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Volume 17, Number 11,
Issue of June 1, 1997
pp. 4302-4311
Copyright ©1997 Society for Neuroscience
The Fusiform Face Area: A Module in Human Extrastriate Cortex
Specialized for Face Perception
Nancy Kanwisher1, 2,
Josh McDermott1, 2, and
Marvin M. Chun2, 3
1 Department of Psychology, Harvard University,
Cambridge, Massachusetts 02138, 2 Massachusetts General
Hospital NMR Center, Charlestown, Massachusetts 02129, and
3 Department of Psychology, Yale University, New Haven,
Connecticut 06520-8205
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
FOOTNOTES
REFERENCES
ABSTRACT
Using functional magnetic resonance imaging (fMRI), we found an
area in the fusiform gyrus in 12 of the 15 subjects tested that was
significantly more active when the subjects viewed faces than when they
viewed assorted common objects. This face activation was used to define
a specific region of interest individually for each subject, within
which several new tests of face specificity were run. In each of five
subjects tested, the predefined candidate "face area" also
responded significantly more strongly to passive viewing of (1) intact
than scrambled two-tone faces, (2) full front-view face photos than
front-view photos of houses, and (in a different set of five subjects)
(3) three-quarter-view face photos (with hair concealed) than photos of
human hands; it also responded more strongly during (4) a consecutive
matching task performed on three-quarter-view faces versus hands. Our
technique of running multiple tests applied to the same region defined
functionally within individual subjects provides a solution to two
common problems in functional imaging: (1) the requirement to correct
for multiple statistical comparisons and (2) the inevitable ambiguity
in the interpretation of any study in which only two or three
conditions are compared. Our data allow us to reject alternative
accounts of the function of the fusiform face area (area "FF") that
appeal to visual attention, subordinate-level classification, or
general processing of any animate or human forms, demonstrating that
this region is selectively involved in the perception of
faces.
Key words:
extrastriate cortex;
face perception;
functional MRI;
fusiform gyrus;
ventral visual pathway;
object recognition
INTRODUCTION
Evidence from cognitive psychology (Yin, 1969 ;
Bruce et al., 1991 ; Tanaka and Farah, 1993 ), computational vision (Turk
and Pentland, 1991 ), neuropsychology (Damasio et al., 1990 ; Behrmann et
al., 1992 ), and neurophysiology (Desimone, 1991 ; Perrett et al., 1992 )
suggests that face and object recognition involve qualitatively different processes that may occur in distinct brain areas. Single-unit recordings from the superior temporal sulcus (STS) in macaques have
demonstrated neurons that respond selectively to faces (Gross et al.,
1972 ; Desimone, 1991 ; Perrett et al., 1991 ). Evidence for a similar
cortical specialization in humans has come from epilepsy patients with
implanted subdural electrodes. In discrete portions of the fusiform and
inferotemporal gyri, large N200 potentials have been elicited by faces
but not by scrambled faces, cars, or butterflies (Ojemann et al., 1992 ;
Allison et al., 1994 ; Nobre et al., 1994 ). Furthermore, many reports
have described patients with damage in the occipitotemporal region of
the right hemisphere who have selectively lost the ability to recognize
faces (De Renzi, 1997 ). Thus, several sources of evidence support the
existence of specialized neural "modules" for face perception in
extrastriate cortex.
The evidence from neurological patients is powerful but limited in
anatomical specificity; however, functional brain imaging allows us to
study cortical specialization in the normal human brain with relatively
high spatial resolution and large sampling area. Past imaging studies
have reported regions of the fusiform gyrus and other areas that were
more active during face than object viewing (Sergent et al., 1992 ),
during face matching than location matching (Haxby et al., 1991 , 1994 ;
Courtney et al., 1997 ), and during the viewing of faces than of
scrambled faces (Puce et al., 1995 ; Clark et al., 1996 ), consonant
strings (Puce et al., 1996 ), or textures (Malach et al., 1995 ; Puce et
al., 1996 ). Although these studies are an important beginning, they do
not establish that these cortical regions are selectively
involved in face perception, because each of these findings is
consistent with several alternative interpretations of the mental
processes underlying the observed activations, such as (1) low-level
feature extraction (given the differences between the face and various
control stimuli), (2) visual attention, which may be recruited more
strongly by faces, (3) "subordinate-level" visual recognition
(Damasio et al., 1990 ; Gauthier et al., 1996 ) of particular exemplars
of a basic-level category (Rosch et al., 1976 ), and (4) recognition of
any animate (or human) objects (Farah et al., 1996 ).
Such ambiguity of interpretation is almost inevitable in imaging
studies in which only two or three conditions are compared. We
attempted to overcome this problem by using functional magnetic resonance imaging (fMRI) to run multiple tests applied to the same
cortical region within individual subjects to search for discrete
regions of cortex specialized for face perception. (For present purposes, we define face perception broadly to include any
higher-level visual processing of faces from the detection of a face as
a face to the extraction from a face of any information about the
individual's identity, gaze direction, mood, sex, etc.). Our strategy
was to ask first whether any regions of occipitotemporal cortex were
significantly more active during face than object viewing; only one
such area (in the fusiform gyrus) was found consistently across most
subjects. To test the hypothesis that this fusiform region was
specialized for face perception, we then measured the activity in this
same functionally defined area in individual subjects during four
subsequent comparisons, each testing one or more of the alternative
accounts listed in the previous paragraph.
MATERIALS AND METHODS
General design. This study had three main parts. In
Part I, we searched for any occipitotemporal areas that might be
specialized for face perception by looking within each subject for
regions in the ventral (occipitotemporal) pathway that responded
significantly more strongly during passive viewing of photographs of
faces than photographs of assorted common objects. This comparison
served as a scout, allowing us to (1) anatomically localize candidate "face areas" within individual subjects, (2) determine which if any
regions are activated consistently across subjects, and (3) specify
precisely the voxels in each subject's brain that would be used as
that subject's previously defined region of interest (ROI) for the
subsequent tests in Parts II and III.
We used a stimulus manipulation with a passive viewing task (rather
than a task manipulation on identical stimuli) because the perception
of foveally presented faces is a highly automatic process that is
difficult to bring under volitional control (Farah et al., 1995 ).
Imagine, for example, being told that a face will be flashed at
fixation for 500 msec and that you must analyze its low-level visual
features but not recognize the face. If the face is familiar it will be
virtually impossible to avoid recognizing it. Thus when faces are
presented foveally, all processes associated with face recognition are
likely to occur no matter what the task is, and the most effective way
to generate a control condition in which those processes do not occur
is to present a nonface stimulus (Kanwisher et al., 1996 ).
The results of Part I showed only one region that was activated
consistently across subjects for the faces versus objects comparison;
this area was in the right fusiform gyrus (and/or adjacent sulci). We
hypothesized that this region was specialized for some aspect of face
perception, and we tested alternatives to this hypothesis with several
different stimulus comparisons in Parts II and III. In Part II, each of
five subjects who had revealed a clear fusiform face activation in Part
I was tested on two new stimulus comparisons. In each, the
methodological details were identical to those of the faces versus
objects runs, and only the stimulus sets differed. Our first new
stimulus comparison in Part II was between intact two-tone faces
(created by thresholding the photographs used in Part I) and scrambled
two-tone faces in which the component black regions were rearranged to
create a stimulus unrecognizable as a face (see Fig. 3b).
This manipulation preserved the mean luminance and some low-level
features of the two-tone face stimuli and avoided producing the
"cut-and-paste" marks that have been a problem in the scrambling
procedures of some earlier studies; this contrast therefore served as a
crude test of whether the "face areas" were simply responding to
the low-level visual features present in face but not nonface stimuli. Our second stimulus contrast front view photographs of faces versus front view photographs of houses (see Fig. 3c) was designed
to test whether the "face area" was involved not in face perception per se but rather in processing and/or distinguishing between any
different exemplars of a single class of objects.
Fig. 3.
Results of Part II. Left column,
Sample stimuli used for the faces versus objects comparison as well as
the two subsequent tests. Center column, Areas that
produced significantly greater activation for faces than control
stimuli for subject S1. a, The faces versus objects
comparison was used to define a single ROI (shown in green
outline for S1), separately for each subject. The time courses
in the right column were produced by (1) averaging the
percentage signal change across all voxels in a given subject's ROI
(using the original unsmoothed data), and then (2) averaging these
ROI-averages across the five subjects. F and
O in a indicate face and object epochs;
I and S in b indicate
intact and scrambled face epochs; and F and
H in c indicate face and hand
epochs.
Fig. 4.
Results of Part III. Stimulus contrasts for
each test are shown in the left column.
a, Face ROIs were defined separately for each subject
using the average of two face versus object scans as described for
Figure 3a. The resulting brain slice with statistical overlay for one subject (S10) is shown in the center
column, and the time course of signal intensity averaged over
the five subjects' ROIs is shown at the right. As
described for Figure 3a (Part II), the ROI
specified on the basis of the faces versus objects comparison was used
for the two subsequent comparisons of passive viewing of three-quarter
faces versus hands (b), and the consecutive matching task on three-quarter faces versus hands (c).
[View Larger Version of this Image (86K GIF file)]
In Part III, a new but overlapping set of five subjects who had
revealed clear candidate face areas in Part I were tested on two new
comparisons. (Subjects S1 and S2 participated in both Parts II and
III.) In the first new comparison, subjects passively viewed
three-quarter-view photographs of faces (all were of people whose hair
was tucked inside a black knit ski hat) versus photographs of human
hands (all shot from the same angle and in roughly the same position).
This comparison (see Fig. 4b) was designed to test several
different questions. First, would the response of the candidate face
area generalize to different viewpoints? Second, is this area involved
in recognizing the face on the basis of the hair and other external
features of the head (Sinha and Poggio, 1996 ) or on the basis of its
internal features? Because the external features were largely hidden
(and highly similar across exemplars) in the ski hat faces, a response
of this area to these stimuli would suggest that it is primarily
involved in processing the internal rather than external features of
the face. Third, the use of human hands as a control condition also
provided a test of whether the face area would respond to any animate
or human body part. In the second new comparison, the same stimuli
(three-quarter-view faces vs hands) were presented while subjects
performed a "1-back" task searching for consecutive repetitions of
identical stimuli (pressing a button whenever they detected a
repetition). For this task, a 250 msec blank gray field was sandwiched
between each successive 500 msec presentation of a face. The gray field
produced sensory transients over the whole stimulus and thereby
required subjects to rely on higher-level visual information to perform the task (Rensink et al., 1997 ). Because the 1-back task was, if
anything, more difficult for hand than face stimuli, the former should
engage general attentional mechanisms at least as strongly as the
latter, ruling out any account of greater face activation for faces in
terms of general attentional mechanisms.
Tests of each subject in Parts II and III were run on the basic face
versus object comparison from Part I in the same session, so that the
results of Part I could be used to generate the precise ROIs for that
subject for the comparisons in Parts II and III. For the passive
viewing conditions, subjects were instructed to maintain fixation on
the dot when it was present, and otherwise to simply look at the
stimuli attentively without carrying out other mental games at the same
time.
Subjects. Tests of 20 normal subjects under the age of 40 were run, and all of the subjects reported normal or
corrected-to-normal vision and no previous neurological history. The
data from five of them were omitted because of excessive head motion or
other artifacts. Of the remaining 15 subjects (9 women and 6 men), 13 participants described themselves as right-handed and two as
left-handed. All 15 subjects participated in Part I. (Subject S1 was
run on Part I many times in different scanning sessions spread over a 6 month period both to measure test-retest reliability within a subject
across sessions and to compare the results from Part I with a number of
other pilot studies conducted over this period.) Subjects S1, S2, S5,
S7, and S8 from Figure 2 were run in Part II, and subjects S1, S5, S9,
S10, and S11 from Figure 2 were run in Part III. Subjects S1-S10
described themselves as right-handed, whereas subjects S11 and S12
described themselves as left-handed. The experimental procedures were
approved by both the Harvard University Committee on the Use of Human
Subjects in Research and the Massachusetts General Hospital
Subcommittee on Human Studies; informed consent was obtained from each
participant.
Bottom two rows, Anatomical images
overlaid with color-coded statistical maps from the 10 right-handed
subjects in Part I who showed regions that produced a significantly
stronger MR signal during face than object viewing. For each of the
right-handed subjects (S1-S10), the slice containing the right
fusiform face activation is shown; for left-handed subjects S11 and
S12, all the fusiform face activations are visible in the slices shown. Data from subjects S1 and S2 resliced into sagittal, coronal, and axial
slices (top right). Data from the three subjects who showed no regions that responded significantly more strongly for faces
than objects are not shown.
Fig. 2.
Stimuli. Samples of the stimuli used in these experiments
are shown in Figures 3 and 4. All stimuli were ~300 × 300 pixels in size and were gray-scale photographs (or photograph-like
images), except for the intact and scrambled two-tone faces used in
Part II. The face photographs in Parts I and II were 90 freshman ID photographs obtained with consent from members of the Harvard class of
1999. The three-quarter-view face photos used in Part II were members
of or volunteers at the Harvard Vision Sciences Lab. (For most subjects
none of the faces were familiar.) The 90 assorted object photos (and
photo-like pictures) were obtained from various sources and included
canonical views of familiar objects such as a spoon, lion, or car. The
90 house photographs were scanned from an architecture book and were
unfamiliar to the subjects.
Each scan lasted 5 min and 20 sec and consisted of six 30 sec stimulus
epochs interleaved with seven 20 sec epochs of fixation. During each
stimulus epoch in Parts I and II, 45 different photographs were
presented foveally at a rate of one every 670 msec (with the stimulus
on for 500 msec and off for 170 msec). Stimulus epochs alternated
between the two different conditions being compared, as shown in
Figures 1, 3, and 4. The 45 different stimuli used in the first
stimulus epoch were the same as those used in the fifth stimulus epoch;
the stimuli used in the second stimulus epoch were the same as those
used in the sixth. The stimuli in Part III were the same in structure
and timing, except that (1) a total of 22 face stimuli and 22 hand
stimuli were used (with most stimuli occurring twice in each epoch),
and (2) the interval between face or hand stimuli was 250 msec.
Fig. 1.
Results from subject S1 on Part I. The
right hemisphere appears on the left for
these and all brain images in this paper (except the resliced images
labeled "Axial" in Fig. 2). The brain images at the
left show in color the voxels that
produced a significantly higher MR signal intensity (based on smoothed
data) during the epochs containing faces than during those containing
objects (1a) and vice versa (1b) for 1 of
the 12 slices scanned. These significance images (see color
key at right for this and all figures in this paper) are overlaid on a T1-weighted anatomical image of the same slice. Most of the other 11 slices showed no voxels that reached significance at the p < 10 3 level or
better in either direction of the comparison. In each image, an ROI is
shown outlined in green, and the time course of raw
percentage signal change over the 5 min 20 sec scan (based on
unsmoothed data and averaged across the voxels in this ROI) is shown at
the right. Epochs in which faces were presented are indicated by the vertical gray bars marked with an
F; gray bars with an O
indicate epochs during which assorted objects were presented; white bars indicate fixation epochs.
[View Larger Version of this Image (133K GIF file)]
Stimulus sequences were generated using MacProbe software (Hunt, 1994 )
and recorded onto videotape for presentation via a video projector
during the scans. Stimuli were back-projected onto a ground-glass
screen and viewed in a mirror over the subject's forehead (visual
angle of the stimuli was ~15 × 15°).
MRI acquisition. Scans were conducted using the 1.5 T MRI
scanner (General Electric Signa, Milwaukee, WI) at the Massachusetts General Hospital NMR Center (Charlestown, MA), using echo-planar imaging (Instascan, ANMR Systems, Wilmington, MA) and a bilateral quadrature receive-only surface coil (made by Patrick Ledden, Massachusetts General Hospital NMR Center). Functional data were obtained using an asymmetric spin echo sequence (TR = 2 sec, TE = 70 msec, flip angle = 90°, 180° offset = 25 msec). Our 12 6 mm slices were oriented parallel to the inferior edge of the occipital and temporal lobes and covered the entire occipital and most of the
temporal lobe (see Fig. 5). Head motion was minimized with a bite bar.
Voxel size was 3.25 × 3.25 × 6 mm. Details of our procedure
are as described in Tootell et al. (1995) , except as noted here.
Fig. 5.
Midsagittal anatomical image from subject S1
showing the typical placing of the 12 slices used in this study. Slices
were selected so as to include the entire ventral surface of the
occipital and temporal lobes.
[View Larger Version of this Image (158K GIF file)]
Data analysis. Five subjects of the 20 scanned had excessive
head motion and/or reported falling asleep during one or more runs; the
data from these subjects were omitted from further analysis. Motion was
assessed within a run by looking for (1) a visible shift in the
functional image from a given slice between the first and last
functional image in one run, (2) activated regions that curved around
the edge of the brain and/or shifted sides when the sign of the
statistical comparison was reversed, and/or (3) ramps in the time
course of signal intensity from a single voxel or set of voxels. Motion
across runs was assessed by visually inspecting the raw functional
images for any change in the shape of a brain slice across runs.
For the remaining 15 subjects no motion correction was carried out.
Pilot data had indicated that the significance from a single run was
sometimes weak, but became much stronger when we averaged across two
identical runs within a subject (i.e., when the two corresponding
values for each voxel, one from each scan, were averaged together for
each of the 160 images × 12 slices collected during a single 5 min 20 sec scan). We therefore ran each test twice on each subject, and
averaged over the two runs of each test. The data were then analyzed
statistically using a Kolmogorov-Smirnov test, after smoothing with a
Hanning kernel over a 3 × 3 voxel area to produce an approximate
functional resolution of 6 mm. This analysis was run on each voxel
(after incorporating a 6 sec lag for estimated hemodynamic delay),
testing whether the MR signal intensity in that voxel was significantly
greater during epochs containing one class of stimuli (e.g., faces)
than epochs containing the other (e.g., objects). Areas of activation were displayed in color representations of significance level, overlaid
on high-resolution anatomical images of the same slice. Voxels of
significant activation were also inspected visually by plotting the
time course of raw (unsmoothed) signal intensity over the 5 min 20 sec
of the scan.
To identify all regions within our chosen slices and coil range that
responded more strongly to faces than objects in Part I, as well as
their Talairach coordinates, each subject's anatomical and functional
data were first fitted into their own Talairach space and then analyzed
(using the program Tal-EZ by Bush et al., 1996 ) to find all the regions
that produced a stronger signal for faces than objects at the
p < 10 4 level of significance
(uncorrected for multiple comparisons). This analysis was intended as a
scout for candidate face areas and revealed that the only region in
which most of our subjects showed a significantly greater activation
for faces than objects was in the right fusiform gyrus. This region
therefore became the focus of our more detailed investigations in Parts
II and III.
For each subject in Parts II and III, a face ROI was identified that
was composed of all contiguous voxels in the right fusiform region in
which (1) the MR signal intensity was significantly stronger during
face than object epochs at the p < 10 4
level, and (2) a visual inspection of the raw time course data from
that voxel did not reveal any obvious ramps, spikes, or other artifacts. For subject S11, who was left-handed and had very large and
highly significant activations in both left and right fusiform gyri,
the ROI used in Part III included both of these regions.
For each of the comparisons in Parts II and III we first averaged over
the two runs from each subject and then averaged across the voxels in
that subject's predefined face ROI (from Part I) to derive the time
course of raw signal intensity in that subject's ROI. Two further
analyses were then carried out. First, the average MR signal intensity
in each subjects' ROI for each epoch was calculated (by averaging
within a subject across all the voxels in their ROI and across all the
images collected in each epoch). The average MR signal intensities for
each subject and stimulus epoch were then entered into a three-way
ANOVA across subjects (epoch number × face/control × test)
separately for Parts II and III. The factor of epoch number had three
levels corresponding to the first, second, and third epochs for each
condition; the test factor had three levels for the three different
stimulus comparisons (faces vs objects/scrambled vs intact faces/faces
vs houses for Part II and faces vs objects/passive faces vs
hands/1-back faces vs hands for Part III). These ANOVAs allowed us to
test for the significance of the differences in signal intensity
between the various face and control conditions and also to test
whether this difference interacted with epoch number and/or comparison
type.
Second, for each subject we converted the raw time course of MR signal
intensity from that subject's face ROI into a time course of percent
signal change, using that subject's average signal across all the
fixation epochs in the same runs (in the face ROI) as a baseline. These
time courses of percent signal change for each subject's face ROI
could then be averaged across the five subjects who were run on the
same test, for all the tests in Parts I through III. By averaging
across each subject's ROI and across all the data collected during
each epoch type, we derived an average percentage signal change for the
face and control conditions for each test. The ratio of the percentage
signal change for the faces versus control condition for each test
provides a measure of the selectivity of the face ROI to the stimulus
contrast used in that test.
RESULTS
Part I
In Part I we asked whether any brain areas were significantly more
active during face viewing than object viewing. Figure 1a shows the results from a single subject
(S1), revealing a region in the right fusiform gyrus that
produced a significantly higher signal intensity during epochs in which
faces were presented than during epochs in which objects were presented
(in five adjacent voxels at the p < 10 4
level based on an analysis of smoothed data). This pattern is clearly
visible in the raw (unsmoothed) data for this single subject shown in
Figure 1a (right), where the percentage signal
change is plotted over the 5 min 20 sec of the scan, averaged over the five voxels outlined in green (Fig. 1a, left).
The opposite effect, a significantly higher MR signal (each significant
at the p < 10 4 level) during the viewing
of objects than during face viewing, was seen in a different, bilateral
and more medial area including two adjacent voxels in the right
hemisphere and eight in the left in the same slice of the same data set
(Fig. 1b). A similar bilateral activation in the
parahippocampal region for objects compared with faces was seen in most
of the subjects run in this study; this result is described briefly in
Kanwisher et al. (1996) , where images of this activation are shown for
three different subjects. The two opposite activations for faces and
objects constitute a double dissociation and indicate that the face
activation cannot merely be an artifact of an overall tendency for the
faces to be processed more extensively than the objects or vice
versa.
To scout for any regions of the brain that might be specialized for
face perception consistently across subjects, we tabulated (in Table 1)
the Talairach coordinates of all the regions in each subject that
produced a stronger signal for faces than objects at the
p < 10 4 level of significance
(uncorrected for multiple comparisons). The only region in which most
of our subjects showed a significantly greater activation for faces
than objects was in the right fusiform gyrus. This region therefore
became the focus of our more detailed investigations in Parts II and
III.
Table 1.
Talairach coordinates of brain regions with stronger
responses to faces than objects in individual
subjects
| Subject |
Fusiform face area |
MT gyrus/ST
sulcus |
Other activation loci |
Other activation loci |
|
| A.
Right-handed subjects |
| S1 |
(40, 48,
12), 2.1, 10 |
|
(43, 75, 6), 2.1, 10 |
| S2 |
(37, 57, 9), 0.4, 7 |
(50, 54,
15), 0.3, 6 |
( 37, 57, 21), 0.6, 5 |
( 43, 72,
25), 0.7, 5 |
|
|
|
(0, 54, 28), 6.1, 8 |
| S3 |
(43, 54, 18), 1.8, 9 |
(65, 51, 9),
3.6, 6 |
(37, 78, 15), 0.6, 8 |
(40, 69, 40),
2.8, 5 |
|
|
(56, 60, 3), 1.6, 5 |
(56, 27,
18), 1.1, 5 |
| S4 |
(31, 62, 6), 0.9, 10 |
(56,
57, 6), 0.9, 2e 7 |
(34, 42, 21), 0.3, 4 |
|
( 31,
62, 15), 1.3, 6 |
| S5 |
(50, 63, 9), 2.1, 10 |
|
(34, 81, 6), 0.6, 6 |
(40, 30, 9),
0.2, 6 |
| S6 |
(37, 69, 3), 0.1, 4 |
(46, 48,
12), 0.7, 4 |
( 34, 69, 0), 0.2, 4 |
|
( 34,
69, 0), 0.1, 4 |
| S7 |
(46, 54, 12), 0.8, 6 |
|
(43, 69, 3), 0.4, 5 |
( 12, 87, 0), 3.1, 5 |
|
( 40, 69, 12), 0.5, 5 |
|
(0, 75,
6), 1.9, 9 |
(21, 90, 3), 3.7, 6 |
|
|
|
( 6, 75, 34), 4.2, 8 |
(40, 54, 34), 2.8, 5 |
|
|
|
|
(12, 81, 46), 1.7, 6 |
| S8 |
(40, 39, 6), 0.06, 6 |
|
(3, 72,
31), 2.7, 6 |
|
( 34, 75, 3), 0.06, 8 |
| S9 |
(40, 51, 12), 0.7, 1.10 |
| S10 |
(34, 57, 15), 1.4, 13 |
(56,
60, 6), 0.2, 5 |
|
( 37, 41, 12), 0.4, 6 |
| B. Left-handed subjects |
| S11 |
( 37, 42,
12), 1.9, 12 |
(46, 69, 0), 0.4, 5 |
( 62, 30,
12), 0.4, 5 |
|
(40, 48, 12), 1.1, 8 |
( 53,
54, 0), 1.4, 5 |
| S12 |
( 34, 48, 6), 0.4, 8 |
(56, 42, 21), 0.5, 5 |
(3, 60, 12), 0.3, 5 |
(34, 90, 6), 0.3, 4 |
|
|
|
(6, 60,
31), 3.5, 5 |
|
Regions that responded significantly (at the p < 10 4 level) more strongly during face than object epochs
(Part I) for each subject. For each activated region is given (1) the
Talairach coordinates (M-Lx, A-Py, S-Iz), (2) size (in
cm3), and (3) exponent (base 10) of the p level
of the most significant voxel (based on an analysis of unsmoothed data)
in that region (in italics). This table was generated
using a program (Tal-EZ) supplied by G. Bush et al. (1996) . Subject S5
was run with a surface coil placed over the right hemisphere, so only
right hemisphere activations could be detected.
|
|
Fusiform activations for faces compared with objects were observed in
the fusiform region in 12 of the 15 subjects analyzed; for the other
three subjects no brain areas produced a significantly stronger MR
signal intensity during face than object epochs at the
p < 10 4 level or better. [Null results
are difficult to interpret in functional imaging data: the failure to
see face activations in these subjects could reflect either the absence
of a face area in these subjects or the failure to detect a face module
that was actually present because of (1) insufficient statistical
power, (2) susceptibility artifact, or (3) any of numerous other
technical limitations.] The slice showing the right fusiform face
activation for each of the 12 subjects is shown in Figure
2. An inspection of flow-compensated anatomical images
did not reveal any large vessels in the vicinity of the activations.
Despite some variability, the locus of this fusiform face activation is
quite consistent across subjects both in terms of gyral/sulcal
landmarks and in terms of Talairach coordinates (see Table 1). Half of
the 10 right-handed subjects showed this fusiform activation only in the right hemisphere; the other half showed bilateral activations. For
the right-handed subjects, the right hemisphere fusiform area averaged
1 cm3 in size and was located at Talairach coordinates 40x,
55y, 10z (mean across subjects of the coordinates of the most
significant voxel). The left hemisphere fusiform area was found in only
five of the right-handed subjects, and in these it averaged 0.5 cm3 in size and was located at 35x, 63y, 10z. (As
shown in Table 1, the significance level was also typically higher for
right hemisphere than left hemisphere face activations.) For cortical parcellation, the data for individual subjects were resliced into sagittal, coronal, and axial slices (as shown for S1 and S2 in Fig. 2).
This allowed localization of these activated areas to the fusiform
gyrus at the level of the occipitotemporal junction (parcellation unit TOF in the system of Rademacher et al., 1993 ), although in several cases we cannot rule out the possibility that the
activation is in the adjacent collateral and/or occipitotemporal sulci.
Subject S1 was run on the basic faces versus objects comparison in Part
I in many different testing sessions spread over a period of 6 months.
A striking demonstration of the test-retest reliability of this
comparison can be seen by inspecting the activation images for this
subject from four different sessions in which this same faces versus
objects comparison was run; these are shown in Figure 1a,
the two different axial images for subject S1 in Figure 2 (bottom
left and top right), and Figure
3a. The high degree of consistency in the
locus of activation suggests that the complete lateralization of the
face activation to the right hemisphere in this subject is not an
artifact of partial voluming (i.e., a chance positioning of the slice
plane so as to divide a functional region over two adjacent slices,
thereby reducing the signal in each slice compared with the case in
which the entire region falls in a single slice). Although our sample
size is too small to permit confident generalizations about the effects
of handedness, it is worth noting that our 10 right-handed subjects showed either unilateral right-hemisphere or bilateral activations in
the fusiform region, whereas one left-handed subject (S11) showed a
unilateral left-hemisphere and the other (S12) showed a bilateral
activation.
In addition to the activation in the fusiform region, seven subjects
also showed an activation for faces compared with objects in the region
of the middle temporal gyrus/superior temporal (ST) sulcus of the right
hemisphere. Talairach coordinates for these activations are provided in
the second column of Table 1. Most subjects also showed
additional face (compared with object) activations in other regions
(Table 2, third and fourth columns), but none of these
appeared to be systematic across subjects.
Table 2A.
Part
I
| Faces |
Objects |
Ratio |
Intact |
Scrambled |
Ratio |
Face |
House |
Ratio |
|
| 1.9% |
0.7% |
2.8 |
1.9% |
0.6% |
3.2 |
1.6% |
0.2% |
6.6 |
|
|
|
Table B.
Part
II
| Faces |
Objects |
Ratio |
Passive
|
1-Back
repetition detection
|
| 3/4 Faces |
Hands |
Ratio |
3/4
Faces |
Hands |
Ratio |
|
| 3.3% |
1.2% |
2.7 |
2.7% |
0.7% |
4.0 |
3.2% |
0.7% |
4.5 |
|
|
Mean percent signal change (from average fixation baseline)
across all five subjects for face epochs versus control epochs for each
of the comparisons in Parts II and III. The ratio of percent signal
change for faces to the percent signal change for the control condition
is a measure of face selectivity.
|
|
Part II
Part II tested whether the activation for faces compared with
objects described in Part I was attributable to (1) differences in
luminance between the face and object stimuli and/or (2) the fact that
the face stimuli but not the object stimuli were all different
exemplars of the same category. Five subjects who had also been run in
Part I were run on Part II in the same scanning session, allowing us to
use the results from Part I to derive previous face ROIs for the
analysis of the data in Part II.
First we defined a "face" ROI in the right fusiform region
separately for each of the five subjects, as described above, and then
averaged the response across all the voxels in that subjects own face
ROI during the new tests. The pattern of higher activation for face
than nonface stimuli was clearly visible in the raw data from each
subject's face ROI for each of the tests in Part II. To test this
quantitatively, we averaged the mean MR signal intensity across each
subject's ROI and across all the images collected within a given
stimulus epoch and entered these data into a three-way ANOVA across
subjects (face/control × epoch number × test). This analysis revealed a main effect of higher signal intensity during face
epochs than during control stimulus epochs
(F(1,4) = 27.1; p < 0.01). No
other main effects or interactions reached significance. In particular,
there was no interaction of face/control × test (F < 1), indicating that the effect of higher signal
intensity during face than control stimuli did not differ significantly across the three tests. As a further check, separate pairwise comparisons between the face and control stimuli were run for each of
the three tests, revealing that each reached significance independently
(p < 0.001 for faces vs objects,
p < 0.05 for intact vs scrambled faces, and
p < 0.01 for faces vs houses). Note that because the
ROI and exact hypothesis were specified in advance for the latter two
tests (and because we averaged over all the voxels in a given
subject's ROI to produce a single averaged number for each ROI), only
a single comparison was carried out for each subject in each test, and
no correction for multiple comparisons is necessary for the intact
versus scrambled faces and faces versus houses comparisons.
For each subject the ROI-averaged time course data were then converted
into percentage signal change (using the average MR signal intensity
across the fixation epochs in that subject's face ROI as a baseline).
The average across the five subjects' time courses of percentage
signal change are plotted in Figure 3, where the data clearly show
higher peaks during face epochs than during nonface epochs. An index of
selectivity of the face ROI was then derived by calculating the average
percentage signal change across all subjects' face ROIs during face
epochs to the average percentage signal change during nonface epochs.
This ratio (see Table 2) varies from 2.8 (the faces vs objects test) to
6.6 (faces vs houses), indicating a high degree of stimulus selectivity in the face ROIs. For comparison purposes, note that Tootell et al.
(1995) reported analogous selectivity ratios from 2.2 to 16.1 for the
response of visual area MT to moving versus stationary displays.
In sum, these data indicate that the region in each subject's fusiform
gyrus that responds more strongly to faces than objects also responds
more strongly to intact than scrambled two-tone faces and more strongly
to faces than houses.
The selectivity of the MT gyrus/ST sulcus activation could not be
adequately addressed with the current data set because only one of the
five subjects run in Part II showed a greater response for faces than
objects in this region. (For this subject, S2, the ST/MT gyrus region
activated for faces vs objects was activated only weakly if at all in
the comparisons of intact vs scrambled faces and faces vs houses.)
Part III
Part III tested whether the activation for faces compared with
objects described in Part I was attributable to (1) a differential response to animate (or human) and inanimate objects, (2) greater visual attentional recruitment by faces than objects, or (3)
subordinate-level classification. Five subjects (including two who were
run on Part II in a different session) were run on Parts I and III in
the same session. The data were analyzed in the same way as the data from Part II: fusiform face ROIs were defined on the basis of the faces
versus objects data from Part I, and these ROIs were used for the
analysis of the two new tests. Each subjects' individual raw data
clearly showed higher signal intensities in the face ROI during the two
new face compared with nonface tests (passive three-quarter faces vs
hands and 1-back faces vs hands). The 3-way ANOVA across subjects on
the mean signal intensity in each subject's face ROI for each of the
stimulus epochs (face/control × epoch number × test)
revealed a significant main effect of higher signal intensity for face
than nonface stimuli (F(1,4) = 35.2;
p < 0.005); no other main effects or interactions
reached significance. Separate analyses of the mean signal intensity
during face versus control stimulus epochs confirmed that each of the
three tests independently reached significance
(p < 0.001 for faces vs objects,
p < 0.02 for faces vs hands passive, and
p < 0.005 for faces 1-back vs hands 1-back).
As in Part II, we also calculated the percentage signal change in each
subject's prespecified face ROI. The averages across the five
subjects' time courses of percentage signal change are plotted in
Figure 4, where the data clearly show higher peaks during face than nonface epochs. The face selectivity
ratios (derived in the same way described in Part II) varied from 2.7 for faces versus objects to 4.5 for faces versus hands 1-back (Table
2), once again indicating a high degree of selectivity for faces. Thus,
the data from Part III indicate that the same region in the fusiform
gyrus that responds more strongly to faces than objects also responds
more strongly during passive viewing of three-quarter views of faces
than hands, and more strongly during the 1-back matching task on faces
than hands.
We have only partial information about the selectivity of the MT
gyrus/ST sulcus activation in the two comparisons of Part III, because
only two of the five subjects run in Part III contained activations in
the MT/ST region for faces versus objects (S10 and S11). Both of these
subjects showed significantly greater signal intensities in this region
for faces versus hands, suggesting that it is at least partially
selective for faces; however, this result will have to be replicated in
future subjects to be considered solid.
Although a technical limitation prevented recording of the behavioral
responses collected from subjects in the scanner during the 1-back
task, the experimenters were able to verify that the subject was
performing the task by monitoring both the subject's responses and the
stimulus on-line during the scan. All subjects performed both tasks
well above chance. Subsequent behavioral measurements on different
subjects (n = 12) in similar viewing conditions in the
lab found similar performance in the two tasks (86% correct for hands
and 92% correct for faces, corrected for guessing), although all
subjects reported greater difficulty with the hands task than the faces
task. Thus the hands task was at least as difficult as the faces task,
and general attentional mechanisms should be at least as actively
engaged by the hands task as the faces task.
DISCUSSION
This study found a region in the fusiform gyrus in 12 of 15 subjects that responded significantly more strongly during passive viewing of face than object stimuli. This region was identified within
individual subjects and used as a specific ROI within which further
tests of face selectivity were conducted. One test showed that the face
ROIs in each of five subjects responded more strongly during passive
viewing of intact two-tone faces than scrambled versions of the same
faces, ruling out luminance differences as accounting for the face
activation. In a second test, the average percentage signal increase
(from the fixation baseline) across the five subjects' face ROIs was
more than six times greater during passive viewing of faces than during
passive viewing of houses, indicating a high degree of stimulus
selectivity and demonstrating that the face ROI does not simply respond
whenever any set of different exemplars of the same category are
presented. In a third test, the face ROIs in a new set of five subjects
responded more strongly during passive viewing of three-quarter-view
faces with hair concealed than during viewing of photographs of human
hands, indicating that (1) this region does not simply respond to any animal or human images or body parts and (2) it generalizes to respond
to images of faces taken from a different viewpoint that differed
considerably in their low-level visual features from the original set
of face images. Finally, in a fourth test, each of the five subjects'
face ROIs were shown to respond more strongly during a consecutive
matching task carried out on the three-quarter-view faces than during
the same matching task on the hand stimuli. Because both tasks required
subordinate-level categorization, and the hand task was at least as
difficult as the face task, the greater activation of the face ROIs
during the face task indicates that the activity of this region does
not reflect general processes associated either with visual attention
or with subordinate-level classification of any class of stimuli
(contrary to suggestions by Gauthier et al., 1996 ). The elimination of
these main alternative hypotheses provides compelling evidence that the
fusiform face area described in this study, which we will call area
"FF," is specifically involved in the perception of faces.
Area FF responds to a wide variety of face stimuli, including
front-view gray-scale photographs of faces, two-tone versions of the
same faces, and three-quarter-view gray-scale faces with hair
concealed. Although it is possible that some low-level visual feature
present in each of these stimuli can account for the activation observed, this seems unlikely given the diversity of faces and nonface
control stimuli used in the present study. Furthermore, another study
in our lab (E. Wojciulik, N. Kanwisher, and J. Driver, unpublished
observations) has shown that area FF also responds more strongly during
attention to faces than during attention to houses, even when the
retinal stimulation is identical in the two cases. (The faces in that
study were also smaller and were presented to the side of fixation,
indicating further that area FF generalizes across the size and retinal
position of the face stimuli.) We therefore conclude that area FF
responds to faces in general rather than to some particular low-level
feature that happens to be present in all the face but not nonface
stimuli that have been tested so far. In addition, the fact that area FF responds as strongly to faces in which the external features (e.g.,
hair) are largely concealed under a hat suggests that area FF is more
involved in face recognition proper than in "head recognition" (Sinha and Poggio, 1996 ).
Our use of a functional definition of area FF allowed us to assess the
variability in the locus of the "same" cortical area across
different individual subjects. Before considering the variability across individuals, it is important to note that our face-specific patterns of activation were highly consistent across testing sessions within a single subject. The remarkable degree of test-retest reliability can be seen in the results from four different testing sessions in subject S1 (see the brain images in Fig. 1a, S1
in the bottom left of Fig. 2, S1 in the top right of Fig. 2,
and in Fig. 3a). Given the consistency of our within-subject
results, it is reasonable to suppose that the variation observed across individuals primarily reflects actual individual differences.
Area FF was found in the fusiform gyrus or the immediately adjacent
cortical areas in most right-handed subjects (Fig. 2, Table 1). This
activation locus is near those reported in previous imaging studies
using face stimuli, and virtually identical in Talairach coordinates to
the locus reported in one (40x, 55y, 10z for the mean of our
right-hemisphere activations; 37x, 55y, 10z in Clark et al., 1996 ).
We found a greater activation in the right than left fusiform, a
finding that is in agreement with earlier imaging studies (Sergent et
al., 1992 ; Puce et al., 1996 ). We suspect that our face activation is
somewhat more lateralized to the right hemisphere than that seen in
Courtney et al. (1997) and Puce et al. (1995 , 1996) , because our use of
objects as comparison stimuli allowed us to effectively subtract out
the contribution of general object processing to isolate face-specific
processing. In contrast, if scrambled faces are used as comparison
stimuli (Puce et al., 1995 ; Courtney et al., 1997 ), then regions
associated with both face-specific processing and general shape
analysis are revealed and a more bilateral activation is produced. (See the image in Fig. 3b for a bilateral activation in our own
intact vs scrambled faces run.) Our results showing complete
lateralization of face-specific processing in some subjects (e.g., S1)
but not in others (e.g., S4) are consistent with the developing
consensus from the neuropsychology literature that damage restricted to the posterior right hemisphere is often, although not always, sufficient to produce prosopagnosia (De Renzi, 1997 ).
In addition to the fusiform face area described above, seven subjects
in the present study also showed a greater activation for faces than
objects in a more superior and lateral location in the right hemisphere
in the region of the middle temporal gyrus/STS (Table 1). Although
other areas were observed to be activated by faces compared with
objects in individual subjects (Table 1), they were not consistent
across subjects.
Physiological studies in macaques have shown that neurons that
respond selectively to faces (Gross et al., 1972 ; Desimone, 1991 ;
Perrett et al., 1991 ) are located in both the inferior temporal gyrus
and on the banks of the STS. Cells in inferotemporal cortex tend to be
selective for individual identity, whereas cells in STS tend to be
selective for facial expression (Hasselmo et al., 1989 ) or direction of
gaze or head orientation (Perrett et al., 1991 ). Lesion studies have
reinforced this view, with bilateral STS lesions leaving face-identity
matching tasks unimpaired but producing deficits in gaze discrimination
(Heywood and Cowey, 1993 ). Similarly, studies of human neurological
patients have demonstrated double dissociations between the abilities
to extract individual identity and emotional expression from faces, and
between individual identity and gaze direction discrimination,
suggesting that there may be two or three distinct brain areas involved
in these different computations (Kurucz and Feldmar, 1979 ; Bruyer et
al., 1983 ; Adolphs et al., 1996 ). A reasonable hypothesis is that the
fusiform face area reported here for humans is the homolog of the
inferotemporal region in macaques, whereas the face-selective regions
in the STS of humans and macaques are homologs of each other. If so,
then we would expect future studies to demonstrate that the human
fusiform face area is specifically involved in the discrimination of
individual identity, whereas the MT gyrus/STS area is involved in the
extraction of emotional expression and/or gaze direction.
The import of our study is threefold. First, it demonstrates the
existence of a region in the fusiform gyrus that is not only responsive
to face stimuli (Haxby et al., 1991 , Sergent et al., 1992 ; Puce et al.,
1995 , 1996 ) but is selectively activated by faces compared
with various control stimuli. Second, we show how strong evidence for
cortical specialization can be obtained by testing the responsiveness
of the same region of cortex on many different stimulus comparisons
(also see Tootell et al., 1995 ). Finally, the fact that special-purpose
cortical machinery exists for face perception suggests that a single
general and overarching theory of visual recognition may be less
successful than a theory that proposes qualitatively different kinds of
computations for the recognition of faces compared with other kinds of
objects.
Recent behavioral and neuropsychological research has suggested that
face recognition may be more "holistic" (Behrmann et al., 1992 ;
Tanaka and Farah, 1993 ) or "global" (Rentschler et al., 1994 ) than
the recognition of other classes of objects. Future functional imaging
studies may clarify and test this claim, for example, by asking (1)
whether area FF can be activated by inducing similarly holistic or
global processing on nonface stimuli, and (2) whether the response of
area FF to faces is attenuated if subjects are induced to process the
faces in a more local or part-based fashion. Future studies can also
evaluate whether extensive visual experience with any novel class of
visual stimuli is sufficient for the development of a local region of
cortex specialized for the analysis of that stimulus class, or whether
cortical modules like area FF must be innately specified (Fodor,
1983 ).
FOOTNOTES
Received Dec. 30, 1996; revised Feb. 26, 1997; accepted March 13, 1997.
We thank the many people who helped with this project, especially Oren
Weinrib, Roy Hamilton, Mike Vevea, Kathy O'Craven, Bruce Rosen, Roger
Tootell, Ken Kwong, Lia Delgado, Ken Nakayama, Susan Bookheimer, Roger
Woods, Daphne Bavelier, Janine Mendola, Patrick Ledden, Mary Foley,
Jody Culham, Ewa Wojciulik, Patrick Cavanagh, Nikos Makris, Chris
Moore, Bruno Laeng, Raynald Comtois, and Terry Campbell.
Correspondence should be addressed to Nancy Kanwisher, Department of
Psychology, Harvard University, Cambridge, MA
02138.
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A. C. H. Lee, V. L. Scahill, and K. S. Graham
Activating the Medial Temporal Lobe during Oddity Judgment for Faces and Scenes
Cereb Cortex,
March 1, 2008;
18(3):
683 - 696.
[Abstract]
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Y. Chen, D. Norton, D. Ongur, and S. Heckers
Inefficient Face Detection in Schizophrenia
Schizophr Bull,
March 1, 2008;
34(2):
367 - 374.
[Abstract]
[Full Text]
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T. L. TAYLOR and M. E. THERRIEN
Inhibition of return for the discrimination of faces
Atten Percept Psychophys,
February 1, 2008;
70(2):
279 - 290.
[Abstract]
[PDF]
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M. P. Ewbank, W. A.P. Smith, E. R. Hancock, and T. J. Andrews
The M170 Reflects a Viewpoint-Dependent Representation for Both Familiar and Unfamiliar Faces
Cereb Cortex,
February 1, 2008;
18(2):
364 - 370.
[Abstract]
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J. P. Mitchell
Activity in Right Temporo-Parietal Junction is Not Selective for Theory-of-Mind
Cereb Cortex,
February 1, 2008;
18(2):
262 - 271.
[Abstract]
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S. He
Holes, objects, and the left hemisphere
PNAS,
January 29, 2008;
105(4):
1103 - 1104.
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T. A. Polk, J. Park, M. R. Smith, and D. C. Park
Nature versus Nurture in Ventral Visual Cortex: A Functional Magnetic Resonance Imaging Study of Twins
J. Neurosci.,
December 19, 2007;
27(51):
13921 - 13925.
[Abstract]
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N. Kriegeskorte, E. Formisano, B. Sorger, and R. Goebel
Individual faces elicit distinct response patterns in human anterior temporal cortex
PNAS,
December 18, 2007;
104(51):
20600 - 20605.
[Abstract]
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