Anterior Regions of Monkey Parietal
Cortex Process Visual 3D Shape
Jean-Baptiste Durand,1,5Koen Nelissen,1,5Olivier Joly,1,5Claire Wardak,1James T. Todd,2J. Farley Norman,3
Peter Janssen,1Wim Vanduffel,1,4and Guy A. Orban1,*
1Lab Neuro- en Psychofysiologie, K.U. Leuven, Medical School, Campus Gasthuisberg, Herestraat 49, B-3000, Leuven, Belgium
2Department of Psychology, Ohio State University, 142 Townshend Hall, Columbus, OH 43210, USA
3Department of Psychology, Western Kentucky University, 1906 College Heights Boulevard, Bowling Green, KY
4Athinoula A. Martinos Center for Biomedical Imaging, 13th Street, Charlestown, MA 02129, USA
5These authors contributed equally to this work.
of visually guided actions, like reach-to-grasp
movements, which require extracting the 3D
shape and position of objects from 2D retinal
images. Using fMRI in behaving monkeys, we
investigated the role of the intraparietal cortex
in processing stereoscopic information for re-
covering the depth structure and the position
in depth of objects. We found that while several
areas (CIP, LIP, and AIP on the lateral bank; PIP
and MIP on the medial bank) are activated by
stereoscopic stimuli, AIP and an adjoining por-
tion of LIP are sensitive only to depth structure.
Furthermore, only these two regions are sensi-
tive to both the depth structure and the 2D
shape of small objects. These results indicate
that extracting 3D spatial information from ste-
reo involves several intraparietal areas, among
which AIP and anterior LIP are more specifically
engaged in extracting the 3D shape of objects.
Primates are unique in possessing both a versatile manip-
ulative tool, the grasping hand (Napier, 1980), and an effi-
stereovision (Julesz, 1971; Wheatstone, 1838). Stereo-
scopic vision provides robust information about the shape
and position of objects along the third dimension of visual
space (i.e., their depth structure and position in depth),
overcoming the loss of information inherent to the projec-
tion of a 3D visual scene onto 2D retinas (Howard and
Rogers, 2002). Assessing the 3D shape of objects and
their position in 3D space is important for selecting proper
hand configurations for grasping them (Castiello, 2005;
Jeannerod, 1986; Smeets and Brenner, 1999) and appro-
priate hand trajectories for reaching them (Jeannerod,
1981), respectively. Several intraparietal sulcus (IPS)
regions are involved in the visual control of movements:
the anterior intraparietal (AIP) area in grasping (Gallese
et al., 1994; Sakata et al., 1995; Taira et al., 1990), the lat-
eral intraparietal (LIP) area in saccades, and the medial
intraparietal (MIP) area in reaching (Andersen and Buneo,
2002; Snyder et al., 1997). Yet, surprisingly little is known
concerning how stereoscopic information is integrated
into the control of goal-directed actions in the intraparietal
cortex (Goodale and Milner, 1992; Ungerleider and
Stereovision allows the visual system to extract the
depth structure of objects through the spatial integration
of binocular disparity (Howard, 2002; Rogers and Cage-
nello, 1989). Combined with information regarding their
2D shape on the retina, depth structure provides a de-
scription of the 3D shape of objects, required for the con-
trol of grasping movements. Yet, it is unknown whether or
not the anterior intraparietal (AIP) area gains access to 3D
2000), a finding which has been taken as evidence for 3D
shape selectivity in this area. However, the use of objects
differing along the three dimensions of space in this study
does not preclude that AIP neurons are selective only for
the 2D retinal shape of objects. Notably, such selectivity
for 2D shapes has been found in the lateral intraparietal
(LIP) area (Lehky and Sereno, 2007; Sereno and Maunsell,
1998), whose involvement in depth structure processing
is unclear (Nakamura et al., 2001; Sereno et al., 2002;
Vanduffel et al., 2002). In contrast, it has been established
that neurons in the caudal intraparietal (CIP) area process
the depth structure of planar surfaces (Tsutsui et al., 2005)
from binocular disparity (Shikata et al., 1996; Taira et al.,
2000) and/or monocular depth cues (Tsutsui et al., 2001,
3D surfaces and are weakly selective for the 2D shape
of their bounding contours (Sakata et al., 1999; Shikata
et al., 1996), questioning their involvement in 3D shape
processing (Sakata et al., 1998, 2005). To date, neurons
processing the shape of small visual objects along the
three dimensions of space (i.e. selective both to their
depth structure and to their 2D shape) have been found
Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc. 493
only in a small region of the infero-temporal cortex (Jans-
sen et al., 1999, 2000; Orban et al., 2006).
Besides its use in recovering the depth structure of 3D
objects, stereovision also provides valuable information
regarding the position of visual objects and their arrange-
ment in 3D space. Such pieces of 3D spatial information
are important for steering the hand toward an object
(Jeannerod, 1981) while avoiding potential obstacles (Tre-
silian, 1998). Since the medial intraparietal (MIP) area
controls arm-reaching movements (Buneo and Andersen,
2006; Snyder et al., 1997), its involvement in processing
these positional and structural aspects of the 3D visual
scene is likely but remains to be tested. Selectivity for the
position in depth of stereo targets has been shown only in
LIP (Genovesio and Ferraina, 2004; Gnadt and Mays,
1995), where such information is used for controlling eye
movements in 3D space.
Here, we used functional imaging techniques with be-
experiment, the intraparietal areas involved in processing
structural and positional stereoscopic information. Stimuli
were designed to engage regions processing the depth
structure of either 3Dobjects or3Darrangements of visual
elements. Previous imaging studies have investigated 2D
shape processing (Denys et al., 2004; Sawamura et al.,
2005), stereoscopic depth processing (Tsao et al., 2003),
and the extraction of depth structure from monocular
cues (Sereno et al., 2002; Vanduffel et al., 2002), but these
studies did not allow one to localize the regions involved
in processing shape information along all three dimen-
sions of space. We performed two additional experiments
to identify the regions more specifically engaged in pro-
cessing the 3D shape of visual objects. Since many of the
objects we handle daily are typically bounded by small,
curved surfaces yielding complex 2D shape outlines,
these experiments were designed to identify the regions
sensitive to the stereoscopic depth structure (curvature
and orientation in depth) and the 2D shape of small and
complex visual objects.
Experiment 1: Structural and Positional Depth
Processing in the Intraparietal Cortex
The aims of the first experiment were to obtain an exhaus-
tive picture of the intraparietal regions implicated in pro-
cessing structural and positional stereoscopic information
and also to compare the processing of depth structures
from stereo and from motion. We used stimuli composed
of connected random-line segments (Figures 1A and Fig-
ure S4Afoundin the SupplementalData available withthis
article online), as used in previous motion experiments
Figure 1. IPS Regions Processing Stereoscopic Information in Experiment 1
(A) Examples ofstimuli forthethreeconditions(3Dstructure,3Dposition, andNodisparity)and schematic representationofthecorresponding stereo
(B) Regions sensitive to structural and positional stereoscopic information are projected onto the flattened representations of left and right IPS, color
coded in red and in yellow, respectively, with mixed sensitivity indicated in orange (p < 10?5uncorrected, masked by all stimulus conditions versus
fixation baseline at p < 10?3uncorrected). Blue outlines delineate the regions sensitive to structural depth from motion (same statistical threshold).
White dotted lines indicate the AIP/LIP borders derived from the saccade-related activity (same statistical threshold). Gray open symbols demarcate
anatomically defined neighboring areas: Opt, PG, PFG, and PF on the inferior parietal lobule (Rozzi et al., 2006), and V6 and V6A on the parieto-
occipital sulcus (Luppino et al., 2005).
494 Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc.
3D Shape Processing in Monkey IPS
(Orban et al., 1999; Vanduffel et al., 2002). Such stimuli
can be considered either as 3D objects (resembling
partially unfolded paper clips) or as collections of line seg-
ments forming 3D structures. They contain both first- and
second-order depth, defined by the spatial orientation of
the segments and by their connections, respectively.
In the stereo test, sensitivity to depth structure was
assessed by contrasting stimulus conditions in which
binocular disparity specified 3D patterns of connected
segments (3D structure; Figure 1A, left column) or 2D
fronto-parallel patterns away from the fixation plane (3D
position; Figure 1A, central column). Note that depth
structure in such stereo stimuli can be recovered from ori-
entation disparity and/or disparity gradients. We targeted
sensitivity to position in depth (zero-order depth) by con-
trasting the condition 3D position with a no-disparity con-
dition (Figure 1A, right column) in which equivalent stimuli
were systematically displayed in the fixation plane. We
scanned three animals while they performed a demanding
high-acuity fixation task (Sawamura et al., 2005; Vanduffel
et al., 2001). To assess sensitivity to depth structure from
motion, we used monocular versions of the same stimuli.
Motion specified either rotating 3D patterns of connected
segments (3D motion) or 2D patterns translating horizon-
tally in the fixation plane (2D motion).
Figure 1B presents, overlaid onto flattened representa-
tions of the left and right intraparietal sulcus (IPS; see
Experimental Procedures), results of the group analysis
(SPM99) for the stereo sensitivity to structural informa-
tion (red), to positional information (yellow), and to both
(orange). Several regions are stereosensitive, with mixed
sensitivities to structural and positional information lo-
cated mainly in the posterior half of the IPS (both lateral
and medial banks). The posterior activation on the lateral
bank corresponds to area CIP, where neurons have been
shown to respond selectively to the 3D orientations and
positions of rod stimuli (Sakata et al., 1998). It also closely
matches the architectonically defined lateral occipital pa-
rietal (LOP) area (Lewis and Van Essen, 2000; Figure S1)
and a region previously documented for its 2D shape
sensitivity and named pIPS (Denys et al., 2004). The sec-
dorsal to CIP to a location close to the anterior tip of the
IPS. It exhibits a heterogeneous pattern of depth sensitiv-
ity, with positional sensitivity in the back, structural sensi-
tivity in the front, and an intermediate region of mixed
sensitivity, which extends further ventrally. The white dot-
ted lines in Figure 1B indicate the border between LIP and
AIP. It was derived from the saccade-related activity
(Baker et al., 2006; Gnadt and Andersen, 1988) obtained
from an independent experiment (C. Wardak et al., 2005,
Soc. Neurosci., abstract; see Experimental Procedures)
showing that LIP, but not AIP, responded to saccadic eye
movements (Figure 2). The location (y ??5 mm) of this
border agrees with other studies (Luppino et al., 1999;
Murata et al., 2000), and it reveals that AIP is sensitive
Figure 2. Path Activity Profiles for the
Lateral Bank Activations in Experiment 1
(A) Paths running along postero-anterior axes
on the IPS lateral banks, passing through
CIP, LIP, and AIP. Black symbols indicate the
flat map segments constituting the paths (one
per coronal level; from ?14 to +2 mm).
(B) MR signal change (± standard error of the
mean) along the paths for the subtractions 3D
structure – 3D position (red) and 3D position –
No disparity (yellow). Filled symbols indicate
the visually active segments for which MR sig-
nal change was significantly above zero (one-
tailed t test), both for the group (p < 0.001)
and for 2/3 of the individuals (p < 0.01). Note
that, while results issued from path activity
profiles and those given by SPM99 are very
consistent with each other, slight differences
can arise due to the use of unsmoothed data
and additional statistical requirements (signifi-
cance for 2/3 of the individuals) in the path
(C and D) Same as (B) for the subtraction 3D
motion – 2D motion in the 3D motion test (C),
and for the subtraction Saccades – Visual
control in the Saccade test (D). (n, number of
Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc. 495
3D Shape Processing in Monkey IPS
only to depth structure from stereo, while the heteroge-
neous pattern of depth sensitivity described above mainly
belongs to LIP.
We drew paths passing through CIP, LIP, and AIP di-
rectly onto the flattened IPS representations (Figure 2A)
and plotted the magnetic resonance (MR) signal change
along these paths for contrasts of interest (Figures 2B–
2D; see Experimental Procedures). Red and yellow ‘‘path
activity profiles’’ in Figure 2B indicate, respectively, stereo
sensitivity to structural (3D structure ? 3D position) and
positional (3D position – no disparity) information (the
0% level corresponds to an equal MR signal change in
the two conditions). Filled symbols indicate data points
(flat map segments) with significant sensitivity (i.e., signif-
icantly above the 0% difference level) and significant acti-
vation (compared to fixation) at the group level and for at
least 2/3 of the individuals. These path activity profiles
confirm the results drawn at the group level: CIP is sensi-
tive to both structural and positional information while AIP
is sensitive only to structural information. They also indi-
cate that the heterogeneous stereodepth sensitivity in
LIP emanates from opposing sensitivity gradients, with in-
creasing sensitivity to structural information and decreas-
its anterior end. Note that enlarging the width of these
paths (five segments instead of one at each coronal level)
had little effect on the activity profiles (Figure S2), indicat-
ing that similar conclusions would have been drawn with
slightly different paths.
On the medial bank, two posterior regions were sensi-
tive to both structural and positional information from ste-
reo (Figure 1B). Their location, anterior to areas V6/V6A
(Luppino et al., 2005), correspond to MIP and to the ante-
rior portion of the posterior intraparietal (PIP) area as
defined by Lewis and Van Essen (2000). The MR signal
change sampled along paths passing through MIP and
ual subjects, the stereo sensitivity of these medial bank
areas both for structural (Figure 3B, red curve) and posi-
tional (yellow curve) information. Once again, enlarging
thewidth ofthesepathshadlittle effect onthe activitypro-
files (Figure S2). The presence of saccade-related activity
in MIP (Figure 3D) is in line with a previous single cell study
(Snyder et al., 2000). Note that despite their spatial prox-
imity, PIP differs from MIP, and also from CIP (Figure 2D),
by the absence of saccade-related activity.
Since a weak sensitivity to kinetic depth (Wallach and
O’Connell, 1953) has been described in the monkey intra-
parietal cortex (Vanduffel et al., 2002), we assessed its
involvement in processing depth structure from motion
using monocular versions of the same stimuli. Sensitivity
to depth structure from motion was assessed by contrast-
ing 3D motion and 2D motion conditions. The same three
monkeys as those used in the stereo test, plus an
Figure 3. Path Activity Profiles for the
Medial Bank Activations in Experiment 1
(A) Paths running along ventro-dorsal axes on
the IPS medial banks, from the fundus to the
medial lips, and passing through PIP and MIP.
Black symbols represent the flat map seg-
ments constituting the paths (in adjoining
coronal segments at ?11 mm, from the fundus
to PIP, and at ?10 mm, from MIP to the medial
(B–D) MR signal change (± SEM) along these
paths for the subtractions 3D structure – 3D
position (red) and 3D position – No disparity
(yellow), in the first stereo experiment (B), for
the subtraction 3D motion – 2D motion in the
3D motion test (C), and for the subtraction
Saccades – Visual control in the Saccade test
(D). Same conventions as Figure 2.
496 Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc.
3D Shape Processing in Monkey IPS
additional monkey included in a previous study (Vanduffel
et al., 2002), were involved in this motion test. As shown
in Figure 1B (blue outlines), only AIP (with possibly a slight
extension into ventral LIP) and the ventral part of PIP were
sensitive to structural information specified by motion.
Plotting the MR signal change for the subtraction 3D mo-
tion – 2D motion along the same paths as those used for
the stereo test confirmed the sensitivity of AIP (Figure 2C)
and PIP (Figure 3C) to depth structure from motion at the
group and at the individual-subject level (see also Fig-
ure S2 for confirmation with larger paths).
sitivity to depth from motion found only in PIP (Figure 3C)
and saccade-related activity only in MIP (Figure 3D). Im-
portantly, while the depth structure of random lines spec-
ified by stereo activates a large intraparietal network,
equivalent information defined by motion engages only
a restricted network in the IPS.
Experiment 2: Depth Structure Processing for Stereo
Surfaces in the Intraparietal Cortex
parietal regions most specifically engaged in processing
the depth structure of small and relatively complex visual
objects. We used stereo random-dot surfaces bounded
by irregular 2D shape outlines (Figures 4A and 4B and
Figure S4B), whose 3D structure is processed by neurons
in the infero-temporal cortex (Janssen et al., 1999, 2000).
In interleaved runs, we tested for differences in the sensi-
and orientation in depth (first-order depth; Figure 4B). We
scanned three monkeys (two of which were involved in the
stereo and motion tests of the first experiment) in a 2 3 2
factorial design with four stimulus conditions (3D struc-
parity; see Experimental Procedures). We identified depth
structure sensitivity, for either curvature or orientation in
depth, by the interaction between disparity (disparity ver-
sus no disparity conditions) and depth order (structural
versus positional conditions). Position in depth sensitivity
was assessed by contrasting the 3D position condition
and its control condition with no disparity.
As shown in Figure 4C for the group of three monkeys,
sensitivity to the curvature in depth of these small stereo
surfaces (red and orange) was restricted to AIP and an
adjoining portion of LIP. Sensitivity to their orientation in
depth (pink outlines) largely overlapped, although it ex-
tended slightly less into LIP. Sensitivity to structural and
positional information from stereo (orange) was again
found in LIP.
Using the same lateral paths (Figure 5A) as those in the
first experiment (Figure 2A), we assessed the sensitivity to
structural depth information, either curvature (Figure 5B)
or orientation (Figure 5C) by plotting the MR signal change
for the subtraction 3D curvature (or orientation) ? 3D
Figure 4. IPS Regions Sensitive to the Curvature and Orientation in Depth of Stereo Surfaces in Experiment 2
Examples of stimuli for the 3D curvature (A) and 3D orientation (B) conditions, and schematic representation of the corresponding stereo percepts.
Several curvature and slant profiles specified by binocular disparity were used for testing 3D curvature and 3D orientation processing in interleaved
runs. (C) Regions sensitive to curvatures in depth and positions in depth are projected onto the flattened representations of left and right IPS with the
same conventions as Figure 1. Pink outlines delineate the regions sensitive to orientations in depth from stereo. (*sensitivity to structural depth, either
curvature or orientation, was assessed by the interaction between disparity and depth order).
Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc. 497
3D Shape Processing in Monkey IPS
position after subtracting their respective control lacking
disparity. Sensitivity to positional information was derived
from by the subtraction 3D position – no disparity. These
path activity profiles confirmed, for the individual subjects
as well, that AIP is sensitive both to the curvature in depth
(Figure 5B, red curve) and to the orientation in depth (Fig-
ure 5C, pink curve) of these stereo surfaces, but not to
their position in depth (Figures 5B and 5C, yellow curves).
opposing sensitivity gradients for structural and positional
information in LIP, as shown in the first experiment
Thus, although less extensive than in the first experi-
ment, the stereo activations found in AIP and the adjoining
However, in striking contrast, posterior parietal regions
were only weakly (CIP) or not at all (MIP, PIP) engaged
by these small stereo surfaces bounded by complex 2D
Experiment 3: 2D Shape Processing
in the Intraparietal Cortex
After identifying the regions involved in processing the
depth structure of small objects, we studied 2D shape
sensitivity within the intraparietal cortex by complement-
ing and reanalyzing a previous monkey imaging study
(Denys et al., 2004) and performing an additional control
The same three monkeys as those used in the first ex-
periment were involved in the experiment that replicated
the protocol of Denys et al. (2004). Stimuli were grayscale
images and line drawings of objects that were contrasted
with spatially scrambled versions of the same stimuli (Fig-
ure 6A) to assess 2D shape sensitivity. Figure 6C presents
the 2D shape-sensitive regions (pale and dark blue) ob-
tained in the group analysis from the main effect of scram-
bling. In agreement with this previous study, we found two
regions sensitive to 2D shapes on the lateral bank of the
IPS. The posterior region, called pIPS in this previous
as defined in the first experiment. The anterior region in-
cludes both AIP and the anterior part of LIP, distinguished
by the saccade-related activity (Figure 2D). Using the
same lateral paths (Figure 7A) as those used in previous
analyses (Figures 2 and 5), we plotted the difference in
MR signal change for the subtraction intact – scrambled
images (Figure 7B) for the grayscale images (circular sym-
bols) and line drawings (square symbols) separately. Both
profiles indicatethat 2Dshapesensitivity peaks withinCIP
and near the border between LIP and AIP.
The line drawing stimuli represent only impoverished
versions of the grayscale stimuli, lacking the detailed
shape-related information contained in the objects’ sur-
faces and defined by their texture and/or luminance
(Kourtzi and Kanwisher, 2000). To reveal the intraparietal
regions sensitive to this additional information, we looked
at the interaction between image type and scrambling.
found in the anterior, but notposterior, regions. Inspection
for grayscale images in LIP and AIP (dark blue asterisks
indicate significant difference between the curves for the
group and at least 2/3 of the individuals). Thus, filling the
surfaces of objects defined by their 2D shape outlines in-
duces additional activation only in these anterior regions,
indicating that they integrate information about contours
and surfaces for representing visual objects.
Using smaller grayscale images of objects (size of 4.6?
on average against 10?on average in the study of Denys
Figure 5. Path Activity Profiles for the
Lateral Bank Activations in Experiment 2
(A) Same paths as Figure 2.
(B) MR signal change (± SEM) along the paths
for the subtractions 3D curvature –3D position
(*after subtraction of their respective No
disparity control), in red, and 3D position ?
No disparity, in yellow, in the 3D curvature test.
(C) Same as (B) for the subtraction 3D orienta-
disparity, in yellow, in the 3D orientation test.
Same conventions as Figure 2.
498 Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc.
3D Shape Processing in Monkey IPS
et al.), Sawamura et al. (2005) found only one region sen-
sitive to 2D visual shapes, situated in the anterior portion
of the IPS lateral bank. To assure that the discrepancy
between these studies depended on stimulus size rather
than on a difference between the sets of images, we per-
formed a control experiment with a smaller version (50%
scaling) of the grayscale stimuli (Figure 6B) used by Denys
et al. (2004), adjusting the stimulus size to approximate
those in the study of Sawamura et al. (2005). We scanned
two of the three monkeys involved in the test with large
2D shapes. Magenta outlines in Figure 6C indicate the
2D shape-sensitive regions obtained by contrasting the
intact and scrambled versions of these smaller grayscale
images of objects. It can be seen that 2D shape sensitivity
disappears in CIP but is still present within LIP and AIP.
Pathactivity profiles for theintact –scrambled subtraction
(Figure 7C) confirmed the sensitivity of LIP and AIP to
small 2D shapes at the group level and in individual sub-
jects. The interaction term between scrambling and size
(2-way ANOVA) was significant in CIP, (Figure 7C; aster-
isks), indicating that CIP responds to large, but not small,
2D shapes. These activity profiles also indicate that 2D
shape sensitivity peaks at the same location, near the
AIP-LIP border, for large (Figure 7B; circular symbols)
and small (Figure 7C) 2D shapes.
The first experiment revealed the involvement of several
intraparietal areas in processing the arrangement in depth
of connected random line segments: CIP, LIP and AIP, on
an extensive network underscores the importance of
stereopsis forvisually guided actions(MelmothandGrant,
2006; Servos et al., 1992; Watt and Bradshaw, 2003) and
contrasts with the restricted network (AIP and part of PIP)
involved in kinetic depth extraction (Vanduffel et al.,2002).
These parietal areas differed markedly regarding both
the type of information and the type of stimuli they pro-
cess. Posterior areas (CIP, PIP, and MIP) are sensitive to
both structural and positional stereo information. In LIP,
stereo-depth sensitivity is inhomogeneous, with opposing
gradients of increasing sensitivity to depth structure and
decreasing sensitivity to position in depth from its poste-
rior to its anterior end. More anteriorly, AIP processes
solely depth structure information specified either by
stereo or motion. The second experiment revealed that,
among these parietal areas, only AIP and the adjoining
portion of LIP are clearly involved in processing the curva-
ture and orientation in depth of small stereo surfaces
bounded by complex 2D shape outlines. The third
Figure 6. IPS Regions Sensitive to 2D Shapes in Experiment 3
(A) Examples of grayscale images and line drawings of objects, presented with their respective scrambled control (Denys et al., 2004; Kourtzi and
(B)Example of a half-sized (from ?10?to?5?on average) grayscale image and its scrambled version as used inthe control experiment (overall size of
the stimuli was identical: 15?).
(C) 2D shape-sensitive regions projected onto the flattened representations of left and right IPS. Blue regions, whether pale or dark, indicate a signif-
icant main effect of scrambling for large 2D shapes. Dark blue regions exhibit in addition a significant interaction between scrambling and image type
in the test with large shapes. Magenta outlines delineate the 2D shape-sensitive regions for the half-sized grayscale images. Same conventions as
Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc. 499
3D Shape Processing in Monkey IPS
experiment showed that LIP and AIP are also sensitive to
2D shapes, whether large or small, and integrate informa-
tion about contours and surfaces. In contrast, CIP, found
to correspond to the 2D shape-sensitive region named
pIPS (Denys et al., 2004) but also to the architectonically
defined area LOP (Lewis and Van Essen, 2000; see Fig-
ure S1), was recruited mainly for large 2D shapes, and re-
sponded chiefly to their contours. These results, drawn at
the group level, were found bilaterally, and they were con-
firmed for at least 2/3 of the individuals with path activity
profiles, ensuring their generality. The same three mon-
keys were involved in the first and third experiment, and
two of these animals were also involved in the second ex-
periment, making unlikely that our results are confounded
by between-group heterogeneity.
Since the parietal cortex is involved in spatial attention
(Colby and Goldberg, 1999; Goldberg et al., 2006), it is im-
portant to assess whether our results could be explained
by the fact that certain stimulus conditions engage the ob-
servers’ attention more strongly than others (for instance,
3D stimuli could capture attention more effectively than
2D stimuli and 2D stimuli more so than their scrambled
counterparts). The attention-demanding high-acuity fixa-
tion task (Sawamura et al., 2005; Vanduffel et al., 2001)
used in the first experiment entails a negative manipula-
tion of spatial attention (drawing attention away from the
stimuli) and is thus presumed to minimize or cancel any
stimulus-driven attentional effect. Nevertheless, a broad
stereo network was revealed in the intraparietal cortex
by this first experiment, arguing against an explanation
of our results based upon an attentional effect. Using a
comparable task, Denys et al. (2004) reached a similar
conclusion concerning 2D shape sensitivity in the IPS.
Moreover, while an attentional explanation would predict
rather homogeneous activation patterns reflecting the
degree of attention captured by different stimulus types,
we observed distinct differences in functional properties
regarding depth and shape processing, between parietal
areas, and even within LIP. In addition, our results are in
agreement with the few single cell studies that addressed
neuronal selectivity in these parietal areas regarding both
depth and shape processing (see below). Differential eye
movements across stimulus conditions is another possi-
ble confound, notably because binocular disparity is
known to evoke fusional vergence eye movements (Boltz
and Harwerth, 1979). However, eye movements were sys-
tematically monitored during scanning and quality of fixa-
tion across stimulus conditions was assessed (Table S1)
so that this potential confound could be ruled out.
have a prominent role in processing the 3D shape of visual
objects, since they are sensitive both to their depth struc-
ture and to their 2D shape. In AIP, neuronal selectivity to
real 3D objects has been documented (Murata et al.,
2000), but with objects differing along the three dimen-
sions of space. Thus, whether this selectivity originated
from the distinct depth structure and/or 2D optical projec-
tion of these objects could not be assessed directly. Since
both sources of information are essential for recovering
3D shape features that can serve to control hand manipu-
lation tasks (Fagg and Arbib, 1998; Jeannerod et al., 1995;
Sakata et al., 1995), such a result was expected, but still
needed to be established. In LIP, our results confirm the
neuronal selectivity documented for position in depth
(Genovesio and Ferraina, 2004; Gnadt and Mays, 1995)
and for 2D shapes (Lehky and Sereno, 2007; Sereno and
Maunsell, 1998), they also fit with the report of 3D orienta-
tion-selective neurons in locations that could encompass
LIP as defined here (Nakamura et al., 2001). Importantly,
we also obtained evidence for the heterogeneous nature
Figure 7. Path Activity Profiles for the
Lateral Bank Activations in Experiment 3
(A) Same paths as Figure 2.
(B) MR signal change (± SEM) along the paths
for the subtraction Intact – Scramble for the
grayscale images (circles) and for the line
drawings (squares) with large 2D shapes.
Dark blue asterisks indicate significant differ-
ence (two-tailed t test) between these two sub-
tractions, at the group level (p < 0.001) and for
at least 2/3 of the individuals (p < 0.01).
(C) Same as (B) for the subtraction Intact –
Scramble in the test with small grayscale
shapes. Black asterisks indicate a significant
interaction in the 2-way ANOVA with stimulus
size and scrambling as factors (p < 0.05 at
the group level and for the two individuals,
Bonferroni correction for the number of tests).
Same conventions as Figure 2.
500 Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc.
3D Shape Processing in Monkey IPS
of LIP, with opposing sensitivity gradients for structural
and positional stereo information. These gradients fore-
shadow the sensitivity for structural, but not positional,
stereo information in AIP, indicating that AIP and the ad-
joining portion of LIP arelikely to work in close relationship
for processing the depth structure of 3D objects. The spa-
tial accuracy required for fine-scale analysis of 3D shape
the presence of a central visual field representation lo-
cated in the anterior part of LIP (Ben Hamed et al., 2001;
Blatt et al., 1990; Fize et al., 2003).
In CIP, sensitivity to both structural and positional ste-
reo information was revealed using random-line stimuli in
line with the joint neuronal encoding of the 3D orientation
and 3D position of rod stimuli described for this area
(Sakata et al., 1998). At first glance, the weak (if any) sen-
sitivity for small 3D surfaces appears to contradict previ-
ous single cell reports (Taira et al., 2000; Tsutsui et al.,
2001, 2003). However, our surfaces differed from those
employed in these previous studies by the complexity of
their contours (generally surfaces with square-shaped
outlines have been used in the single cell studies), sug-
gesting that CIP could have a limited role in processing
detailed 3D shape features. Our finding that CIP is only
sensitive to the contours of large 2D shapes supports this
view. This stimulus-size effect fits the observation that
neuronal response strength increases monotonically
with the size of the stimuli in CIP (Sakata et al., 1999;
Shikata et al., 1996), and probably explains why very large
stimuli have been used to investigate neuronal properties
in this area (Nakamura et al., 2001; Sakata et al., 1998;
for the fact that, contrary to the small stereosurfaces used
in the second experiment, large stereocheckerboard
surfaces efficiently activate CIP (Tsao et al., 2003). In ad-
dition, this size effect confirms that stimulus size was the
critical difference between the two previous imaging stud-
ies concerning the involvement of CIP (pIPS) in 2D shape
processing (Denys et al., 2004; Sawamura et al., 2005).
Overall, these observations suggest that CIP is more in-
volved in recovering the spatial arrangement of large
background elements in the visual scene than in recover-
ing the 3D shape of small objects.
Our finding that both MIP and PIP process stereoscopic
information fits with the known involvement of MIP in
reaching arm movements (Andersen and Buneo, 2002;
Snyder et al., 1997) and with the report (Nakamura et al.,
2001) of 3D orientation selective cells in a location encom-
passing PIP as defined here. Despite their spatial proxim-
ity, these areas are functionally segregated by the sac-
cade-related activity found only in MIP (Snyder et al.,
2000) and the sensitivity to kinetic depth found only in PIP.
Moreover, these areas differ from neighboring area CIP by
the absence of 2D shape sensitivity, suggesting that they
house representations of the visual scene layout that lack
object-related information. Such representations could be
sufficient for the control of actions containing guidance
and obstacle-avoidance components but no direct inter-
action with objects, such as arm-reaching movements
By showing the prominent role of AIP and anterior LIP in
3D shape processing, our results question the proposal
that CIP extracts 3D-shape-related information that is
forwarded to AIP for controlling hand manipulation tasks
(Sakata et al., 1998, 2005). Sensitivity to 3D shape fea-
tures emerges in anterior LIP and comes with the uncou-
pling of structural and positional stereo information, sug-
gesting that salient or behaviorally relevant objects could
be isolated from the background in LIP (Gottlieb, 2007;
Gottlieb et al., 1998) for analysis of their 3D shape in ante-
rior IPS. It will be the aim of future experiments to test this
hypothesis. Also, it will be important to assess whether
additional input from ventral visual areas, and in particular
the inferotemporal (IT) cortex, which houses neurons se-
lective for complex 2D shapes (Tanaka, 1996), is required
to recover fine information about the 3D shape of objects
the selectivity of a distinct group of inferotemporal neu-
rons for the depth structure of the stereo surfaces used
in the second experiment (Janssen et al., 1999, 2000)
and the direct connections reported between IT and ante-
rior IPS (G. Luppino et al., 2004, Soc. Neurosci., abstract;
Webster et al., 1994).
By using the fMRI technique in behaving monkeys, we
studied the involvement of parietal areas in processing
of stereo information (structural and/or positional) and
3D-shape-related information. This study goes beyond
previous imaging studies (Sereno et al., 2002, Tsao et al.,
2003, Vanduffel et al., 2002) by demonstrating not only
that different parietal areas process distinct aspects of
visual 3D space in line with their involvement in distinct
sensorimotor functions, but also that 3D shape features
are specifically represented in anterior intraparietal re-
gions, where such information is required for the efficient
control of hand manipulation tasks.
In total, six male rhesus monkeys (4–7 kg; 4–7 years old) were
scanned. Animal care and experimental procedures met the national
and European guidelines and were approved by the ethical committee
of the K.U. Leuven Medical School. Procedures related to fMRI tech-
niques with behaving monkeys have been described in detail (Fize
et al., 2003; Nelissen et al., 2005, 2006; Vanduffel et al., 2001) and
are only briefly presented here.
Monkeys sat in a sphinx position within the horizontal bore of the
magnet (1.5 T MR scanner Sonata; Siemens), a radial receive-only
lucent screen 54 cm from the eyes, and visual stimuli were rear-pro-
jected from a Barco 6300 LCD projector. One eye was monitored
during scanning using a pupil-corneal reflection tracking system
(50 Hz; RK-726PCI, Iscan). A contrast agent (MION, or an equivalent
session to improvebothcontrast-to-noise ratio (Leite et al.,2002; Van-
duffel et al., 2001) and spatial selectivity of the MR signal (Mandeville
andMarota,1999; Zhao etal.,
2006) compared toBOLD
Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc. 501
3D Shape Processing in Monkey IPS
Time series were analyzed using SPM99 and MATCH software.
Functional volumes (whole brain GE-EPI; TR = 2.4 s; TE = 27 ms; 32
sagittal slices; 8 mm3isotropic voxels) were rigidly coregistered with
a template anatomy (M12; 0.04 mm3isotropic voxels) in stereotaxic
space. They were further warped to this template (MATCH algorithm;
Chef d’Hotel et al., 2002; Hermosillo et al., 2002; Figure S2A), resliced
to 1 mm3isotropic voxels, and smoothed with a Gaussian kernel
(FWHM = 1.5 mm). Group analyses (fixed effects) were performed
with equal number of volumes per monkey, supplemented with single
subject analysis. Statistical threshold was set at p < 10?5uncorrected
(masked at p < 10?3for overall activation relative to fixation baseline).
Realignment and eye movement traces were included as covariates of
series and verify that monkeys fixated equally well across the different
conditions (Table S1).
In the stereo test of the first experiment, monkeys (M3, M5, and M11)
performed a high-acuity fixation task to prevent disparity-driven ver-
gence eye movements. They interrupted an infrared beam with the
hand to signal sudden changes in orientation of a small fixation bar
(whose size was set to obtain 80% of correct detections) and received
fluid reward for correct responses (Sawamura et al., 2005; Vanduffel
et al., 2001).
Monkeys performed a passive fixation task in the motion test of the
first experiment (M1, M3, M5, and M11), in the second stereo experi-
ment (M3, M6, and M11), and in the tests with large 2D shapes (M3,
They received fluid reward for gazing at a fixation target and maintain-
ing fixation within a small window (±1?, occasionally increased to ±
1.5?vertically to accommodate an artifact caused by the scanning
In the Saccade test (C. Wardak et al., 2005, Soc. Neurosci., ab-
stract), which was based on a previous study (Koyama et al., 2004),
monkeys (M3, M5, and M9) had to saccade toward a red visual target
(0.1?3 0.1?) jumping pseudo-randomly among three locations along
cade had to be initiated within 500 ms after target appearance and the
fixation held (within a window of about 1?3 2?) until displacement of
the visual target to a new position (after about 2.2 s of steady fixation).
Mean saccade latency was 350 ms and, on average, a saccade was
performed each 2.8 s. In the visual control condition, monkeys had
cessively flashed for 350 ms, with 2.2 s intervals, at 7?or 14?of eccen-
tricity either to the left or to the right of the fixation target. Direction and
eccentricity of the visual targets in the saccade condition and visual
distractors in the visual control condition were balanced (1/2 left and
1/2 right; 2/3 at 7?and 1/3 at 14?).
A block design was used in all the experiments. Blocks (conditions) of
10–15 functional volumes immediately succeeding one another were
embedded in time series during which 160–225 volumes were ac-
quired. Condition order was pseudorandomized between the time
series, but not within a time series (containing 2–4 repetitions of the
complete sequence of conditions). All the experiments contained a
baseline condition with a fixation spot (0.3?diameter), or a fixation bar
in the first stereo experiment (0.2?3 0.05?for M5 and M3 and 0.15?3
avoid adaptation during thevisual conditions, stimuli wererefreshed at
a frequency of 0.4 Hz in the stereo and motion tests of the first exper-
iment (new pattern of random lines) at a frequency of 1 Hz in the sec-
1.67 Hz in the third experiment (new intact or scrambled 2D shape).
In the first experiment, stimuli (Figures 1A and S4A) were composed
of 9 to 12 connected segments forming random angles. They were
about 9?in diameter, and the lengths of the segments varied between
0.5?and 9?(width 0.05?). In the stereo test, stimuli were presented bin-
ocularly through red/green filter stereoglasses. There were 3 stimuli
conditions, with binocular disparity (range of ± 0.6?) specifying 3D
structures of random lines (3D structure), 2D patterns outside of the
Structural and positional depth sensitivity was assessed by the con-
trasts 3D structure – 3D position and 3D position – no disparity, re-
spectively. Presentation was monocular in the motion test. There were
also three stimuli conditions, with motion specifying rotating 3D struc-
tures (3D motion), translating 2D patterns (2D motion), or without mo-
tion (static). Sensitivity to kinetic depth specifying 3D structure was
revealed by contrasting 3D motion and 2D motion.
consisted of stereo random-dot surfaces embedded in 1 of 4 different
2Dshapeoutlines (Janssenetal.,1999).Theymeasured 5.6?35.6?on
average, with a dot density of 50% and a dot size of 0.065?, and they
were also displayed through red/green filter stereoglasses. Several
curvatures (1, 1/2 or 1/4 vertical sinusoidal cycle and antiphase coun-
terparts) and slants (±37?slants about the horizontal, vertical or obli-
que axes) specified by binocular disparity (range of ± 0.5?) were
used for testing 3D curvature and 3D orientation processing in inter-
leaved runs. There were four stimulus conditions in both tests (3D
structure, either orientation or curvature inspace,3D positionand their
respective controls with no disparity). The ‘‘no disparity’’ controls were
generated by presenting identical stereo half-images to both eyes
(either from the 3D structure or 3D position stimuli). Structural depth
sensitivity was assessed by the interaction between 3D information
sensitivity and disparity sensitivity, while position in depth processing
was targeted by the contrast 3D position – no disparity.
In the third experiment, four stimuli conditions were used for the test
of line drawings and grayscale images of objects (Denys et al., 2004;
Kourtzi and Kanwisher, 2000). Both the main effect of scrambling
and the interaction with image type were assessed. For the small 2D
shapes (?5?on average), only grayscale images were used. They
were similar to the large grayscale images except that the scrambling
grid was removedand the objects (but not the white background) were
half-sized. There were four stimulus conditions, corresponding to in-
tact or scrambled versions that were either static or moving. For this
study, we targeted 2D shape sensitivity by contrasting the conditions
with intact and scrambled versions of the static grayscale images.
Finally, in the Saccade test, saccade-related activity was obtained
by contrasting the Saccade and Visual control conditions.
Flattening of the Intraparietal Sulcus
We designed a procedure to flatten the IPS specifically in order (1) to
avoid the substantial distortions inherent to the flattening of whole
hemispheres or even large cortical regions (Van Essen, 2005), (2) to
allow a clear visualization of stereotaxic and anatomical landmarks,
and (3) to better control the projection of functional data. A custom-
designed algorithm was developed to capture strips of gray matter
(Figure S2B) within successive coronal sections of the template anat-
omy (M12) covering the whole left and right IPS (from y = ?18 to +8
mm, in 1 mm steps). These strips were subdivided into adjoining 1
mm segments, whose center was used to derive a flattened represen-
tation (Figure S2C) that best preserved the intrinsic 3D geometry of the
IPS (with a nonlinear multidimensional scaling; ISOMAP algorithm;
Tenenbaum et al., 2000). Voronoi triangulation was then applied to en-
close each segment center in the 2D space representation. Thin lines
linking segments belonging to the same coronal section indicated an-
tero-posterior levels. The lips and fundus of the IPS were indicated by
thick lines passing through the segments corresponding to these ana-
tomical landmarks in each coronal section (gray arrows in Figure S2B).
Statistical scores were assigned to each segment by placing a 2D
sampling grid upon their central region (coronal orientation; spacing
0.2 mm; radius 0.3 mm) and computing the median value of the sam-
pled t-scores (calculated by SPM99). Restricting the sampling to the
502 Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc.
3D Shape Processing in Monkey IPS
segments’ central region avoided possible contamination between
facing segments on the medial and lateral banks of the sulcus. We in-
dicated segments that reached statistical significance by color-coding
their corresponding patches on the flat maps.
Path Activity Profiles
ity, (2) the magnitude of the effects we observed, and (3) how the ac-
tivity profiles evolve within, but also between, the activated regions.
Symmetrical paths were drawn directly onto the flattened representa-
tions of the left and right IPS. Lateral paths run along postero-anterior
axes on the IPS lateral banks, passing through CIP, LIP, and AIP, with
one segment per coronal level (from ?14 to +2 mm). Medial paths run
along ventro-dorsal axes on the medial banks, with adjoining coronal
segments at y = ?11 mm, from the fundus to PIP, and at ?10 mm,
from MIP to the medial lip.
Time courses of adjusted signal (calculated by SPM99) were ex-
tracted from unsmoothed functional volumes (otherwise similar to the
smoothed preprocessed volumes) to minimize spatial correlations be-
tween neighboring segments. For each segment of these paths, a me-
dian time course was computed using the same sampling grid as for
into blocks according to the experimental design, and we derived the
MR signal for each block by averaging its constituent time points (ex-
cluding the first three to take into account the hemodynamic delay). To
obtain the mean MR signal change (%) between two conditions, the
MR signals associated to the blocks belonging to these two condition
were subtracted from each other and averaged (the variability ex-
pressed between blocks rather than between successive time points
avoid possible temporal correlations between repeated measures).
In plots of the mean MR signal change along the paths (± standard
error of the mean), filled symbols indicate data points (flat map seg-
ments) with significant sensitivity (i.e. significantly above the 0% differ-
ence level) and significant activation (compared to fixation) at the
group level and for at least 2/3 of the individuals. Significance was as-
sessed with a one-tailed t test, both at the group level (p < 0.001) and
for the individual subjects (p < 0.01) using only the blocks included in
the group analysis. Note that slight differences can arise between
the results issued from the analysis of these path activity profiles and
those given by SPM99 due to the use of unsmoothed data and addi-
tional statistical requirements (significance for 2/3 of the individuals)
for the path activity profiles.
In addition, we performed complementary analyses to ensure that
the path activation profiles were representative for the regions that
were crossed (Figure S2). Paths were enlarged by adding two seg-
ments on both sides of each segment initially contained in the paths
(Figure S2A). Large paths were thus ?5 mm wide, as opposed to
?1 mm wide for the initial paths. For both the lateral (Figure S2B)
and medial (Figure S2C) paths, activity profiles obtained with wider
paths were very similar to the ones obtained with the initial paths,
arguing in favor of the representativeness of the latter.
The Supplemental Data for this article can be found online at http://
The authors are indebted to A. Coeman, C. Fransen, M. Depaep, W.
Depuydt, P. Kayenbergh, and G. Meulemens for help with the experi-
ments and to S. Raiguel, R. Vogels, R. Vandenberghe, G. Luppino, M.
Imbert, and R. Andersen for comments on earlier versions of the man-
uscript. The work was supported by grants FWO G151.04, GOA 2005/
18, IUAP 5/04, EF/05/014, GSKE, R01 EB000790, EU-projects Insight
2+ and Neurobotics and Fyssen Fundation (J.-B.D). The laboratoire
Guerbet (Roissy, France) provided the contrast agent Sinerem.
Received: November 17, 2006
Revised: May 24, 2007
Accepted: June 28, 2007
Published: August 1, 2007
Andersen, R.A., and Buneo, C.A. (2002). Intentional maps in posterior
parietal cortex. Annu. Rev. Neurosci. 25, 189–220.
Baker, J.T., Patel, G.H., Corbetta, M., and Snyder, L.H. (2006). Distri-
bution of activity across the monkey cerebral cortical surface, thala-
mus and midbrain during rapid, visually guided saccades. Cereb. Cor-
tex 16, 447–459.
BenHamed,S.,Duhamel,J.R., Bremmer, F.,and Graf,W.(2001).Rep-
monkeys: A quantitative receptive field analysis. Exp. Brain Res. 140,
Blatt, G.J., Andersen, R.A., and Stoner, G.R. (1990). Visual receptive
field organization and cortico-cortical connections of the lateral intra-
parietal area (area LIP) in the macaque. J. Comp. Neurol. 299, 421–
Boltz, R.L., and Harwerth, R.S. (1979).Fusional vergence ranges of the
monkey: A behavioral study. Exp. Brain Res. 37, 87–91.
Buneo, C.A., and Andersen, R.A. (2006). The posterior parietal cortex:
Sensorimotor interface for the planning and online control of visually
guided movements. Neuropsychologia 44, 2594–2606.
Castiello, U. (2005). The neuroscience of grasping. Nat. Rev. Neurosci.
Chef d’Hotel, C., Hermosillo, G., and Faugeras, O. (2002). Flows of
diffeomorphisms for multimodal image registration. Proc. IEEE Int. S.
Biol. Im. 7–8, 753–756.
Colby, C.L., and Goldberg, M.E. (1999). Space and attention in parietal
cortex. Annu. Rev. Neurosci. 22, 319–349.
Denys, K., Vanduffel, W., Fize, D., Nelissen, K., Peuskens, H., Van Es-
sen, D., and Orban, G.A. (2004). The processing of visual shape in the
cerebral cortex of human and nonhuman primates: A functional mag-
netic resonance imaging study. J. Neurosci. 24, 2551–2565.
Fagg, A.H., and Arbib, M.A. (1998). Modeling parietal-premotor inter-
actions in primate control of grasping. Neural Netw. 11, 1277–1303.
Fize, D., Vanduffel, W., Nelissen, K., Denys, K., Chef d’Hotel, C., Fau-
geras, O., and Orban, G.A. (2003). The retinotopic organization of
primate dorsal V4 and surrounding areas: A functional magnetic reso-
nance imaging study in awake monkeys. J. Neurosci. 23, 7395–7406.
Gallese, V., Murata, A., Kaseda, M., Niki, N., and Sakata, H. (1994).
Deficit of hand preshaping after muscimol injection in monkey parietal
cortex. Neuroreport 5, 1525–1529.
Genovesio, A., and Ferraina, S. (2004). Integration of retinal disparity
and fixation-distance related signals toward an egocentric coding of
distance in the posterior parietal cortex of primates. J. Neurophysiol.
Gnadt, J.W., and Andersen, R.A. (1988). Memory related motor plan-
ning activity in posterior parietal cortex of macaque. Exp. Brain Res.
Gnadt, J.W., and Mays, L.E. (1995). Neurons in monkey parietal area
LIP are tuned for eye-movement parameters in three-dimensional
space. J. Neurophysiol. 73, 280–297.
cades, salience and attention: The role of the lateral intraparietal area
in visual behavior. Prog. Brain Res. 155, 157–175.
Goodale, M.A., and Milner, A.D. (1992). Separate visual pathways for
perception and action. Trends Neurosci. 15, 20–25.
Gottlieb, J. (2007). From thought to action: The parietal cortex as
a bridge between perception, action, and cognition. Neuron 53, 9–16.
Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc. 503
3D Shape Processing in Monkey IPS
Gottlieb, J.P., Kusunoki, M., and Goldberg, M.E. (1998). The represen-
tation of visual salience in monkey parietal cortex. Nature 391, 481–
Hermosillo, G., Chef d’Hotel, C., and Faugeras, O. (2002). Variational
Methods for Multimodal Image Matching. Int. J. Comput. Vis. 50,
Howard, I.P. (2002). Basic Mechanisms, Volume 1 (Toronto: I. Por-
Howard, I.P., and Rogers, B.J. (2002). Depth Perception, Volume 2
(Toronto: I. Porteus).
Janssen, P., Vogels, R., and Orban, G.A. (1999). Macaque inferiortem-
poral neurons are selective for disparity-defined three-dimensional
shapes. Proc. Natl. Acad. Sci. USA 96, 8217–8222.
Janssen, P., Vogels, R., and Orban, G.A. (2000). Selectivity for 3D
shape that reveals distinct areas within macaque inferior temporal
cortex. Science 288, 2054–2056.
Jeannerod, M. (1981). Intersegmental coordination during reaching at
naturalvisualobjects.InAttention andPerformances IX,J.LongandA.
Baddley, eds. (Hillsdale, NJ: Erlbaum), pp. 153–168.
cortically mediated visuomotor pattern. Behav. Brain Res. 19, 99–116.
Jeannerod, M., Arbib, M.A., Rizzolatti, G., and Sakata, H. (1995).
Grasping objects: The cortical mechanisms of visuomotor transforma-
tion. Trends Neurosci. 18, 314–320.
Julesz, B.(1971). Foundations ofCyclopeanPerception(Chicago:Uni-
versity of Chicago Press).
Kourtzi, Z., and Kanwisher, N. (2000). Cortical regions involved in
perceiving object shape. J. Neurosci. 20, 3310–3318.
Koyama, M., Hasegawa, I., Osada, T., Adachi, Y., Nakahara, K., and
Miyashita, Y. (2004). Functional magnetic resonance imaging of ma-
caque monkeys performing visually guided saccade tasks: Compari-
son of cortical eye fields with humans. Neuron 41, 795–807.
Lehky, S.R., and Sereno, A.B. (2007). Comparison of shape encoding
in primate dorsal and ventral visual pathways. J. Neurophysiol. 97,
Leite, F.P., Tsao, D., Vanduffel, W., Fize, D., Sasaki, Y., Wald, L.L.,
Dale, A.M., Kwong, K.K., Orban, G.A., Rosen, B.R., et al. (2002).
Repeated fMRI using iron oxide contrast agent in awake, behaving
macaques at 3 Tesla. Neuroimage 16, 283–294.
Lewis, J.W., and Van Essen, D.C. (2000). Mapping of architectonic
ital cortex. J. Comp. Neurol. 428, 79–111.
Luppino, G., Murata, A., Govoni, P., and Matelli, M. (1999). Largely
segregated parietofrontal connections linking rostral intraparietal cor-
tex (areas AIP and VIP) and the ventral premotor cortex (areas F5 and
F4). Exp. Brain Res. 128, 181–187.
Luppino, G., Hamed, S.B., Gamberini, M., Matelli, M., and Galletti, C.
(2005). Occipital (V6) and parietal (V6A) areas in the anterior wall of the
parieto-occipital sulcus of the macaque: A cytoarchitectonic study.
Eur. J. Neurosci. 21, 3056–3076.
Mandeville, J.B., and Marota, J.J. (1999). Vascular filters of functional
MRI: Spatial localization using BOLD and CBV contrast. Magn. Reson.
Med. 42, 591–598.
the control of reaching and grasping. Exp. Brain Res. 171, 371–388.
Murata, A., Gallese, V., Luppino, G., Kaseda, M., and Sakata, H.
(2000). Selectivity for the shape, size, and orientation of objects for
grasping in neurons of monkey parietal area AIP. J. Neurophysiol.
Nakamura, H., Kuroda, T., Wakita, M., Kusunoki, M., Kato, A., Mikami,
A., Sakata, H., and Itoh, K. (2001). From three-dimensional space vi-
sion to prehensile hand movements: The lateral intraparietal area links
the area V3A and the anterior intraparietal area in macaques. J. Neuro-
sci. 21, 8174–8187.
Napier, J.R. (1980). Hands (London: Geaorge Allen & Unwin Ltd).
Nelissen, K.,Luppino, G.,Vanduffel,W.,Rizzolatti,G.,and Orban, G.A.
(2005). Observing others: Multiple action representation in the frontal
lobe. Science 310, 332–336.
Nelissen, K., Vanduffel, W., and Orban, G.A. (2006). Charting the lower
superior temporal region, a new motion-sensitive region in monkey
superior temporal sulcus. J. Neurosci. 26, 5929–5947.
Orban, G.A., Sunaert, S., Todd, J.T., Van Hecke, P., and Marchal, G.
(1999). Human cortical regions involved in extracting depth from mo-
tion. Neuron 24, 929–940.
Orban, G.A., Janssen, P., and Vogels, R. (2006). Extracting 3D struc-
ture from disparity. Trends Neurosci. 29, 466–473.
Rogers, B., and Cagenello, R. (1989). Disparity curvature and the per-
ception of three-dimensional surfaces. Nature 339, 135–137.
Rozzi, S., Calzavara, R., Belmalih, A., Borra, E., Gregoriou, G.G.,
Matelli, M., and Luppino, G. (2006). Cortical connections of the inferior
parietal cortical convexity of the macaque monkey. Cereb. Cortex 16,
Sakata, H., Taira, M., Murata, A., and Mine, S. (1995). Neural mecha-
nisms of visual guidance of hand action in the parietal cortex of the
monkey. Cereb. Cortex 5, 429–438.
Sakata, H., Taira, M., Kusunoki, M., Murata, A., Tanaka, Y., and Tsut-
sui,K.(1998).Neural coding of3Dfeatures ofobjectsfor handaction in
the parietal cortex of the monkey. Philos. Trans. R. Soc. Lond. B Biol.
Sci. 353, 1363–1373.
Sakata, H., Taira, M., Kusunoki, M., Murata, A., Tsutsui, K., Tanaka, Y.,
Shein, W.N., and Miyashita, Y. (1999). Neural representation of three-
dimensional features of manipulation objects with stereopsis. Exp.
Brain Res. 128, 160–169.
Sakata, H., Tsutsui, K., and Taira, M. (2005). Toward an understanding
of the neural processing for 3D shape perception. Neuropsychologia
Sawamura, H., Georgieva, S., Vogels, R., Vanduffel, W., and Orban,
G.A. (2005). Using functional magnetic resonance imaging to assess
adaptation and size invariance of shape processing by humans and
monkeys. J. Neurosci. 25, 4294–4306.
Sereno, A.B., and Maunsell, J.H. (1998). Shape selectivity in primate
lateral intraparietal cortex. Nature 395, 500–503.
Sereno, M.E., Trinath, T., Augath, M., and Logothetis, N.K. (2002).
Three-dimensional shape representation in monkey cortex. Neuron
Servos, P., Goodale, M.A., and Jakobson, L.S. (1992). The role of bin-
Shikata, E.,Tanaka,Y.,Nakamura, H.,Taira,M.,andSakata,H.(1996).
Selectivity of the parietal visual neurones in 3D orientation of surface of
stereoscopic stimuli. Neuroreport 7, 2389–2394.
Smeets, J.B., and Brenner, E. (1999). A new view on grasping. Motor
Control 3, 237–271.
Snyder,L.H.,Batista, A.P.,and Andersen, R.A. (1997).Coding ofinten-
tion in the posterior parietal cortex. Nature 386, 167–170.
Snyder, L.H., Batista, A.P., and Andersen, R.A. (2000). Saccade-
related activity in the parietal reach region. J. Neurophysiol. 83,
Taira, M., Mine, S., Georgopoulos, A.P., Murata, A., and Sakata, H.
(1990). Parietal cortex neurons of the monkey related to the visual
guidance of hand movement. Exp. Brain Res. 83, 29–36.
Taira, M., Tsutsui, K.I., Jiang, M., Yara, K., and Sakata, H. (2000). Pa-
rietal neurons represent surface orientation from the gradient of binoc-
ular disparity. J. Neurophysiol. 83, 3140–3146.
504 Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc.
3D Shape Processing in Monkey IPS
Tanaka, K. (1996). Inferotemporal cortex and object vision. Annu. Rev.
Neurosci. 19, 109–139.
Tenenbaum, J.B.,de Silva, V., and Langford, J.C. (2000). A global geo-
metric framework for nonlinear dimensionality reduction. Science 290,
Tresilian, J.R. (1998). Attention in action or obstruction of movement?
A kinematic analysis of avoidance behavior in prehension. Exp. Brain
Res. 120, 352–368.
Tsao, D.Y., Vanduffel, W., Sasaki, Y., Fize, D., Knutsen, T.A., Mande-
ville, J.B., Wald, L.L., Dale, A.M., Rosen, B.R., Van Essen, D.C., et al.
(2003). Stereopsis activates V3A and caudal intraparietal areas in ma-
caques and humans. Neuron 39, 555–568.
Tsutsui, K., Jiang, M., Yara, K., Sakata, H., and Taira, M. (2001). Inte-
gration of perspective and disparity cues in surface-orientation-selec-
tive neurons of area CIP. J. Neurophysiol. 86, 2856–2867.
relates for perception of 3D surface orientation from texture gradient.
Science 298, 409–412.
Tsutsui, K., Taira, M., and Sakata, H. (2005). Neural mechanisms of
three-dimensional vision. Neurosci. Res. 51, 221–229.
Ungerleider, L.G., and Mishkin, M. (1982). Two cortical visual systems.
In Analysis of Visual Behavior, D.J. Ingle, M.A. Goodale, and R.J.
Mansfield, eds. (Cambridge, MA: MIT Press), pp. 549–586.
Van Essen, D.C. (2005). A Population-Average, Landmark- and Sur-
face-based (PALS) atlas of human cerebral cortex. Neuroimage 28,
Vanduffel, W., Fize, D., Mandeville, J.B., Nelissen, K., Van Hecke, P.,
Rosen, B.R., Tootell, R.B., and Orban, G.A. (2001). Visual motion pro-
cessing 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., and Orban, G.A. (2002). Extracting 3D from motion: Differences
in human and monkey intraparietal cortex. Science 298, 413–415.
Wallach, H., and O’Connell, D.N. (1953). The kinetic depth effect. J.
Exp. Psychol. 45, 205–217.
Watt, S.J., and Bradshaw, M.F. (2003). The visual control of reaching
and grasping:Binoculardisparityand motionparallax.J.Exp.Psychol.
Hum. Percept. Perform. 29, 404–415.
Webster, M.J., Bachevalier, J., and Ungerleider, L.G. (1994). Connec-
tions of inferior temporal areas TEO and TE with parietal and frontal
cortex in macaque monkeys. Cereb. Cortex 4, 470–483.
Wheatstone, C. (1838). Contribution to the physiology of vision - Part
the first On some remarkable and hitherto unobserved phenomena
of binocular vision. Philos. Trans. R. Soc. Lond. B Biol. Sci. 128,
Zhao, F., Wang, P., Hendrich, K., Ugurbil, K., and Kim, S.G. (2006).
Cortical layer-dependent BOLD and CBV responses measured by
spin-echo and gradient-echo fMRI: Insights into hemodynamic regula-
tion. Neuroimage 30, 1149–1160.
Neuron 55, 493–505, August 2, 2007 ª2007 Elsevier Inc. 505
3D Shape Processing in Monkey IPS