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The Journal of Neuroscience, October 1, 1999, 19(19):8560-8572
The Representation of Illusory and Real Contours in Human
Cortical Visual Areas Revealed by Functional Magnetic Resonance
Imaging
Janine D.
Mendola,
Anders M.
Dale,
Bruce
Fischl,
Arthur K.
Liu, and
Roger B. H.
Tootell
Massachusetts General Hospital Nuclear Magnetic Resonance Center,
Charlestown, Massachusetts 02129
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ABSTRACT |
Illusory contours (perceived edges that exist in the absence of
local stimulus borders) demonstrate that perception is an active
process, creating features not present in the light patterns striking
the retina. Illusory contours are thought to be processed using
mechanisms that partially overlap with those of "real"
contours, but questions about the neural substrate of these percepts
remain. Here, we employed functional magnetic resonance imaging to
obtain physiological signals from human visual cortex while subjects viewed different types of contours, both real and illusory. We sampled
these signals independently from nine visual areas, each defined by
retinotopic or other independent criteria. Using both within- and
across-subject analysis, we found evidence for overlapping sites of
processing; most areas responded to most types of contours. However,
there were distinctive differences in the strength of activity across
areas and contour types. Two types of illusory contours differed in the
strength of activation of the retinotopic areas, but both types
activated crudely retinotopic visual areas, including V3A, V4v, V7, and
V8, bilaterally. The extent of activation was largely invariant across
a range of stimulus sizes that produce illusory contours perceptually,
but it was related to the spatial frequency of displaced-grating
stimuli. Finally, there was a striking similarity in the pattern of
results for the illusory contour-defined shape and a similar shape
defined by stereoscopic depth. These and other results suggest a role
in surface perception for this lateral occipital region that includes
V3A, V4v, V7, and V8.
Key words:
neuroimaging; shape perception; stereopsis; surface
segmentation; visual cortex; lateral occipital
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INTRODUCTION |
Illusory contours are perceived
edges that typically bridge gaps between precisely aligned luminance
edges, but do not physically exist in the image. Shapes defined by
illusory contours are of special interest because they reveal
mechanisms that segment figures from their background, but are not
confounded with luminance-defined cues (Kanizsa, 1979 ; Petry and Meyer,
1987). In contrast, luminance contours can arise because of a wide
variety of factors in addition to object boundaries, such as shadows,
highlights, or internal texture. Thus, direct comparison of the
physiological response to luminance and illusory contours may reveal
brain mechanisms that contribute critically to object perception.
The mechanisms involved in illusory contour perception are thought to
overlap with those responsible for the perception of real contours, at
least partially (von der Heydt and Peterhans, 1984; Vogels and Orban,
1987; Paradiso et al., 1989; Dresp and Bonnet, 1994). Experiments in
cats and monkeys suggest that neurons in at least two visual areas, V1
and V2, carry signals related to illusory contours, and that signals in
V2 are more robust than in V1 (Redies et al., 1986; von der Heydt and
Peterhans, 1989; Grosof et al., 1993; Sheth et al., 1996). However,
such electrophysiological studies have not focused on the
representation of illusory contours in the many visual areas beyond V2.
In addition, the extent to which results depend on the exact choice of
stimuli is unclear. There may be an important distinction between
stimuli in which the illusory contour lies parallel to the inducing
edges and those in which the illusory contour lies perpendicular to the
inducing lines (Lesher and Mingolla, 1993).
Recently, functional magnetic resonance imaging (fMRI) has
furnished evidence on the neural substrates of illusory contour perception in humans (Hirsch et al., 1995a; ffytche and Zeki, 1996), but exactly which visual areas were activated remains unknown. Few functional landmarks were available in these studies to serve as
reference points. Also, none of these studies tested more than one type
of illusory contour, which makes it difficult to generalize the
findings across a range of stimuli.
It is also of interest to compare the cortical circuits activated by
shapes defined by illusory contours and by stereoscopic depth. Illusory
shapes possess implied depth ordering caused by the perceived occlusion
of inducing shapes, i.e., amodal completion. Comparing the cortical
response to implied depth with the response to actual stereoscopic
depth might indicate common regions associated with the grouping of
retinal features to reconstruct the relations between three-dimensional
surfaces in the world.
For these reasons, we collected functional magnetic resonance images of
human visual cortex during the perception of multiple types of illusory
and real contours. We designed the current experiments to address
specific questions regarding contour representation in human visual
cortex. (1) Do visual areas activated by illusory contours largely
overlap with those activated by real contours? (2) Do contours defined
by different types of illusory contours activate different cortical
regions? (3) Is there evidence for common processing of shapes defined
by illusory contours and shapes defined by stereoscopic depth?
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MATERIALS AND METHODS |
Magnetic resonance imaging
Methods were similar to those reported previously ( Tootell et
al., 1997). Subjects were scanned in a General Electric 1.5 Tesla
scanner with echoplanar imaging (Advanced NMR, Wilmington, MA).
Subjects' heads rested in a semicylindrical bilateral quadrature receive-only surface coil. After a sagittal localizing scan was obtained, one or more scans were collected to optimize (15-5 Hz; full
width at half max) the settings of four shim coils (linear x, y, z, and quadratic spherical
harmonic z) (Reese et al., 1995). Then, a T1-weighted
inversion recovery sequence [repetition time (TR), 21 sec; inversion
time (TI), 1100 msec] was used to acquire 16 contiguous 4 mm
slices with 1.5 × 1.5 mm in-plane resolution, oriented
perpendicular to the calcarine sulcus, extending posteriorly to the
occipital pole. These scans were used for anatomical registration (described below).
Next, multiple functional scans were acquired using the same slice
prescription selected in the anatomical scans with 3 × 3 mm
in-plane resolution. For each scan, 128 functional images were
collected from each of the 16 slices (2048 images), including all of
the occipital, and posterior parietal and temporal lobes. Functional
signals reflecting neural activity via local oxygen consumption and
blood flow were acquired (Kwong et al., 1992; Ogawa et al., 1992) using
an asymmetric spin echo (ASE) pulse sequence [TR, 2 sec; echo time
(TE), 70 msec; 180° refocusing pulse offset by  25 msec; matrix,
64 × 64]. For most stimulus comparisons, three functional scans
of 4 min, 16 sec duration were repeated in one scanning session
and averaged together. In the case of functional scans used to
determine the retinotopy of visual areas (see Visual Stimuli) we used
scans of 8 min, 32 sec duration (TR, 4), with all other
parameters as described above. The entire scanning procedure typically
lasted 2-3 hr, including 8-15 functional scans, except in the rare
event of equipment failure or subject discomfort. In the latter cases,
the scans were terminated prematurely.
Head movement (within and between scans) was minimized by the use of a
bite bar, in which subjects stabilized their jaw in a rigid, deep
individual dental impression, mounted in an adjustable frame. As in
previous studies (Tootell et al., 1997), the use of a bite bar
typically reduced head motion to <1 mm. Motion correction algorithms
were available (Woods et al., 1992; Jiang et al., 1995; Friston et al.,
1996) but were not necessary for the data we report here. Informed
consent was obtained from all subjects, and procedures were approved by
Massachusetts General Hospital Human Studies Protocol #90-7227.
Overall, 16 subjects participated in this study. Because of the
investment of time needed to obtain surface reconstructions of
individual brains, our subjects came from a limited pool of experienced
subjects, comprised of local colleagues and Massachusetts General
Hospital personnel. These subjects were relatively sophisticated psychophysical observers, and had a high motivation level. Although we
did not monitor eye movements, the MR data indicate adequate fixation
during each functional scan. If subjects had not maintained fixation,
we would not have obtained the retinotopically specific data we show
(see Results). Furthermore, the stimuli were simple, predictable, and
symmetric around the fixation point, so they did not produce a tendency
for eye drift (e.g., optokinetic nystagmus).
Visual stimuli
During the MR imaging experiments, the visual stimuli were
generated by a Silicon Graphics Onyx computer or a Macintosh IIvx computer with a resolution of 640 × 480 pixels. In either case, the video output was converted to a 60 Hz interlaced composite S-VHS
signal, which served as input to a Sharp 2000 color LCD projector. The
projector's image passed through a focusing lens into the bore of the
magnet, and appeared (~17.5 × 13 cm; ~40 × 30°) on a
plastic rear-projection screen (Day-tex) placed in front of the
subject's chin. The subjects viewed the screen, which was oriented
perpendicular to the long axis of their prone body, by looking straight
up at a mirror placed at an ~45° angle to both the screen and the
subject's line of sight. In this manner subjects could comfortably
view the stimulus.
All the stimuli created for this study were similar in that they
contained an achromatic single contour, arranged as a circle or square,
centered on the fixation point (Fig. 1).
Throughout each experiment, subjects fixated the center of these
figures so that contours were always approximately isoeccentric
(ranging from 1-9o). Within a scan
session, the size of all comparable stimuli remained constant. All
control and experimental comparisons were matched with respect to
luminance levels, unless that variable was being assessed directly.
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Figure 1.
Stimuli used in the experiments. An example is
shown from the experimental and from the control epoch of each stimulus
comparison. A, B, Aligned inducers
(Kanizsa) versus rotated inducers; C, D, aligned
(Kanizsa) inducers versus aligned inducers with luminance occluder;
E, F, displaced-grating illusory contour
versus nondisplaced grating; G, H, radial
displaced-grating illusory contour versus nondisplaced radial grating;
I, J, stereopsis-defined shape versus
random-dot background; K, L,
luminance-defined shape versus fixation point alone. The square
outline and shadow in I were not
present in the actual stimuli; they have been added here to clarify the
nature of the stereo-based stimuli. The scale bar indicates the size of
the stimuli, in degrees of visual angle.
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During most functional scans, subjects viewed alternating experimental
and control epochs in a two-condition, blocked design. The experimental
and control alternation always occurred at 16 sec intervals during the
4 min, 16 sec scan (eight cycles per scan). Within each epoch,
the stimuli typically alternated between two versions of the
experimental stimulus (called E1 and E2) and two versions of the
control stimulus (called C1 and C2) every 2 sec (eight times per
epoch). This alternation was usually a reversal of stimulus contrast.
This alternation within each epoch was used to prevent retinotopic
visual aftereffects and to make the stimulus more dynamic and
interesting. At least in the case of illusory contours, opposing
contrasts do not reduce or eliminate contour perception (Prazdny, 1983;
Shaply and Gordon, 1983).
Illusory contours: Kanizsa-type. Our first experiment
compared the effects of an illusory contour-defined shape with the
absence of that shape. In the experimental stimulus, four inducers
("pacmen") were aligned to create the percept of an illusory
diamond shape (Fig. 1A). In the control stimulus, the
same pacmen were rotated to disrupt the percept of that diamond shape
(Fig. 1B) (Kanizsa 1979; Hirsch et al.,
1995a). In an additional control experiment, in one subject, a
blank screen with a fixation point was interposed between the
experimental and control conditions so that the time course of the fMRI
signal could be plotted and related to the fixation baseline. We used a
diamond configuration of inducers so that any possible fMRI signal
caused by the small change in the location of inducer edges between the
two conditions could be localized relative to the vertical or
horizontal meridian representations in visual cortex. This stimulus
subtended 15.8° in maximal extent, along the vertical and horizontal
meridians. Each inducer was 3.6° in diameter, and the inducers were
separated by 8.6° (center to center) for a support ratio of 0.4 (i.e., the ratio of the portion of the illusory shape perimeter which
was defined by the luminance edges of the inducers, to the total
perimeter of the illusory shape). The sign of contrast (black on gray
vs white on gray) reversed every 2 sec. All subjects reported the
sensation of an illusory diamond shape when the inducers were aligned,
but not in the alternating epochs when the inducers were not aligned.
Two other experiments used Kanizsa-type inducers. For these experiments
we arranged the inducers to form an illusory square rather than a
diamond, to confirm that the results were not specific to the diamond
shape. One experiment compared the response to illusory squares of
varying size (each vs a rotated inducer control). In those experiments,
we compared inducer separations of 1.9, 3.8, 5.5, and 7.5° (center to
center), all with a support ratio of 0.5. The second experiment
compared an illusory square with a stimulus that was identical except
that the central square was created by actual luminance contrast (Fig.
1C,D). The contrast of the inducers and the luminance square
reversed every 2 sec. In the latter experiment, the average Michelson
contrast of the square against the background was 11%.
Illusory contours: displaced gratings. For this experiment,
the experimental stimuli were gratings with a central region displaced to form a diamond shape (Fig. 1E). The control
stimuli were standard gratings that lacked this displacement (Fig.
1F). The sign of contrast reversed every 2 sec as
described above. Three versions of the grating-based illusory contour
stimuli were used in which the line spacing was 0.5, 1, and 2°
(spatial frequencies of 2, 1, and 0.5 cycles/°, respectively). As a
further control, a radial version of the grating-based contours was
also used, with inducing lines perpendicular to the illusory circular
shape (Fig.
1G,H).
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Figure 2.
FMRI signal across time for the Kanizsa comparison
in four retinotopic areas and in the lateral occiptial region
(LOR), in subject N.K. A, The stimulus
comparison was between aligned inducers (1) and
rotated inducers (2). B, The
average time course of all the voxels that fell within the areas V1,
V2, V3, and VP (top graph) is compared with the average
time course of all the voxels that fell within the LOR (shown in
C-E) defined by activation in the stimulus comparison
shown in A (bottom graph). For both
graphs, the experimental epochs are indicated by pink,
the control epochs by green, and an interposed period of
blank screen with fixation point is labeled with white.
Visual areas V1, V2, V3, and VP show a similar-sized response to both
aligned and rotated inducers, whereas the experimentally defined region
anterior to those retinotopic areas shows a stronger response to
aligned than to rotated inducers. C-E, Regions of
cortex that respond more to the aligned inducers versus rotated
inducers are shown with a red p  10 2 to white p 106 color scale, in the right hemisphere. The
normally folded cortical surface (C) has been
inflated (D) so that sulci and gyri are equally
visible. Cortical gyri and sulci are uniformly light and
dark gray, respectively. The dotted yellow
lines in D and E show the lateral
aspect of the cut that was made to isolate the posterior pole.
E, The posterior third of the cortex is shown in
flattened format, and the scale bar indicates an approximate distance
on the cortical surface. The inflated posterior pole, which is
approximately cone-shaped in its normal folded state, has been opened
along the calcarine sulcus and unfolded. In D and
E some of the notable sulci are labeled with
abbreviations: C, central sulcus; PC,
postcentral sulcus; IP, intrapvarietal sulcus;
LO, lateral occipital sulcus; ST,
superior temporal sulcus; IT, inferior temporal sulcus;
PO, parieto-occipital sulcus; OT,
occipitotemporal sulcus; Co, collateral sulcus. The
distance scale bar (1 cm) applies to E.
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Stereopsis contours. Static red-green random dot stereograms
(RDS) (Julesz, 1971) with a dot size of 0.19° were used to create depth from binocular stereopsis (Fig. 1I,J).
In the experimental epochs, a depth-defined square (8.8 × 8.8°)
was visible at a depth nearer than background because of a disparity of
0.56°. The control epoch was a homogeneous, achromatic, random dot
field. During the stereopsis scans, subjects wore plastic glasses with
a red filter over one eye and a green filter over the other. To ensure stable binocular fusion, we omitted the 2 sec alternation, except in a
control version in two subjects. All subjects reported clear binocular
depth boundaries.
Luminance contours. These stimuli were created using Vision
Shell (MicroML) software on a Macintosh IIvx. A single circular shape
(7.7° eccentric) alternated with a homogeneous background every 16 sec (Fig. 1K,L). The sign of contrast reversed every 2 sec, as described above. The luminance-defined circle had a mean
luminance of 132.2 Foot-Lamberts and a Michelson contrast of
15%.
Ipsilateral field mapping. Additional experiments studied
the activation produced in the ipsilateral hemisphere by visual stimuli
contained in a retinotopically fixed sector (displaced by 20° of
polar angle from the vertical meridian, also avoiding a circle of
0.5° radius centered around the fixation point). This wedge-shaped
aperture contained colored images of recognizable scenes and objects
(Tootell et al., 1998a).
Retinotopic mapping. This study took advantage of previously
reported methods developed for mapping retinotopic areas with slowly
moving phase-encoded stimuli comprised of counterphasing luminance
checks (DeYoe et al., 1994, 1996; Engel et al., 1994, 1997;
Sereno et al., 1995; Tootell et al., 1997; Hadjikhani et al., 1998).
Very briefly, we used stimuli that systematically map either visual
field polar angle or eccentricity during paired but separate scans. The
data from these paired scans was combined to yield field sign maps in
which visual area borders were made visible. Visual area naming
conventions are as described in Tootell et al. (1998) and are
consistent with previous retinotopic studies. The superior portions of
V1, V2, and V3, contain representations of the contralateral lower
visual field, whereas the inferior portions of V1, V2, VP, and V4v
contain representations of the contralateral upper visual field. V3A
represents both the lower and upper contralateral field. Areas V1, V2,
VP, V3, V3A, and V4v are "classical" retinotopic areas that have
been described previously. Anterior to these areas there is a
"fringe" region including V7 and V8, whose cruder retinotopy has
been demonstrated only with high-field scanning (Hadjikhani et al.,
1998). This fringe region has also been shown to be activated by both
left and right visual fields (Tootell et al., 1998a). Thus, the
evidence suggests that areas V7 and V8 lie near the end of a continuum of decreasing retinotopy and increasing receptive field sizes.
Intracortical connections between human visual areas are not yet known.
Here we presume these connections and the resultant cortical hierarchy
are similar to those shown in macaque (Felleman and Van Essen, 1991).
Conveniently, the hierarchical levels of cortical areas V1, V2, V3/VP,
V3A/V4v, V7/V8, and MT are approximately consistent with their cortical
location, running from posterior to anterior, respectively. Thus, we
use the terms "lower-tier" and "higher-tier" to refer to
general positions in the presumptive human hierarchy.
Retinotopic maps were obtained from all of our 16 subjects sufficient
to discriminate the borders of these areas. For individual subject
analysis, the borders from each subject's field sign map were
extracted and overlaid on the activation patterns produced by other
stimuli (Fig. 3B,C). We also
used the field sign maps to define regions of interest for the
across-subject analysis described later in this section.
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Figure 3.
Relation of illusory contour signals to the
borders of visual areas and other functional landmarks on the flattened
cortical surface from subject B.K. A, The field sign map
is shown, including the classically retinotopic areas (V1, V2, V3/VP,
V3A, and V4v) in the left hemisphere. The left hemisphere has been
left-right reversed to aid comparison with other figures. Areas colored
dark blue represent the visual field in its normal
polarity, whereas areas colored yellow represent a
mirror-reversed visual field. Also indicated in A
(green) is the activation obtained (above a
significance threshold of p = 102) in a previous experiment that labeled
bilaterally responsive cortex sensitive to naturalistic scenes of
objects and landscapes (Tootell et al., 1998a), as well as the
activation acquired in another experiment that labeled the
motion-sensitive area MT+ (Tootell et al., 1995) (light
blue, significance threshold of p = 102). B shows the extent of
activation produced by a luminance contour compared with the uniform
gray control stimulus. Functional landmarks from the same subject have
been overlaid. Horizontal meridian representations are drawn with
solid lines; vertical meridians are shown by
dotted lines. Area MT+ and the anterior border of the
bilaterally labeled region are indicated with dashed
lines. Other conventions are as described in previous figures.
B shows regions of cortex that respond more to aligned
inducers than to rotated inducers. The overlap between
this region and the bilateral cortex shown in A is
extensive. The comparison between B and C
shows that the luminance contour activated the lower-tier retinotopic
areas more strongly than the illusory contours.
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Cortical surface reconstruction
Details of the cortical surface analysis have been described
elsewhere (Dale and Sereno, 1993; Dale et al., 1999; Fischl et al.,
1999). Briefly, brain reconstruction was begun by collecting whole-head
Siemens magnetization-prepared rapid gradient-echo (MP-RAGE)
scans (1 × 1 × 1 mm), optimized for contrast between gray
and white matter, for each subject. Voxels containing white matter in
an intensity-normalized volume were labeled using an anisotropic planar
filter. A region-growing algorithm was then used to ensure that each
cortical hemisphere was represented by a single connected component
with no interior holes. The surfaces of these components were
tessellated (~150,000 vertices), refined against the MRI data using a
deformable template technique, and manually inspected for topological
defects, i.e., departures from spherical topology. In a separate step,
the cortical surface was computed by expanding the gray-white surface
by 3 mm and refining it against the MR data. The sampled functional
signal included most of cortical gray matter, but it was centered just
above the gray-white boundary to avoid the pial surface where
macrovascular fMRI artifacts are greatest, and to ensure that
functional signals were assigned to the correct sulcal bank.
The surface reconstructions of the subjects' brains were
"inflated" by an iterative algorithm that reduced local curvature while approximately preserving local areas and angles. Flattened patches of cortex were obtained by "cutting off" the posterior third of cortex from the inflated hemispheres and making an additional cut (i.e., disconnection of vertices) along the fundus of the calcarine
fissure (Fig. 2D,E). These cortical
patches were flattened with a relaxation algorithm that minimized
linear and angular distortion. Residual linear and angular distortion
varies across the flattened surface (Sereno et al., 1995; Tootell et
al., 1997), but recent analyses indicate that residual distortion
averages only ~10% (Fischl et al., 1998).
Functional MR data analysis
Individual subjects analysis. The MR data acquired
for three-dimensional surface reconstruction was used to register
anatomically the T1-weighted echoplanar imaging inversion
recovery scans (1.5 × 1.5 × 4 mm resolution) that were
obtained for the functional scans. The two data sets were manually
aligned by direct iterative comparisons of the coronal, horizontal, and
sagittal planes. Once the optimal registration was achieved, the same
registration matrix was applied to the functional data to align them
with the reconstructed cortical surface. For cortical inflating and
flattening, the lower resolution functional data (3 × 3 × 4 mm) was smoothly interpolated onto the high-resolution surface reconstruction.
For each functional scan, a Fourier analysis was done on the time
series of each voxel. For two-condition comparisons, significance values were computed for each voxel by performing an F test
on the ratio of the signal at the stimulus cycle frequency (eight cycles per scan) compared to all other nonharmonic frequencies between
3 and 64 cycles per scan, excluding ±1 cycle around the stimulus
frequency. Excluding cycle frequencies <3 helps to remove baseline
drift, and head motion artifacts. Harmonic frequencies were excluded
because any periodic signal that is not perfectly sinusoidal will be
expressed by the sum of sine waves at its fundamental frequency and all
of its harmonics. The phase of the signal at the stimulus frequency was
used to distinguish between signal increases and decreases in the MR
signal for two-condition comparisons and to encode visual field
location in phase-mapped retinotopic experiments.
Across-subjects analysis. To generate regions of interest
(ROIs) specific to a given visual area, or part of such areas, patches of flattened cortex that corresponded to each retinotopic area were
defined based on the retinotopic field sign map for each subject. These
objectively defined borders were available for visual areas V1
(superior and inferior), V2 (superior and inferior), V3, VP, V3A, and
V4v. Given that several of our experiments produced activation
immediately adjacent to V3A and V4v, we created two additional ROIs
adjacent to these areas to encompass the newly defined crudely
retinotopic areas V7 (adjacent to V3A) and V8 (adjacent to V4v). The
eccentricity range of these ROIs was ~1-15°. For the classical
retinotopic areas (V1, V2, VP, V3, V3A, V4v) an additional analysis was
done using restricted ROIs within each visual area that included only
the eccentricities from 3 to 9o, as
assessed by retinotopic mapping of eccentricity in each subject. This
eccentricity range included the location of the isoeccentric contours
in the illusory and real contour stimuli.
We also created an ROI for area MT+. This area refers to presumptive
human area MT, but the term MT+ is used to acknowledge the possibility
that other small, adjacent motion areas are included (DeYoe et al.,
1996). This ROI was defined by taking all the cortical surface voxels
that exceeded a functional statistical threshold of p 102 included in the area MT+ defined
by our standardized stimulus comparison (low contrast motion vs
stationary) (Tootell et al., 1995). For each subject, we also created
an additional functional ROI based on the aligned (Kanizsa) inducers
versus rotated inducers experiment (see Results). Again, this ROI
consisted of all the cortical surface voxels that exceeded a
statistical threshold of p 102.
For each ROI, the time course of the fMRI signal was averaged for all
voxels. Then, the average magnitude for the experimental and control
epochs were calculated separately, and their difference was computed,
factoring in a 4 sec hemodynamic delay. These difference scores were
then averaged across subjects and analyzed statistically using
t tests, with correction for multiple comparisons. These data were also analyzed with pairwise multivariate ANOVAs to determine if the relative pattern of activation across visual areas varied for
the different stimulus comparisons.
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RESULTS |
Representation of illusory figures on single-subject flat maps
Illusory contour-defined figures: aligned (Kanizsa) inducers versus
rotated inducers
In the first experiment, we presented stimuli that either did or
did not give rise to illusory contours, but were otherwise very similar
to each other (Kanizsa, 1979; Hirsch et al., 1995a). In the
experimental stimulus, four inducers (pacmen) were aligned to create
the percept of an illusory diamond shape (Fig. 2A). In the control stimulus, the pacmen were rotated to destroy the perception of the diamond shape.
For 12 subjects, the regions of cortex that responded more to the
experimental condition than to the control condition were analyzed (44 scans; 90,112 images). Such results are shown for four representative
subjects (Figs. 2E, 3B; see
5B,D). In all but one subject (who
showed no significant signal specific to illusory contours), the
differential activation was located bilaterally, centered on the
lateral surface of the occipital lobe. The pattern of activation was an
elongated stripe centered on the lateral occipital sulcus, that tended
to become patchy toward the parietal and temporal lobes. In each of the
11 subjects, such signals were obtained from both the right and left hemispheres.
To demonstrate more explicitly the relative signal strength across
visual areas in the above comparison, we performed an additional experiment in which we repeated the comparison between aligned and
rotated inducers, with interposed epochs consisting of a fixation point
alone. This made it possible to plot a time course for those cortical
surface voxels preferentially activated by the Kanizsa stimulus (Fig.
2B). Furthermore, we can compare the signals from this statistically defined region to the locations of the known visual
areas, defined by retinotopic mapping in the same subjects. It is
evident that the region of interest, which was obtained in a separate
scan of aligned versus rotated inducers in the same subject (Fig.
2E), is distinguished by a stronger response to aligned than to rotated inducers. In contrast, lower-tier visual areas
such as V1, V2, V3, and VP show a response to both aligned and rotated
inducers that is not reliably different for individual subjects
(although small but significant differences were seen in the
across-subjects analysis described later).
We directly compared the map of retinotopic areas with the illusory
contour-related activity in each of the 12 subjects (38 scans; 77,824 images). The illusory contour signals were concentrated in the lateral
occipital region, including V7 and V8, but often extended into V3A and
V4v. The relative lack of signal in V1, V2, V3, and VP was consistent
across individual subjects, and representative cases are shown (Figs.
3B; see 5B,D).
Finally, we performed an additional control experiment to exclude the
possibility that the brain activation produced by the original Kanizsa
comparison represents a simple sensitivity to the small displacement of
inducer edges that acompanies their rotation. In this case, we compared
a stimulus like that in Figure 1B (except that all
inducers were facing left) with a similar stimulus in which each
inducer was rotated by 180° (all facing right). In this case, neither
configuration was consistent with an illusory shape. Correspondingly,
this comparison yielded no differential activation.
Luminance-defined figures
The next step was to test the extent of overlap between the
cortical regions that responded more to illusory contours, compared to
those regions that were activated by a comparable "real" contour. When we examined the brain regions that responded more to an
isoeccentric luminance-defined contour than to a homogeneous field, we
found an irregular but continuous line of activation along an
isoeccentric contour that runs perpendicular to the long axis of the
retinotopic areas, in both hemispheres of 11 subjects (Fig.
3C). In the subjects with the greatest extent of
activation, no clear difference was visible in the strength of
activation across retinotopic visual areas, although there was
variability in the extent of activation anterior to V3A and V4v. Thus,
the luminance-defined shape provided a clear contrast with the illusory
contour shape by activating all the visual areas approximately equally
(see across-subjects analysis below).
Size invariance of illusory contour response
It could be argued that lower-tier retinotopic areas were not
strongly activated by the illusory shapes because of a large mismatch
between receptive field size compared to stimulus size. Perhaps the
lateral occipital region was selectively activated simply because it
contains neurons with large receptive fields capable of bridging the
gaps (8.6°) between inducing elements. We tested this hypothesis by
comparing the extent of activation produced by edge-type (Kanizsa)
stimuli of different sizes (gap sizes of 1.9, 3.8, 5.5, and 7.5°) in
6 subjects. In comparison with the original results with gaps of
8.6°, we obtained no evidence of greater activation in the lower-tier
retinotopic areas (V1, V2, V3, and VP) (Fig.
4). The focus of maximal activation
produced by the four smaller sizes was similar to that obtained
originally. The consistency of responses over a range of stimulus
sizes fits nicely with other data, suggesting that receptive fields are
large and bilateral in this region (Tootell et al., 1998a). Similar size-invariant responses have been documented in single neuron responses in the inferotemporal region of monkey cortex (Lueschow, 1994). This property is thought to underlie the ability of monkey and
human observers to recognize objects over a wide range of stimulus
sizes.
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Figure 4.
FMRI response to illusory contour stimuli of a
common type but varying in size. A-D show flat maps of
the right posterior pole from the subject J.M. A shows a
map of phase-encoded retinotopic eccentricity along with area
boundaries derived from the field sign map. As indicated by the logo,
foveal eccentricities are labeled in red
(~0-2o), peripheral eccentricities are labeled in
green (~6-15°), and intervening eccentricities are
labeled in blue (2-6o).
B-D show the areas that responded more to the aligned
inducers than to the rotated inducer control, for three sizes of
illusory shape (3.8, 5.5, and 7.5°, respectively; see stimulus logos
in each panel). The activation patterns were remarkably consistent
across a wide variation in stimulus size. See previous figures for
other conventions.
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Aligned inducers (Kanizsa) versus aligned inducers with
luminance occluder
Based purely on the above data, it could be argued that the
results of the original Kanizsa comparison could still be caused by
factors other than the presence versus absence of an illusory shape.
Perceptually, the aligned inducer condition created an illusory closed
figure that appeared to occlude the inducers. To investigate this
effect of occlusion, we compared the original stimulus with a stimulus
in which the area of the illusory shape was filled in with an actual
luminance change (Fig. 1C,D).
The results for this test (seven subjects; 24 scans; 49,152 images)
were similar to those obtained for the original comparison, in that
greater activation was obtained for the illusory Kanizsa stimulus in
V3A, V4v, V7, and V8. However, we found two further differences. The
overall signal strength was weaker in these areas when the
luminance-occluding figure served as a control. Also, in visual areas
V1 and V2, there was greater activation during the luminance occluder
epoch than during the illusory-occluder epoch. This effect is
consistent with recordings in monkey V2 showing more vigorous single
unit responses to a luminance edge than to an illusory edge (Peterhans
and von der Heydt, 1989). This type of comparison does not allow us to
distinguish between fMRI responses to illusory (or real) contours as
opposed to surfaces, but it does suggest that the lower- versus
higher-tier areas respond with opposite "preferences" to the
luminance and illusory shapes. These conclusions are confirmed by the
across-subjects analysis described later.
Stereopsis-defined figures
Next we localized the regions that responded more to an
isoeccentric contour in depth than to a zero depth random dot display. The pattern of results for the stereo-defined shape was similar to the
illusory shape in that the activation peak was centered in the anterior
visual areas (Fig. 5A,C).
Comparison between the regions activated by the illusory
contour-defined shape and the stereopsis-defined shape indicated a
significant overlap, particularly in V3A and V7 (Fig. 5). The degree of
overlap decreased inferiorly (e.g., anterior to V4v), where the
illusory contour stimuli produced more activity than the stereo
stimuli.
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Figure 5.
Comparison of isoeccentric stereopsis-defined
contours versus illusory contours on the flattened cortical surface of
two subjects. A and B show data from one
subject (S1; J.M.), whereas C and
D show data from a second subject (S2;
T.W.). A, C, These panels show
regions of cortex that respond more to an isoeccentric shape defined by
0.56° binocular disparity compared with a zero-disparity control, in
the right hemispheres of two subjects. Visual area borders are
transposed from the field sign map in the same subjects.
B, D, These panels show regions of cortex
that respond more to an isoeccentric shape defined by aligned (Kanizsa)
inducers compared with rotated inducers. Other conventions are as
described previously. Both the stereopsis- and illusory-defined shapes
activated V3A, and the lateral occipital region anterior to it (i.e.,
to the right in this figure), to a greater degree than the lower-tier
retinotopic areas.
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Displaced versus nondisplaced gratings
Here we compared the results obtained from the Kanizsa-type
stimuli to those produced by grating-based illusory contours. These two
stimulus types have known psychophysical differences (Petry et al.,
1983; Lesher and Mingolla, 1993). Also, displaced-grating illusory
contours have been used often in physiological experiments in animals
(von der Heydt and Peterhans, 1989; Grosof et al., 1993; Sheth et al.,
1996), and these studies suggest that displaced gratings may evoke a
stronger response in lower-tier areas than the Kanizsa-type.
For this experiment, the experimental stimuli was a grating with a
central region displaced to form a diamond shape (Fig. 2E), whereas the control grating lacked this
displacement (Fig. 2F). We initially used stimuli
with a line spacing of 0.5° (2 cycles/°). As was observed for the
other illusory contour comparisons, this stimulus comparison
selectively activated the higher-tier visual areas. In addition, this
stimulus produced an isoeccentic "contour" representation in the
retinotopic areas V1, V2, V3, and VP (Fig.
6A).
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Figure 6.
Comparison of the fMRI signal produced by
grating-based illusory contours, across a range of spatial frequencies,
in subject J.M. A-C show flat maps of the left
occipital cortex in one subject. The activation maps are shown for
three spatial frequencies. The three spatial frequencies were 2, 1, and
0.5 cycles/°. The stimulus logo next to each map shows a
diamond figure, but not the stimulus background; the
actual stimuli are indicated in Figure 2. Other conventions are
described in previous figures. Signal strength is similar across
spatial frequency in the classical retinotopic areas, but increases
with decreasing spatial frequency in the lateral occiptial region
anterior to (to the right of) those areas.
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It could be argued that the activation in retinotopic areas is an
artifact caused by the Fourier energy at the orientation and location
(phase) of the illusory contours in this stimulus (Ginsburg, 1975;
Skottun, 1994). To reduce this artifact, we created two additional
versions of this stimulus, in which the line spacing was increased to 1 and 2° (1 and 0.5 cycles/°, respectively) (Fig. 6B,C). Interestingly, the resultant
signal in retinotopic areas did not decrease; instead, the differential
activation in the lateral occipital region actually increased. This
general pattern was seen in all nine subjects tested.
Another control experiment attempted to generalize the results with
grating-based contours to a case in which the illusory contour was
produced at a different angle relative to the inducing lines. In two
subjects, we repeated the experiment using radial lines that ran
perpendicular to an illusory circle (Fig.
2I,J). The results were very similar to those
obtained with the standard gratings.
The fact that the differential signal grew stronger as the number of
line terminations was reduced (lower spatial frequency) also helps to
support the conclusion that the presence of line terminations
themselves was not the primary source of activation. Furthermore, we
performed an additional control experiment to equate the presence of
line terminations in three subjects. The new control stimuli consisted
of the original displaced-grating stimuli with the line terminations
misaligned, i.e., interleaved with each other, so as not to form an
illusory contour (von der Heydt and Peterhans, 1989). The
displaced-grating experimental stimuli were unchanged. The results were
very similar to the original comparison, suggesting again that these
areas show a response to illusory contours that goes beyond the
response to line terminations per se. This trend was seen, despite the
fact that the interleaved version does not entirely eliminate the
global figure-ground segmentation.
Across-subjects analysis for isoeccentric figures
In these experiments, the stimuli were comprised of single figures
with edges that remained approximately isoeccentric at 7-9°
eccentricity. Such isoeccentric contours produced very orderly maps on
the flattened cortical surface: essentially straight lines crossing the
retinotopic isopolar lines, including the isopolar area borders. This
was consistent with earlier retinotopic evidence for an approximately
polar coordinate system, similar to that found in other species
(Schwartz, 1977). The representation of a square/diamond (rather than a
circle) produced a predictable deviation from the isoeccentric lines,
but this deviation was small because of the moderating influence of the
cortical magnification factor. It is experimentally convenient that a
single, approximately isoeccentric contour produced a single
stripe of activation that runs across the visual areas, because this
allowed for direct comparison of the activity patterns across visual
areas (Fig. 3C). Also, using just a single contour allowed
us to predict with accuracy the resulting site of activation in
retinotopic cortex.
The individual flat maps imply that certain areas lack responsiveness
to certain stimuli, (e.g., the lack of response to aligned vs rotated
inducers in lower-tier areas like V1 and V2). To test such negative
results more rigorously, we devised a strategy that allowed for data to
be averaged across subjects quantitatively. First, we created ROIs
based on nine separate visual areas (see Materials and Methods). For
each of these ROIs we calculated the average percentage of fMRI signal
change that was produced by the stimulus comparisons discussed above.
The percent signal change score for each area could then be averaged
across subjects. In areas V1, V2, VP, V3, V4v, and V3A, we also
performed a similar analysis on restricted ROIs that included only the
eccentricities from 3-9°, the
eccentricity at which the isoeccentric contours were represented. It
should be noted that the choice between larger ROIs or the restricted
(by eccentricity) ROIs involves certain tradeoffs. Because of
differences in receptive field size and retinotopic point spread across
areas, using larger ROIs may put the lower-tier retinotopic areas at a
disadvantage. Using restricted ROIs can mitigate this problem, but this
analysis was not applied to less retinotopic areas such as V7, V8, and
MT+, effectively putting them at a disadvantage.
To test for differences between the two hemispheres, we compared the
average percent signal change for all visual areas in the left
hemisphere with those in the right hemisphere, using a t
test. In all cases, the difference between left and right hemispheres
was not significant (luminance, p = 0.19; stereopsis, p = 0.72; aligned vs rotated inducers,
p = 0.32; displaced vs nondisplaced gratings,
p = 0.99).
These tests of hemispheric lateralization were particularly
interesting, because a previous study reported stronger signals in the
right hemisphere for the aligned versus rotated comparison (Hirsch et
al., 1995a). In our study, the average right hemisphere the
modulation was 0.078%, whereas that for the left hemisphere was
0.056%, but this difference was not significant. To test for hemispheric asymmetry more extensively, we measured the extent of
activation in individual subjects. For each of 11 subjects, we
determined the number of voxels that exceeded the significance threshold of p = 102
(colored red and white) separately in the right (R) hemisphere and the
left hemisphere (L). Then we calculated the mean laterality index
[(R L)/(R + L)] to be 0.13. If a higher threshold is chosen that includes the voxels >p = 105 (colored white) the mean index
increases to 0.34. The regions included at those two significance
levels can be estimated from the pseudocolor activation in Figure 5.
Thus, in individual subjects, highly thresholded data can indicate a
laterality effect that does not survive across-subject analysis.
Therefore, in the following analyses, we averaged together the percent
signal change obtained for corresponding ROIs in the left and the right hemispheres.
The across-subjects results confirmed the conclusions from individual
subject analysis (Fig. 7). Specifically,
signal changes were relatively constant across retinotopic areas for
luminance contours, but shifted anteriorly for the contours defined by
stereopsis and illusory contours. F tests confirm that
signals were greater in anterior retinotopic areas compared to the
lower-tier retinotopic areas for the stereopsis-defined figure
(F(5,50) = 4.38; p = 0.01), the aligned (Kanizsa) inducers versus rotated inducers
(F(5,55) = 7.65; p < 0.0001), and the displaced versus nondisplaced grating (F(5,40) = 7.2; p < 0.0001). The two types of illusory contours differed in that larger
signals were produced by the grating-type illusory contours in the
lower-tier retinotopic areas. Finally, there was also a significant
change across visual areas in the case of illusory versus luminance
(Kanizsa) squares (F(5,30) = 6.1;
p < 0.0005).
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Figure 7.
Comparison across subjects in the response of
individual visual areas to shapes defined by real and illusory
contours. The bar graphs in A-G show the average fMRI
signal change for individual visual areas across all subjects tested
(A-D, n = 11; E,
n = 12; F, n = 9; G, n = 7). Data from
corresponding visual areas in the left and right hemispheres areas are
averaged together. Error bars indicate SEM. Plus
signs and asterisks indicate the signal
modulations that are significantly different from zero based on
t tests at p < 0.05. Asterisks indicate modulations with p
values that survive Bonferroni correction. A-G, The
bullets with heavy error bars above each bar indicate
the increased modulation that could be detected when the regions of
interest were restricted to the 3-9o eccentricity
representation in the retinotopic areas. A, B,
Isoeccentric contours defined by luminance and stereopsis,
respectively. C, Comparison between aligned inducers and
rotated inducers. D, Grating-based illusory contour
versus nondisplaced grating control (lowest spatial frequency case).
E, Aligned inducers versus aligned inducers with
luminance occluder. F, The locations of the ROIs are
shown on the flattened cortical surface of an individual subject in
schematic form. The fMRI signals are strongest in higher-tier areas for
the stereopsis-defined shape, and the shapes defined by illusory
contours.
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Figure 7 also shows the results for the restricted ROIs within each
retinotopic area, including only the eccentricities from 3 to
9o (see bullets with heavy error bars). As
expected, the smaller regions of interest resulted in greater apparent
signal changes. This is particularly interesting when comparing results
in the aligned versus rotated inducers comparison (Fig. 7C). After all of our efforts to increase the statistical power of the data, we see
that signal changes in areas V1 and V2 increase to nonzero values. This
indicates not only that there was a small but detectable response to
the Kanizsa-type illusory shape in lower-tier visual areas, but that
the signals were retinotopically specific.
To formally test for different levels of modulation across
retinotopic visual areas, we performed several multivariate
ANOVAs with six subjects. A grand 4 × 8 ANOVA with
factors of cue (shape defined by: luminance, stereopsis, Kanizsa-type
illusory contour, and lowest spatial frequency displaced-grating
illusory contour) and visual area (V1, V2, V3, VP, V3A, V4v, V7, and
V8) was performed. The cue-by-area interaction was significant
(F(21,126) = 3.25; p = 0.0001). The equivalent analysis for restricted ROIs had a borderline
significant cue-by-area interaction in a 4 × 6 ANOVA (F(15,120) = 1.59; p = 0.08).
We followed up the significant grand ANOVA with pairwise comparisons
between all of the cues (Table 1). The
pairwise comparisons were performed for the full area retinotopic ROIs,
and the eccentricity restricted retinotopic ROIs. Because of the large
number of tests here, we also considered the effects of multiple
comparisons. We have indicated with asterisks the p values
that would survive a Bonferroni correction of 6 (the number of pairwise
comparisons in each case). We report all of the p values
because they provide a concise indication of signal strength and
variance.
The cue-by-visual area ANOVAs test for a main effect of cue, a main
effect of visual area, and their interaction. Significant main effects
of cue indicate that (averaging over all visual areas) there is a
difference in signal magnitude, which could possibly be caused by
differences in stimulus visibility. Table 1 shows that we did obtain a
few marginally significant main effects of cue, but they do not
dominate, or survive multiple-test correction, except in the case of
Kanizsa-type versus displaced-grating type illusory shape. More
importantly, we obtained two cue-by-area interactions that were clearly
significant. Such significant interactions indicate that the pattern of
response across visual areas differed across cues, even when constant
overall differences in signal strength were removed. The interactions
confirm that the signals from higher-tier areas are larger than those
in lower-tier areas for shapes defined by illusory contours. It is also
interesting that these interactions were markedly reduced in the case
of the restricted ROIs, because of the boost in signal that this
manipulation gives to the lower-tier areas. The interactions between
other pairs of cues (e.g., stereopsis vs luminance and Kanizsa-type vs
displaced-grating illusory shape) were marginally significant. The
current technique (using a 1.5 T scanner) may lack the power to detect
these interactions; future high-field scanning at 3 T should resolve
the issue.
Activation maps from individual subjects indicated that MR signals
varied with the spatial frequency of the displaced-grating illusory
shape stimuli (Fig. 6). We followed up on this observation with an
ANOVA across nine subjects (Fig.
8). A 3 × 8 ANOVA showed a
significant effect of spatial frequency
(F(2,14) = 0.047; p = 0.05), and a significant effect of visual area
(F(7,49) = 6.85; p = 0.0001), but no interaction (F(14,98) = 0.45; p = 0.95).
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Figure 8.
Analysis across subjects of variation of
Kanizsa-type stimulus size and displaced-grating stimulus spatial
frequency. A, B, Bar graphs show the
average fMRI signal change, for individual visual areas, across
subjects (A, n = 9;
B, n = 5). Corresponding visual
areas in the left and right hemispheres areas are averaged together.
Error bars indicate SEM. A, Displaced grating versus
nondisplaced grating for three spatial frequencies. ANOVA indicates a
significant effect of spatial frequency. B, Aligned
versus rotated inducers for four Kanizsa square sizes. ANOVA does not
show a significant effect of size.
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Finally, we compared the four sizes of Kanizsa squares used in
the aligned versus rotated inducer comparisons, across five subjects. A 4 × 8 ANOVA showed no significant effect of size
(F(3,12) = 1.93; p = 0.20). It is with caution that we accept this null hypothesis, but
there is 75% power to exclude a correlation between stimulus size and
MR signal  0.5 (assuming independent samples; p = 0.05, one-tailed). It would be worthwhile to address this issue again
with high-field scanning. As expected, there was a significant effect
of visual area (F(7,28) = 10.65;
p = 0.0001) and no interaction
(F(21,84) = 0.62; p = 0.89).
To describe the location of our visual area ROIs more precisely within
the cortical volume, we computed the mean Talairach coordinate for each
visual area ROI using the automated stereotaxic procedure provided by
the Montreal Neurological Institute (Collins et al., 1994). For all
ROIs, we calculated the mean Talairach coordinates of all cortical
surface vertices, then averaged the coordinates across subjects (Table
2). According to Collins et al. (1994),
the average (uncorrected) variability in location of cortical
anatomical landmarks across subjects is 7.74 ± 1.74 mm. Not
surprisingly, we see slightly higher variability for our occipital ROIs
created by purely functional specification, because coordinates likely
reflect some variation of functional location with respect to
anatomical landmarks. Also, these functional areas extend over a
relatively large cortical territory, particularly along their long
axis, so more variability is expected.
Visual field representation in the lateral occipital region
Very strong signals were produced by illusory contour stimuli in
the cortex immediately adjacent to V3A and V4v. That region of cortex
is located on the lateral occipital surface of the cortex (Figs. 2, 3),
and it is likely to contain multiple visual areas. We calculated the
mean Talairach coordinate of all statistically significant voxels for
the 11 subjects who produced activation maps for the aligned Kanizsa
inducers versus rotated inducers comparison. The coordinates were
33.2 ± 9.4, 83.7 ± 7.2, and 2.9 ± 9.5 in the left
hemisphere, and 27.4 ± 7.0, 84.7 ± 8.0, and 10.0 ± 9.1 for the right hemisphere. The exact relation between the regions of
cortex activated in this study, and the complex called "LO" in a
previous report (Malach et al., 1995) is not yet known, although some
overlap is likely. The Talairach coordinates published for LO by Malach
et al. (1995) are 42.8 ± 2.7, 72.7 ± 8, and 18.2 ± 9.8. The coordinates for LO in the Malach study are similar, but not
identical to the ones we obtained for the Kanizsa comparison. In
particular, Malach et al. (1995) obtained signals more ventrally with
their paradigm. One likely source of this difference is that Malach et
al. (1995) included recognizable objects (as well as abstract
sculpture) in their experimental epoch; the control epoch consisted of
visual textures. Several previous studies comparing recognizable
objects with various controls have localized responses in the ventral
occipital region around the fusiform gyrus (Stern et al., 1996;
Kanwisher et al., 1997; Halgren et al., 1999)
Subsequent to the completion of this study, our research group has
mapped additional retinotopic areas adjacent to V3A and V4v (V7 and V8,
respectively) fueled primarily by the availability of a new 3 Tesla
scanner (Hadjikhani et al., 1998). Although these new areas show some
degree of retinotopy, it is cruder than in the six classically
retinotopic areas (Tootell et al., 1998b). These and other results
suggest that the receptive field sizes in these regions are relatively
large (Tootell et al., 1997).
We have also demonstrated that this lateral occipital region can be
strongly driven by the ipsilateral field (Tootell et al., 1998a). For
the present study, we specifically compared (four subjects; eight
scans; 16,384 images) the area that responded to the illusory contour
comparisons with the region activated by the ipsilateral presentation
of complex natural scenes. The two activation patterns overlapped
extensively (Fig. 3A,B). Because this ipsilaterally driven
area was also activated by contralateral stimulation, we know that it
is activated bilaterally and presume that the underlying receptive
fields are bilateral.
Additional comparisons (11 subjects; 22 scans; 45,066 images) were made
to determine the relationship between the illusory contour activation
and the motion-sensitive area MT+ described previously (Watson et al.,
1993; Tootell et al., 1995). In all of the subjects, MT+ was located
anterior to the cortical regions activated by illusory contours. Thus,
the region activated by the illusory contour comparisons lies between
the most anterior classical retinotopic areas (V3A and V4v) and MT+,
and it is largely comprised of bilaterally responsive cortex. Here we
use the term LO region to refer to this lateral occiptial region.
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DISCUSSION |
By monitoring brain activity in many predefined visual areas
simultaneously, we have explored the representation of several types of
contours. Our results suggest a great deal of overlap in the visual
areas that respond to luminance, stereopsis, and illusory contours. The
visual areas we examined responded to all of the visual cues we tested,
to some degree. However, the contours defined by different cues
produced some differences as well. Significantly, illusory contours and
stereopsis-defined contours were marked by relatively high signal
changes in higher-tier cortical regions. In the following section we
discuss the neural repsonse to illusory and stereopsis-defined contours
and propose that a surface-based level of visual processing in the
lateral occipital region may be a shared feature.
The neural response to illusory contours
Our results suggest that illusory contours are processed
throughout the visual pathway, but signals are strongest in higher-tier areas, V3A, V7, V4v, and V8. The literature describing single-unit physiology in animals has shown neural responses to illusory contours in area V2, and to lesser extent, V1 (Peterhans and von der Heydt, 1989; von der Heydt and Peterhans, 1989; Grosof et al., 1993; Sheth et
al., 1996). Although our individual subject analysis did not show that
V1 or V2 neurons are activated by Kanizsa-type illusory stimuli, small
signals were seen in V1 and V2 in the most sensitive across-subjects
analysis. Furthermore, several additional factors mitigate any apparent
discrepancy with respect to previous animal experiments. (1) Most
obviously, previous single-unit studies did not test for responses to
illusory contours in areas beyond V2. A testable prediction from our
findings is that responses to illusory contours should be very strong
in macaque areas V3A and dorsal V4; (2) We may have isolated responses
specific to closed illusory contours or surfaces, as opposed to single
illusory contours; (3) Our subjects were humans, rather than macaque
monkeys; and (4) We recorded population signals, rather than specific
single units.
We demonstrated significant activation for Kanizsa-type illusory shapes
in the lower-tier retinotopic areas when we averaged across subjects,
despite the lack of response shown in the individual, thresholded
activity maps. This apparent difference is caused by the much better
signal-to-noise ratio obtained by averaging many retinotopically
restricted ROIs, compared to examining each individual activity map.
Almost all the cortical regions that were activated in single subjects
were contained within our quantitative ROIs; all such areas have at
least some degree of retinotopy (which defined the borders). Thus, in
this study the illusory contour comparisons activated primarily
retinotopic areas. One possible exception is a region in the
intraparietal sulcus that was seen as a distinct foci in several
subjects (Figs. 3B, 5B). Overall, our results
indicate a graded increase in responsiveness to illusory contour-defined shapes as one proceeds through the presumed cortical hierarchy. Luminance-defined shapes, for example, produced a different pattern, with stronger signals in lower-tier areas.
Our results indicate a larger signal in retinotopic areas in response
to displaced-grating illusory contours compared to the Kanizsa-type.
The results are consistent with the published evidence that
displaced-grating contours are more likely to drive single neurons in
V1 than the Kanizsa-type (Grosof et al., 1993; Sheth et al., 1996).
There are multiple interpretations of the difference between the two
types of illusory contours. One possibility is that the displaced
gratings produced a response to the edges of each grating per se.
However, the fact that the signals in the retinotopic areas did not
decrease when we reduced the number of inducing lines argues that the
signals reflected a response to the illusory contour itself. The
population response to displaced-grating stimuli has been studied in V1
and V2 in experimental animals (Sheth et al., 1996), and both areas
responded in an orientation-specific manner to the illusory contour,
the inducing lines, and a combination of the two, with a greater
proportional response to the illusory contour in V2 than in V1. Because
of the local discontinuities present in the displaced gratings, our
Kanizsa-type comparisons may be a purer test for illusory contour representation.
Our results are consistent with the results of previous human
neuroimaging work using illusory contours that reported extrastriate activation loci for (Kanizsa) stimulus comparisons like that in Figure
2, A and B (Hirsch et al., 1995a; ffytche
and Zeki, 1996). However, we report more widespread signals than
Hirsch et al. (1995). This difference likely reflects our efforts to
achieve greater sensitivity using increased signal averaging, different hardware (e.g., surface coil), and analysis (e.g., across-subject averaging). Our results support the idea that both the right and left
hemispheres have access to the bilateral neural representation of
illusory shapes, as suggested by Mattingly et al. (1997). We also
provide the first evidence that signals related to illusory contours
are retinotopically specific in retinotopic areas, and that visual
areas beyond V1 and V2 areas are the sites of most active processing.
This information should be useful for models of illusory contour
perception (Grossberg and Mingolla, 1985; Peterhans and von der Heydt,
1989; Takemoto and Yoshimichi, 1997). For instance, the role of
feedback connections in V1 and V2 could be considered with greater
emphasis, in addition to that of lateral connections between areas.
The neural response to stereopsis-defined contours
The stereopsis-defined contour produced activation that was strong
in V3A and the lateral occipital region. In the case of stereo, we do
not think that the higher activation in the relatively anterior regions
was caused simply by a stronger "bottom-up" driving force, because
signal amplitudes in V1 and V2 were roughly equal when produced by
luminance-defined versus stereopsis-defined figures.
One PET study has reported areas that were activated by binocular
disparity discrimination (Gulyas and Roland, 1994). However, in that
study subjects performed a task, and there was no fixation. The most
relevant comparison in that study was a luminance-based task subtracted
from a depth discrimination task. In that case, a strongly activated
locus was found in the "occipital superior gyrus" bilaterally with
Talairach coordinates (17, 79, 17; 28, 78, 14), which are close
to those obtained for our ROI in V3A (Table 2). Additional brief
reports have indicated the importance of V3A and the inferior parietal
region in depth perception (Savoy et al., 1995, Nagahama et al.,
1996), although other brief reports have emphasized earlier areas
including V1 (Ptito et al., 1993; Hirsch, 1995b; Kahn et al., 1997).
Methodological and stimulus differences may help explain the difference
in results. Unlike our results, several studies, particularly PET
studies, have reported an asymmetry favoring the right hemisphere in
tests of binocular disparity (Ptito et al., 1993; Hirsch, 1995b;
Nagahama et al., 1996), but this was not universally reported
(Savoy et al., 1995).
A surface-based level of visual processing
We found a dissociation between stimuli containing stereoscopic
depth cues or implied occlusion, compared to stimuli that did not
create strong segmentation in depth. The illusory contour stimuli that
produced strong signals in higher-tier areas include Kanizsa-type
stimuli as well as our most artifact-free displaced-grating stimulus.
Both these stimuli also give a clear impression of a solid shape
occluding the background, as does the shape defined by stereopsis.
Thus, the activation in the LO region might be related to segmentation
of figures from background. Such a task is thought to occur at an
intermediate level of processing (after edge detection, but before
object recognition), and it may be associated with partial
reconstruction of the three-dimensional depth relations between
surfaces (Kanizsa, 1979; Marr, 1980; Nakayama et al., 1995).
Theoretical and psychophysical support exists for a surface-based
representation of the visual image (Petry and Meyer, 1987; Nakayama and
Shimojo, 1992), but physiological evidence for such representations is limited.
It is likely that certain stages of surface processing require large
bilateral receptive fields, e.g., the ability to integrate over distant
retinal cues. Therefore, the fact that the LO region contains cortex
that is bilaterally responsive is an important finding. One hypothesis
regarding the function of the lateral occipital region is that it
contains neurons that subserve long-range grouping, which is important
for surface perception. Thus, activation including the LO region has
been reported for stimuli that contain surfaces defined by kinetic
contours (Van Oostende et al., 1997), for abstract
three-dimensional shapes (Malach et al., 1995), and for symmetric
stimuli (Tyler and Baseler, 1998). Future experiments will address the
relationship between the stimuli with implied depth used in this study,
and shapes defined by other means, to clarify the segmentation
processes that are used constantly in normal vision.
| |
FOOTNOTES |
Received Nov. 6, 1998; revised July 12, 1999; accepted July 20, 1999.
This research was supported by grants from McDonnell-Pew to J.M., and
Human Frontiers Program and National Institutes of Health Grant EY07980
to R.B.H.T. We are indebted to Ken Kwong, Bruce Rosen, Robert
Weisskoff, Thomas Brady, Terry Campbell, Mary Foley, and Patrick Ledden
for their critical contributions. We are grateful to Jody Culham and
Patrick Cavanagh for generously providing stimulus presentation
software. Discussions with Nava Rubin and Hany Farid were particularly
helpful. We also thank Robert Savoy and The Rowland Institute for
Science for technical and equipment support, and the Brain Imaging
Center at the Montreal Neurological Institute for stereotaxic software.
Correspondence should be addressed to Janine Mendola, Massachusetts
General Hospital Nuclear Magnetic Resonance Center, 149 13th Street
(2301), Charlestown, MA 02129.
| |
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TOP
ABSTRACT
INTRODUCTION
