Attention to 3-D Shape, 3-D Motion, and Texture in 3-D
Structure from Motion Displays
Hendrik Peuskens1, Kristl G. Claeys1,2, James T. Todd3,
J. Farley Norman4, Paul Van Hecke5, and Guy A. Orban1
Abstract
& We used fMRI to directly compare the neural substrates of
three-dimensional (3-D) shape and motion processing for
realistic textured objects rotating in depth. Subjects made
judgments about several different attributes of these objects,
including 3-D shape, the 3-D motion, and the scale of surface
texture. For all of these tasks, we equated visual input,
motor output, and task difficulty, and we controlled for differ-
INTRODUCTION
We live in a three-dimensional (3-D) world; we see and
interact with 3-D objects. Because the retinal image is
flat, the brain has to recreate the third dimension.
Several different aspects of optical structure are known
to provide perceptually salient information about an
object’s 3-D form. One especially powerful source of
information is provided by the optical deformations that
occur when objects are observed in motion (Todd &
Norman, 1991; Ullman, 1979; Wallach & O’Connell,
1953). Recent imaging work in both humans (Kriegeskorte et al., 2003; Paradis et al., 2000; Orban, Sunaert,
Todd, Van Hecke, & Marchal, 1999) and monkeys (Sereno, Trinath, Augath, & Logothetis, 2002; Vanduffel
et al., 2002) has shown that motion displays evoking
the perception of a 3-D object activate a range of cortical
areas, including lateral occipital, parietal, and occipitotemporal visual regions. This widespread activation in
passive subjects has been considered as evidence that
3-D shape is processed in both the dorsal and ventral
streams. It is important to keep in mind, however, that
moving displays produce several distinct perceptual
attributes. For example, one possible interpretation of
the pattern of activation during passive viewing is that
the dorsal pathway analyzes the 3-D motion of a moving
object, whereas the ventral pathway is primarily involved in the analysis of 3-D shape (Grünewald, Bradley,
& Andersen, 2002; Goodale & Milner, 1992; Ungerleider
& Mishkin, 1982). Such a division of labor would be in
1
K.U.Leuven, Medical School, 2University of Antwerpen, 3The
Ohio State University, 4Western Kentucky University, 5UZ
Gasthuisberg
D 2004 Massachusetts Institute of Technology
ences in spatial attention. Judgments about 3-D shape from
motion involve both parietal and occipito-temporal regions.
The processing of 3-D shape is associated with the analysis of
3-D motion in parietal regions and the analysis of surface
texture in occipito-temporal regions, which is consistent with
the different behavioral roles that are typically attributed to the
dorsal and ventral processing streams. &
line with the traditional distinction between the attributes that are processed by the ventral and dorsal pathways (Aguirre & D’Esposito, 1997; Haxby et al., 1994;
Ungerleider & Mishkin, 1982). Alternatively, 3-D shape
might be processed in both the dorsal and ventral
stream. In order to investigate these possibilities we have
performed an active experiment in which subjects made
judgments about several different attributes (Corbetta,
Miezin, Dobmeyer, Shulman, & Petersen, 1991) of moving objects, including their 3-D shapes and 3-D motions.
In all conditions, subjects viewed successive animation sequences of randomly shaped textured objects
rotating about a vertical axis slanted in depth. In the
three main conditions, they made same–different judgments about the 3-D shape, the 3-D axis of rotation, or
the spatial scale of the texture (Figure 1). Whereas the
3-D shape and 3-D motion conditions required the
processing of the optic flow (Norman, Todd, & Philips,
2001), the texture judgments did not. Two additional
control conditions were included using exactly the same
displays, in which subjects were required to detect a
slight dimming in the luminance of either the central or
peripheral regions of the moving objects. These controls were added because a pilot experiment had revealed that judgments of 3-D shape or motion involved
the whole object, whereas texture judgments were
primarily based on its central part, and it is known that
differences in distribution of visuospatial attention can
influence retinotopic patterns of activation in visual
cortex (Peuskens, Sunaert, Dupont, Van Hecke, &
Orban, 2001; Brefczynski & De Yoe, 1999; Tootell
et al., 1998). The visual input, the two alternative
forced-choice paradigm, and motor response were identical over all five conditions. All that changed was the
Journal of Cognitive Neuroscience 16:4, pp. 665–682
Figure 1. Schematic representation of texture judgment trials: same trial (A) and different trial (B). Stimulus 1 and 2 show the central and
peripheral dimming, respectively. The timing of the stimulus presentations and response period is indicated. The vertical line indicates the axis of
rotation, which was slanted in the z direction (outside the plane of this figure).
particular stimulus attribute the observers were required
to judge, which has been shown to enhance the tuning of
neurons selective for the attended attribute (Treue &
Martinez Trujillo, 1999). Finally, a fixation-only condition
was included as a low-level reference condition. To further rule out effects of spatial attention, an additional
control experiment was performed in which portions of
the depicted objects were masked, thus forcing observers
to focus their attention either centrally or peripherally in
order to perform the required judgments.
RESULTS
Behavioral Performance
Average performance over the different conditions of
the main experiment ranged from 81% to 84% correct,
which was not significantly different, F(4,56) = 0.64,
p = .63. In the control experiment average performance
was 85% correct for the three peripheral conditions and
ranged between 82% and 84% for the central conditions.
Subjects maintained fixation well during the active
epochs; eye blinks were allowed and occurred typically
on trial termination. Eye movements and blinks were
counted and compared over the different conditions of
666
Journal of Cognitive Neuroscience
the main experiment. No significant difference in eye
movement counts was found between the active epochs
(Friedman Fr = 7.8114, p = .098). During passive fixation epochs, blinks and saccades were more frequent
(total average of 15.9/min) as compared to during active
epochs (7–9.4/min).
Group Analysis of Main Imaging Experiment:
Activation Sites Specific to Discrimination of
Different Attributes
In the principal analysis of the main experiment, we
compared directly the MR activity averaged over subjects
in one discrimination task to that in each of the two
others. We use a color code (Figure 2) to visualize the
results of the main experiment, with red indicating regions involved in 3-D shape judgments more than in the
two other discriminations, yellow for 3-D motion-specific
regions, and blue for texture-specific regions. Intermediate selectivity is indicated by intermediate colors; for
example, orange indicates voxels where both 3-D shape
and 3-D motion judgments differed significantly from
texture judgments. This activation pattern indicates that
the regions involved with judgments of 3-D shape are
located both ventrally and dorsally. The regions involved
Volume 16, Number 4
with 3-D motion judgments, in contrast, are all located
in the lateral occipito-temporal and parietal cortex,
whereas regions involved with judgments of texture are
all confined to the ventral occipito-temporal cortex.
Within this activation pattern, only 13 regions reached
the strict significance criterion (see Methods) and are
described further as specific regions (Table 1). Ten of
these regions were symmetric in the two hemispheres,
while three were lateralized in a single hemisphere.
Three bilateral regions, numbered 2–4 in Figure 2, were
specific only for 3-D shape: lateral occipital sulcus (3,
LOS, Orban et al., 1999), inferior temporal gyrus (2,
ITG), and posterior intraparietal sulcus (4, IPS). Two
other bilateral regions (labeled 1 and 5 in Figure 2) were
involved in both 3-D shape and 3-D motion judgments:
hMT/V5+ (Tootell et al., 1995; Dupont, Orban, De
Bruyn, Verbruggen, & Mortelmans, 1994; Watson et al.,
1993; Zeki et al., 1991) and anterior IPS. Local maxima
for hMT/V5+ in the main subtractions (R: 54, 60, 0;
L: 45, 72, 3) correspond closely to those from the
motion localizer runs (R: 51, 66, 3; L: 54, 72, 3).
No region was found to be specific for just 3-Dmotion judgments. On the other hand, several regions
were involved in texture judgments. Many of these
were located in the posterior occipital cortex, at the
level of the early retinotopic regions. Since these regions
(indicated by a black dashed curve in Figure 2) were
more active in the dimming central condition than the
dimming peripheral one, their activation was considered to reflect visuospatial attention differences rather
than texture processing as such. This common activation of early visual regions in texture judgments and in
central dimming detection agrees with our psychophysical pilot results. The remaining texture-selective
regions included the right posterior and middle collateral sulcus (labeled 8 and 6, respectively, in Figure 2)
as well as the left middle lingual gyrus (labeled 7 in
Figure 2). The texture-selective regions in the right
hemisphere were also activated to some degree by
judgments of 3-D shape, whereas that in the left
hemisphere was additionally engaged by judgments
of 3-D motion. Although more voxels in Figure 2 were
related to texture judgments (purple voxels), these did
not meet the criterion for defining specific regions.
Figures 3 and 4 show the localization of 8 of the 13
activation sites (Figure 3), as well as their activity in the
five discrimination and detection tasks (Figure 4). For
the bilateral sites (three 3-D shape regions and two
3-D shape/3-D motion regions) only one of the two
symmetric sites is illustrated. The fixation condition is
Figure 2. The patterns of
activation revealed by a
random-effects analysis,
thresholded at p < .001
uncorrected for multiple
comparisons, and rendered on
a standard brain template.
Numbers denote local maxima
in areas significant at p < .05
corrected for multiple
comparisons. Color scale
indicates relative activation in
three different conditions:
attention to 3-D shape from
motion (red), to orientation of
rotation axis (3-D motion, pale
yellow) or to texture ( blue).
Dotted outline in the occipital
lobe demarcates brain regions
for which a significant effect of
visuospatial attention was found
in the comparison
between the detection of central
and peripheral dimming. In this
area, only texture-specific voxels
were found. Numbers indicate
specific regions: 1: hMT/V5+,
2: inferior temporal gyrus,
3: lateral occipital sulcus,
4: posterior intraparietal sulcus,
5: anterior intraparietal sulcus, 6:
right middle collateral sulcus, 7:
left middle lingual gyrus,
8: right posterior collateral
sulcus.
Peuskens et al.
667
Table 1. Localization of the Specific Regions (n = 13) in the Main Experiment with Z Scores (Random Effects) in the Group
Analysis and Number of Subjects Showing Significant Activation
A. Shape-Specific Regions
No. of Subjectsa
x
y
z
SM
ST
SM
ST
Both Tasks
R LOS
42
78
12
3.37
4.99
12/15
12/15
11/15
L LOS
36
90
12
4.45
3.5
11/15
9/15
9/15
R ITG
51
69
12
3.63
4.64
11/15
13/15
11/15
L ITG
48
66
12
4.22
4.45
12/15
11/15
10/15
R posterior IPS
21
72
54
3.66
4.86
12/15
15/15
12/15
L posterior IPS
18
60
63
3.55
4.35
12/15
12/15
10/15
B. Shape- and Motion-Selective Regions
No. of Subjects
x
y
R hMT/ V5+
54
60
L hMT/ V5+
45
R anterior IPS
L anterior IPS
z
ST
MT
ST
MT
Both Tasks
0
3.40
4.34
12/15
14/15
12/15
72
3
3.4
4.86
12/15
14/15
12.15
36
33
42
3.26
4.14
12/15
14/15
12/16
42
42
51
3.12
4.79
11/15
13/15
9/15
C. Texture-Specific Regions
No. of Subjects
x
y
z
TS
TM
b
TS
TM
Both Tasks
8/15
11/15
5/15
R middle collateral sulcus
30
45
15
0.1
3.55
L middle lingual gyrus
18
51
18
4.45
1.26
12/15
6/15
4/15
R posterior collateral sulcus
36
81
15
3.26
4.86
9/15
11/15
7/15
a
Single subjects reaching p < .001 uncorrected.
Bold: Z > 4.31, p < .05 corrected (random effects).
SM = 3-D shape compared to 3-D motion; ST = 3-D shape compared to texture; MT = 3-D motion compared to texture; TS = texture compared to
3-D shape; TM = texture compared to 3-D motion.
b
SM: Z = 4.45.
not indicated in the activity profiles (Figure 4), since
the analysis ensured that all regions were more active
in the task conditions than during simple fixation. For
most shape-selective regions (1–6) the MR signals
during shape discrimination also differed significantly
from those recorded in the detection conditions, with
the exception of posterior IPS. In all regions, including
the texture-selective ones, the activity during the two
detection tasks was similar, indicating that none of the
main effects in these regions can be due to variations in
spatial attention (Nobre et al., 1997; Vandenberghe et al.,
1996; Corbetta, Miezin, Shulman, & Petersen, 1993;
Corbetta et al., 1998).
668
Journal of Cognitive Neuroscience
Group Analysis of Main Imaging Experiment:
Activation Sites Common to All
Discrimination Tasks
The group analysis of the main experiment has thus
far concentrated on regions specifically involved in one
or two same–different tasks. Theoretically, a number of
cortical regions could also be engaged in all three
discrimination tasks. Only four regions (Figure 5) were
significantly ( p < .05 corrected) engaged by all three
tasks: Two local maxima were located in the right ITG,
the two other in the right middle fusiform gyrus and
right inferior parietal lobule. The two right ITG sites
Volume 16, Number 4
were proportionally more engaged by the 3-D shape
judgments than the two other judgments, in keeping
with their proximity to the ITG site specific for 3-D
shape judgments. This involvement of right ITG in
temporal same–different tasks is in agreement with a
string of articles from this laboratory indicating the
Figure 3. Coronal sections of
the average brain of 15 subjects
with activation patterns
rendered using the same color
scale as Figure 2. The black
outline demarcates activation
obtained in the motion localizer
scans ( p < .0001 uncorrected
for multiple comparisons). The
y coordinate of sections is
indicated in the top right corner
of each panel. Numbering as in
Figure 2.
Peuskens et al.
669
involvement of this region in successive discrimination
of orientation (Fias, Dupont, Reynvoet, & Orban, 2002;
Cornette, Dupont, Bormans, Mortelmans, & Orban,
2001; Faillenot, Sunaert, Van Hecke, & Orban, 2001;
Orban, Dupont, Vogels, Bormans, & Mortelmans,
1997), of direction (Cornette et al., 1998), and of
speed (Orban et al., 1998).
Single-Subject Analysis: Individual Activation
Patterns
Figure 4. Activity profiles (group analysis) show percent MR signal
change compared to the average of the dimming control tasks. Error
bars: SEM from fixed effect group analysis; numbering as in Figures 2
and 3; 1: hMT/ V5 ( 45, 72, 3); 2: inferior temporal gyrus ( 48,
63, 12); 3: lateral occipital sulcus (42, 81, 9); 4: posterior
intraparietal sulcus ( 18, 60, 66); 5: anterior intraparietal sulcus
(36, 33, 42); 6: right middle collateral sulcus (30, 45, 15); 7: left
middle lingual gyrus ( 18, 51, 18); 8: right posterior collateral
sulcus (36, 81, 15). 3-D SFM = 3-D shape from motion task; 3-D
MOT = orientation of rotation axis task; TEX = texture task;
LDC = luminance dimming detection in center; LDP = luminance
dimming detection in periphery.
670
Journal of Cognitive Neuroscience
In addition to the group analysis, we performed singlesubject analyses of the main experiment. While the
random effect analysis ensures that the results described so far can be generalized to all young and
healthy humans, it provides no information about variability across subjects. Single-subject analyses also
make it possible to compute the activity profile of
cortical regions defined by the motion localizer or
shape localizer. Figure 6 shows the activation pattern
using the color code of Figure 2 on the rendered
brains of five individual subjects. Two subjects were
chosen for the strength of their activation pattern, the
three others because the LO localizer was tested in
these subjects. Motion localizer tests were available for
all subjects, but rather than indicating all motionsensitive regions, only two of them, hMT/ V5+ and
dorsal intraparietal sulcus anterior (DIPSA) (Sunaert,
Van Hecke, Marchal, & Orban, 1999), are indicated in
Figure 6. In general, the activation pattern in the single
subjects agrees with the group pattern (Figure 2), but
it is of course much noisier. Given the random effects
option pursued in this study, the number of functional
volumes sampled in each subject is relatively small
according to our own standards (Vanduffel et al.,
2002). Despite this variability, 3-D shape-specific and
3-D shape- and 3-D motion-specific regions were observed (at p < .001 uncorrected) in more than half the
subjects (Table 1). The texture-specific regions are
generally defined by a single contrast and, in this case,
more than half the subjects showed a significant
activation (Table 1). We tested statistically whether
subjects for whom a given region was significant for
a given subtraction performed better than those for
whom this subtraction did not reach significance. After
correction for multiple comparison (n = 14) none of
the region/subtraction combinations were associated
with a significant difference in performance. All subjects were naı̈ve to the tasks before being enrolled in
the experiment. Hence, the relatively small number of
functional volumes sampled per subject is likely to be
the primary source of variability among subjects.
Figure 6 also indicates that the pITG region (2) is
located below hMT/V5+, while the motion-sensitive
region DIPSA is located in between the posterior and
anterior IPS regions (4 and 5). The LOS region (3) is
Volume 16, Number 4
Figure 5. Activity profiles
(group analysis) plotting
percent MR signal change
compared to the average of the
dimming control tasks for
regions common to the three
same–different judgments.
Error bars: SEM from
fixed-effect group analysis.
(A) right ITG (54, 57, 12);
(B) right ITG (42, 75, 3);
(C) right middle fusiform gyrus
(39, 39, 24); (D) right
inferior parietal lobule (51, 30,
54). Same conventions as
Figure 4.
located behind hMT/V5+, but also more dorsal compared to hMT/V5+ and even to the 2-D shape-sensitive
LOS region.
Single-Subject Analysis: Involvement of
Motion-Sensitive Regions
To investigate the relationship between the regions
active in the behavioral tasks and the 2-D motion-sensitive regions, we tested the most significant voxel of
motion-sensitive regions, obtained in the motion localizer for its activity in the different behavioral tasks of the
main experiment. We concentrated (Figure 7) on four
motion-sensitive regions (Sunaert et al., 1999): hMT/
V5+, LOS, dorsal intraparietal sulcus medial (DIPSM),
and DIPSA. The functional profile of motion-sensitive
LOS (Figure 7A) is very similar to that of the LOS region
in the group analysis (Figure 4), suggesting that this
might be the same region. Human MT/V5+ (Figure 7C)
is indeed involved in judgments of both 3-D shape and
orientation of the rotation axis, again in agreement with
the group result. Additional probing 9 mm above and
below the local motion localizer maximum indicated
that the dorsal part of the MT/V5 complex is relatively
more involved in 3-D motion judgments and the ventral
part more in 3-D shape judgments (Figure 7B and D).
This ventral part is contiguous to the 3-D shape-specific
pITG region. Thus, the dorsoventral gradient across
hMT/V5+ from 3-D motion specific dorsally to 3-D
shape specific ventrally, is not an effect of smoothing
in the group analysis. This transition has also been
documented by Kourtzi, Bulthoff, Erb, and Grodd
(2002). The motion-sensitive region DIPSM shows a
profile similar to that of the posterior IPS region in
the group analysis (4). On the other hand, DIPSA has a
profile intermediate between that of posterior and of
anterior IPS of the group analysis (4 and 5), in agreement with its anatomical position. With respect to the
LO complex (Malach et al., 1995, Kourtzi & Kanwisher,
2000), the three 2-D shape-sensitive regions, LOS, pITG,
or mFG were, to various degrees, involved in all three
discriminations (Figure 8). In fact, these activity
profiles are similar to those of the regions involved in
all discriminations according to the group analysis
(Figure 6).
Control Imaging Experiment: Spatial Attention
versus Featural Attention
In all 13 regions specifically engaged by one or two of
the same–different judgments, the difference in activity
between central and peripheral dimming detection was
extremely small, indicating that these regions were not
engaged in overt control of spatial attention. This does
not exclude the possibility that spatial attention and
featural attention interact. For example, the subjects
might have attended more to the peripheral parts of
the objects in the 3-D motion and 3-D shape judgments
than in the texture judgments. To control for different
spatial attention demands across the three judgments,
we tested all three judgments both with peripheral and
central attention focus in the control experiment. To
analyze the results of this experiment we made exactly
the same contrasts as in Figure 2, but averaged them
Peuskens et al.
671
672
Journal of Cognitive Neuroscience
Volume 16, Number 4
over central and peripheral conditions. This yielded the
same regions as in the main experiment, with the
exception that the middle collateral sulcus region, specific for texture and shape, was now observed bilaterally,
increasing the number of specific regions to 14 (Table 2).
For each of the 14 regions we tested the interaction
between spatial attention and featural attention and it
only reached significance ( p < .001 uncorrected) in
hMT/V5+, in which the central judgments evoked more
MR activity than the peripheral judgments. Yet, the main
effects of featural attention were extremely significant
(Table 2). The activity profiles (Figure 9) confirm that
the specific engagement of all regions by one or two
discrimination tasks is not dependent on the focus of
spatial attention. For comparison a region (posterior
fusiform gyrus) in which both the spatial attention
effects and the difference between texture judgements
and 3-D shape or 3-D motion judgements were significant is also shown. This region was located within the
black dashed curve at the back of the brain in Figure 2.
Finally, the posterior lingual region illustrates a region in
which spatial attention had a significant effect in all three
tasks. In this region, the activity modulation is complete,
indicating that the spatial attention manipulation was
very effective.
DISCUSSION
In order to study the effect of attention to different
attributes of dynamic 3-D displays, we equated not only
visual input, motor response, and performance level, but
also, indirectly, the region of space attended. The latter
was directly controlled in a separate experiment. Because behavioral purpose (Goodale & Milner, 1992) and
cognitive operations (Fias et al., 2002) have been shown
to differ between dorsal and ventral pathways, those
were kept constant across the discriminations tasks in
order to isolate the effect of stimulus attribute on the
dorsal/ventral pathway distinction. The results revealed
that 3-D shape is processed in both dorsal and ventral
pathways, but that 3-D motion is processed predominantly in the dorsal pathway and texture (as quality of an
object) is processed exclusively in the ventral pathway.
These findings indicate that the two pathways are not
completely segregated with respect to the stimulus
attributes they process. 3-D shapes are apparently of
sufficient biological importance to be processed in both
dorsal and ventral streams.
The human MT/V5 complex was engaged by both 3-D
shape and 3-D motion judgments but not texture judgments. There is growing evidence from imaging studies
that this motion-sensitive complex (Tolias, Smirnakis,
Augath, Trinath, & Logothetis, 2001; Vanduffel et al.,
2001; Tootell et al., 1995; Dupont et al., 1994; Watson
et al., 1993; Zeki et al., 1991) is involved in extracting 3-D
structure from motion in humans (Vanduffel et al., 2002;
Orban et al., 1999) and also in monkeys (Sereno et al.,
2002; Vanduffel et al., 2002). The monkey imaging
experiments in which exactly the same stimuli were
used in awake monkeys as well as in humans (Vanduffel
et al., 2002) indicate that in addition to MT/V5 itself, FST
extracts 3-D structure from motion, in agreement with
Sereno et al. (2002). Thus, it is likely that in the human
complex the homologues of MT/V5 and of FST also
contribute heavily to its activation by 3-D structure from
motion stimuli. The MR activation of MT/V5 by 3-D
structure from motion stimuli establishes a direct link
between the activation of hMT/V5+ by 3-D structure
from motion and the properties of MT/V5 neurons in
monkeys. These neurons have been shown to be selective for the direction of speed gradients, which corresponds to the tilt of a 3-D surface (Xiao, Marcar, Raiguel,
& Orban, 1997; see also Bradley, Chang & Andersen,
1998). The present results extend these observations
and, for the first time, indicate that this motion information about 3-D structure is actively used when subjects make judgments about 3-D shape. The fact that
hMT/V5+ was also engaged by 3-D motion judgments is
consistent with the view that hMT/V5+ represents a
relative early stage in the processing of dynamic 3-D
stimuli, in which the different functional consequences
of optic flow are not yet separated. It could be argued
that this common engagement of hMT/V5+ by 3-D
shape and 3-D motion judgements is due to selection
of the whole object (O’Craven, Downing, & Kanwisher,
1999), so that regions processing all of its attributes are
activated, even if only a single attribute is attended. This
is unlikely since several other regions, including other
motion-sensitive regions, are engaged in judgements of
3-D shape, but show no activation for judgements of 3-D
motion. Furthermore, the gradient of specificity observed across the hMT/V5+ complex would be difficult
to reconcile with the whole object-selection hypothesis.
Judgments of 3-D shape involved both dorsal and
ventral regions, contrary to predictions based on the
initial distinction between these pathways (Haxby et al.,
1994; Ungerleider & Mishkin, 1982). This finding for
Figure 6. The patterns of activation revealed by single-subject analysis, thresholded at p < .001 uncorrected for multiple comparisons, and
rendered on the subjects’ brain (lateral view). (A–C) Right and left hemisphere of Subject 6 (A), Subject 1 (B), and Subject 13 (C). (D) Right
hemisphere of Subject 14 and left hemisphere of Subject 15. Color scale (see Figures 2 and 3) indicates relative activation in three different
conditions: attention to 3-D shape from motion (red), to orientation of rotation axis (3-D motion, pale yellow), or to texture (blue). Numbers as in
Figures 2 and 3. Black outlines: hMT/ V5+ and DIPSA ( p < .05 corrected contour). White outlines: LO complex localizer ( p < .05 corrected
contour).
Peuskens et al.
673
674
Journal of Cognitive Neuroscience
Volume 16, Number 4
motion-defined shapes is in agreement with an earlier
PET study of Faillenot, Toni, Decety, Gregoire, and
Jeannerod (1997) using real 3-D objects. It adds to the
growing list of imaging studies indicating that 2-D and 3D shape are processed in both streams (Kriegeskorte
et al., 2003; James, Humphrey, Gati, Menon, & Goodale,
2002; Sereno et al., 2002; Vanduffel et al., 2002; Paradis
et al., 2000; Orban et al., 1999; Grill-Spector et al., 1998;
Van Oostende, Sunaert, Van Hecke, Marchal, & Orban,
1997). All previous experiments involving 3-D shape
were performed in passive subjects, however, so it is
difficult to determine the precise aspects of the stimulus
displays that may have been responsible for the
cerebral activation pattern. The present study using
active judgments provides conclusive evidence that both
dorsal and ventral streams are actively involved in the
perception of 3-D shape. While the role of inferotemporal cortex in processing visual shape information has
long been established (Kovács, Vogels, & Orban, 1995;
Logothetis & Pauls, 1995; Tanaka, Saito, Fukada, Moriya,
1991; Gross, Rocha-Miranda, & Bender, 1972), singlecell studies have also indicated that parietal neurons
can actively process shape information (Sereno &
Maunsell, 1998).
The regional distribution of neural activation for 3-D
shape from motion judgments is relatively similar to the
pattern of activation in passive experiments (Vanduffel
et al., 2002; Orban et al., 1999), although the ventral
involvement is clearer in 3-D shape discrimination than
in the passive case. The ventral region involved in shape
judgments was located at the edge of the LO complex
(Kriegeskorte et al., 2003; James et al., 2002; Kourtzi &
Kanwisher 2000; Grill-Spector et al., 1998; Van Oostende
et al., 1997; Malach et al., 1995), indicating that at least
parts of this complex region (Denys et al., 2002) process
3-D information about objects (Kourtzi & Kanwisher,
2001; Moore & Engel, 2001). Previous studies in passively fixating monkeys ( Janssen, Vogels, & Orban, 1999,
2000) have also shown the involvement of the ventral
cortex in the analysis of 3-D shape defined from stereo.
In the monkey this stereo region is a restricted part of
the inferotemporal cortex. The present study also suggests that only a small subpart of the LO complex,
located at the edge of pITG, corresponding to the LO
as generally defined by others (see Malach, Levy, &
Hasson, 2002, for a review), is involved in the 3-D shape
from motion processing. The major part of the LO
complex is not specifically involved (Figure 8), in agreement with the results of Kourtzi and Kanwisher (2000).
We refer to the most posterior and dorsal part of the LO
complex as LOS. Although the LO localizer scans were
performed in only three subjects, our results suggest
that within LOS the 2-D shape and 2-D motion-sensitive
parts behave differently and that only the motion-sensitive part is involved in 3-D shape judgements. This is
reminiscent of a recent study by Murray, Olshausen, and
Woods (2003), who also dissociated a motion-sensitive
subregion (LOS) from two shape-sensitive parts (which
they labeled LO and SLO). They observed that 3-D from
motion displays activate SLO, but not LOS or LO (their
terminology). The location of SLO (Murray et al., 2003)
seems similar to that of the LOS part involved in 3-D
shape judgements (Region 3) in our study.
The posterior IPS region overlaps the motion-sensitive
region DIPSM (Sunaert et al., 1999), which has been
shown to react to 3-D structure from motion stimuli
(Vanduffel et al., 2002; Orban et al., 1999). On the other
hand, the anterior IPS region is located ventral and
anterior from another motion-sensitive region, DIPSA
(Sunaert et al., 1999), also engaged by passive viewing
of 3-D SFM stimuli (Vanduffel et al., 2002; Orban et al.,
1999). The two IPS regions of the present study match
the anterior (36, 33, 39) and posterior (+/ 9, 59, 62)
IPS regions involved in judging the 3-D orientation of
textured surfaces (Shikata et al., 2001). The IPS region
(36, 48, 54) involved in judging 3-D shape from shading
(Taira, Nose, Inoue, & Tsutsui, 2001) seems located in
between these two IPS regions. Finally, the anterior IPS
region matches the region involved in visual 3-D object
encoding (Grefkes, Weiss, Zilles, & Fink, 2002). Monkey
single-cell studies have shown that neurons in the anterior part of the IPS are selective for 3-D objects (Murata,
Gallese, Luppino, Kaseda, & Sakata, 2000), and those in
the posterior part selective for 3-D surface orientation
from stereo (Taira, Tsutsui, Jian, Yara, & Sakata, 2000)
and from texture (Tsutsui, Sakata, Naganuma, & Taira,
2002). Given the functional interspecies differences recently observed (Denys et al., 2002; Vanduffel et al.,
2002) or conjectured (Simon, Mangin, Cohen, Le Bihan,
& Dehaene, 2002) in the intraparietal sulcus, the exact
homology between these human and monkey regions is
presently unclear.
Judgments of 3-D motion or surface texture, on the
other hand, were found to involve exclusively or predominantly dorsal and ventral regions, respectively.
These findings are more in line with the traditional
distinction between the dorsal and ventral pathways
(Ungerleider & Mishkin, 1982). The involvement of
dorsal regions in 3-D motion judgments agrees with
the results of our earlier passive study (Orban et al.,
Figure 7. Activity profiles (single-subject analysis) of 2-D motion-sensitive regions, identified by the motion localizer, plotting percent MR
signal change in the five tasks compared to the average of the dimming control tasks, averaged over subjects (n = 15) and over the two
hemispheres. Error bars: SEM from fixed-effect group analysis. Profiles of most significant voxel of LOS motion-sensitive region (A), of hMT/V5+ (C),
9 mm above (B) and 9 mm below (D) the hMT/ V5+ maximum, of most significant voxel of DIPSM (E), of DIPSA (F), and 9 mm below and 3 mm
anterior to the DIPSA maximum (G). 3-D SFM = 3-D shape from motion task; 3-D MOT = orientation of rotation axis task; TEX = texture task;
LDC = luminance dimming detection in center; LDP = luminance dimming detection in periphery.
Peuskens et al.
675
Figure 8. Activity profiles
(single-subject analysis) of 2-D
shape sensitive regions,
identified by the LO complex
localizer, plotting percent MR
signal change in the five tasks
compared to the average of the
dimming control tasks,
averaged over subjects (n = 3)
and over the two hemispheres.
Error bars: SEM from
fixed-effect group analysis.
Profiles of most significant
voxel of LOS (A), posterior
inferior temporal gyrus (pITG)
(B), corresponding to LO, and
of middle fusiform gyrus
(mFG) (C) corresponding to
pFG (see Malach et al., 2002,
for a review). Same
conventions as in Figure 7.
676
Journal of Cognitive Neuroscience
Volume 16, Number 4
Table 2. Localization of the Specific Regions (n = 14) in the Control Experiment, with Z Scores (Fixed Effects) of Main Effects and
Interactions (int)
A. Shape-Specific Regions
SHA-MOT
Z
a
SHA-TEX
Z int
b
Z
a
Z int b
x
y
z
R LOS
39
81
18
L LOS
36
87
12
7.75
–
6.62
–
R ITG
36
60
9
3.26
–
3.95
–
L ITG
51
63
12
–
5.80
–
R posterior IPS
12
60
72
L posterior IPS
18
57
66
>8.0
–
>8.0
6.91
>8.0
>8.0
–
–
>8.0
–
–
>8.0
–
B. Shape- and Motion-Selective Regions
SHA-TEX
z
Z
a
MOT-TEX
b
a
Z int b
x
y
R hMT/ V5+
48
63
3
>8.0
3.68
>8.0
3.31
L hMT/ V5+
51
69
0
>8.0
2.69
>8.0
3.29
R anterior IPS
39
42
57
>8.0
–
>8.0
–
L anterior IPS
42
42
66
–
>8.0
–
Z int
5.73
Z
C. Texture-Specific Regions
TEX-SHA
x
y
z
Z
R middle collateral sulcus
30
54
15
L middle collateral sulcus
30
51
15
L middle lingual gyrus
18
42
R posterior collateral sulcus
27
87
a
TEX-MOT
Z int
b
Z
a
Z int b
–
5.55
–
3.73
–
5.73
2.03
21
4.64
–
–
–
21
3.14
–
4.16
–
a
Z score main effect.
b
Z score interaction.
1999) in which viewing the trajectory in depth of a flat
object was shown to activate hMT/V5+ and an anterior
IPS region. In that study, this latter activation was always
weaker than that evoked by 3-D motion displays. The
dorsal motion-sensitive regions along the IPS have also
been shown to be activated by attentive tracking of
multiple objects moving in space (Culham et al., 1999).
The anterior IPS region involved in judgments of 3-D
orientation of the rotation axis is close to the implicitobject-motion IPS region recently described by Kriegeskorte et al. (2003) and the PSA region described by
Murray et al. (2003). In monkey, parietal neurons have
been shown to represent motion trajectories (Assad &
Maunsell, 1995). The involvement of ventral regions in
texture judgments agrees with earlier imaging results of
Puce, Allison, Asgari, Gore, & McCarthy (1996). In
monkey, selectivity of inferotemporal neurons for texture has been well established (Komatsu & Ideura, 1993;
Tanaka et al., 1991).
The combined involvement of the anterior ends of the
respective pathways with 3-D shape and 3-D motion for
the dorsal stream, and with 3-D shape and texture in the
ventral stream, is in excellent agreement with the behavioral role that is typically attributed to these pathways (Goodale & Milner, 1992). In order to successfully
grasp a moving object it is obviously necessary to analyze
both its 3-D shape and its 3-D motion, and the successful
recognition or classification of objects must clearly
involve an analysis of both texture and shape information, whether 2-D or 3-D. Not surprisingly, the anterior
Peuskens et al.
677
IPS region is close to regions involved in grasping
(Simon et al., 2002; Binkofski et al., 1998, 1999), while
the ITG and middle collateral sulcus regions are active in
recognition (Bar et al., 2001; Grill-Spector, Kushnir,
Hendler, & Malach, 2000; Rosier et al., 1999).
METHODS
Subjects
Fifteen healthy, right-handed human subjects (9 men,
6 women, mean age 24 years, range: 20–32) participated
in the main fMRI experiment. Three subjects (3 male,
mean age 25 years, range: 24–28), including 2 from the
main experiment, participated in the additional control
experiment. All subjects had normal or corrected-tonormal vision and no history of neurological or psychiatric disease. Subjects viewed a translucent display
screen positioned in the bore of the magnet, at a
distance of 36 cm from the subjects’ eyes, through a
mirror angled 458 to the line of sight. Subjects were
instructed to fixate a point on the screen. During
scanning, eye movements were recorded with an Ober2
eye-tracking system. The study was approved by the
Ethical Committee of the K.U.Leuven Medical School
and subjects gave their written informed consent, in
accordance with the declaration of Helsinki.
Stimuli and Tasks
Figure 9. Activity profiles (control experiment) plotting percent MR
signal change compared to fixation baseline for the 14 task-specific
regions (1–8) and for two regions displaying significant spatial
attention effects (9–10). Profiles 1–6 and 9–10 are averaged over the
right and left hemisphere. For localization of Regions 1–8, see Table 2;
coordinates Region 9: 27, 72, 15 and 24, 69, 12; and Region 10:
6, 84, 6 and 9, 84, 12. C = central; P = peripheral, other
conventions as in Figure 4.
678
Journal of Cognitive Neuroscience
Stimuli were back projected onto the translucent screen
using a Barco Reality 6300 (Kuurne, Belgium) projector
with a spatial resolution of 1280 1024 pixels. Stimuli
consisted of a central fixation point and two brief
presentations of textured, randomly deformed spheres
(Norman, Todd, & Philips, 1995) rotating back and forth,
roughly 9 visual degrees in diameter (mean luminance
218 cd/m2) on a 20 15 visual degrees background
(Figure 1). In each trial, rotating deformed spheres were
presented twice for 750 msec with an interstimulus
interval of 300 msec and an intertrial interval of
1000 msec. In addition, the luminance of the central
or peripheral part of the rotating spheres decreased for
200 msec in one out of two trials.
Subjects were required to make same–different judgments about the overall 3-D shape, orientation of the
rotation axis, or the spatial scale of the texture by
pressing a response button in the left (same) or right
(different) hand. Differences in 3-D shape were created by adding a small sinusoidal perturbation in depth
over the entire surface; differences in the pattern of
motion were achieved by varying the amount of slant
in depth of the axis of rotation; and differences in
spatial scale of the texture by shifting the mean spatial
frequency. Psychophysical studies have shown that for
simple same–different tasks, the paired comparison
strategy is optimal (Vogels & Orban, 1986). Debriefing
confirmed that in the 3-D shape-discrimination task
subjects indeed compared the 3-D surface characteristics of the two deformed spheres. In the main
Volume 16, Number 4
experiment, two additional conditions were also included in which subjects were required to detect the
brief luminance dimming in the central or peripheral
regions of the moving object (Figure 1). Subjects
pressed the left button when dimming occurred in
the trial, and the right button otherwise. In the control
experiment, only the three same–different tasks were
included, but each of these were performed with
either the central 48 of the objects in view, or with
the peripheral part (outside the central 48) visible.
While in the main experiment, dimming of central or
peripheral parts of the object was present in all
conditions, no dimming occurred in the control experiment. It is important to emphasize that animation
sequences were identical in all five response conditions of the main experiment and all three central or
peripheral conditions of the control experiments. The
objects presented in each pair of trial intervals were
varied independently with respect to 3-D shape, 3-D
motion, surface texture and, when present, central or
peripheral dimming. The only systematic difference
among the various conditions was the judgment an
observer was required to perform.
In two training sessions prior to scanning, subjects
were trained to keep fixation, and to perform the tasks
for increasingly small stimulus differences or luminance
decrements. A threshold was determined for each individual subject and response task so that performance
could be equated at approximately 84% accuracy for
all conditions.
Scanning
Functional time series consisted of 150 (main experiment) and 180 (control study) gradient EPI whole-brain
scans (Siemens Sonata 1.5-T, TR/TE = 3010/50 msec,
FOV 192 192 mm2, 3 3 mm in plane resolution, 32
noncontiguous sagittal slices of 4.5-mm slice thickness
with a 0.5-mm gap, Erlangen, Germany). Since more
than four conditions had to be compared, a block design
was considered more optimal than an event-related
design. Thus, each of the five main experimental conditions were presented during epochs of 27 sec (9
whole-brain scans) and replicated once per time series.
They were interspersed with baseline fixation (epochs of
18 sec) during which only the fixation point was shown.
In the control experiment each time series included the
six experimental conditions, 3 (tasks) 2 (object parts),
presented in 27-sec epochs (9 scans), each followed by
an 18-sec fixation epoch (6 scans) and replicated once.
Both in the main and control experiments, subjects
received an auditory cue signaling the nature of the
next task at the end of every fixation epoch. Eight time
series were recorded in each subject yielding 144 wholebrain scans per condition and per subject.
In every subject, two additional time series were acquired in which passive viewing of a moving (78 diameter,
68/sec, eight random directions) random texture pattern
alternated every 10 images with the viewing of the same
but stationary pattern (Sunaert et al., 1999). These runs
were used to localize motion responsive areas, more
specifically hMT/V5+, COS/ MOT, DIPSM, and DIPSA.
Finally, anatomical images were acquired for every
subject (3-D MPRAGE, TR/ TE 1950/3.9 msec, TI 800 msec,
FOV 240 256 mm2, 240 256 matrix, 160-mm slab
thickness, 160 sagittal partitions, 1 1 1-mm3 voxels).
Localization of the lateral occipital complex, and
more generally of areas involved in processing object
shape, was done comparing passive viewing of grayscale images and image outlines versus scrambled
versions of these stimuli (Kourtzi & Kanwisher, 2000,
stimuli used with kind permission) in three subjects.
Four time series were recorded per subject, with each
series including epochs of presentations of intact grayscale images, intact outline drawings of objects, scrambled grayscale images, scrambled line drawings, and a
visual baseline containing only a fixation point.
Data Analysis
Image preprocessing was done using SPM99 (Wellcome
Department of Cognitive Neurology, London, UK ) and
included realignment, coregistration of the anatomical
images to the functional scans, and spatial normalization
into a standard space (Montreal Neurological Institute
template) using affine and nonlinear transformations.
Functional images were spatially smoothed with a
Gaussian kernel (8-mm full width at half maximum).
Global changes in BOLD signal were removed by
scaling; low-frequency drifts in the fMRI were removed
by using high-pass filter. Condition effects were estimated by applying appropriate linear contrasts (Friston
et al., 1995).
The resulting contrast images from all subjects in the
main experiment were entered into a random-effects
analysis per contrast, using a one-sample t test in order
to create a statistical parametric map, enabling the
inference based on specific contrasts to be extended
to the general population (Friston, Holmes, & Worsley,
1999). This random-effects analysis was restricted a
priori to visually responsive voxels, i.e., voxels reaching
p < .001 uncorrected in the contrast of all active
conditions minus fixation only. In the main analysis,
the three discrimination conditions were compared
pairwise, yielding six contrasts. The results of these
comparisons were color-coded using a triangular
scheme. Colors at the endpoints of the triangle in
Figures 2 and 4 denote significant activation ( p < .001
uncorrected for multiple comparisons, restricted to
visually responsive voxels) of one condition compared
to both the other conditions; middle colors denote
activation in common to two conditions relative to the
remaining condition. Only regions ( n = 13) in which
local maxima reached p < .05 corrected for multiple
Peuskens et al.
679
comparisons (for visually responsive voxels) at least in
one of the six subtractions, were considered further. In
an additional analysis, all three discrimination tasks were
compared to the two dimming detection tasks. Also,
conditions in which central or peripheral dimming was
attended were compared. These contrasts yielded voxels
in which visuospatial attention had a significant effect
( p < .001 uncorrected). Finally, the main experiment
was also subjected to a single-subject analysis. For single
subjects the level of significance was set at p < .001
uncorrected.
A fixed-effect analysis was performed on the data of
the control experiment. As in the analysis of the main
experiment, the three discrimination conditions were
compared pairwise, yielding six contrasts, but data were
averaged over central and peripheral presentations.
Acknowledgments
The authors are indebted to Y. Celis, P. Kayenbergh, G.
Meulemans, M. De Paep, and W. Depuydt for technical help.
This study was supported by GOA 2000/11, FWO G.0202.99,
G.0401.00, and GSKE. H. P. is a research assistant of the FWO.
Reprint requests should be sent to Guy A. Orban, K. U. Leuven,
Medical School, Laboratorium Neuro- en Psychofysiologie,
Campus Gasthuisberg, B-3000 Leuven, Belgium.
The data reported in this experiment have been deposited in
the fMRI Data Center (http://www.fmridc.org). The accession
number is 2-2003-114DG.
REFERENCES
Aguirre, G. K., & D’Esposito, M. (1997). Experimental
knowledge is subserved by separable dorsal/ventral neural
areas. Journal of Neuroscience, 17, 2512–2518.
Assad, J. A., & Maunsell, J. H. (1995). Neuronal correlates of
inferred motion in primate posterior parietal cortex. Nature,
373, 518–521.
Bar, M., Tootell, R. B., Schacter, D. L., Greve, D. N., Fischl, B.,
Mendola, J. D., Rosen, B. R., & Dale, A. M. (2001). Cortical
mechanisms specific to explicit visual object recognition.
Neuron, 29, 529–535.
Binkofski, F., Buccino, G., Posse, S., Seitz, R. J., Rizzolatti, G.,
& Freund, H. (1999). A fronto-parietal circuit for object
manipulation in man: Evidence from an fMRI study.
European Journal of Neuroscience, 11, 3276–3286.
Binkofski, F., Dohle, C., Posse, S., Stephan, K. M., Hefter, H.,
Seitz, R. J., & Freund, H. J. (1998). Human anterior
intraparietal area subserves prehension: A combined lesion
and functional MRI activation study. Neurology, 50,
1253–1259.
Bradley, D. C., Chang, G. C., & Andersen, R. A. (1998).
Encoding of three-dimensional structure-from-motion by
primate area MT neurons. Nature, 392, 714–717.
Brefczynski, J. A., & DeYoe, E. A. (1999). A physiological
correlate of the ‘‘spotlight’’ of visual attention. Nature
Neuroscience, 2, 370–374.
Corbetta, M., Akbudak, E., Conturo, T. E., Snyder, A. Z.,
Ollinger, J. M., Drury, H. A., Linenweber, M. R., Petersen,
S. E., Raichle, M. E., Van Essen, D. C., & Shulman, G. L.
(1998). A common network of functional areas for attention
and eye movements. Neuron, 21, 761–773.
680
Journal of Cognitive Neuroscience
Corbetta, M., Miezin, F. M., Dobmeyer, S., Shulman, G. L.,
& Petersen, S. E. (1991). Selective and divided attention
during visual discriminations of shape, color, and speed:
Functional anatomy by positron emission tomography.
Journal of Neuroscience, 11, 2383–2402.
Corbetta, M., Miezin, F. M., Shulman, G. L., & Petersen, S. E.
(1993). A PET study of visuospatial attention. Journal of
Neuroscience, 13, 1202–1226.
Cornette, L., Dupont, P., Bormans, G., Mortelmans, L., &
Orban, G. A. (2001). Separate neural correlates for the
mnemonic components of successive discrimination and
working memory tasks. Cerebral Cortex, 11, 59–72.
Cornette, L., Dupont, P., Rosier, A., Sunaert, S., Van Hecke, P.,
Michiels, J., Mortelmans, L., & Orban, G. A. (1998). Human
brain regions involved in direction discrimination. Journal
of Neurophysiology, 79, 2749–2765.
Culham, J. C., Dukelow, S. P., Vilis, T., Hassard, F. A., Gati, J. S.,
Menon, R. S., & Goodale, M. A. (1999). Recovery of fMRI
activation in motion area MT following storage of the
motion aftereffect. Journal of Neurophysiology, 81,
388–393.
Denys, K., Vanduffel, W., Fize, D., Peuskens, H., Nelissen, K.,
Vandenberghe, R., & Orban, G. A. (2002). The lateral
occipital complex in the monkey and the human. Society for
Neuroscience Abstracts, 161.1.
Dupont, P., Orban, G. A., De Bruyn, B., Verbruggen, A., &
Mortelmans, L. (1994). Many areas in the human brain
respond to visual motion. Journal of Neurophysiology, 72,
1420–1424.
Faillenot, I., Sunaert, S., Van Hecke, P., & Orban, G. A. (2001).
Orientation discrimination of objects and gratings
compared: An fMRI study. European Journal of
Neuroscience, 13, 585–596.
Faillenot, I., Toni, I., Decety, J., Gregoire, M. C., & Jeannerod,
M. (1997). Visual pathways for object-oriented action and
object recognition: Functional anatomy with PET. Cerebral
Cortex, 7, 77–85.
Fias, W., Dupont, P., Reynvoet, B., & Orban, G. A. (2002). The
quantitative nature of a visual task differentiates between
ventral and dorsal stream. Journal of Cognitive
Neuroscience, 14, 646–658.
Friston, K. J., Holmes, A. P., Poline, J. B., Grasby, P. J., Williams,
S. C., Frackowiak, R. S., & Turner, R. (1995). Analysis of fMRI
time-series revisited. Neuroimage, 2, 45–53.
Friston, K. J., Holmes, A. P., & Worsley, K. J. (1999). How many
subjects constitute a study? Neuroimage, 10, 1–5.
Goodale, M. A., & Milner, A. D. (1992). Separate visual
pathways for perception and action. Trends in
Neuroscience, 15, 20–25.
Grefkes, C., Weiss, P. H., Zilles, K., & Fink, G. R. (2002).
Crossmodal processing of object features in human anterior
intraparietal cortex: An fMRI study implies equivalencies
between humans and monkeys. Neuron, 35, 173–184.
Grill-Spector, K., Kushnir, T., Hendler, T., Edelman, S., Itzchak,
Y., & Malach, R. (1998). A sequence of object-processing
stages revealed by fMRI in the human occipital lobe. Human
Brain Mapping, 6, 316–328.
Grill-Spector, K., Kushnir, T., Hendler, T., & Malach, R. (2000).
The dynamics of object-selective activation correlate with
recognition performance in humans. Nature Neuroscience,
3, 837–843.
Gross, C. G., Rocha-Miranda, C. E., & Bender, D. B. (1972).
Visual properties of neurons in inferotemporal cortex of the
Macaque. Journal of Neurophysiology, 35, 96–111.
Grünewald, A., Bradley, D. C., & Andersen, R. A. (2002).
Neural correlates of structure-from-motion perception in
macaque V1 and MT. Journal of Neuroscience, 22,
6195–6207.
Volume 16, Number 4
Haxby, J. V., Horwitz, B., Ungerleider, L. G., Maisog, J. M.,
Pietrini, P., & Grady, C. L. (1994). The functional
organization of human extrastriate cortex: A PET-rCBF study
of selective attention to faces and locations. Journal of
Neuroscience, 14, 6336–6353.
James, T. W., Humphrey, G. K., Gati, J. S., Menon, R. S., &
Goodale, M. A. (2002). Differential effects of viewpoint on
object-driven activation in dorsal and ventral streams.
Neuron, 35, 793–801.
Janssen, P., Vogels, R., & Orban, G. A. (1999). Macaque inferior
temporal neurons are selective for disparity-defined
three-dimensional shapes. Proceedings of the National
Academy of Sciences, U.S.A., 96, 8217–8222.
Janssen, P., Vogels, R., & Orban, G. A. (2000). Selectivity for 3D
shape that reveals distinct areas within macaque inferior
temporal cortex. Science, 288, 2054–2056.
Komatsu, H., & Ideura, Y. (1993). Relationships between
color, shape, and pattern selectivities of neurons in the
inferior temporal cortex of the monkey. Journal of
Neurophysiology, 70, 677–694.
Kourtzi, Z., Bulthoff, H. H., Erb, M., & Grodd, W. (2002).
Object-selective responses in the human motion area
MT/MST. Nature Neuroscience, 5, 17–18.
Kourtzi, Z., & Kanwisher, N. (2000). Cortical regions involved
in perceiving object shape. Journal of Neuroscience, 20,
3310–3318.
Kourtzi, Z., & Kanwisher, N. (2001). Representation of
perceived object shape by the human lateral occipital
complex. Science, 293, 1506–1509.
Kovács, G., Vogels, R., & Orban, G. A. (1995). Selectivity of
macaque inferior temporal neurons for partially occluded
shapes. Journal of Neuroscience, 15, 1984–1997.
Kriegeskorte, N., Sorger, B., Naumer, M., Schwarzbach, J., van
den Boogert, E., Hussy, W., & Goebel, R. (2003). Human
cortical object recognition from a visual motion flowfield.
Journal of Neuroscience, 15, 1451–1463.
Logothetis, N. K., & Pauls, J. (1995). Psychophysical and
physiological evidence for viewer-centered object
representations in the primate. Cerebral Cortex, 5, 270–288.
Malach, R., Levy, I., & Hasson, U. (2002). The topography of
high-order human object areas. Trends in Cognitive
Sciences, 6, 176–184.
Malach, R., Reppas, J. B., Benson, R. R., Kwong, K. K., Jiang, H.,
Kennedy, W. A., Ledden, P. J., Brady, T. J., Rosen, B. R., &
Tootell, R. B. H. (1995). Object-related activity revealed by
functional magnetic resonance imaging in human occipital
cortex. Proceedings of the National Academy of Sciences,
U.S.A., 92, 8135–8139.
Moore, C., & Engel, S. A. (2001). Neural response to perception
of volume in the lateral occipital complex. Neuron,
29, 277.
Murata, A., Gallese, V., Luppino, G., Kaseda, M., & Sakata, H.
(2000). Selectivity for the shape, size, and orientation of
objects for grasping in neurons of monkey parietal area AIP.
Journal of Neurophysiology, 83, 2580–2601.
Murray, S. O., Olshausen, B. A., & Woods, D. L. (2003)
Processing shape, motion end three-dimensional
shape-from-motion in the human cortex. Cerebral Cortex,
13, 508–516.
Nobre, A. C., Sebestyen, G. N., Gitelman, D. R., Mesulam,
M. M., Frackowiak, R. S. J., & Frith, C. D. (1997). Functional
localization of the system for visuospatial attention using
positron emission tomography. Brain, 120, 515–533.
Norman, J. F., Todd, J. T., & Orban, G. A. (2001). The
perception and discrimination of global 3-D shape from the
deformations of texture, shading, and specular highlights.
Journal of Vision, 1, 392a.
Norman, J. F., Todd, J. T., & Philips, F. (1995). The perception
of surface orientation from multiple sources of
optical information. Perception and Psychophysics, 57,
629–636.
O’Craven, K. M., Downing, P. E., & Kanwisher, N. (1999). fMRI
evidence for objects as the units of attentional selection.
Nature, 401, 584–587.
Orban, G. A., Dupont, P., De Bruyn, B., Vandenberghe, R.,
Rosier, A., & Mortelmans, L. (1998). Human brain activity
related to speed discrimination tasks. Experimental Brain
Research, 122, 9–22.
Orban, G. A., Dupont, P., Vogels, R., Bormans, G., &
Mortelmans, L. (1997). Human brain activity related to
orientation discrimination tasks. European Journal of
Neuroscience, 9, 246–259.
Orban, G. A., Sunaert, S., Todd, J., T., Van Hecke, P., & Marchal,
G. (1999). Human cortical regions involved in extracting
depth from motion. Neuron, 24, 929–940.
Paradis, A. L., Cornilleau-Pérès, V., Droulez, J. Van De Moortele,
P. F., Lobel, E., Berthoz, A., Le Bihan, D., & Poline, J. B.
(2000). Visual perception of motion and 3-D structure
from motion: An fMRI study. Cerebral Cortex, 10,
772–783.
Peuskens, H., Sunaert, S., Dupont, P., Van Hecke, P.,
& Orban, G. A. (2001). Human brain regions involved in
heading estimation. Journal of Neuroscience, 21,
2451–2461.
Puce, A., Allison, T., Asgari, M., Gore, J. C., & McCarthy, G. M.
(1996). Differential sensitivity of human visual cortex to
faces, letter strings, and textures: A functional magnetic
resonance imaging study. Journal of Neuroscience, 16,
5205–5215.
Rosier, A. M., Cornette, L., Dupont, P., Bormans, G.,
Mortelmans, L., & Orban, G. A. (1999). Regional brain activity
during shape recognition impaired by a scopolamine
challenge to encoding. European Journal of Neuroscience,
11, 3701–3714.
Sereno, A. B., & Maunsell, J. H. (1998). Shape selectivity in
primate lateral intraparietal cortex. Nature, 395, 500–503.
Sereno, M. E., Trinath, T., Augath, M., & Logothetis, N. K.
(2002). Three-dimensional shape representation in monkey
cortex. Neuron, 33, 635–652.
Shikata, E., Hamzei, F., Glauche, V., Knab, R., Dettmers, C.,
Weiller, C., & Büchel, C. (2001). Surface orientation
discrimination activates caudal and anterior intraparietal
sulcus in humans: An event-related fMRI study. Journal of
Neurophysiology, 85, 1309–1314.
Simon, O., Mangin, J.-F., Cohen, L., Le Bihan, D., & Dehaene, S.
(2002). Topographical layout of hand, eye, calculation,
and language-related areas in the human parietal lobe.
Neuron, 33, 475–487.
Sunaert, S., Van Hecke, P., Marchal, G., & Orban, G. A. (1999).
Motion-responsive regions of the human brain.
Experimental Brain Research, 127, 355–370.
Taira, M., Nose, I., Inoue, K., & Tsutsui, K. I. (2001). Cortical
areas related to attention to 3D surface structures based on
shading: An fMRI study. Neuroimage, 14, 959–966.
Taira, M., Tsutsui, K. I., Jiang, M., Yara, K., & Sakata, H. (2000).
Parietal neurons represent surface orientation from the
gradient of binocular disparity. Journal of Neurophysiology,
83, 3140–3146.
Tanaka, K., Saito, H., Fukada, Y., & Moriya, M. (1991).
Coding visual images of objects in the inferotemporal
cortex of the macaque monkey. Journal of Neurophysiology,
66, 170–189.
Todd, J. T., & Norman, J. F. (1991). The visual perception of
smoothly curved surfaces from minimal apparent motion
sequences. Perception & Psychophysics, 50, 509–523.
Tolias, A. S., Smirnakis, S. M., Augath, M. A., Trinath, T., &
Peuskens et al.
681
Logothetis, N. K. (2001). Motion processing in the macaque:
Revisited with functional magnetic resonance imaging.
Journal of Neuroscience, 21, 8594–8601.
Tootell, R. B., Reppas, J. B., Kwong, K. K., Malach, R., Born,
R. T., Brady, T. J., Rosen, B. R., & Belliveau, J. W. (1995).
Functional analysis of human MT and related visual cortical
areas using magnetic resonance imaging. Journal of
Neuroscience, 15, 3215–3230.
Tootell, R. B. H., Hadjikhani, N., Hall, E. K., Marrett, S.,
Vanduffel, W., Vaughan, J. T., & Dale, A. M. (1998). The
retinotopy of visual spatial attention. Neuron, 21, 1409.
Treue, S., & Martinez Trujillo, J. C. (1999). Feature-based
attention influences motion processing gain in macaque
visual cortex. Nature, 399, 575–579.
Tsutsui, K. I., Sakata, H., Naganuma, T., & Taira, M. (2002).
Neural correlates for perception of 3D surface orientation
from texture gradient. Science, 298, 409–412.
Ullman, S. (1979). The interpretation of visual motion.
Cambridge: MIT Press.
Ungerleider, L. G., & Mishkin, M. (1982). Two cortical visual
systems. In D. J. Ingle, M. A. Goodale, & R. J. W. Mansfield
(Eds.), Analysis of visual behavior (pp. 549–586).
Cambridge: MIT Press.
Vandenberghe, R., Dupont, P., De Bruyn, B., Bormans, G.,
Michiels, J., Mortelmans, L., & Orban, G. A. (1996). The
influence of stimulus location on the brain activation
pattern in detection and orientation discrimination.
A PET study of visual attention. Brain, 119, 1263–1276.
Vanduffel, W., Fize, D., Mandeville, J. B., Nelissen, K., Van
Hecke, P., Rosen, B. R., Tootell, R. B. H., & Orban, G. A.
682
Journal of Cognitive Neuroscience
(2001). Visual motion processing investigated using contrast
agent-enhanced fMRI in awake behaving monkeys. Neuron,
32, 565–577.
Vanduffel, W., Fize, D., Peuskens, H., Denys, K., Sunaert, S.,
Todd, J. T., & Orban, G. A. (2002). Extracting 3D from
motion: Differences in human and monkey intraparietal
cortex. Science, 298, 413–415.
Van Oostende, S., Sunaert, S., Van Hecke, P., Marchal, G., &
Orban, G. A. (1997). The kinetic occipital (KO) region in
man: An fMRI study. Cerebral Cortex, 7, 690–701.
Vogels, R., & Orban, G. A. (1986). Decision processes in
visual discrimination of line orientation. Journal of
Experimental Psychology: Human Perception and
Performance, 12, 115–132.
Wallach, H., & O’Connell, D. N. (1953). The kinetic depth
effect. Journal of Experimental Psychology, 45, 205–217.
Watson, J. D. G., Myers, R., Frackowiak, R. S. J., Hajnal, J. V.,
Woods, R. P., Mazziota, J. C., Shipp S., & Zeki S. (1993).
Area V5 of the human brain: Evidence from a combined
study using positron emission tomography and magnetic
resonance imaging. Cerebral Cortex, 3, 79–94.
Xiao, D. K., Marcar, V. L., Raiguel, S. E., & Orban, G. A.
(1997). Selectivity of macaque MT/V5 neurons for
surface orientation in depth specified by motion.
European Journal of Neuroscience, 9,
956–964.
Zeki, S., Watson, J. D., Lueck, C. J., Friston, K. J., Kennard, C.,
& Frackowiak, R. S. (1991). A direct demonstration of
functional specialization in human visual cortex. Journal
of Neuroscience, 11, 641–649.
Volume 16, Number 4