ‘grouping’ responses have not been reported in area V1 cells (von der Heydt and Peterhans, 1989). In addition, our experiments demonstrating that these activation reversals are independent of specific inducer orientation or precise position (features expected to influence V1 cell responses) suggest that these responses arise outside V1.

What other sources might give rise to activation reversal in V1? Since the activation reversal map is dependent on the signaling of an orientation that is not explicitly present in the stimulus and that we and others have shown to be signaled by V2 (von der Heydt and Peterhans, 1989; Ramsden et al., 1998; Ramsden et al., 1999a), a possible candidate is the illusory contour cell in V2. That V1 cell activity may be influenced by signals from V2 and other visual cortical areas during ‘higher-level’ vision has been suggested (Lee et al., 1998). Although feedback from V2 has been largely associated with a facilitatory modulation of area V1 (Salin and Bullier, 1995; Zipser et al., 1996; Hupé et al., 1998), some precedence for suppressive effects via feedback have been suggested by inactivation studies (Alonso et al., 1993; Bullier et al., 1996; Martinez-Conde et al., 1999; Shao and Burkhalter, 1999). Primate anatomical studies show that V2 feedback projections likely mediate excitatory action, but may target both inhibitory and excitatory V1 neurons (Rockland and Douglas, 1993). Electrophysiological and anatomical evidence suggest that V2 feedback can influence a broad range of orientation specificities (Ts'o et al., 1986; Shmuel et al., 1998; Nowak et al., 1999; Roe and Ts'o, 1999). Thus, cortical feedback could play an important role in mediating relative suppressive and facilitative effects that are both context-dependent and orientation-specific. Two possible feedback effects leading to activation reversal in single V1 neurons are illustrated in Figure 13b. However, many other feedback influences from V2 may also exist. As shown in Figure 7, not all V1 neurons exhibit activation reversal and may therefore lack or receive different feedback influences from V2. However, the net effect of all these influences is one of activation reversal.

That V2 feedback might mediate apparently opposite effects on V1 depending on stimulus may seem counter-intuitive. How could V2–V1 circuitry mediate relative facilitation of an orientation domain in one instance (real contours) and relative suppression in another instance (illusory contours)? One possibility is that there are two distinct pools of V2 cells — one pool activated only by real contours, and another activated by both real and illusory contours. If so, these separate V2 populations may have distinct feedback circuitries with different effects on orientation populations in V1. When illusory rather than real contours are presented, a different set of V2 neurons could become engaged. This, in turn, could lead to a change in balance of effect of the two parallel feedback circuitries, evoking a reversed map in V1. Although others have suggested that the balance between facilitatory and suppressive effects from V2 can indeed be stimulus dependent (Bullier et al., 1996; Hupé et al., 1998; Shao and Burkhalter, 1999), little is known about the specific circuitries that underlie feedback from V2. At this time we can therefore only speculate about possible circuit mechanisms. Further experiments will be needed to better elaborate the structural connections between V2 and V1, and how these structural connections are functionally engaged in differing stimulus conditions.

Why Multiple Cortical Representation?

Why should V1 and V2 change their patterns of co-activation during real and illusory processing? Perhaps the answer lies in a balance between the need for cortex to draw inferences about common features (e.g. A is like B) and the need to maintain sufficient distinctions (e.g. A is not like B). In some ways an illusory contour is like a real line, but in other ways it is not. Activation of illusory contour cells in V2 inherently contains ambiguity regarding real versus illusory aspects of the stimulus. Differential signaling by cortical areas in different contexts may be one mechanism that solves such perceptual dilemmas at the earliest stages of visual processing. In this scenario, the proper detection of an illusory contour results from the conjunction of signals from multiple cortical areas: one from V2, which signals the presence of a contour (whether real or illusory), in conjunction with one from V1, which signals the fact that it is not a real contour at that orientation. Both positive (what it is) and negative (what it is not) signals are necessary for identification. We thus suggest that each cortical area provides a specific (and uniquely abstracted) view of the visual world, each of which by itself is insufficient, but when considered together provides unique identification. Indeed, we suggest that the reason for multiple cortical representation is not so much for redundancy, but rather for unambiguous identification.

Together, our findings offer an explanation for apparent discrepancies between previous electrophysiological and imaging findings of contour processing in primary visual cortex. In addition, they provide a framework for a new interpretation of how V1 and V2 might work together to encode illusory contours. We propose that, even as early as area V1, cortical visual processing is mediated via a multi-areal orchestration rather than a simple hierarchical progression and that the degree to which functional domains couple and de-couple may be more closely associated with visual context than with explicit stimulus features. These ideas may be further tested with other higher order contours.

Notes

This work was supported by grants from NIH (EY11744), Whitehall and Brown-Coxe Foundations. We thank F.L. Healy for exceptional technical assistance, V. Bernardo for hardware design and manufacture, J. Pettigrew for generously providing pilot study support, and N. Daw, B. Heider, L. Nowak, A. Puce, C. Schroeder and M. Tanifuji for helpful comments during the preparation of this manuscript. We thank J. Holahan for statistical advice and helpful comments.

Address correspondence to Anna W. Roe, Section of Neurobiology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520, USA. Email: anna.roe@yale.edu.

Table 1

Orientation domain overlap in Areas V1 and V2

The table summarizes the spatial relationships between real and illusory orientation domain types. Compared domain types are shown figuratively at the top of the table. + indicates a significant (P < 0.001) overlap of domain types, – indicates a significant (P < 0.001) segregation of domain types. Numerical values are the determined coefficients of spatial association, c, which may range from +1.0 (complete overlap of real and illusory domains) to –1.0 (complete segregation of real and illusory domains). n.s. indicates a statistically insignificant (P > 0.05) or very weak (–0.2 < c < 0.2) spatial relationship. In area V2, significant overlap occurs between real and illusory domains of matching orientations. In area V1, however, significant overlap occurs between real and illusory domains of orthogonal orientations.

Figure 1.

 Real and illusory contours in visual scenes. (a) In natural visual scenes, such as this Grand Canyon vista, borders are often not explicitly distinct (e.g. mesa edge, circled, top). The arrangement of adjacent visual cues (e.g. oriented texture elements) help to infer the presence of such ‘higher order’ contours. This may be compared with borders that are defined explicitly via luminance contrast (e.g. river bank, circled, bottom). (b) In simplified visual stimuli, such as the ‘abutting line grating’ illusion, higher order illusory contours can also be inferred by the arrangement of local orientation cues (inducers). A horizontal illusory contour orientation is salient despite the absence of luminance contrast across the illusory contours. How does the visual system encode these illusory stimuli?

Figure 1.

 Real and illusory contours in visual scenes. (a) In natural visual scenes, such as this Grand Canyon vista, borders are often not explicitly distinct (e.g. mesa edge, circled, top). The arrangement of adjacent visual cues (e.g. oriented texture elements) help to infer the presence of such ‘higher order’ contours. This may be compared with borders that are defined explicitly via luminance contrast (e.g. river bank, circled, bottom). (b) In simplified visual stimuli, such as the ‘abutting line grating’ illusion, higher order illusory contours can also be inferred by the arrangement of local orientation cues (inducers). A horizontal illusory contour orientation is salient despite the absence of luminance contrast across the illusory contours. How does the visual system encode these illusory stimuli?

Figure 2.

 Stimulus configurations. (a) Illusory contour stimulus as it appears on the monitor. Left, horizontal illusory. Right, vertical illusory. For both horizontal and vertical illusory stimuli, inducing lines are moved back and forth in axis along their orientation (45° arrow), producing a percept of illusory contours moving orthogonal to their orientation (left, vertical arrow; right, horizontal arrow). Detail of stimulus geometry are shown expanded in circled regions. (b) Real contour stimuli. Left, horizontal real. Right, vertical real. Line spacings are identical to those of illusory contours shown in (a). Line motions, indicated by arrows below, identical to that perceived of illusory contours in (a). Dimensions are in degrees of visual angle (dva).

Figure 2.

 Stimulus configurations. (a) Illusory contour stimulus as it appears on the monitor. Left, horizontal illusory. Right, vertical illusory. For both horizontal and vertical illusory stimuli, inducing lines are moved back and forth in axis along their orientation (45° arrow), producing a percept of illusory contours moving orthogonal to their orientation (left, vertical arrow; right, horizontal arrow). Detail of stimulus geometry are shown expanded in circled regions. (b) Real contour stimuli. Left, horizontal real. Right, vertical real. Line spacings are identical to those of illusory contours shown in (a). Line motions, indicated by arrows below, identical to that perceived of illusory contours in (a). Dimensions are in degrees of visual angle (dva).

Figure 3.

 Optical images of orientation maps in V1. All images obtained from same field of view, Case E. (a) Single condition maps (blank subtracted, first frame analysis) in response to real lines at each of four orientations (indicated by bar in upper left corner of each image). Dark pixels indicate strong response and light pixels weak response to each condition. Colored outlines delineate pixels included in statistical analyses following low-pass filtering and thresholding (see Materials and Methods). Scale bar: 1 mm, applies to (ad). (b) Difference maps resulting from subtraction of horizontal and vertical real (left) and acute and obtuse real (right). Maps calculated using first frame analysis. Dark pixels indicate strong preference for horizontal (acute) and light pixels indicate strong preference for vertical (obtuse). (c) Left, blood vessel map of imaged region. Right, ocular dominance map derived by subtracting left eye conditions (dark pixels) from right eye conditions (light pixels). (d) Composite color-coded map of thresholded single condition maps shown in (a). Colored bars at top-left indicate corresponding orientation maps. Right, electrophysiological recordings of single unit responses from three sampled sites. Orientation tuning curves obtained in response to sequential presentation of 16 different orientations (only eight shown in axis labeling). The ordinate is time; the abscissa is the firing rate. In general, orientation preferences of recorded cells were similar to that revealed by imaging.

Figure 3.

 Optical images of orientation maps in V1. All images obtained from same field of view, Case E. (a) Single condition maps (blank subtracted, first frame analysis) in response to real lines at each of four orientations (indicated by bar in upper left corner of each image). Dark pixels indicate strong response and light pixels weak response to each condition. Colored outlines delineate pixels included in statistical analyses following low-pass filtering and thresholding (see Materials and Methods). Scale bar: 1 mm, applies to (ad). (b) Difference maps resulting from subtraction of horizontal and vertical real (left) and acute and obtuse real (right). Maps calculated using first frame analysis. Dark pixels indicate strong preference for horizontal (acute) and light pixels indicate strong preference for vertical (obtuse). (c) Left, blood vessel map of imaged region. Right, ocular dominance map derived by subtracting left eye conditions (dark pixels) from right eye conditions (light pixels). (d) Composite color-coded map of thresholded single condition maps shown in (a). Colored bars at top-left indicate corresponding orientation maps. Right, electrophysiological recordings of single unit responses from three sampled sites. Orientation tuning curves obtained in response to sequential presentation of 16 different orientations (only eight shown in axis labeling). The ordinate is time; the abscissa is the firing rate. In general, orientation preferences of recorded cells were similar to that revealed by imaging.

Figure 4.

 Optical images of area V1 cortex in response to illusory contour and real line stimulation. Data shown are from Case A. (a) Top panel, real line orientation map (horizontal minus vertical), darkest areas indicate strongest response to horizontal orientation (circled in panel below in orange over same orientation map), lightest areas indicate strongest response to vertical orientation (circled in panel below in blue). Maps calculated without first frame analysis. (b) Top panel, illusory contour orientation map (horizontal minus vertical), darkest areas indicate strongest response to horizontal orientation, lightest areas indicate strongest response to vertical orientation. Bottom panel, same illusory contour orientation map overlaid with demarcated real orientation domains from (a). In V1, strong horizontal real domains (orange circles) overlay strongest vertical illusory domains (lightest shaded areas). Conversely, strong vertical real domains (blue circles) overlay strongest horizontal illusory domains (darkest shaded areas). Maps calculated without first frame analysis. (c) Blood vessel pattern landmarks. (d) Ocular dominance map, confirming that the imaged area is V1 cortex. Darkest areas indicate strongest left eye responses.

Figure 4.

 Optical images of area V1 cortex in response to illusory contour and real line stimulation. Data shown are from Case A. (a) Top panel, real line orientation map (horizontal minus vertical), darkest areas indicate strongest response to horizontal orientation (circled in panel below in orange over same orientation map), lightest areas indicate strongest response to vertical orientation (circled in panel below in blue). Maps calculated without first frame analysis. (b) Top panel, illusory contour orientation map (horizontal minus vertical), darkest areas indicate strongest response to horizontal orientation, lightest areas indicate strongest response to vertical orientation. Bottom panel, same illusory contour orientation map overlaid with demarcated real orientation domains from (a). In V1, strong horizontal real domains (orange circles) overlay strongest vertical illusory domains (lightest shaded areas). Conversely, strong vertical real domains (blue circles) overlay strongest horizontal illusory domains (darkest shaded areas). Maps calculated without first frame analysis. (c) Blood vessel pattern landmarks. (d) Ocular dominance map, confirming that the imaged area is V1 cortex. Darkest areas indicate strongest left eye responses.

Figure 5.

 Quantitative analysis of real line and illusory contour domain distributions in area V1. (a) Single condition orientation maps for real line stimulation. Darkest areas indicate strongest activations, lightest areas indicate weakest responses. Suprathreshold activations (see Materials and Methods) are demarcated in orange, blue and green for horizontal, vertical and acute (45°) orientations, respectively. (b) Difference map for real stimulation. Horizontal and vertical responses were subtracted (top panel). Darkest areas indicate strongest horizontal real response and lightest areas indicate strongest vertical real response (scale, right, reflectance change –ΔR/R). Lower panel, spatially filtered real map. (c) Difference map for illusory stimulation. Horizontal and vertical illusory responses were subtracted to reveal illusory components (top panel). Darkest areas indicate strongest horizontal illusory response and lightest areas indicate strongest vertical illusory response (scale, right, reflectance change –ΔR/R). Although illusory subtraction responses are weaker than real subtraction responses (c.f. (b) top panel, and note different scaling), differential signal is qualitatively evident (e.g. domains circled in red). Domains are enhanced after spatial filtering (middle panel). Suprathreshold horizontal and vertical responses of enhanced map are demarcated in red and black, respectively (lower panel). (d) Overlay of demarcated domains for all real and illusory orientation maps shown in (a). In V1, strong horizontal real domains (orange areas) tend to overlay strongest vertical illusory domains (black outlines). Conversely, strong vertical real domains (blue areas) tend to overlay strongest horizontal illusory domains (red outlines). Data shown in (ad) are from Case A. (e) Overlay map for a second monkey V1 cortex case (Case C), demonstrating similar patterns of spatial correlations. All maps calculated using first frame analysis. Scale bars, 1 mm.

Figure 5.

 Quantitative analysis of real line and illusory contour domain distributions in area V1. (a) Single condition orientation maps for real line stimulation. Darkest areas indicate strongest activations, lightest areas indicate weakest responses. Suprathreshold activations (see Materials and Methods) are demarcated in orange, blue and green for horizontal, vertical and acute (45°) orientations, respectively. (b) Difference map for real stimulation. Horizontal and vertical responses were subtracted (top panel). Darkest areas indicate strongest horizontal real response and lightest areas indicate strongest vertical real response (scale, right, reflectance change –ΔR/R). Lower panel, spatially filtered real map. (c) Difference map for illusory stimulation. Horizontal and vertical illusory responses were subtracted to reveal illusory components (top panel). Darkest areas indicate strongest horizontal illusory response and lightest areas indicate strongest vertical illusory response (scale, right, reflectance change –ΔR/R). Although illusory subtraction responses are weaker than real subtraction responses (c.f. (b) top panel, and note different scaling), differential signal is qualitatively evident (e.g. domains circled in red). Domains are enhanced after spatial filtering (middle panel). Suprathreshold horizontal and vertical responses of enhanced map are demarcated in red and black, respectively (lower panel). (d) Overlay of demarcated domains for all real and illusory orientation maps shown in (a). In V1, strong horizontal real domains (orange areas) tend to overlay strongest vertical illusory domains (black outlines). Conversely, strong vertical real domains (blue areas) tend to overlay strongest horizontal illusory domains (red outlines). Data shown in (ad) are from Case A. (e) Overlay map for a second monkey V1 cortex case (Case C), demonstrating similar patterns of spatial correlations. All maps calculated using first frame analysis. Scale bars, 1 mm.

Figure 6.

 Optical images of area V2 cortex in response to illusory contour and real line stimulation. Data shown are from Case F. (a) Blood vessel pattern landmarks (top), and ocular dominance map (bottom) showing termination of dominance columns at V1/V2 border. The yellow box demarcates portion of V2 imaged in (bc). (b) Top panel, real line orientation map (horizontal minus vertical), darkest areas indicate strongest response to horizontal orientation, lightest areas indicate strongest response to vertical orientation. Bottom panel, real line orientation map with selected strong orientation domains demarcated in orange (horizontal) and blue (vertical). (c) Top panel, illusory contour orientation map (horizontal minus vertical), darkest areas indicate strongest response to horizontal orientation, lightest areas indicate strongest response to vertical orientation. Bottom panel, illusory contour orientation map overlaid with demarcated real orientation domains from (b), indicating qualitative similarity of illusory contour and real line domain organization in area V2. Colored bars signify contour orientation. Black scale bars, 1 mm. (d) Overlay of demarcated domains for all real and illusory orientation maps shown for cortical region shown in (b) and (c). In V2, strong horizontal real domains (orange areas) can show alignments with strongest horizontal illusory domains (red outlines). Conversely, strong vertical real domains (blue areas) can align with strongest vertical illusory domains (black outlines). These alignments are opposite to that which is found in V1. (e) Summary of responses in V1 and V2. When a horizontal illusory stimulus is processed by V2, the strongest responses coincide with horizontal real domains. However, when a horizontal illusory stimulus is processed by V1, the weakest responses coincide with horizontal real domains. Black scale bars, 1 mm.

Figure 6.

 Optical images of area V2 cortex in response to illusory contour and real line stimulation. Data shown are from Case F. (a) Blood vessel pattern landmarks (top), and ocular dominance map (bottom) showing termination of dominance columns at V1/V2 border. The yellow box demarcates portion of V2 imaged in (bc). (b) Top panel, real line orientation map (horizontal minus vertical), darkest areas indicate strongest response to horizontal orientation, lightest areas indicate strongest response to vertical orientation. Bottom panel, real line orientation map with selected strong orientation domains demarcated in orange (horizontal) and blue (vertical). (c) Top panel, illusory contour orientation map (horizontal minus vertical), darkest areas indicate strongest response to horizontal orientation, lightest areas indicate strongest response to vertical orientation. Bottom panel, illusory contour orientation map overlaid with demarcated real orientation domains from (b), indicating qualitative similarity of illusory contour and real line domain organization in area V2. Colored bars signify contour orientation. Black scale bars, 1 mm. (d) Overlay of demarcated domains for all real and illusory orientation maps shown for cortical region shown in (b) and (c). In V2, strong horizontal real domains (orange areas) can show alignments with strongest horizontal illusory domains (red outlines). Conversely, strong vertical real domains (blue areas) can align with strongest vertical illusory domains (black outlines). These alignments are opposite to that which is found in V1. (e) Summary of responses in V1 and V2. When a horizontal illusory stimulus is processed by V2, the strongest responses coincide with horizontal real domains. However, when a horizontal illusory stimulus is processed by V1, the weakest responses coincide with horizontal real domains. Black scale bars, 1 mm.

Figure 7.

 Single unit activity in V1 during real line, illusory contour and blank screen stimulus presentations. (a) Time series histogram showing changes in firing rates during consecutive epochs of real and illusory stimulation at preferred (135°) and non-preferred (45°) orientations. During real line stimulation (middle panel), strongest responses occur at the preferred orientation. However, during illusory contour stimulation (left panel) weakest responses occur at the preferred (real line) orientation. The weakest illusory responses can be substantially less than mean spontaneous firing rates (right panel), suggesting suppressive modulatory processes. Spontaneous activity variance (mean ± 1 SD) is indicated by dotted lines. (b) Receptive field and real line orientation tuning responses for V1 cell described in (a). Preferred orientation is 135°. (c) Modulation indices (modi, modr) were determined for V1 cells (n=25) from mean spike counts for preferred (tP) and non-preferred (tN) stimulus epochs. (d) Hypothetical distributions of cell modulation indices that we predicted would arise if real and illusory spike firing modulations showed uncorrelated (left), in-phase (middle) or reversed (right) activation patterns. (e) Significant illusory modulations (modi < –0.2, or modi > 0.2) were negative, supporting an ‘activation reversal’ pattern for the V1 cell population sampled, i.e. when illusory contours are shown at the preferred real orientation, responses are not optimal but instead are relatively suppressed. Modulation indices for illusory responses (modi, dots) and spontaneous activity (mods, crosses). Dotted line, ±2 SD of mods. In cases where orientation maps were also obtained, single-cell orientation preference was generally consistent with that shown by the orientation map.

Figure 7.

 Single unit activity in V1 during real line, illusory contour and blank screen stimulus presentations. (a) Time series histogram showing changes in firing rates during consecutive epochs of real and illusory stimulation at preferred (135°) and non-preferred (45°) orientations. During real line stimulation (middle panel), strongest responses occur at the preferred orientation. However, during illusory contour stimulation (left panel) weakest responses occur at the preferred (real line) orientation. The weakest illusory responses can be substantially less than mean spontaneous firing rates (right panel), suggesting suppressive modulatory processes. Spontaneous activity variance (mean ± 1 SD) is indicated by dotted lines. (b) Receptive field and real line orientation tuning responses for V1 cell described in (a). Preferred orientation is 135°. (c) Modulation indices (modi, modr) were determined for V1 cells (n=25) from mean spike counts for preferred (tP) and non-preferred (tN) stimulus epochs. (d) Hypothetical distributions of cell modulation indices that we predicted would arise if real and illusory spike firing modulations showed uncorrelated (left), in-phase (middle) or reversed (right) activation patterns. (e) Significant illusory modulations (modi < –0.2, or modi > 0.2) were negative, supporting an ‘activation reversal’ pattern for the V1 cell population sampled, i.e. when illusory contours are shown at the preferred real orientation, responses are not optimal but instead are relatively suppressed. Modulation indices for illusory responses (modi, dots) and spontaneous activity (mods, crosses). Dotted line, ±2 SD of mods. In cases where orientation maps were also obtained, single-cell orientation preference was generally consistent with that shown by the orientation map.

Figure 8.

 Illusory response in V1 is not dependent on inducer orientation. (a) Above, stimulus condition subtraction. Top panels, horizontal minus vertical illusory maps obtained with acute inducers (left) and with obtuse inducers (right). Middle panels, horizontal illusory domains (darkest pixels after low-passing and thresholding) are outlined in red (left) and in pink (right). Bottom panels, red (left) and pink (right) outlines indicate horizontal illusory domains; black (left) and brown (right) outlines indicate vertical illusory domains. Right, scale, reflectance change –ΔR/R. (b) Top panels, horizontal illusory domains obtained with acute (left, red outlines) and obtuse (right, pink outlines) inducers superimposed over real vertical (blue) domains (same as shown in Fig. 3). Bottom panel, direct superposition of these domains (panel below) further demonstrates the similarity of these maps (red and pink). Note that strongest horizontal illusory domains are also the weakest vertical illusory domains; thus strongest vertical real domains overlie the weakest vertical illusory domains. (c) Top panels, vertical illusory domains obtained with acute (left, black outlines) and obtuse (right, brown outlines) inducers superimposed over real horizontal (orange) domains (same as shown in Fig. 3). Bottom panel, direct superposition of these domains (panel below) further demonstrates the similarity of these maps (black and brown). Note that strongest vertical illusory domains are also the weakest horizontal illusory domains; thus strongest horizontal real domains overlie the weakest horizontal illusory domains. Data shown are from Case E.

 Illusory response in V1 is not dependent on inducer orientation. (a) Above, stimulus condition subtraction. Top panels, horizontal minus vertical illusory maps obtained with acute inducers (left) and with obtuse inducers (right). Middle panels, horizontal illusory domains (darkest pixels after low-passing and thresholding) are outlined in red (left) and in pink (right). Bottom panels, red (left) and pink (right) outlines indicate horizontal illusory domains; black (left) and brown (right) outlines indicate vertical illusory domains. Right, scale, reflectance change –ΔR/R. (b) Top panels, horizontal illusory domains obtained with acute (left, red outlines) and obtuse (right, pink outlines) inducers superimposed over real vertical (blue) domains (same as shown in Fig. 3). Bottom panel, direct superposition of these domains (panel below) further demonstrates the similarity of these maps (red and pink). Note that strongest horizontal illusory domains are also the weakest vertical illusory domains; thus strongest vertical real domains overlie the weakest vertical illusory domains. (c) Top panels, vertical illusory domains obtained with acute (left, black outlines) and obtuse (right, brown outlines) inducers superimposed over real horizontal (orange) domains (same as shown in Fig. 3). Bottom panel, direct superposition of these domains (panel below) further demonstrates the similarity of these maps (black and brown). Note that strongest vertical illusory domains are also the weakest horizontal illusory domains; thus strongest horizontal real domains overlie the weakest horizontal illusory domains. Data shown are from Case E.

Figure 10.

 Random line control. (a) Left, illusory horizontal minus illusory vertical map with thresholded horizontal illusory domains circled in red below. Right, illusory horizontal minus random line map with thresholded horizontal illusory domains circled in red below. (b) Top panel, strongest horizontal illusory domains [red outlines, same as in (a)] overlie vertical real domains (blue). Bottom panel, weakest horizontal illusory domains (black outlines) overlie horizontal real domains (orange). (c) Top panel, strongest horizontal illusory domains (red outlines) show no consistent relationship with either acute real (green) or obtuse real (pink) domains. Neither do weakest horizontal illusory domains (black outlines) show any consistent relationship with either acute real (green) or obtuse real (pink) domains. (d) How alignment of line ends affects response in V1 as measured by magnitude of reflectance change –ΔR/R (abscissa). Activation by random line stimulus (graph, left) is similar in real horizontal (orange bar, A) and real vertical (blue bar, B) domains. Activation by illusory horizontal domains (graph, right), in contrast, suppresses activation in horizontal real (orange, A) domains and enhances activation in vertical real (blue, B) domains.

Figure 10.

 Random line control. (a) Left, illusory horizontal minus illusory vertical map with thresholded horizontal illusory domains circled in red below. Right, illusory horizontal minus random line map with thresholded horizontal illusory domains circled in red below. (b) Top panel, strongest horizontal illusory domains [red outlines, same as in (a)] overlie vertical real domains (blue). Bottom panel, weakest horizontal illusory domains (black outlines) overlie horizontal real domains (orange). (c) Top panel, strongest horizontal illusory domains (red outlines) show no consistent relationship with either acute real (green) or obtuse real (pink) domains. Neither do weakest horizontal illusory domains (black outlines) show any consistent relationship with either acute real (green) or obtuse real (pink) domains. (d) How alignment of line ends affects response in V1 as measured by magnitude of reflectance change –ΔR/R (abscissa). Activation by random line stimulus (graph, left) is similar in real horizontal (orange bar, A) and real vertical (blue bar, B) domains. Activation by illusory horizontal domains (graph, right), in contrast, suppresses activation in horizontal real (orange, A) domains and enhances activation in vertical real (blue, B) domains.

Figure 11.

 Comparison of single condition maps. (a) Single condition maps to stimulus configurations shown above. Below are shown the same maps with acute domain activations (green circles) overlaid (see inset). Left four stimuli are composed of acute real lines (horizontal illusory with acute inducers, vertical illusory with acute inducers, random acute lines, and acute real lines). The four maps obtained from these stimuli exhibit similar organizations (compare green overlays below). Right three stimuli do not have any acute real line content and resulting maps are different from the real acute map (see overlays below). Bottom, checks indicate alignment, crosses indicate lack of alignment with green circles. Right, scale, reflectance change –ΔR/R. (b) Subtraction eliminates common acute signal. Horizontal illusory minus vertical illusory map (left) and horizontal illusory minus random line map (right). Below, each of these two maps is shown repeatedly with each of four real orientations overlaid (colored circles). In each subtraction, we see that by eliminating common acute signal, the alignment with horizontal real (orange) and vertical real (blue) is revealed (checked images). Inset: single condition orientation maps for a region of V1 (blood vessel map shown in bottom panel). Colored circles indicate approximate positions of activation domains in each map. These circles are only meant as guides for qualitative inspection of alignment; their placements were not quantitatively determined. Scale bar: 1 mm.

Figure 11.

 Comparison of single condition maps. (a) Single condition maps to stimulus configurations shown above. Below are shown the same maps with acute domain activations (green circles) overlaid (see inset). Left four stimuli are composed of acute real lines (horizontal illusory with acute inducers, vertical illusory with acute inducers, random acute lines, and acute real lines). The four maps obtained from these stimuli exhibit similar organizations (compare green overlays below). Right three stimuli do not have any acute real line content and resulting maps are different from the real acute map (see overlays below). Bottom, checks indicate alignment, crosses indicate lack of alignment with green circles. Right, scale, reflectance change –ΔR/R. (b) Subtraction eliminates common acute signal. Horizontal illusory minus vertical illusory map (left) and horizontal illusory minus random line map (right). Below, each of these two maps is shown repeatedly with each of four real orientations overlaid (colored circles). In each subtraction, we see that by eliminating common acute signal, the alignment with horizontal real (orange) and vertical real (blue) is revealed (checked images). Inset: single condition orientation maps for a region of V1 (blood vessel map shown in bottom panel). Colored circles indicate approximate positions of activation domains in each map. These circles are only meant as guides for qualitative inspection of alignment; their placements were not quantitatively determined. Scale bar: 1 mm.

Figure 12.

 Schematized illustration of relative activations of different orientation domains during horizontal real (a), acute real (b), horizontal illusory (c) and vertical illusory (d) contour stimulation. Orientation domains are color-coded as shown by colored bars at right. Maps (bd) exhibit similar activations of acute (green) domains, but differ in their relative horizontal (orange)/vertical (blue) activations. These differences may be attributed to the illusory contour content of the stimulus. (e) Horizontal illusory minus vertical illusory eliminates common acute (green) signal and accentuates vertical real (blue) and horizontal real (orange) differences.

Figure 12.

 Schematized illustration of relative activations of different orientation domains during horizontal real (a), acute real (b), horizontal illusory (c) and vertical illusory (d) contour stimulation. Orientation domains are color-coded as shown by colored bars at right. Maps (bd) exhibit similar activations of acute (green) domains, but differ in their relative horizontal (orange)/vertical (blue) activations. These differences may be attributed to the illusory contour content of the stimulus. (e) Horizontal illusory minus vertical illusory eliminates common acute (green) signal and accentuates vertical real (blue) and horizontal real (orange) differences.

Figure 13.

 Context-dependent signaling of orientation in V1 and V2. (a) Matching orientation domains in V1 and V2 are co-activated by real horizontal contours (above). With illusory horizontal contours (below), V2 horizontal orientation domains are activated and V1 horizontal orientation domains relatively suppressed. Thus, these V1/V2 horizontal orientation domains that are functionally coupled during real contour processing become uncoupled during illusory contour processing. (b) Change in balance of orientation activation in V1 may be due to feedback from V2. During illusory contour processing, such feedback could directly or indirectly cause a suppression of horizontal domains in V1 and/or an enhancement of orientations away from horizontal.

Figure 13.

 Context-dependent signaling of orientation in V1 and V2. (a) Matching orientation domains in V1 and V2 are co-activated by real horizontal contours (above). With illusory horizontal contours (below), V2 horizontal orientation domains are activated and V1 horizontal orientation domains relatively suppressed. Thus, these V1/V2 horizontal orientation domains that are functionally coupled during real contour processing become uncoupled during illusory contour processing. (b) Change in balance of orientation activation in V1 may be due to feedback from V2. During illusory contour processing, such feedback could directly or indirectly cause a suppression of horizontal domains in V1 and/or an enhancement of orientations away from horizontal.

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