Cerebral Cortex June 2007;17:1423--1432
doi:10.1093/cercor/bhl054
Advance Access publication August 21, 2006
Face Configuration Processing in the
Human Brain: The Role of Symmetry
Chien-Chung Chen1,2, Kai-Ling C. Kao1 and
Christopher W. Tyler2
1
Department of Psychology, National Taiwan University,
Taipei 106, Taiwan and 2Smith-Kettlewell Eye Research
Institute, San Francisco, CA 94115, USA
Keywords: fMRI, fusiform, intraoccipital sulcus, inverted face,
object perception, occipital face area
Introduction
Face recognition and discrimination may be one of the most
developed perceptual skills of visual object processing. An adult
can discriminate and recognize hundreds of faces (Bharick and
others 1975). Much evidence has shown that face perception
cannot be achieved by analyzing facial features alone and that
facial configuration, or the spatial relationships among facial
features, is crucial to face perception (Fantz 1961; Valentine
1988; O’Toole and others 1994; Leder and Bruce 2000; Webster
and others 2004).
There are, however, many possible spatial relations among
facial features. It is not clear what types of spatial relations are
essential for a human observer to analyze the facial configuration. Much attention on facial configuration has focused on the
relative distance between features (e. g., Fellous 1997), such as
the distance from the center of the face to several landmarks on
a face (e.g., Anderson and Wilson 2005), from the eyes to the
eyebrows (e.g., Brown and Perrett 1993), from the eyes to the
nose and the mouth (Hosie and others 1988), and so on. On
the other hand, there are reports that configuration cues such as
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mirror symmetry are important in face perception. There is
a well-established relationship between facial symmetry and
perceived attractiveness (or beauty) of potential mates in
humans (Grammer and Thornhill 1994; Mealey and others
1999; Rhodes and others 2001, 2002; Jacobsen and Hofel
2002). There is also a preference for facial asymmetry that is
related to emotion expressiveness (Swaddle and Cuthill 1995;
Zaidel and others 1995; Kowner 1996). Recently, Rhodes and
others (2005) showed that humans can detect symmetry better
in upright faces than in either inverted faces or contrast
reverted faces and argued that there should be a mechanism
in the human visual system specific for the symmetry of faces.
Brain areas supporting face processing have been reported
both in monkey (Perrett and others 1982) and in humans
(Kanwisher and others 1997; McCarthy and others 1997;
Halgren and others 1999; Haxby and others 2000). In particular,
part of the fusiform gyrus and the inferior occipital gyrus have
been reported as specific for face perception and are designated
the fusiform face area (FFA, Kanwisher and others 1997) and
occipital face area (OFA, Halgren and others 1999; Rossion and
others 2003), respectively (although there is disagreement on
the exact role of the FFA, see Gauthier and others 1999; Haxby
and others 2001). It is, however, not clear whether these brain
areas are involved in the analysis of local facial features, facespecific configurations, or other gestalt properties of faces. In
behavioral studies, the configuration-specific system is generally
isolated by contrasting performance for upright faces and
inverted faces (Yin 1969; Carey and Diamond 1977; Thompson
1980). A manipulation that causes performance degradation in
inverted relative to upright faces is considered to reflect
processing by mechanisms specific to the absolute facial configuration because the relative configuration of the features is
undisturbed by rotation.
There have been several neuroimaging studies contrasting
brain activation to upright and inverted faces, but significant
differential activations for upright face vs. inverted face have
not been reported in either FFA or OFA (Kanwisher and others
1998; Aguirre and others 1999; Haxby and others 1999) until
recently (Yovel and Kanwisher 2004). Because faces are much
less recognizable when upside down, the implication of the
predominantly negative result is that these areas are responding
to the basic aspects of facial stimuli that are equally present
when the face is inverted, such as the local features and the
configuration aspects such as symmetry, rather than the higherlevel perceptual processes of facial recognition, which are
substantially degraded by inversion.
Our purpose here is to identify brain areas specific for the
configuration properties of facial symmetry. Given recent
reports on brain areas responding to image symmetry per se
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Symmetry is an important cue in face perception. We manipulated
symmetry and other configurational variables to study their role in
face processing in the human brain. We employed 2 types of
symmetry: image symmetry (where one part of the image is defined
as the mirrored transform of the other part about an axis) and
object symmetry (where the spatial relationships among the image
components are interpreted as parts of a symmetric 3-dimensional
object). We compared blood oxygenation level dependent responses in healthy human observers for upright front-view faces
with responses to different symmetry-controlled images. The
cortical areas activated by the face images, relative to Fouriermatched scrambled images, were the fusiform (FFA) and occipital
(OFA) face areas, the middle occipital gyri (MOG), and areas around
the superior temporal and intraoccipital sulci (IOS). Contrasting
faces and their image-symmetric scrambled versions showed
a similar activation pattern except in the right OFA, suggesting
an involvement in facial symmetry processing. The upright versus
inverted faces (with the same image symmetry but unfamiliar
object identity) showed robust differential activation in the FFA,
OFA, MOG, IOS, and precuneus. The response to frontal-view
versus 3/4-view faces (having the same object symmetry but
disrupted image symmetry) showed little differential activation in
the FFA or the OFA but strong responses in the MOG and IOS,
suggesting that face processing in the FFA and the OFA is holistic
and viewpoint invariant.
1. To reveal all relevant areas supporting face processing
(except those for early visual processing), we first contrasted
brain activations between faces and asymmetric scrambled
versions of the same images with identical Fourier energy.
These images should generate the same net activation for
arrays of neurons acting as local linear filters.
2. To identify the cortical areas responding to symmetry per se,
we compared the activation for the asymmetric random
images and symmetricized versions of the same images (as in
Tyler and others 2005a).
3. To identify cortical regions involved in the processes of face
recognition, we then compared brain activation of the frontview faces and their inverted versions. Inverted faces are
known to disrupt the facial configuration mechanisms and
degrade the function of the face recognition mechanisms.
Thus, because inverted faces maintain the same local
features, the same image symmetry, and the same object
symmetry as the upright faces, the null hypothesis is that
they should produce no activation to regions containing
either local mechanisms of symmetry processing for facial
recognition. Hence, any significant differences in activation
for the upright versus inverted faces should reveal the
operation of holistic facial configuration mechanisms.
4. To examine whether the differential activation patterns
from (3) are due to face-specific symmetry or to early image
symmetry processing, we also contrasted front-view upright
faces with their phase-scrambled versions that were vertically symmetric. A contrast between faces and vertically
symmetric scrambled images should reveal all relevant areas
supporting face processing that are insensitive to symmetry.
A comparison of the last 2 experiments should thus uncover
whether areas that are attributed to face processing are
actually responding to the symmetry of the faces rather than
more informative cues.
5. Finally, to study the role of object versus image symmetry
(under the assumption that faces are symmetric objects),
we compared the responses to upright frontal-view faces and
3/4-view faces of the same persons. The 3/4-view faces
retain the same semantic and object-centered properties
as the frontal-view faces but have radically altered image
symmetry. Cortical areas encoding image symmetry should
be differentially activated by this comparison, but those
encoding object symmetry or semantic content should show
little or no differential activation with the change in
viewpoint of the same faces.
Methods
Stimuli
Figure 1 shows examples of the stimuli used in our experiment. We had
5 types of images: upright frontal-view faces, inverted faces, 3/4-view
faces, symmetric scrambled images, and asymmetric scrambled images.
The face images were taken from The Facial Recognition Technology
(FERET) Database (Phillips and others 2000) provided by the National
Institute of Standards and Technology, USA. We computed the symmetry index (Tyler and others, 2003) of the frontal-view faces of the
1010 subjects in the FERET database and selected the 36 face images
with greatest symmetry index values. The symmetry index is computed
based on the power spectrum of the Fourier transform of the face
images. Here we were only interested in the horizontal symmetry.
Hence, we computed the difference of the power at the points (kx, ky)
and (–kx, ky), where kx and ky are horizontal and vertical spatial
frequencies of the images (in the upper half-plane, excluding the
horizontal axis). The symmetry index is computed as a function of the
root mean square difference of the power between corresponding
frequencies summed over the spectrum.
The inverted faces were simply the upside-down versions of the same
36 images. The 3/4-view images were pictures of the same persons
available from the database with their head rotated 67.5° either to their
left (17 images) or to their right (19 images). The 2 types of scrambled
images were created by manipulating the phase spectrum of the frontalview face images. We first normalized the face images by subtracting
their mean luminance values to remove the DC component and then
computed their Fourier transforms. The phase spectra were scrambled
Figure 1. Examples of the stimulus types used. (a) Frontal face, (b) inverted face, (c) 3/4-view face, (d) symmetricized phase-zeroed face image, (e) phase-scrambled face image.
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(Sasaki and others 2005; Tyler and others 2005a) and the
behavioral evidence for facial symmetry mechanisms (Rhodes
and others 2005), we are interested in the role of symmetry in
brain areas responding to faces. We may conceptualize 2 types
of face symmetry. The first type, ‘‘image symmetry,’’ occurs
when one image component is a mirrored transform of another
image component about some axis of transformation. This type
of symmetry specifies the direct spatial relations between the
parts of the 2-dimensional (2D) projections of the faces and is
not concerned with the interpretation of the image as an object
in space. The second type of symmetry is ‘‘object symmetry,’’
which specifies the spatial relationships among the components
of the image interpreted as the representation of a 3D object.
Hence, those components or facial features will be processed
through a face gestalt or 3D template of the human head. This
kind of object symmetry may not be consistent with image
symmetry due to an asymmetric viewpoint of the observer or
the rotation of the object’s axis of symmetry away from the line
of sight. Thus, a 3/4 view of a symmetric face forms an
asymmetric image, even though it is the image of a symmetric
object and can be understood to have accurate object symmetry. Our experiments were designed to test the role of these 2
types of symmetry in the facial representations of the FFA and
the OFA. In detail, our goals were as follows:
randomly for the asymmetric scrambled images and set to zero phase for
the symmetric scrambled images. We then generated the control images
by taking inverse Fourier transforms of the original amplitude spectra
combined with the new phase spectra of the 2 types. Note that this
novel zero-phase manipulation introduces noticeable edge structures
throughout the images similar to that of the intact faces, so it tends to
equate for nonlinear edge processing in the face images in addition to
the presence of bilateral symmetry. The luminance and contrast of the
inverse Fourier-transformed images were normalized to match the mean
luminance and contrast energy of the face images. The phase zeroed
scrambled images had point symmetry, so they were converted to
bilateral symmetry by inverting their left half relative to the right half.
A fourth-power Gaussian aperture (1/e scale parameter = 3.2°) was
applied to all images to remove image features outside face areas (cf.,
Tyler and Chen forthcoming). A fixation point of 6.759 3 6.759 size was
inserted at the center of the face image.
Data Acquisition and Analysis
The images were collected with a Bruker 3T scanner located at National
Taiwan University. Within each scanning session, both functional (T2*
weighted, BOLD) responses and anatomical (T1 weighted) images were
acquired in identical planes. The images were collected in 20 transverse
planes parallel to the anterior commissure--posterior commissure line.
An echo-planar imaging (EPI) sequence (Stehling and others 1991) was used
to acquire the functional data (time repetition = 3000 ms, time echo =
40 ms, flip angle = 90°, voxel resolution = 2.34 3 2.34 3 3 mm). A highresolution anatomical (T1 weighted) MRI volume scan of the entire head
was run once on each observer (voxel size = 1 3 1 3 1 mm). The main
experiment lasted 225 s (75 images). The first 9 s (3 images) were
excluded from further analyses to avoid the start-up transient. Thus, the
data analyzed for each scan spanned 216 s (72 images). To correct headmotion artifacts, we used SPM (Friston and others 1995) to realign the
EPI images acquired. The realigned images, as well as the anatomic
images, were then normalized to a standard template with SPM. The
normalized images were fed to the mrVista software (Wandell and
others 2000) for coregistration, data analysis, and 3D visualization.
Statistical analysis of the BOLD activation was based on the spectral
correlation between the BOLD activation time series and the experimental sequence (Engel and others 1997). For each run, the Fourier
transform was calculated for each BOLD time series. The spectral
correlation, or coherence, was then computed as the power at the
frequency of block alternation divided by the square root of the energy
of the spectrum for each voxel. The signal amplitude is given by the
square root of the signal power.
There were situations where we needed to test differential contrasts
across 2 or more block design runs. For this purpose, we followed the
procedure proposed by Joseph and others (2002). That is, we first
identified a region of interest (ROI) defined by a specific parametric
contrast from coherence maps for individual runs. The signal amplitude
of the averaged waveform over the voxels in this ROI from each
Localizers
In addition to the main experiments, all observers participated in
localizer experiments in a separate session, in order to identify relevant
brain areas reported in the literature. The lateral occipital complex
(LOC) was identified by the differential BOLD activation to pictures of
common objects (objects that can be seen everyday life) versus blockscrambled versions of themselves, as developed by Kourtzi and
Kanwisher (2001). The human motion sensitive complex (hMT+) was
identified by the differential BOLD activation to low-contrast moving
dots and their stationary versions. The moving dots (4.59 by 4.59 square)
oscillated between expansion and contraction once per second with
a spatial density of 2% and a speed of 4.5°/s. The retinotopic areas were
identified with checkerboard rotating wedges that spanned 180° and
rotated 30° every 3 s, taking 36 s to go around the display, with 6 periods
in one retinotopic run. The symmetry areas were identified by the
differential BOLD activation to the symmetric versus the asymmetric
scrambled images.
Result and Discussion
Localizers
The symmetry localizer consisted of two types of nonsense
scrambled images computed from the Fourier spectrum of the
face stimuli: one vertically symmetric and the other nonsymmetric. Figure 2(a) shows the activation map averaged across
observers on 3 views of the inflated brain. The gray shading
denotes the gyral (light) and sulcal (dark) layout. The pseudocolor denotes the average coherence between the response
waveform and the experimental sequence. The predominant
symmetry response occurred in the inferior occipital gyrus, the
middle occipital gyrus (MOG) and the areas around intraoccipital sulcus (IOS). The MOG activation is posterior to
hMT+ (red contour) and partially overlaps with LOC (magenta
contour). The dorsal predominance of the symmetry response is
consistent with that observed by Tyler and others (2005a) and
Sasaki and others (2005).
Figure 2(b) shows areas localized by localizers on a flatmap.
The flatmaps here and in the remainder of this paper had their
center near the occipital poles and extended 80 mm in radius
around this point. The areas delineated by yellow borders are
the first-tier retinotopic areas (V1--V3), identified with a rotating
wedge. The criterion for delineating visual areas is discussed
elsewhere (Tyler and others 2005b). The magenta borders
denote the LOC as identified by contrasting BOLD activation to
pictures of objects and their scrambled versions. The red
borders denote hMT+ as identified by the motion localizer.
The blue contours delimit the extent of the symmetry response.
The outline of these areas will be shown for reference in the
subsequent flat maps.
Brain Areas for Face Processing
Figure 3 (row 1) shows the averaged activation map across
observers for a face localizer contrasting the upright frontalview faces and the asymmetric scrambled images. We show
selected slices of all conditions contrasting upright frontview faces with other images in this figure for ready comparison. The pseudocolored voxels in the figures denote voxels
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Procedure
We used the blood oxygenation level dependent (BOLD) signal from
a block-design functional Magnetic Resonance Imaging (fMRI) paradigm
to measure the cortical response to the stimulus contrasts. Each of the 4
experimental runs had 18-s epochs of upright frontal-view faces
alternating with 18-s epochs of one of the other image types in 6 cycles
(36-s period) of the 2-epoch block alternation. Each 18-s epoch
consisted of 18 presentations of the images for 850 ms followed by a
150-ms blank period. To keep the observers’ attention on the presented
images regardless of block content, the observers were instructed to
press a response key when the currently presented image physically
matched the previous one (one-back task).
Stimuli were delivered with MRVision 2000 goggles from Resonance
Technology, Inc. (Northridge, CA). At 800 (H) by 600 (V) resolution, the
pixel size of the display was specified as 2.259.
Six observers participated in this study, including 2 of the authors and
4 paid observers naı̈ve to the purpose of the study. All observers had
normal or corrected-to-normal (by the focusing lenses included with
the goggles) visual acuity. All observers gave informed consent for their
participation.
observer was then fed to a repeated measure analysis of variance
(ANOVA) that assessed the effect of conditions for the specified
contrast. In addition, to get detailed information of the differential
contrasts in specific ROIs defined by the localizers, we followed up
significant main effects in the ANOVA with pairwise comparison t-tests
of differences in activation between conditions in the specified ROIs.
with coherence above 0.475 or Bonferroni corrected P-value
(considering all cortical voxels) less than 0.001.
Compared with the scrambled images, the face images
bilaterally activated the fusiform, the inferior occipital, and
the middle occipital gyri areas around the superior temporal
sulcus (STS) and areas around the IOS. The Talairach coordinates (Talairach and Tournoux, 1988) of those activated areas
are given in Table 1. Notice that the first-tier retinotopic areas
did not show significant differential activation between the two
types of images. On average, the BOLD signal modulations in V1
of the left and the right hemispheres were 0.24% and 0.20%
(with confidence intervals of 0.29% and 0.24%), respectively.
These values are not statistically significant and are much
(significantly) smaller than typical V1 responses to contrast
energy change, which is about 1--2% modulation, with a confidence interval of about 10% of this value (Engel and others
1997; Tootell and others 1998; Boynton and others 1999). This
null result demonstrates that our phase spectrum manipulation
equated all the relevant activations in early vision within
experimental error. This is an important result because many
previous approaches to equating images with their scrambled
versions have resulted in significant activation in the early
retinotopic areas (Murray and others 2002, 2004; Altmann and
others 2003, 2004). It is therefore a worthwhile advance to have
1426 Face Symmetry
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Figure 3. Average group activations shown in standardized brain slices for (a) face
localizer, (b) symmetry localizer, (c) face versus inverted face, and (d) frontal versus
rotated faces. Colored symbols indicated mean locations of activations from other
studies (see key). Activation colors as in Figure 2.
Table 1
Brain areas responding to face information
Activated areas
Fusiform
Inferior occipital gyrus
IOS
MOG
Talairach coordinates
Left
Right
Left
Right
Left
Right
Left
Right
(ÿ32, ÿ46, ÿ17)
(28, ÿ57, ÿ14)
(ÿ28, ÿ70, ÿ15)
(29, ÿ77, ÿ15)
(ÿ31, ÿ75, 16)
(24, ÿ86, 13)
(ÿ30, ÿ84, 1)
(27, ÿ88, 1)
developed a form of scrambling that reduces the residual
activation in early areas below the typical level of fMRI
detectability.
The IOS activation extended to a more dorsal region along the
sulcus than did the symmetry localizer. The green symbols
denote the mean locations of the FFA reported in the literature
(triangles: averaged from individuals in Kanwisher and others
1997; diamonds: average reported in Rossion and others 2003;
circle: reported value in Halgren and others 1999). The cyan
symbols denote the OFA reported in Rossion and others (2003).
The fusiform form gyrus activation is consistent with the FFA
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Figure 2. (a) Activation maps for the symmetry localizer (vs. Fourier-equated random
images) averaged across observers on 3 views of the inflated brain. Gyral (light) and
sulcal (dark) denoted by gray shading. Orange color denotes the average activation
pattern. Anterior (A) and posterior (P) directions indicated on underside view. (b) The
symmetry-specific activation (yellow-orange coloration) depicted in flatmaps centered
on the occipital poles. Yellow borders: V1--V3; magenta borders: LOC; red borders:
hMT+. Yellow-orange coloration codes amplitude of significant activation at corrected
P < 0.001 (color bar). The dark blue border denotes the extent of the activated areas.
Figure 4. Activation maps for the face localizer (vs. Fourier-equated random images)
averaged across observers (a) on 3 views of the inflated brain and (b) occipital-pole
flatmaps. Yellow borders: V1--V3; magenta borders: LOC; red borders: hMT+; green
borders: FFA; cyan borders: OFA; black borders: IOS; blue borders: symmetry
activation—Colored symbols indicated locations of activations in individual subjects
from other studies (see key). Activation colors as in Figure 2.
Image Symmetry Effect
The contrast between the upright frontal-view faces and the
symmetric scrambled images (Fig. 3, row 2) was designed to
remove the factor of symmetry from the cortical face response
in the previous condition. This contrast showed significant
activation in the fusiform, the inferior occipital and the middle
occipital gyri, and also the area around the IOS. Figure 5
compares the differential activation (pseudocolor patches) in
relation to the symmetry (blue contour) and the face areas (FFA:
green contours, OFA: cyan contours, and IOS: black contours)
identified above. Qualitatively speaking, the major difference
between this and the previous condition contrasting with
asymmetric scrambled was in the right OFA. The number of
activated voxels dropped from 82 to 10 in the right OFA when
the symmetry information was available in the scrambled
images. The differential contrast (Joseph and others 2002)
between the face versus symmetric scrambled condition and
the face versus asymmetric scrambled was also significant (F5,10 =
9.98, P = 0.0251 < 0.05) in the right OFA. The average response
amplitude drops from 0.33% to 0.19% (t (5) = 3.87, P = 0.0059 <
0.05). On the other hand, the left OFA and the bilateral FFA did
not show significant activation response change when symmetry was present in the scrambled images. The activation
changes were only from 0.49% to 0.46% (t (5) = 0.58, P = 0.29
> 0.05, not significant [NS]) for the left OFA, from 0.49% to
0.41% (t (5) = 1.56, P = 0.09 > 0.05, NS) for the right fusiform,
and 0.44% to 0.35% (t (5) = 1.21, P = 0.14 > 0.05, NS) for the left.
Figure 5. Activation maps for the face responses versus symmetry-equated
scrambled averaged across observers (a) on 3 views of the inflated brain and
(b) occipital-pole flatmaps. FFA: green borders; OFA: cyan borders; IOS: black borders;
blue borders: symmetry activation. Other details as in Figure 2.
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and the inferior occipital gyrus activation is consistent with the
OFA reported in the literature. Regions around the STS have
been reported as relating to face processing both in humans
(Puce and others 1998) and in monkeys (Perrett and others
1982). The IOS activation partially overlaps with the area
identified by the symmetry localizer.
For a better understanding of the spatial relationships
between the activated areas, Figure 4 shows an occipital flatmap
and inflated version of the same activation. As in Figure 2, the
flatmap is centered at the occipital pole and displays the spatial
location of the activation across the cortical surface. The firsttier retinotopic areas and the human motion area, identified in
separate scans, are retained for reference. It may be seen that
the face-specific activation runs in a strip lying between these
two reference regions. The concentrations corresponding to
the FFA and OFA from other studies are identified by triangles
and diamonds, respectively. In addition, there is a pronounced
dorsal activation in the IOS centered at Talairach (–37, 75, 16)
for the left and (24, –86, 13) for the right hemisphere. This
region has rarely been mentioned in previous studies of facespecific activation, but appears to be the strongest site of
activation in the present dataset. The subsequent conditions are
designed to disentangle their particular roles in the agglomeration of cues present in the face localizer.
As shown in Figure 3 (row 3), upright versus inverted faces
showed robust differential activation in the areas in the
fusiform, the inferior occipital, and the middle occipital gyri,
and also the areas around IOS and the precuneus. Figure 6
shows the flatmap version of the same activation. The differential activation in the FFA and the OFA was no less than that
between faces and asymmetric scrambled images (F5,10 =
0.0277, P = 0.88 > 0.05). These results confirm that the
symmetry processing in the OFA found in the previous
condition is indeed face specific, or at least orientation specific
with respect to face stimuli.
BOLD activation for face inversion has been in reported in
many areas throughout the brain (Servos and others 1999;
Leube and others 2003; Yovel and Kanwisher 2004, 2005).
Reports of the face inversion effect in the literature for the FFA,
however, are mixed. Early fMRI studies showed either no
(Aguirre and others 1999; Haxby and others 1999) or a weak
(Kanwisher and others 1998) face inversion effect in the FFA.
More recent fMRI studies have shown a robust face inversion
effect in the FFA (Yovel and Kanwisher 2004, 2005). The Yovel
and Kanwisher (2005) face inversion effect extended beyond
the FFA to an extensive area on the ventral and the lateral
occipital surfaces, which is quite similar to ours. Although the
cause of this discrepancy in the literature is not resolved, it is
possible that the face stimuli used in those studies played a role.
The papers reporting no face inversion effect in FFA (Aguirre
and others 1999; Haxby and others 1999) used stimuli that had
the external contours of the face removed and the one that
Face Configuration/Inverted Face Effect
We next compared mean brain activation for the upright versus
inverted faces. This is an interesting manipulation because it
distinguishes between absolute and relative configuration
effects. An absolute configuration effect is one that is specific
to the particular orientation and scale of the configuration.
For instance, the mouth is located 3° below the eyes with
a horizontal position midway between the eyes. This type of
configuration is also called the first-order configuration in some
face perception literature (Carey and Diamond 1977). A relative
configuration effect is one that maintains all the geometric relations
among a set of features, regardless of their absolute orientation
or scale. For instance, the mouth and the 2 eyes form a triangle
regardless whether the faces are upright, tilted, or inverted. This
type of configuration should not be confused with the secondorder configuration specified in some face perception literature (Carey and Diamond 1977), which refers to the relative
distances between facial features. The relative configuration
here emphasizes the orientation of the configuration, which is
not generally discussed in the second-order configuration
literature. In terms of the particular property of symmetry,
inverted faces are equated to the upright faces with respect to
both the relative and absolute configurations of ‘‘image’’
symmetry. However, the absolute face configuration (or face
template) response would be disrupted by the face inversion.
Hence, if a brain area such as the OFA processes symmetry in
faces in the same way as generic image symmetry, this area
should not show differential activation for upright versus
inverted face stimuli. On the other hand, if the symmetry is
processed as a part of an orientation-specific face gestalt (as
would be implied by our constant environmental exposure to
upright faces), this area should still show differential activation
for these 2 types of faces.
Figure 6. Activation maps for upright faces versus inverted faces averaged across
observers (a) on 3 views of the inflated brain and (b) occipital-pole flatmaps. FFA:
green borders; OFA: cyan borders; IOS: black borders; blue borders: symmetry
activation. Other details as in Figure 2.
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Thus, the data for the latter 3 ROIs are consistent with the null
hypothesis that the face activation in these areas was insensitive
to the symmetry information in the faces, whereas the right OFA
showed a significant symmetry component in its response.
Because the difference between the asymmetric and symmetric scrambled images lies in their image symmetry, the activation
difference between the 2 conditions should reveal the areas
processing 2D image symmetry information. Therefore, the OFA
activation is apparently influenced by image symmetry. However, the OFA is not one of the areas identified by our symmetry
localizer but lies just next to it. The plausible explanation is that
the OFA processes face-specific symmetry information (Rhodes
and others 2005). The adjacent relation between the OFA and
the symmetry areas hints that the OFA may receive input from
nearby symmetry area for facial processing.
The IOS activations, on the other hand, are significantly
stronger for the symmetry-equated face/scrambled contrast
than for the symmetric/asymmetric noise contrast (F5,10 =
17.85, P = 0.0083 < 0.05, for the right hemisphere, F5,10 =
10.39, P = 0.032 < 0.05 for the left; activation change increased
from 0.89% to 1.18%, t (5) = 2.86, P = 0.017 < 0.05 for the right
and from 0.46% to 0.62%, t (5) = 3.73, P = 0.007 < 0.05 for the
left). Thus, although it is the major locus of activation by
symmetry, the IOS is even more strongly activated by the face
configuration with symmetry equated. The implication is that
this is a cortical region specialized for processing configuration
effects, of which symmetry and face arrangements are 2
separate forms.
Object Structure
The upright frontal-view faces and the 3/4-view faces share the
same 3D object structure but not the same image symmetry.
Hence, a brain area for image symmetry would show differential
activation for these 2 types of images, whereas an area
processing symmetry based on the 3D object structure inferred
from the image information should respond equally to these 2
types of faces. Perceptually, we understand that the face is still
symmetric although it is 3D rotated, so there must be some
brain circuitry that carries this perceptual equivalence. This
analysis is supported by the finding that sparsely sampled
information about the positions of object features relies on an
exclusively 3D coding of object properties (Likova and Tyler
2003). The fact that the face retains the same object structure
when 3D rotated relative to the plane of projection can be
appreciated only by a neural circuit that has encoded the 3D
structure of the projected images.
The upright frontal-view faces and the 3/4-view faces showed
less differential activation (Fig. 3, row 4, also see Fig. 7 for
inflated and flat versions) than the face template areas
identified by faces versus inverted faces. The pseudocolor
patches in Figure 7(c) identify the regions showing significant
differential activation (F5,10 = 8.95, P = 0.03 < 0.05) between
faces and inverted faces but not between faces and 3/4-view
faces. This reduction is quite pronounced in the FFA, as more
than 61% of voxels showing significant differential activation for
faces versus inverted faces (52% for the right and 87% for the
left) did not show significant activation in this condition. The
activation modulation reduces from 0.49% for faces versus
inverted faces to 0.20% for faces versus 3/4-view faces in the
left FFA (t (5) = 2.43, P = 0.029 < 0.05). A similar reduction was
observed in the right FFA as well (from 0.43% to 0.25%) though
the difference is not statistically significant (t (5) = 0.79, P = 0.23
> 0.05, NS).
The activated area in the OFA was also substantially reduced
(see Figs 6 vs. 7), although there were some spots still showing
activation. The activation modulation was reduced from 0.49%
to 0.20% (t (5) = 2.43, P = 0.0296 < 0.05) for the left OFA and
0.47% to 0.26% for the right OFA (t (5) = 2.28, P = 0.036 < 0.05)
The implication of these results is that much of the coding in
Figure 7. Activation maps for frontal-view faces versus 3/4-view faces averaged
across observers (a) on 3 views of the inflated brain and (b) occipital-pole flatmaps. (c)
Flatmaps showing the regions of differential activation between faces and inverted
faces but not between faces and 3/4-view faces (yellow-orange coloration). FFA:
green borders; OFA: cyan borders; IOS: black borders; blue borders: symmetry
activation. Other details as in Figure 2.
the FFA and OFA is based on the 3D representation of the faces,
which ‘‘look the same’’ to these neural circuits despite the
radical change in image symmetry. The areas near the IOS and
the MOG, however, still showed robust activation to the 3D
rotation of the faces as 65% (right) to 90% (left) of IOS voxels
showed significant activation in this condition. This strong
response implies that they are coding image symmetry rather
than object symmetry.
To understand this activation, we may consider the factors
that change versus those that are invariant in the image of a 3Drotated face (Fig. 1a vs. 1c). The invariant factors are low-level
ones such as the local edge structure and feature properties,
midlevel ones such as the 3D representation of the face
structure and high-level ones such as the emotional expression,
social position, and personal identity of the individual depicted.
Cerebral Cortex June 2007, V 17 N 6 1429
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reported weak face inversion effect (Kanwisher and others
1998) had part of the face covered. On the other hand, studies
reporting robust face inversion effects (Yovel and Kanwisher
2004, 2005; and the current study) showed pictures of whole
faces as stimuli, including the hair and the neck. It has been
suggested that the external contour of a face is also an
important part of the face template (Sinha and Poggio 1996;
Maurer and others 2002). An incomplete face stimulus may not
optimally activate the neurons responsible for the full-face
template and may in turn produce insufficient differential activation between upright face and inverted face.
The precuneus activation has a temporal phase opposite to
that of the other significant activations. It has been reported that
the precuneus is involved in mental rotation (Bonda and others
1995; Cohen and others 1996; Jordan and others 2001). Hence,
one likely explanation for the greater activation in the precuneus is that the observers were rotating the inverted face
information to enhance recognition. To clarify the exact role of
the precuneus in inverted face processing would, however,
require further study.
The factors that do change with 3D rotation are the local
relations between local feature properties (such as angles
between the edges) and 2D configurational relations among
the features as a whole, including the symmetry relations that
activated these regions in the first experiment. We therefore
conclude that the MOG and IOS regions are more involved in 2D
configural processing, including symmetry relations, than the
FFA and OFA, which are mostly concerned with properties that
are invariant under rotation.
Ventral and Dorsal Face Processing
By this point, the roles of the ventral areas in face configuration
processing are clear. The right OFA, located just next to
common image symmetry areas, does process face-related
image symmetry. Hence, it shows differential activation between faces and asymmetric scrambled images but not between
faces and symmetric scrambled images.
The symmetry information processed in the right OFA is either
orientation specific or a part of face gestalt. After all, the OFA
does show differential activation between upright and inverted
faces, along with the reduction of differential activation
between front view and 3/4 view. The FFA (at least its anterior
part) on the other hand, has little interest in image symmetry.
Alternation between symmetric- and asymmetric scrambled
images produces no detectable effect in this area. In terms of
face-specific stimuli, the FFA shows strong differential activation between upright and inverted faces but not between front1430 Face Symmetry
d
Chen and others
Conclusions
We draw 5 main conclusions from the pattern of results to
the symmetry manipulations: 1) The complex of cortical areas
activated by the face images, relative to Fourier-matched scrambled images, were the fusiform, inferior, and middle occipital gyri,
and areas around the STS and IOS. This is a larger range of dorsal
cortical areas than has been previously reported for face-specific
activation. 2) The areas responding to symmetry per se were
predominantly in the MOG and the IOS. Conversely, the OFA and
the FFA did not show significant correlation changes for symmetry
in the scrambled images. 3) To identify cortical regions involved in
the processes of face recognition, we compared brain activation
of the front-view faces and their inverted versions. The upright
versus inverted faces showed robust differential activation in
the areas in the fusiform, inferior occipital and middle occipital
gyri, around the IOS, and in the precuneus. 4) Contrasting the
responses to faces and to their vertically symmetric phasescrambled versions showed a response pattern similar to that
produced by contrasting the responses to faces and asymmetric
scrambled images (except in the right OFA). This result suggests
that the OFA may be involved in processing symmetry specific to
face images (in addition to other aspects of the facial configuration). 5) Finally, to study the role of object versus image symmetry,
we compare the responses to frontal and 3/4-view faces of the
same individuals. This contrast showed little differential activation
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Viewpoint Invariance
Our result on viewpoint invariance is consistent with those of
Grill-Spector and others (1999), which showed that the fusiform
activation in both hemispheres had greater viewpoint invariance
than did the dorsal occiput. Vuilleumier and others (2002) used
the repetition priming technique to show that left (but not
right) fusiform activation had viewpoint-invariant behavior for
viewing objects, although size invariance was exhibited bilaterally. It is interesting to note that both our stimulus sets
and those of Grill-Spector and others (1999) contained faces,
whereas those of Vuilleumier and others (2002) contained only
nonbiological objects. Hence, the discrepancy with the latter
results may be due to the sampling of stimuli.
Behavioral studies of face recognition showed a viewpointdependent effect. When asked whether an image of a face was
from the same person as a previously shown face image, the
observers‘ recognition performance depends on the viewpoint
of the learned face (Troje and Bulthoff 1996; Hill and others
1997) but not the test face (Troje and Bulthoff 1996). This
evidence seems contradictory to our fMRI results, which show
little differential activation between 3/4-view and front-view
faces in the FFA and OFA. Such viewpoint invariance is compatible with models suggesting that viewpoint invariance can
be achieved from the concatenation of view-based processes
(for reviews, see Riesenhuber and Poggio 2000; Rolls 2000).
However, it should be noted that an invariance property in
a brain area as a whole does not necessary mean that cells in this
area all have the same invariance property. Given the spatial
resolution of the fMRI, it is likely that each voxel covers
a network of view-based units. Hence, brain areas with such
units would appear as viewpoint invariant in their fMRI
responses, even though neural recognition responses have
access to the individual components of such networks.
view and 3/4-view faces. Hence, the FFA is likely to incorporate
an orientation-specific face gestalt (that is, however, viewpoint
invariant with respect to lateral rotation).
The roles of the dorsal areas may be understood in terms of
relative versus absolute configuration analysis. The symmetry
localizer activated part of the areas around the IOS. Those dorsal
symmetry areas, at least in the left hemisphere, did show
differential activation for the symmetry/asymmetry manipulation and for front-view versus 3/4-view faces, and also between
upright and inverted faces, which are equally symmetric. Hence,
the IOS area may be specialized for processing spatial configurations, either purely of the symmetry type or of the faceinversion type (with symmetry equated). Because this area
responds well to configuration changes whether or not faces
are present, whether or not symmetry was manipulated, and
whether or not the relative configuration was varied, the
implication is that the IOS region is involved in a wide variety
of configuration analyses.
The only manipulation that reduced the response in the
symmetry activation area was 3D face rotation, which eliminated significant response in much of the MOG region. This
region has been particularly associated with the processing of
3D structure (Tyler and others 2006), so the lack of response
may be understood as a similar response to the 2 forms of 3D
structure carried by both the frontal and rotated faces. The
strong response to faces versus scrambled textures makes sense
in this context as a response to the depth structure in the faces,
but the response to symmetric versus asymmetric textures and
to face inversion is harder to understand. It may be that there is
a stronger perception of depth structure in upright than in
inverted faces due to the match to the 3D gestalt of the upright
face, and a stronger sense of 3D structure from the luminance
cues of the symmetric versus asymmetric noise (especially in
the case of noise with the 1/f-type spectrum of the faces). These
are suggestions that would require further study to pin down.
in the FFA or the OFA but strong responses in areas near the MOG
and the IOS, indicating that viewpoint dependence is measurable
in the BOLD responses of some cortical areas. Taken together,
these results suggest that face processing in the FFA and the OFA
is holistic and relatively invariant to the viewpoint from which the
face is seen.
Notes
Supported by National Science council (Taiwan) 94-2752-H-002-007PAE to CCC and National Institutes of Health/National Eye Institute
(USA) EY 13025 to CWT. Conflict of Interest: None declared.
Address correspondence to Chien-Chung Chen, Department of
Psychology, National Taiwan University, Taipei 106, Taiwan. Email:
[email protected].
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