It is known that neurons in area V2 (the second visual area) cansignal the orientation of illusory contours in the primate. Whetherarea V1 (primary visual cortex) can signal illusory contourorientation is more controversial. While some electrophysiologystudies have ruled out illusory signaling in V1, other reports suggestthat V1 shows some illusory-specific response. Here, using opticalimaging and single unit electrophysiology, we report that primate V1does show an orientation-specific response to the ‘abutting linegrating’ illusory contour. However, this response does not signal anillusory contour in the conventional sense. Rather, we find thatillusory contour stimulation leads to an activation map that, afterappropriate subtraction of real line signal, is inversely related to thereal orientation map. The illusory contour orientation is thusnegatively signaled or de-emphasized in V1. This ‘activation reversal’is robust, is not due merely to presence of line ends, is not dependenton inducer orientation, and is not due to precise position of line endstimulation of V1 cells. These data suggest a resolution for previousapparently contradictory experimental findings. We propose that thede-emphasis of illusory contour orientation in V1 may be animportant signal of contour identity and may, together with illusorysignal from V2, provide a unique signature for illusory contourrepresentation.

IntroductionVisual 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

Real and Illusory Contour Processing inArea V1 of the Primate: a CorticalBalancing Act

Benjamin M. Ramsden, Chou P. Hung and Anna Wang Roe

Section of Neurobiology, Yale University School of Medicine,

333 Cedar Street, New Haven, CT 06520, USA

Cerebral Cortex Jul 2001;11:648–665; 1047–3211/01/$4.00© Oxford University Press 2001. All rights reserved.

Figure 1. Real and illusory contours in visual scenes. (a) In natural visual scenes, suchas 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 withborders 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, higherorder illusory contours can also be inferred by the arrangement of local orientation cues(inducers). A horizontal illusory contour orientation is salient despite the absence ofluminance contrast across the illusory contours. How does the visual system encodethese illusory stimuli?

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, mainten-

ance 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 con-

secutive 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 f loating 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 con- stant 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):

modr = (r1 – r2)/(r1 + r2)

and

modi = (i1 – i2)/(r1 + r2)

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:

mods = (s1 – s2)/(r1 + r2)

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

Cerebral Cortex Jul 2001, V 11 N 7 649

design, we have taken advantage of this latter limitation. Single condition

illusory contour responses contain intrinsically significant real orienta-

tion 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.

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 illusorystimuli, 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, verticalarrow; 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 areidentical 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 visualangle (dva).

650 Contour Processing in V1 • Ramsden et al.

Thresholding

To compare the locations of imaged illusory domains with real orientation

domains, we generated thresholded maps (80th percentile, pixel histo-

gram 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:

χ2 = n[(|wz – xy| – (n/2))2]/[(w + x)(y + z)(w + y)(x + z)] (1)

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):

c = (wz – xy)/[(w + x)(x + z)], when wz ≥ xy

= (wz – xy)/[(w + x)(w + y)], when wz < xy and w ≤ z

= (wz – xy)/[(x + z)(y + z)], when wz < xy and w > z

(2)

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

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 responseto 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 (a–d). (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 strongpreference 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 bysubtracting 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 attop-left indicate corresponding orientation maps. Right, electrophysiological recordings of single unit responses from three sampled sites. Orientation tuning curves obtained in

Cerebral Cortex Jul 2001, V 11 N 7 651

can vary with different cut-offs, the sign of the coefficient value remains

robust.

ResultsWe 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 subtrac-

tion 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 inter-

pretation 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 observa-

tions 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 magni-

tude). 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 distri-

bution. 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

Figure 4. Optical images of area V1 cortex in response to illusory contour and real linestimulation. Data shown are from Case A. (a) Top panel, real line orientation map(horizontal minus vertical), darkest areas indicate strongest response to horizontalorientation (circled in panel below in orange over same orientation map), lightest areasindicate strongest response to vertical orientation (circled in panel below in blue). Mapscalculated without first frame analysis. (b) Top panel, illusory contour orientation map(horizontal minus vertical), darkest areas indicate strongest response to horizontalorientation, lightest areas indicate strongest response to vertical orientation. Bottompanel, same illusory contour orientation map overlaid with demarcated real orientationdomains from (a). In V1, strong horizontal real domains (orange circles) overlaystrongest vertical illusory domains (lightest shaded areas). Conversely, strong verticalreal domains (blue circles) overlay strongest horizontal illusory domains (darkest shadedareas). Maps calculated without first frame analysis. (c) Blood vessel patternlandmarks. (d) Ocular dominance map, confirming that the imaged area is V1 cortex.Darkest areas indicate strongest left eye responses.

652 Contour Processing in V1 • Ramsden et al.

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

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 indicatestrongest 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 indicatestrongest horizontal real response and lightest areas indicate strongest vertical real response (scale, right, reflectance change –∆R/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 horizontalillusory response and lightest areas indicate strongest vertical illusory response (scale, right, reflectance change –∆R/R). Although illusory subtraction responses are weaker than realsubtraction 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 forall 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 (a–d) are from Case A. (e) Overlay map for a second monkeyV1 cortex case (Case C), demonstrating similar patterns of spatial correlations. All maps calculated using first frame analysis. Scale bars, 1 mm.

Cerebral Cortex Jul 2001, V 11 N 7 653

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 thresh-

olded 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 orien-

tation preference. Note that correlation indices in V2 tend to be

somewhat lower than in V1 (see text below and Table 1). This

may ref lect 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 electro-

physiological 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

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) spatialrelationship. 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 orthogonalorientations.

654 Contour Processing in V1 • Ramsden et al.

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 ob-

served 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 inf luencing a specific

Figure 6. Optical images of area V2 cortex in response to illusory contour and real linestimulation. Data shown are from Case F. (a) Blood vessel pattern landmarks (top), andocular dominance map (bottom) showing termination of dominance columns at V1/V2border. The yellow box demarcates portion of V2 imaged in (b–c). (b) Top panel, real lineorientation map (horizontal minus vertical), darkest areas indicate strongest response tohorizontal orientation, lightest areas indicate strongest response to vertical orientation.Bottom panel, real line orientation map with selected strong orientation domainsdemarcated in orange (horizontal) and blue (vertical). (c) Top panel, illusory contourorientation map (horizontal minus vertical), darkest areas indicate strongest response tohorizontal orientation, lightest areas indicate strongest response to vertical orientation.Bottom panel, illusory contour orientation map overlaid with demarcated real orientationdomains from (b), indicating qualitative similarity of illusory contour and real line domainorganization 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 forcortical 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 verticalillusory domains (black outlines). These alignments are opposite to that which is foundin V1. (e) Summary of responses in V1 and V2. When a horizontal illusory stimulus isprocessed by V2, the strongest responses coincide with horizontal real domains.However, when a horizontal illusory stimulus is processed by V1, the weakest responsescoincide with horizontal real domains. Black scale bars, 1 mm.

Cerebral Cortex Jul 2001, V 11 N 7 655

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;

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 duringconsecutive epochs of real and illusory stimulation at preferred (135°) and non-preferred (45°) orientations. During real line stimulation (middle panel), strongest responses occur atthe preferred orientation. However, during illusory contour stimulation (left panel) weakest responses occur at the preferred (real line) orientation. The weakest illusory responses canbe substantially less than mean spontaneous firing rates (right panel), suggesting suppressive modulatory processes. Spontaneous activity variance (mean ± 1 SD) is indicated bydotted 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) weredetermined 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 wepredicted would arise if real and illusory spike firing modulations showed uncorrelated (left), in-phase (middle) or reversed (right) activation patterns. (e) Significant illusorymodulations (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 thepreferred 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 theorientation map.

656 Contour Processing in V1 • Ramsden et al.

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

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 withacute 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 –∆R/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 (sameas 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 strongestvertical illusory domains are also the weakest horizontal illusory domains; thus strongest horizontal real domains overlie the weakest horizontal illusory domains. Data shown are fromCase E.

Cerebral Cortex Jul 2001, V 11 N 7 657

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 rearrange-

ment 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 (–∆R/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

The table summarizes the spatial relationships between V1 response maps with different illusoryinduction angle (acute and obtuse inducers; see Fig. 8). Compared domain types are shownfiguratively. Symbols and coefficients are defined as per Table 1. Top two rows: the activationreversal response is not dependent on the induction angle. When real and illusory maps arecompared for matching stimulus orientations, there is always significant negative spatialcorrelation. However, when real and illusory maps are compared for orthogonal stimulusorientations, there is always a significant positive spatial correlation. These data indicate that astatistically similar activation reversal pattern occurs for acute and obtuse induction modes.Bottom row: when the illusory maps associated with different induction angles are compared,there is a significant positive spatial correlation matching the illusory contour orientations (the twoleft-most columns). In contrast, there is a significant negative spatial correlation for orthogonalillusory orientations. These data indicate that the illusory response maps in V1 are significantlyaligned despite the different modes of induction.

658 Contour Processing in V1 • Ramsden et al.

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 9. Illusory response in V1 is independent of precise inducer position. (a) Single unit recorded in V1. Top, composite color-coded orientation map (same as in Fig. 3d) illustratingrecording site. Below left, receptive field (pink box) with line indicating preferred orientation. Below right, orientation tuning histogram illustrating response to stimulation by orientedbars at 16 orientations (only eight shown) shows that the best orientation is at 135°. (b) Illustration of illusory contour geometry (acute illusory at left, obtuse illusory at right) withrespect to this cell’s receptive field. (c) Illusory contour is centered at nine different positions (each shifted by 4 pixel offsets) over receptive field of this V1 cell. (d) Electrophysiologicalrecordings of this cell’s responses to alternating preferred (135°) and non-preferred (45°) sequences of real (left) and illusory (right) contours. This was repeated with the stimuluscentered at each of the nine locations shown in (c). At each of the nine stimulus positions, this cell exhibits greater response to 135° real lines (left, white epochs), but is relativelysuppressed by 135° illusory contours (right, white epochs). Thus, this activation reversal is robust and is not merely due to specific number of line ends or position of line ends enteringthe cell’s receptive field.

Cerebral Cortex Jul 2001, V 11 N 7 659

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, horizon-

tal features are ‘emphasized’ because the horizontal domains

are the most strongly activated. In contrast, during horizontal

illusory contour stimulation, horizontal features are ‘de-

emphasized’ 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.

DiscussionOur 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

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 minusrandom 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 realdomains (blue). Bottom panel, weakest horizontal illusory domains (black outlines) overlie horizontal real domains (orange). (c) Top panel, strongest horizontal illusory domains (redoutlines) show no consistent relationship with either acute real (green) or obtuse real (pink) domains. Neither do weakest horizontal illusory domains (black outlines) show anyconsistent 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 reflectancechange –∆R/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 illusoryhorizontal domains (graph, right), in contrast, suppresses activation in horizontal real (orange, A) domains and enhances activation in vertical real (blue, B) domains.

660 Contour Processing in V1 • Ramsden et al.

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 f lat

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 f lat activation map.

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 contentand 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 –∆R/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 shownin 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; theirplacements were not quantitatively determined. Scale bar: 1 mm.

Cerebral Cortex Jul 2001, V 11 N 7 661

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

ref lects 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-

Figure 12. Schematized illustration of relative activations of different orientationdomains during horizontal real (a), acute real (b), horizontal illusory (c) and verticalillusory (d) contour stimulation. Orientation domains are color-coded as shown bycolored bars at right. Maps (b–d) exhibit similar activations of acute (green) domains,but differ in their relative horizontal (orange)/vertical (blue) activations. Thesedifferences may be attributed to the illusory contour content of the stimulus. (e)Horizontal illusory minus vertical illusory eliminates common acute (green) signal andaccentuates vertical real (blue) and horizontal real (orange) differences.

Figure 13. Context-dependent signaling of orientation in V1 and V2. (a) Matchingorientation domains in V1 and V2 are co-activated by real horizontal contours (above).With illusory horizontal contours (below), V2 horizontal orientation domains areactivated and V1 horizontal orientation domains relatively suppressed. Thus, theseV1/V2 horizontal orientation domains that are functionally coupled during real contourprocessing become uncoupled during illusory contour processing. (b) Change in balanceof orientation activation in V1 may be due to feedback from V2. During illusory contourprocessing, such feedback could directly or indirectly cause a suppression of horizontaldomains in V1 and/or an enhancement of orientations away from horizontal.

662 Contour Processing in V1 • Ramsden et al.

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 connect-

ivity 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 activa-

tion 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

inf luence 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 inf luenced 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 inf luence 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 inf luences 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 inf luences from

V2. However, the net effect of all these inf luences 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 orienta-

tion domain in one instance (real contours) and relative suppres-

sion 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 struc-

tural 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

Cerebral Cortex Jul 2001, V 11 N 7 663

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 imag-

ing 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.

NotesThis 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.

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