Cerebral Cortex April 2006;16:574--586
doi:10.1093/cercor/bhj005
Advance Access publication July 20, 2005

Impaired Face Discrimination in Acquired
Prosopagnosia Is Associated with
Abnormal Response to Individual Faces in
the Right Middle Fusiform Gyrus

Christine Schiltz1, Bettina Sorger2, Roberto Caldara3, Fatima
Ahmed1, Eugene Mayer4, Rainer Goebel2 and Bruno Rossion1

The middle fusiform gyrus (MFG) and the inferior occipital gyrus(IOG) are activated by both detection and identification of faces.
Paradoxically, patients with acquired prosopagnosia following
lesions to either of these regions in the right hemisphere cannot
identify faces, but can still detect faces. Here we acquired
functional magnetic resonance imaging (fMRI) data during faceprocessing in a patient presenting a specific deficit in individual
face recognition, following lesions encompassing the right IOG.
Using an adaptation paradigm we show that the fMRI signal in therMFG of the patient, while being larger in response to faces ascompared to objects, does not differ between conditions presenting
identical and distinct faces, in contrast to the larger response todistinct faces observed in controls. These results suggest that
individual discrimination of faces critically depends on the integrityof both the rMFG and the rIOG, which may interact throughre-entrant cortical connections in the normal brain.

widely used, it is also somewhat misleading, as these regions do
respond to other stimuli than faces and to a different level todistinct objects (e.g. Ishai et al., 2000; Grill-Spector et al.,2004).] Prosopagnosia is classically deﬁned as the inability torecognize faces of conspeciﬁcs despite normal intellectual
abilities and apparently normal recognition of other object
categories (Bodamer, 1947; Farah, 1990; Sergent and Signoret,
1992; Gauthier et al., 1999; Clarke et al., 1997; Laeng andCaviness, 2001). The lesions causing acquired prosopagnosia
can be limited to the right hemisphere (Landis et al., 1988;
Sergent and Signoret, 1992; Uttner et al., 2002) and are usuallyfound in ventral occipito-temporal cortex, involving both oreither of the inferior occipital and fusiform gyri (Damasio et al.,
1982; Sergent and Signoret, 1992; Barton et al., 2002).
Deﬁning the critical roles of the rMFG and the rIOG during
face processing would provide a substantial contribution
towards resolving the apparent paradox between, on the one
hand, neuroimaging data showing that these two visual areas areactivated by both face detection and individuation and, on theother hand, neuropsychological reports of patients impaired inindividual face discrimination but still able to process faces atthe categorical level after brain damage.
To investigate the critical role(s) of the rMFG and the rIOG inface detection and individual recognition we acquired functional magnetic resonance imaging (fMRI) data in a single-casebrain-damaged prosopagnosic patient, P.S., presenting a deﬁcit
restricted to the individual discrimination and recognition of
faces (Rossion et al., 2003; Caldara et al., 2005). Importantly, thepatient’s face detection capacity is intact. Strikingly, her ability
to perform within-category identiﬁcation of stimuli from any
object class other than faces is also in the normal range, eventhough she may show response biases in ‘same/different’ tasks
and be slightly slowed down in visual discrimination tasks on
nonface stimuli compared to normal controls (Rossion et al.,2003). Most importantly, at the anatomical level, her righthemisphere lesion encompasses the inferior occipital cortex
but spares the mid-fusiform gyrus. This is of particular interest
because the lesions underlying prosopagnosia are often more
widely spread (e.g. Sergent and Signoret, 1992) and concern
the right middle fusiform in a large number of cases (e.g. Barton
et al., 2002). Moreover, these patients generally present
associated deﬁcits in object recognition (Damasio et al., 1982;
Gauthier et al., 1999; Laeng and Caviness, 2001). Thus,
measuring neural activation in P.S.’s intact brain areas is an
exceptional means to study the functional neuro-anatomy of theobserved dissociation between intact face detection andimpaired individual discrimination restricted to faces.
To test the hypothesis that face-sensitive neurons in therMFG of P.S. can no longer process facial identity while they are

Keywords: cognitive neuroscience, faces, fMRI, fusiform gyrus,
prosopagnosia, vision
Introduction
Humans are exceedingly efﬁcient in discriminating faces, bothat the category level (‘It’s a face’) and at the individual level (‘It’s
Peter’) (Tanaka, 2001; Grill-Spector et al., 2004). In attempting
to clarify the neuronal mechanisms underlying these complex
discrimination abilities, neuroimaging studies have shown thatthe middle fusiform and inferior occipital gyri consistently yieldsigniﬁcant activations when healthy adults view faces comparedto other objects, with a right hemispheric dominance (e.g.
Sergent et al., 1992; Kanwisher et al., 1997; Halgren et al., 1999;
Gauthier et al., 2000; Rossion et al., 2000; see Haxby et al., 2000
for a review). Recent evidence suggests that these two regionsof the ventral visual pathway, besides being involved in detecting the presence of a face, also play a role in discriminating
individual faces (Gauthier et al., 2000; Eger et al., 2004; GrillSpector et al., 2004; Rotshtein et al., 2005). However, theprecise function(s) of these regions and the nature of theirinteraction with respect to face detection and discrimination
remain(s) largely unresolved.
Given that the middle fusiform gyrus (rMFG) and the inferior
occipital gyrus (rIOG) of the right hemisphere are activated byboth face detection and individuation it is puzzling that brain
damage can impair face identiﬁcation while leaving face detection intact, as in most cases of prosopagnosia (e.g. Damasio
et al., 1982; Gauthier et al., 1999). [These two functional
regions, deﬁned by a comparison of faces and non-face stimuli,
are also referred to in the literature as the ‘fusiform face area’, or‘FFA’ (Kanwisher et al., 1997) and the ‘occipital face area, or
OFA’ (e.g. Gauthier et al., 2000). Even though this terminology is The Author 2005. Published by Oxford University Press. All rights reserved.
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1

Department of Cognitive Development and Laboratoryof Neurophysiology, University of Louvain, Belgium,2
Department of Cognitive Neuroscience, Maastricht
University, The Netherlands; F.C. Donders Centre for
Cognitive Neuroimaging, Nijmegen, The Netherlands,
3
Department of Psychology, University of Glasgow, UK and
4
Department of Neurology, University Hospital Geneva,
Switzerlandstill subserving face detection, we conducted two experiments
using fMR adaptation (Grill-Spector et al., 1999; Kourtzi and
Kanwisher, 2000; Grill-Spector and Malach, 2001; Henson,
2003) in P.S. and in a group of normal controls. Following therationale of the adaptation paradigm, speciﬁcally the regions
coding facial identity yield a larger blood oxygenation leveldependent (BOLD) signal in response to blocks or pairs of trials
displaying different individual faces as compared to blocks orpairs of trials with identical faces (Gauthier et al., 2000; Henson
et al., 2000; Grill-Spector and Malach, 2001; Eger et al., 2004;
Winston et al., 2004; Rotshtein et al., 2005). The recovery fromfMR adaptation to facial identity observed in a face-sensitive
cortical area is taken as evidence that different facial identities
are represented in this region by distinct neuronal response
patterns (see Grill-Spector and Malach, 2001; Henson, 2003).
Here we observed a normal response to faces at thecategorical level in P.S.’s right mid-fusiform gyrus but a failureof recovery from fMR adaptation to facial identity in the same
region. This dissociation between two functions, namely intact
face detection and impaired face discrimination in the same
cortical area, the rMFG, is in line with the behavior of the
prosopagnosic patient P.S. and suggests a lack of contrast
between population responses for different face identities inthis region. More generally, these ﬁndings suggest that thediscrimination of individual faces depends critically on the
integrity of the two ventral visual regions, which may interact
functionally through re-entrant cortical connections.
Materials and Methods
Subjects
The prosopagnosic patient P.S. has been described in detail in Rossion
et al. (2003; see also Caldara et al., 2005) and will only be brieﬂy
described here. P.S. was born in 1950 and sustained a closed head injury
in 1992 which left her with extensive lesions of the left mid-ventral(mainly fusiform gyrus) and the right inferior occipital cortex (Fig. 3A).
Minor damages to the left posterior cerebellum and the right middle
temporal gyrus were also detected on high resolution T1-weighted
anatomical images of her brain. After medical treatment and neuropsychological rehabilitation, P.S. recovered extremely well from her
cognitive deﬁcits following the accident (Mayer et al., 1999). Her only
continuing complaint remains a profound difﬁculty in recognizing faces,
including those of her family, as well as her own face. To determine
a person’s identity, she relies on external (non-face-inherent) cues suchas haircut, moustache or glasses, but also on the person’s voice, posture,gait, etc. The Benton Face Recognition Test (BFRT) (Benton and Van
Allen, 1972) ranks her as highly impaired, and in addition her score atthe Warrington Recognition Memory Test (WRMT) (Warrington, 1984)
for faces characterizes her as signiﬁcantly less accurate than controls(see Table 1 in Rossion et al., 2003). P.S. does not present any difﬁculty
in recognizing objects, even at the subordinate level (Rossion et al.,2003). However, she states that she reads slower than she did prior to
the accident, and she mentions certain difﬁculties in visual orthography.
P.S.’s visual ﬁeld is almost full (small right paracentral scotoma) and hervisual acuity is good (0.8 for both eyes as tested in August 2003), but she
is slightly slower than normal subjects at detecting letters and numbers
in her right visual ﬁeld. She is also slower than normals at a simple
reaction time task.
Besides P.S., a group of seven age-matched females (age range 49--56
years) performed the behavioral experiment. A total of 13 control
subjects participated in the two imaging experiments. Twelve subjects
served as controls in experiment 1, and six of these subjects also took
part in experiment 2. For experiment 1, we scanned three age-matchedfemale controls, two of whom also participated in experiment 2.
However, we had to discard the data of one age-matched subject inexperiment 2 because of excessive head movements. [Note that,
whereas it was clearly important to test all age-matched controls ina behavioural task measuring RTs, this was not a requisite for theneuroimaging experiments, especially since the proﬁle of activation in
the right middle fusiform gyrus remains stable across decades (Brodtmann et al., 2003). As a matter of fact, the proﬁle of response for agematched controls in the present fMRI experiments did not appear todiffer from young controls.] P.S. and the control subjects gave theirinformed written consent prior to the fMRI experiments. The study was
conformed to the Declaration of Helsinki and was approved by the
Ethics Committee of the Medical Department of the University ofLouvain. All subjects proved to be strongly right-handed according to
the Edinburgh Inventory (Oldﬁeld, 1971).
Stimuli and Procedures of the Behavioral Experiment
Five categories of stimuli were used: pictures of faces, cars, chairs, boats
and birds (Fig. 1). Twenty-four individual items were used for eachcategory. All images were presented in grayscale, and sustained a size ofroughly 4 (faces, chairs) or 4.5 (boats, cars, birds) of visual angle. Faces(half male) were cropped so that no external features (hair, etc.) were
present. The subjects were presented with a two-alternative forcedchoice (2AFC) matching task. A ﬁrst stimulus was presented in thecentre of the screen for 1000 ms, followed after 1000 ms of blank screen
by a pair of stimuli remaining on the screen until the subject’s response.
One of the items of the pair was the same as the ﬁrst one, and the otherone was a distractor. The distractor could be either from anothercategory (four possibilities, six trials of each) or from the same category(e.g. two faces). Thus, there were 10 conditions: two levels of
discrimination (‘categorical discrimination’ and ‘individual discrimination’) 3 ﬁve categories; and 24 trials by condition. Participants wererequired to identify the target item in the pair as correctly and as fast as
possible by pressing the left or right of two keys. The pair of stimuli
remained on the screen until the subject’s response. Trials were spacedby 1000 ms. A few practice trials were presented before the beginningof the experiment. The left and right positions of the target stimuli
were counterbalanced across test items and participants received no
feedback for their responses. The whole experiment was divided in two
blocks of 120 trials and lasted for ~25 min.
Data Analysis of the Behavioral ExperimentError rates and RTs for correct responses were analyzed. RTs that werelonger than 3 SDs of the mean were discarded. The difference between
P.S.’s score and the normal controls’ average score divided by thestandard deviations of the normals gave a Z-score, which gives a measureof the patient’s performance relative to controls (e.g. Dixon et al., 1998).
A Z-score > 3 means that P.S.’s performance is above or below 3 SDs of
the normals. We also report the analyses using a modiﬁed t-test

Figure 1. Performance (error rates) in a within-category object-matching task. The
black columns represent the error percentage of P.S. and the transparent columns
depict performance of the seven age-matched control subjects when matching birds,
boats, cars, chairs or faces. P.S. makes significantly and specifically more errors thannormal controls when matching individual faces.

Cerebral Cortex April 2006, V 16 N 4 575

developed to compare a single case to a small sample of normal controls(Crawford and Garthwaite, 2005), avoiding the inﬂation of type I error
rate and exaggeration of the abnormality of patient’s score when using
the Z-score only (Crawford and Howell, 1998).
Stimuli and Procedures of the Imaging Experiments
Subjects were scanned with a 1.5 T Philips Gyroscan Intera scanner at
the University of Louvain, St-Luc Clinic, Brussels (all control subjects
and event-related imaging experiment of P.S.) and a 3 T Siemens AG
Magnetom Trio at the Donders Center in Nijmegen (one localizer
and a pair of runs in the block design experiment for P.S.) provided
with standard quadrature birdcage head coils. In each session,a 3D T1-weighted data set encompassing the whole brain was
acquired for every subject (110 slices, 1.5 mm slice thickness, matrix
size = 256 3 256 3 256). Single shot gradient-echo-planar imaging (EPI)
was performed using the BOLD contrast effect as an indirect marker
of local neuronal activity (Ogawa et al., 1990).
In experiment 1, 30 5 mm axial slices (TR = 3000 ms, TE = 40 ms, ﬂip
angle = 90, matrix size = 64 3 64, FOV = 250) were acquired. Each run
lasted 5 min 33 s (111 TRs). To localize the face-sensitive regions, two or
three independent ‘localizer’ scans were run in which subjects viewed
alternating blocks of faces, blocks of objects (18 s blocks) and a blankﬁxation screen (9 s blocks), as in Rossion et al. (2003). During the blocksof faces and objects stimulation, subjects performed a one-back withincategory discrimination task, as in previous studies (e.g. Kanwisher
et al., 1997). The pairs of localizer scans were repeated three times
for P.S. at different recording sessions separated by several months tocontrol for consistency of the results. Following the localizer scans,three scans were acquired using an fMR adaptation design, which
consisted of alternating blocks of different faces, different cars, identicalfaces, identical cars (18 s blocks) and a blank ﬁxation screen (9 s blocks).
Each face/object block consisted of 18 (different or identical) stimulus
presentations of 800 ms followed by 200 ms blank. Stimuli weregrayscale images subtending, on average, ±3 of the visual ﬁeld, they
were matched for mean luminosity and varied location by 20 pixels in x(10%) and 40 pixels in y (13%). A set of 36 different faces (18 males) and
36 different cars was used in total, minimizing the number of repetitions
for each picture across epochs and runs (4.5 on average). Since facial
identity is known to be processed automatically in the neuronal
populations tested (Rolls, 1992; Gauthier et al., 2000), we used an
independent detection task in both of our fMRI experiments, as done
previously (e.g. Gauthier et al., 2000; Winston et al., 2004; Rotshtein
et al., 2005). More precisely, the subject’s task was to detect theoccurrence of rare face or car stimuli that appeared in red, in a block ofgrayscale stimuli (colour detection task). There were two or threetarget trials by epoch, the same number of targets for all conditions on
average. Using an independent detection task ensured that subjects
were paying attention during the whole experiment, while performingat the same level for all conditions. Furthermore, we used a task that thepatient was able to do (Price and Friston, 1999) as well as normal
controls, in order to avoid the potential confound that any alteredneuronal processing in P.S.’s brain areas could be interpreted asa decrease of general attentional level and/or performance during
scanning. Stimuli and blocks were displayed in a pseudo-random orderwith a PC running E-prime 1.1 (P.S.T, Inc.) through a projector surface
located over the head of the subject and viewed with an angled mirror.
In experiment 2, four runs were acquired using an event-related fMR
adaptation design in which one trial consistent of a sequentiallypresented pair of faces or objects that were either identical or different.
In each run 21 5 mm axial slices (TR = 1500 ms, TE = 40 ms, ﬂip angle =90, matrix size = 4 3 64, FOV = 250) were acquired and runs lasted
5 min. One run contained 32 stimuli pairs (16 identical and 16 different).
Stimuli were presented for 500 ms, separated by a 500 ms blank andeach pair was followed by a 7500 ms blank ﬁxation screen. One second
before each pair the black ﬁxation cross turned red to signal the
upcoming stimuli. The second stimulus of each pair was 10% smaller
than the ﬁrst to minimize adaptation effects due to the repetition of theexact same image (Eger et al., 2004). We used a set of 12 colored faces(6 males) and 12 colored chairs, subtending, on average, ±3 of the visualﬁeld, and subjects had to detect the occurrence of grayscale stimuli(25% of trials). Pictures of chairs were used as control objects in the

576 Face Discrimination in Acquired ProsopagnosiadSchiltz et al.

event-related experiment because they were found to activate the facesensitive areas to a lesser extent than cars, making it easier to localize
the regions of interest.
Data Analysis of the Imaging Experiments
The fMRI signal in the different conditions was compared using
BrainVoyager 2000 (version 4.9, BrainInnovation, Maastricht, The
Netherlands) applying a regression analysis. Prior to analysis, preprocessing consisted of linear trend removal, temporal high-pass ﬁltering(removing frequencies lower than 3 cycles/run) and correction of smallinterscan head movements (Friston et al., 1995). The data were spatiallysmoothed using a Gaussian ﬁlter of 2.8 mm full width at half-maximum(FWHM), and transformed into Talairach space (Talairach and Tournoux, 1988). For anatomical reference, the statistical maps computed
were overlaid to the 3D T1-weighted scans. The predictor time coursesof the regression model were computed on the basis of a linear model ofthe relation between neural activity and hemodynamic response,
assuming a rectangular neural response during phases of visual
stimulation (Boynton et al., 1996).
First, the face-sensitive regions were localized in each individual
subject. In experiment 1 the contrast (faces--objects) was computed
using the ‘localizer’ runs and all contiguous voxels in the middle
fusiform gyrus signiﬁcant at P < 0.05 (one-tailed, Bonferroni-corrected
for multiple comparisons) were considered for further analysis. Given
the reduced sensitivity of the event-related experiment compared tothe block design fMRI (Mechelli et al., 2003) and because normal
subjects performed this experiment at different session than thelocalizers, we localized the face-sensitive areas using the ‘internal
localizer’ (faces--chairs) in the second experiment. Face-sensitive areas
were selected by applying the contrast [(identical faces + different
faces) -- (identical chairs + different chairs)] to the four event-related
runs and voxels in the middle fusiform region signiﬁcant at 0.001 (onetailed, uncorrected) were considered for further analysis. Second, theabove-deﬁned regions of interest (ROI) were tested for fMR adaptation
to facial identity with a repeated-measures ANOVA using the contrast:(different faces--identical faces). Third, in order to directly compare P.S.
and the control subjects, the percent signal change in the ROI was
computed for each condition. In experiment 1 the average percent
signal change was calculated over the 18 s stimulation block. In
experiment 2, three data points around the peak of the hemodynamic
response — deﬁned individually — were averaged to estimate thepercent signal change. fMRI signal changes were calculated using
the baseline epochs displaying a ﬁxation cross as reference. Fourth,the percent signal change was used to compute two fMR-adaptationindexes for faces (DF--SD and DF--SF/DF+SF) and for objects (DO--SO andDO--SO/DO+SO) for each subject, allowing a comparison between P.S.
and the control group in each experiment by means of Z-scores and themodiﬁed t-test score of Crawford and Garthwaite (2005).
The object-sensitive region in the right parahippocampal gyrus wasdetermined by the contrast (objects--faces) computed on the ‘localizer’runs in experiment 1 and by the contrast [(identical chairs + different
chairs) -- (identical faces + different faces)] in experiment 2. Because
this region had a particularly large size (thousands of voxels for somesubjects), for adequate comparison with the face-sensitive areas,a cluster of 4 3 4 3 4 voxels located in the center of the region(P < 0.05 corrected for multiple comparisons) was considered forfurther analysis.

Results
Behavioral Experiment
For discrimination between categories in the 2AFC task,
performance was at ceiling for all subjects (mean: 99% including
P.S., who made no mistakes). P.S.’s RTs were within the normal
range for all conditions of between-category discrimination(Fig. 2A). For the within-category discrimination, all controls
subjects were at ceiling for all conditions ( >98%), including
faces, but the performance was lower for cars (92%). P.S.
differed from controls only for the individual discrimination of

Figure 2. Performance (response times) in between category and within-category object matching tasks. (a) P.S. responds normally fast in a between-category matching task forfaces, birds, boats, cars and chairs. (b) P.S. responds abnormally slow in a within-category face matching task. (c) RTs of correct responses in a within-category matching task
normalized by the corresponding RTs in a between-category matching task [(RTs within -- RTs between)/(RTs within þ RTs between)]. P.S. is significantly and selectively slower
than control subjects in the within-category face matching condition.

faces (83%, Z = 9.44, P < 0.001; t = 9.57, P < 0.001; Fig. 1). Her
correct RTs for individual discrimination did not differ fromcontrols for all the conditions (Fig. 2B), except for faces(slowing down of 794 ms compared to the control mean,
Z = 5.04, P < 0.01; t = 5.09, P = 0.001). When considering theratio between RTs for individual discrimination and categorical
discrimination (i.e. normalizing RTs for each subject), P.S.’s
response times were dramatically slower relative to normal
controls for faces (Z = 3.97, P < 0.001; t = 3.71, P < 0.05) and did
not differ from controls for all other conditions (Zs < 1; ts < 1).
These results complement previous evidence showing that P.S.’sdeﬁcit lies speciﬁcally with the discrimination and recognitionof faces at the individual level (Rossion et al., 2003; Caldara
et al., 2005).

Imaging Experiment 1: Recovery fromfMR Adaptation in a Block Design
Behavioral Data During Scanning
In the localizer experiment, subjects performed the one-backtask at ceiling (mean accuracy 99 ± 0.6%, P.S. 94.3%). P.S. wasslower than both young and age-matched controls (mean RT:
young 416 ± 31ms, age-matched 395 ± 15 ms, P.S. 503 ms;
P < 0.05). Whereas controls performed equally well and fast for
objects and faces, P.S.’s performance for the blocks of objects
was signiﬁcantly better than for faces (16.5 versus 1 error;
P < 0.001) and she tended also to be faster for objects than faces(486 versus 537 ms; t = 0.07).

In the block-adaptation experiment, the color detection task
was performed at ceiling for both controls and P.S. in all four
conditions (DF: 93.9 ± 2.3 versus 94.4; SF: 98.9 ± 1.7 versus
99.5; DO: 98.5 ± 1.6 versus 100; SO: 98.0 ± 2.8 versus 98.8; all
Ps > 0.1, NS). The controls and P.S. also responded with similar
speed in the four conditions (DF: 492 ± 52 versus 460; SF: 449 ± 46
versus 468; DO: 462 ± 34 versus 506; SO: 449 ± 48 versus
481; all Ps > 0.1).
Neuroimaging Results
When comparing blocks of faces and objects in the ‘localizer’
paradigm (Kanwisher et al., 1997), P.S. and all control subjects
showed activation in the rMFG (P < 0.05 corrected for multiple
comparisons, see Fig. 3A,B). The center of activation was
located in the same region in P.S. (36, –54, –20; size: 576 voxels)
as in normal controls (37 ± 6, –47 ± 9, –18 ± 3; size: 545 ± 472
voxels), conﬁrming previous observations (Rossion et al., 2003).
All control subjects also had a signiﬁcant activation in the rIOG
(36 ± 6, –76 ± 10, –10 ± 6; size: 295 ± 365 voxels) whencomparing blocks of faces and objects, whereas this region was
structurally damaged in P.S. (Fig. 3A,B). Additionally, normal
subjects also showed activation in response to faces in the left
MFG (--41 ± 6, –49 ± 9, –16 ± 11; size: 424 ± 230 voxels), again in
an area that was damaged in P.S.’s cortex (Fig. 3).
In the group analysis on normal subjects, the expected
recovery from fMR adaptation to facial identity was highly
signiﬁcant in the rMFG (paired t-test P < 0.001). In addition, inevery single control subject there was a higher activation levelin response to blocks of different faces than during blocks of
Cerebral Cortex April 2006, V 16 N 4 577

identical faces. The contrast ‘different faces--same faces’ (DF--SF)
was signiﬁcant at P < 0.05 in 11/12 normal subjects and showeda non-signiﬁcant trend in the predicted direction at P < 0.139 in
the remaining subject. In this latter subject the same contrast
was highly signiﬁcant (P < 0.001) in the lMFG. In contrast,
the recovery from fMR adaptation in this block design appeared

Figure 3. Regions of interest in the right MGF and in the right PHG in P.S. (a) and in
one control subject (b). The color scale represents statistical values comparing thefMRI signal while subjects viewed blocks of faces versus blocks of objects. Yellow-red
regions yield larger BOLD signal in response to faces than other objects and green-blue
regions respond more to objects than faces. The right MGF (faces versus objects) andPHG (objects versus faces) served as ROI for analyzing the block-design data.

to be reduced in P.S.’s structurally intact rMFG. While blocks
of identical faces yielded similar response proﬁles in the rMFG
of P.S. and controls (see Fig. 4B), the average signal during
blocks of different faces was almost the double (1.7 times
higher) in controls than in P.S. (see ﬁgures 4A and 4B). The
index of recovery from adaptation (DF-SF) was lower for P.S.
than for every individual control subject (see Fig. 5A) and it
was signiﬁcantly smaller in P.S. than in the three age-matched
control subjects taken as a group (Z = 2.04, P < 0.05; t = –1.7,
P < 0.1). There was also a non-signiﬁcant trend in the same
direction when comparing the ratio (DF--SF)/(DF+SF) for
P.S. and the age-matched controls (Z = 1.31, P = 0.09; t = –1.1,
P = 0.19). Moreover, for P.S. the contrast DF--SF was not
signiﬁcant in two of the three scanning sessions (P < 0.463,
P < 0.375 and P < 0.013).
In the rMFG we also observed a signiﬁcant recovery from fMR
adaptation for cars in normal subjects in the group analysis(paired t-test, P < 0.05). This recovery from adaptation was not
signiﬁcantly larger in the controls than in P.S. (DO--SO: Z = 0.15,
P = 0.44; t = –0.16, P = 0.445) and (DO--SO/SO+SO: Z = –0.57,
P = 0.28; t = -0.002, P = 0.5).
Located medially to the rMFG, a region in the right parahippocampal gyrus (rPHG) (24 ± 5, –53 ± 9, –12 ± 3) showed
higher BOLD signal for objects than for faces in the ‘localizer’scans (Epstein and Kanwisher, 1998). In this object-sensitive

Figure 4. Recovery from fMR adaptation in the right MFG and PHG in experiment 1 (block design). (a) Normal recovery from fMR adaptation to facial identity in the right MFG ofcontrol subjects (n 5 12; three runs averaged for each subject) contrasts with (b) reduced recovery from fMR adaptation in the rMGF of P.S. The average percent signal change(±SE) from baseline fixation is plotted for the identical and the different face conditions. Stimulus presentation lasted for 18 s. While the response to blocks of identical faces
yielded a similar response in P.S. as in control subjects, the response to different faces increased on average by 0.25% (SE 0.04) in controls, contrasting with a strongly reduced
0.09% increase in P.S. (c) Normal recovery from fMR adaptation to car identity in the right PHG of control subjects (n 5 12) and (d) P.S.

578 Face Discrimination in Acquired ProsopagnosiadSchiltz et al.

Figure 5. Reduced recovery from fMR adaptation to facial identity in the rMFG of the
prosopagnosic patient P.S. contrasts with a normal recovery from fMR adaptation in
her rPHG (in experiment 1). (a) The difference in percent signal change between DF
and SF (DF--SF) is plotted for P.S. (black bars) and each individual control subject (greybars) in an increasing order. P.S. has a significantly reduced difference in fMRI signal
change compared to the three age-matched control subjects (dark grey bars), for all
three scanning sessions performed on her (three times; three runs averaged). (b) In theright PHG, however, P.S. shows a completely normal recovery from fMR adaptation to
the identity of cars, as indicated by the distribution of her three measurements in a plot
ranking the differences in percent signal change between DO and SO.

region, there was also a recovery from fMR adaptation to object(i.e. cars) identity that reached signiﬁcance in the group analysis(P < 001), and in 5/12 control subjects (P < 0.05). In striking
contrast to the abnormal recovery from fMR adaptation in the
more lateral face-sensitive fusiform region, P.S. showed a normal
difference in percent signal change between different objects(DO) and same objects (SO) in this region (see Fig. 4C,D).
Indeed, the difference in percent signal change between
DO and SO was in the same range for P.S. (0.172) andnormal controls (mean 0.164, SE 0.4) (see Fig. 5B). Both indexes(DO--SO) and (DO--SO/DO+SO) were not signiﬁcantly different
in P.S. and the control subjects (DO--SO: Z = –0.06, P = 0.48;
t = 0.07, P = 0.47) and (DO--SO/SO+SO: Z = –0.3, P = 0.38; t = 0.29,
P = 0.40).
Finally, we analyzed the recovery from adaptation proﬁles in
the rIOG for normal subjects, a cortical region that is structurally damaged in P.S. In the group analysis, we observed
a signiﬁcant recovery from fMR adaptation to facial identity inthis face-sensitive occipital region (paired t-test, P < 0.01) (Fig.
6). Furthermore the activation level in response to blocks ofdifferent faces was higher than during blocks of identical faces
in 11/12 subjects and the contrast (DF--SF) was signiﬁcant at
P < 0.05 in 10 control subjects.
Imaging Experiment 2: Recovery from fMR Adaptationin an Event-related Design
Behavioral Data During Scanning
In the event-related adaptation experiment, the color detection
task was performed at ceiling for both P.S. and controls inall four conditions (DF: 97.5 versus 99.2 ± 1.9; SF: 96.3 versus
99.2 ± 1.9; DO: 95.0 versus 92.5 ± 8.0; SO: 98.8 versus 92.5 ± 8; all

Figure 6. Recovery from fMR adaptation to individual faces in the right IOG of normal
controls in experiment 1 (block design). A significant recovery from fMR adaptation tofacial identity is observed in the right IOG of control subjects (n 5 12; three runs
averaged for each subject), a region that is structurally damaged in P.S.

Ps > 0.1). P.S. and the controls also responded with similar speed
in the four conditions (DF: 625 versus 749 ± 213; SF: 651 versus
543 ± 36; DO: 838 versus 722 ± 171; SO: 759.0 versus 616 ± 205;
all Ps > 0.1).
Neuroimaging Results
The results of the event-related experiment largely conﬁrmed
and extended the abnormal proﬁle of facial identity coding in
the rMFG of P.S.. Whereas normal controls showed a large recovery from fMR adaptation for trials presenting pairs of different faces (paired t-test, P < 0.001) in the rMFG (41 ± 6,
–47 ± 10, –17 ± 5; size: 534 ± 474 voxels), there was no evidenceof such recovery for P.S., as illustrated in Figure 7A. In the facesensitive region of the rMFG (34, –56, –21; size: 133 voxels) her
BOLD response to pairs of different faces (0.18% signal change)
was similar to her BOLD response to pairs of identical faces(0.21% signal change) (see ﬁgure 7B). The contrast comparing
different and same face trials was not signiﬁcant (P < 0.68) in
P.S., whereas this contrast was signiﬁcant in 3/7 control subjects(P < 0.05) and showed a non-signiﬁcant expected trend in thepredicted direction in the remaining control subjects (P < 0.06,
P < 0.07, P < 0.09, P < 0.14). Moreover, in the latter subjects thecontrast DF--SF was signiﬁcant (P < 0.05) in the corresponding
left middle fusiform region. The difference in percent signal
change between pairs of different and identical faces (DF--SF)
was much smaller in P.S. (--0.029) than in the group of control
subjects (mean: 0.12, SE 0.03; Z = 2.26 P < 0.05; t = –2,0, P < 0,05)(Fig. 8A). Likewise, the ratio (DF--SF/DF+SF) was signiﬁcantly
larger in the controls than in P.S. (Z = 3.8, P < 0.001; t = –3.51,
P < 0.01). Contrasting with her abnormally weak BOLD response to pairs of different faces, P.S. had a normal response topairs of identical faces as illustrated in Figure 8B. Conﬁrming
again the results of the block experiment, the BOLD signal
peaks in the SF trials were very similar in P.S. (0.21% signal
change) and normal controls (mean 0.23% signal change, SE0.23) in terms of the peak height (see Fig. 7B).
In the event-related design, we did not observe a signiﬁcantrecovery from fMR adaptation for objects (i.e. chairs) in the
Cerebral Cortex April 2006, V 16 N 4 579

Figure 7. Recovery from fMR adaptation in the right MFG and PHG in experiment 2 (event-related design). (a) The average percent signal change (±SE) from baseline fixation isplotted for the ‘different faces’ and the ‘same faces’ conditions in controls (n 5 7) and (b) in P.S. Reduced response in the rMFG of P.S. to trials with different faces reveal anabnormal neuronal processing of facial identity in the rMFG of the prosopagnosic patient. Trial starts at time 5 0 s. The event-related BOLD response in trials with identical faces
was normal in P.S. compared to the controls. Note that the event-related hemodynamic response appears to start and peak earlier in this condition for P.S. as compared to thegroup of controls, but this was not systematic, i.e. observed in only half of the subjects. The average percent signal change (±SE) in the rPHG to trials with different and identicalchairs did not differ significantly in (c) normal controls and (d) P.S.

rMFG in normal subjects (paired t-test P = 0.36). And the
response pattern in P.S. did not differ from this result, as
indicated by both fMR adaptation indexes (DO--SO: Z = –0.94,
P = 0.17; t = 0.84, P = 0.22) and (DO--SO/SO+SO: Z = –0.54,
P = 0.29; t = 0.44, P = 0.34).
In the object-sensitive region in the rPHG (29 ± 4, –44 ± 11,–13 ± 5), P.S. showed the strongest trend for recovery from
adaptation of all subjects (P < 0.07) for the contrast DO--SO. On
average, her difference in percent signal change between DO
and SO (0.09) was larger than in normal controls (mean 0.03, SE0.04) (Fig. 8B), but this difference was not signiﬁcant (DO--SO:Z = –0.59, P = 0.28; t = 0.51, P = 0.31) and neither was the same
comparison using the ratio (DO--SO/DO+SO) (Z = –0.95,
P = 0.17; t = 0.89, P = 0.20).
Lastly, we focused on the rIOG (44 ± 5, –67 ± 7, –17 ± 7; size
135 ± 105 voxels) of normal subjects, a region which is
structurally damaged in P.S. and found a strong recovery from
adaptation in response to faces in the group analysis (paired
t-test P < 0.01) (Fig. 9). In this occipital region, pairs of different
faces yielded higher activation levels than pairs of identical faces
in 6/7 subjects and this comparison (DF--SF) was signiﬁcant infour controls.
Complementary Analyses for the Localizer Experiment
In the localizer scans (used to identify the face-sensitive regionsin the ventral visual pathway) blocks of different faces (DF) are
580 Face Discrimination in Acquired ProsopagnosiadSchiltz et al.

contrasted with blocks of different objects (DO), while subjects
perform a one-back discrimination task. In the two fMR
adaptation experiments, on the contrary, blocks (or pairs) ofdifferent and identical faces are compared, while subjects are
performing an independent color detection task. Given that we
observed a reduced or absent recovery from adaptation todifferent face stimuli in the rMFG of P.S. in the two latter
experiments, we also analyzed the proﬁle of the hemodynamic
response to different faces and objects in the face localizer
experiment for P.S. and the normal control subjects.
Overall, the average percent signal change difference between faces and objects did not differ between P.S. (DF--DO:
0.43 ± 0.15) and the normal controls (DF--DO: 0.39 ± 0.05)(Z = –0.93, P = 0.18; t = 0.77, P = 0.23), conﬁrming our previous
ﬁndings (Rossion et al., 2003). However, when computing
separately the difference in percent signal change between
faces and objects for the ﬁrst half of the block (1--9 s) and thesecond half of the block (10--18 s), P.S. differed signiﬁcantly
from the control subjects (Fig. 10A,B). During the ﬁrst half ofthe block the differential response was higher in P.S. (DF--DO:0.36) than in controls (DF--DO: 0.22 ± 0.07) (Z = –2.09, P < 0.05;
t = 1.92, P < 0.05). However, this activation level was notsustained and was signiﬁcantly lower than in the controls during
the second half of the block (DF--DO: P.S. 0.5 versus controls
0.55 ± 0.03) (Z = 1.83, P < 0.05; t = –1.60, P < 0.07) (Fig. 10C ).
Thus, while we conﬁrmed our previous ﬁndings of an overall

Figure 8. P.S. shows significantly reduced recovery from fMR adaptation to facial
identity in the rMFG, but normal recovery from fMR adaptation in the rPHG inexperiment 2 (event-related design). (a) The difference in percent signal change
between DF trials and SF trials is plotted for P.S. and each individual control subject in
an increasing order. P.S. (black bars) has a significantly reduced difference in fMRI
signal change compared to the age-matched-control (dark grey bars) and theremaining control subjects in the rMFG. (b) In the rPHG P.S. shows a normal recovery
from fMR adaptation to the identity of cars.

normal range response for faces in the rMFG of patient P.S.
during the localizer scans, her proﬁle of activation indicatesa lack of sustained responses to different faces, in line with theresults of the adaptation experiments reported above. Note that
P.S.’s normal mean response in the rMFG to the block ofdifferent faces is largely due to the fact that the initial responseof the patient in the localizer scans is in the upper range andcompensates for the signiﬁcantly lower response found in thesecond part of the epoch (Fig. 10a).
It should be kept in mind, however, that this result in thelocalizer scans was obtained during a one-back discrimination
task that P.S. was unable to perform correctly. It is of particularinterest that the same proﬁle of response is found in theadaptation experiments in which P.S. performed an independent task as well as controls and in which we had a measure of
the recovery from adaptation by comparing to blocks or trials ofidentical faces repeated.
Although the present design did not directly address thisquestion, it provides indications that P.S. does not have an
intrinsic reduction of signal for faces (versus objects) as
compared to controls in the right fusiform gyrus. Indeed, P.S.
is in the normal range if one compares the percent signal
change when the same face and the same object are repeated(SF--SO) (experiment 1 — block design: P.S. 0.08% versus
controls 0.13 ± 0.16%, Z-score 0.35, P = 0.36; experiment 2 —event-related design: P.S. 0.22% versus controls 0.17 ± 0.21%,
Z-score –0.22, P = 0.41). In other words, when presented
always the same stimulus, P.S. shows normal face selectivity.
Discussion
The neuroimaging experiments reported here reveal that therMFG of P.S. — a patient with acquired prosopagnosia following

Figure 9. Recovery from fMR adaptation to individual faces in the rIOG of normal
controls in experiment 2 (event-related design). A significant recovery from fMR
adaptation to facial identity is observed in the rIOG of control subjects, a region that is
structurally damaged in P.S.

brain damage — presents an anomalous response pattern withrespect to individual face discrimination, despite being structurally intact and responding as well as in normal subjects tofaces at the basic category level. The abnormal signal in P.S.’sright fusiform gyrus most likely reﬂects a failure of recovery toadaptation to different facial identities, because in the patient
the BOLD response to both identical and distinct faces is at thelevel of the response to identical faces in normal control
subjects. The reduced response observed in the ‘different
face’ conditions in P.S.’s rMFG contrasts sharply with therecovery from fMR adaptation to facial identity occurring in
the corresponding area in normal control subjects, as observed
previously (Gauthier et al., 2000; Henson et al., 2000; GrillSpector and Malach, 2001; Eger et al., 2004; Winston et al., 2004;
Rotshtein et al., 2005). It also contrasts with the normal
recovery from fMR adaptation to objects (i.e. cars and chairs)
observed in the patient’s object-sensitive region in the rPHG
(Epstein et al., 1999), showing that the lack of recovery from
adaptation is not unspeciﬁc. [Contrary to the robust adaptation
to faces, words and houses in the rPHG reported previously by
Avidan et al. (2002), the adaptation to chairs in the PHG did notreach signiﬁcance in our study. The reduced sensitivity of thepresent event-related fMRI experiment compared to the block
design used by the previous authors might account for our
failure to observe adaptation in response to chairs in the rPHG
(Mechelli et al., 2003).] The present experiment did not allow
us to test the recovery from adaptation to non-face objects inthe lateral occipital complex (LOC), deﬁned as a region that
responds more to objects than scrambled images of objects(Malach et al., 1995). This area does not appear to present
a larger response to face than non-face object categories, butshows adaptation to shape repetition (Grill-Spector et al., 1999;
Kourtzi and Kanwisher, 2000; Grill-Spector and Malach, 2001).
An interesting extension of this work would thus be to test
whether the LOC, which appears to be functionally preserved
bilaterally in the patient’s brain (Sorger et al., 2004), shows
normal recovery from adaptation to objects, including faces.
This area may contribute to the normal within-category
Cerebral Cortex April 2006, V 16 N 4 581

Figure 10. The differential BOLD response to faces versus objects in the rMFG of P.S. is not sustained throughout the second half of the stimulus presentation block, contrary to theundiminished signal in normal controls. (a) The average percent signal change (±SE) from baseline fixation is plotted for the ‘different faces’ and ‘different objects’ conditions of thelocalizer experiment in controls (n 5 12) and (b) in P.S. (c) When the block is divided into two parts (1--9 s and 10--18 s) it appears that the differential response is higher in P.S. thancontrols during the initial half and lower during the second part of the 18 s stimulation block.

discrimination of non-face objects, but also to some extent to
the reduced — but not abolished — ability of the patient todiscriminate faces at the individual level.
The speciﬁc alteration of the neuronal response to facial
identity is in line with P.S.’s behavioural impairments. In a 2AFC
matching task P.S. correctly and rapidly performed betweencategory discriminations for all object categories tested. [Admittedly, between-category discrimination (e.g. discriminating
a car from a boat) is, almost by deﬁnition, a very simple task. It
may be harder only for objects with similar shapes, belonging to
the same superordinate categories, such as fruits for instance.
We have shown previously that PS was able not only todiscriminate, but to name accurately and quickly all the objects(including all fruits, animals) of the Snodgrass and Vanderwart’s
databank (see Rossion et al., 2003). Moreover, even if theperformance was at ceiling, we measured RTs and subjects were
instructed to respond as fast as possible. P.S.’s RTs in thisbetween-category discrimination task did not differ fromcontrols.] She also discriminated all objects (i.e. cars, chairs,boats, birds) at the individual level, except faces. Thus she
presents an abnormal response pattern speciﬁcally with respect
to individual face discrimination, both at the behavioural andthe neuronal level.
Cases of prosopagnosia described with a deﬁcit restricted tothe category of faces are extremely rare (Sergent and Signoret,1992) and most patients have associated deﬁcits at the basic
582 Face Discrimination in Acquired ProsopagnosiadSchiltz et al.

level for object recognition (e.g. Damasio et al., 1982; Sergent
and Signoret, 1992; Clarke et al., 1997; Dixon et al., 1998;
Gauthier et al., 1999), including the notorious prosopagnosic
patient L.H. described by Farah and colleagues (Farah et al.,
1995; see Levine and Calvanio, 1989). Furthermore, thesepatients are generally found to be impaired at subordinate
judgments of non-face categories, especially when tested in ﬁne
discrimination tasks and/or measuring RTs as well as recognition performance (Damasio et al., 1982; Gauthier et al., 1999;
Laeng and Caviness, 2001). Here, P.S. presents a normal object
recognition performance at the basic level, as also shown by her
ﬂawless recognition of the whole set of colorized Snodgrass-Vanderwart pictures (see Rossion et al., 2003; Table 3).
Moreover, she is able to discriminate non-face categories at
the individual level as accurately and as fast as normal controls,even though, as noted in the Introduction, she may show
response biases and be slightly slowed down in ‘same/different’tasks during within-category discrimination tasks on non-facestimuli compared to normal controls (Rossion et al., 2003). Such
response biases and slowing down are common in braindamaged patients, particularly when task difﬁculty increases(e.g. Benton, 1977, 1986; Gauthier et al., 1999). However,overall, her performance in computer object discrimination
and recognition tasks indicates that, unlike most cases ofacquired prosopagnosia (e.g. Damasio et al., 1982; Levine andCalvanio, 1989; Sergent and Signoret, 1992; Gauthier et al.,

1999), P.S.’s ability to recognize and discriminate non-face
objects is remarkably preserved. Her deﬁcit appears to be
restricted to the extraction of diagnostic information on faces(Caldara et al., 2005), most likely following damage to aneural subsystem for faces developed through extensive
visual experience (Morton and Johnson, 1991; Le Grand et al.,2001).
Neuroimaging studies in normals have consistently shown thestrongest activation in the right fusiform gyrus, both for facedetection and individualization (Gauthier et al., 2000; GrillSpector and Malach, 2001; Eger et al., 2004; Grill-Spector et al.,
2004; Winston et al., 2004; Rotshtein et al., 2005). The
anomalous BOLD response to conditions with different faces
in the rMFG of the prosopagnosic patient P.S. reported here
points towards a critical function of this region in individual
face discrimination. Contrary to the abnormally weak BOLD
signal yielded by the presentation of different facial identities in
the rMFG, as also found in the second time epoch of her
localizer scans, the response to conditions with identical faces
in the same region in P.S. is similar to that of control subjects.
This observation is in accordance with P.S.’s preserved ability tocategorize faces at the basic level, despite her severe andselective impairment in discriminating faces at the individuallevel. We suggest that this normal BOLD response in the rMFG
to ‘identical’ conditions underlies her conserved face detection
skill and conclude that activation in the rMFG is sufﬁcient forface detection. This proposal is consistent with recent evidence
showing that faces that are classiﬁed at the basic category level
activate the face-sensitive region in the fusiform gyrus, even
without being identiﬁed at the subordinate level (Grill-Spector
et al., 2004). Additionally, our data support the view that theinitial input to the rMFG cannot stem exclusively from the rIOG
(Rossion et al., 2003). In P.S.’s brain, the inferior occipital cortex
is damaged, yet the rMFG yields a normal activation level in
response to faces as a category. The input giving rise to thisactivation must therefore originate from posterior, low-levelvisual areas other than the rIOG (Kim et al., 2004).
The evidence that face-sensitive neurons in the fusiform
gyrus code both the global shape of the category ‘face’ and theﬁne characteristics of the identity of individual faces in normal
healthy adults (Halgren et al., 1999; Gauthier et al., 2000; GrillSpector and Malach, 2001; Eger et al., 2004; Grill-Spector et al.,
2004; Winston et al., 2004; Rotshtein et al., 2005) is inaccordance with information analysis of single-cell populationsin the monkey brain, showing that the very same neuronal
population can subserve the two functions (Rolls, 1992; Rolls
and Deco, 2001), perhaps at different time-scales (Sugase et al.,1999). To our knowledge, the present fMR adaptation experiment is the ﬁrst report of a neural dissociation between these
two functions in acquired prosopagnosia. It indicates that anarea like the rMFG can be necessary but not sufﬁcient for
a complex function like face individuation, while being sufﬁcient but not necessary for a simpler task like face detection.
P.S.’s prosopagnosic deﬁcit is most likely due to the massive
damage encompassing the rIOG, the same region in which thelargest overlap of lesions causing prosopagnosia is found(Bouvier and Engel, 2004). However, prosopagnosia can also
follow after more anterior lesions, i.e. to the fusiform gyrus,
sparing the rIOG (e.g. Barton et al., 2002; Delvenne et al., 2004).
These observations indicate that successful face identiﬁcation
requires both the rMFG and the rIOG to be structurally andfunctionally intact. In contrast, the distinction of faces fromother categories, or the segmentation of a face stimulus ina visual scene, can be preserved despite lesions to at least one ofthese two areas.
The reduced BOLD signal in the ‘different faces’ condition in
P.S.’s structurally intact right fusiform gyrus reveals an ineffective coding of facial identity in this face-sensitive visualarea. This abnormal response in the spared visual system ofa patient with acquired prosopagnosia contrasts with therecovery from fMR adaptation observed in the same region innormal adults. The physiological mechanisms underlying therecovery from adaptation effects are not completely understood, and may be plural (see Grill-Spector and Malach, 2001;
Henson, 2003). Regarding the representation of faces, different
facial identities may be coded by partially overlapping or
degenerate (Tononi et al., 1999) subsets of neurons in a relatively small population (Rolls, 1992; Young and Yamane, 1992)
in the extrastriate visual cortex. According to this view (seeRolls and Deco, 2002), the recurring presentation of identicalfaces repeatedly activates the subpopulation of cells coding forthis identity, leading to a decreased neuronal discharge at the
global level that can be recorded in the fMRI hemodynamic
response (the so-called fMR adaptation) (Gauthier et al., 2000;
Grill-Spector and Malach, 2001; Henson, 2003; Winston et al.,2004). In contrast, the presentation of different facial identities
activates a partially distinct neuronal response pattern for eachidentity in the same population, leading to a larger global BOLD
response (recovery from adaptation, see Grill-Spector andMalach, 2001). The failed recovery from fMR adaptation tofacial identity shown here in P.S.’s rMFG mirrors a lack of these
distinct sparse response codes representing the different facial
identities in the rMFG, possibly due to missing (re)entrant input
from the damaged rIOG.
Addressing the question of the nature of face representationsin the two areas discussed here, a recent fMRI study in normal
subjects has shown that fMR adaptation to familiar faces in therIOG reﬂects the physical difference between morphed faces,
whereas the rMFG shows no sensitivity to the physicaldifference as long as the face stimuli are perceived as similar
identities (Rotshtein et al., 2005). However, the rMFG did show
release from adaptation when stimuli were perceived as
different identities (Rotshtein et al., 2005; see also Eger et al.,2004). Even though familiar and unfamiliar faces are processed
differently in these areas, as we have shown previously usingmorphs between familiar and unfamiliar faces (Rossion et al.,2001), our current results are consistent with and complement
the above-mentioned observations. During the blocks or trialsof different face stimuli, we presented clearly distinct facial
identities (corresponding to the ‘between’ condition in Rotshtein et al.’s experiment), thus expecting to observe a recovery
from adaptation in both areas in normal controls, as foundpreviously (Gauthier et al., 2000; Grill-Spector and Malach,2001; Eger et al., 2004; Grill-Spector et al., 2004). For the patient
P.S., the faces that are of different identities are perceived as
identical in a large number of cases, hence the reduced recovery
from adaptation in her rMFG, consistent with the observationsof Rotshtein et al. (2005). However, in this latter study, only
normal controls were tested and thus the question of whether
the rIOG was necessary for intact face discrimination could not
be addressed. Furthermore, in normal subjects, Rotshtein et al.
(2005) have not shown, and not claimed, that the rMFG wasindependent of the rIOG in extracting facial identity. In fact,
this latter study suggests that the rIOG is involved (and the
Cerebral Cortex April 2006, V 16 N 4 583

present study suggests that it is necessary) for ﬁne-grained
discrimination of individual faces, whereas the rMFG appears to
extract a more global (perhaps ‘holistic’, see Rossion et al.,2000) representation of identity. All in all, our results indicatethat when it comes to differentiating faces, both the rMFG and
the rIOG are critical, the rMFG appearing to be dependent on
normal sustained inputs from the rIOG. If the rIOG is unable todetect ﬁne physical differences, it may be that the rMFG is nolonger able to categorize different facial identities, independentof their physical difference. This leads to the interesting
prediction that given her rIOG lesion, in P.S., we should notﬁnd a larger recovery from adaptation in the rMFG in thecondition ‘between’ of Rotshtein et al. (2005) compared totheir condition ‘within’, even in a block design (e.g. alternating
between several pairs of faces).
Both the neuroimaging data of P.S. and the signiﬁcantrecovery from adaptation found in normal controls in therMFG and rIOG in the present study suggest that efﬁcientindividual discrimination of faces has to rely on the integrity,and possibly the functional integration (Price and Friston,2002), taking place between the rMFG and rIOG. Based on
the present data (see also Rossion et al., 2003), we suggest thatthe initial input to the rMFG leading to face-related activation is
independent from face-sensitive responses in the rIOG and may
originate from posterior, low-level visual areas (Kim et al.,2004). However, in the intact brain, the rIOG is critical to faceindividualization, perhaps by entertaining a re-entrant loop withthe more anterior rMFG. The higher-order, face-sensitive visualarea in the rMFG may contribute through re-entrant signallingto the emergence of functional responses in the earlier facesensitive visual area in the rIOG (Bullier et al., 2001; Galuske
et al., 2002), where global information could serve as a header
to set up the processing of ﬁne information related to facial
identity (Sugase et al., 1999). This proposal is in agreement withthe presence of cortical feedback (Mumford, 1992; Lamme andRoelfsema, 2000; Bullier et al., 2001) and re-entrant phasic
signaling in the visual cortex (Edelman, 1993). Through these
feedback connections, higher-level perceptual computations
and representations that involve high-resolution details, ﬁnegeometry and spatial precision may involve lower visual areas
and be reﬂected in the later part of their neurons’ activities(Mumford, 1992; Lee et al., 1998;). Given their smaller receptiveﬁelds, neurons in the rIOG may be ﬁne-tuned to subserve suchﬁne discrimination, which are critical in real life situations (e.g.
recognizing the same identity across age differences, changes inlighting, discriminating siblings or twins, etc.). In sum, in ourview, the damage to the rIOG underlies P.S.’s prosopagnosic
deﬁcit, both directly (i.e. through a damage to the representations and processes taking place normally in this area), but also
indirectly, given that this region cannot provide normal inputs
to other areas, such as the rMFG.
In the present study, we have reported a functional neuroanatomy study of a single case of prosopagnosia to address thequestion of the necessary face-sensitive regions coding for facial
identity in the human brain and to draw hypotheses regarding
their interaction during normal face processing. Our single-casestudy should by no means be generalized to all cases of
prosopagnosia, i.e. that all such patients should present an
absence of recovery from adaptation in the rMFG if it isstructurally intact. There is considerable variability between
acquired prosopagnosics with respect to lesion localizationand extent and performance on various discrimination and
584 Face Discrimination in Acquired ProsopagnosiadSchiltz et al.

recognition tasks (e.g. Sergent and Signoret, 1992; Barton et al.,2002) and the cause of the deﬁcit will vary between different
patients, preventing such generalization. Recently, there has
also been a growing interest in studying cases of developmental
or congenital prosopagnosia, i.e. people presenting a deﬁcit inface processing that is apparent from early childhood, without
any underlying neurological basis (for reviews see Kress andDaum, 2003; Behrmann and Avidan, 2005). With respect to theﬁndings of the present study, it is interesting to note that casesof congenital prosopagnosia appear to show a normal facerelated activation in the rMFG and rIOG, as well as normal
recovery from adaptation in these regions (Avidan et al., 2005).
Thus, in these cases, there is no correlation between behavioral
performance (impaired) in face discrimination and hemodynamic responses (normal) in the intact face-sensitive areas of
the right hemisphere, unlike the pattern reported here in thecase of a brain-damaged patient. Further research will beneeded to determine the neural basis of congenital prosopagnosia, in particular how their behavioral impairments can be
related (or not) to an inefﬁcient coding of individual face
representations in the right ventral pathway.
In summary, the present study revealed a reduced recovery
from fMR adaptation speciﬁc to faces in the structurally intact
rMFG of a patient with pure prosopagnosia following damage tothe right occipital gyrus. These ﬁnding supports the view thatboth the rMFG and the rIOG are critical for coding faces at theindividual level. In addition, they show that two levels ofprocessing, namely face detection and individual face discrimination, can be dissociated (i.e. normal and impaired respectively) in the same cortical area, here the rMFG, in line with the
behavior of the brain-damaged prosopagnosic patient.
Notes
We are very grateful to P.S. for her patience and motivation during theexperiments, and to three anonymous reviewers for helpful andconstructive comments on a previous version of this manuscript. This
study and the ﬁrst author are supported by a grant (ARC 01/06-267,
Communauté Franc
xaise de Belgique — Actions de Recherche Concertées). B.R. is supported by the Belgian National Foundation for
Scientiﬁc Research (FNRS).
Address correspondence to Christine Schiltz, Laboratory of Neurophysiology, 49 avenue Hippocrate, University of Louvain, 1200 Brussels,
Belgium. Email: schiltz@nefy.ucl.ac.be.

References
Avidan G, Hasson U, Hendler T, Zohary E, Malach R (2002) Analysis of
the neuronal selectivity underlying low fMRI signals. Curr Biol
12:964--972.
Avidan, G, Hasson, U, Malach, R, Behrmann M (2005) Detailed
exploration of face-related processing in congenital prosopagnosia:
2. Functional neuroimaging ﬁndings. J Cogn Neurosci (in press).
Barton JJ, Press DZ, Keenan JP, O’Connor M (2002) Lesions of thefusiform face area impair perception of facial conﬁguration inprosopagnosia. Neurology 58:71--78.
Behrmann M, Avidan, G (2005) Congenital prosopagnosia: face blindfrom birth. Trends Cogn Sci 9:180--187.
Benton AL (1977) Interactive effects of age and brain disease on reaction
time. Arch Neurol 34:369--70.
Benton AL (1986) Reaction time and brain disease: some reﬂections.
Cortex 22:129--140.
Benton AL, Van Allen LW (1972) Prosopagnosia and facial discrimination. J Neurol Sci 15:167--172.
Bodamer J (1947) Die-Prosop-agnosie. Arch Psychiatr Nervenkrankh
179:6--54.

Bouvier SE, Engel SA (2004) Patterns of cortical damage in achromatopsia and prosopagnosia. J Vis 4, Suppl 205a.
Boynton GM, Engel SA, Glover GH, Heeger DJ (1996) Linear systems
analysis of functional magnetic resonance imaging in human V1.
J Neurosci 16:4207--4221.
Brodtmann A, Puce A, Syngeniotis A, Darby D, Donnan G (2003) The
functional magnetic resonance imaging hemodynamic response to
faces remains stable until the ninth decade. Neuroimage 20:520--528.
Bullier J, Hupe JM, James AC, Girard P (2001) The role of feedback
connections in shaping the responses of visual cortical neurons. Prog
Brain Res 134:193--204.
Caldara R, Schyns P, Mayer E, Smith ML, Gosselin F, Rossion B (2005)
Does prosopagnosia take the eyes out of face representations?
Evidence for a defect in representing diagnostic facial information
following brain damage. J Cogn Neurosci (in press).
Clarke S, Lindemann A, Maeder P, Borruat FX, Assal G (1997) Face
recognition and postero-inferior hemispheric lesions. Neuropsychologia 35:1555--1563.
Crawford JR, Garthwaite PH (2005) Testing for suspected impairments
and dissociations in single-case studies in neuropsychology: evaluation of alternatives using Monte Carlo simulations and revised tests
for dissociations. Neuropsychology (in press).
Crawford JR, Howell DC (1998) Comparing an individual’s test score
against norms derived from small samples. Clin Neuropsychol
21:482--486
Damasio AR, Damasio H, Van Hoesen GW (1982) Prosopagnosia:
anatomic basis and behavioral mechanisms. Neurology 32:331--341.
Delvenne JF, Seron X, Coyette F, Rossion B (2004) Evidence forperceptual deﬁcits in associative visual (prosop)agnosia: a singlecase study. Neuropsychologia 42:597--612.
Dixon MJ, Bub DN, Arguin M (1998) Semantic and visual determinants offace recognition in a prosopagnosic patient. J Cogn Neurosci
10:362--376.
Edelman GM (1993) Neural Darwinism: selection and reentrant signaling in higher brain function. Neuron 10:115--125.
Eger E, Schyns PG, Kleinschmidt A (2004) Scale invariant adaptation in
fusiform face-responsive regions. Neuroimage 22:232--242.
Epstein R, Kanwisher N (1998) A cortical representation of the local
visual environment. Nature 392:598--601.
Epstein R, Harris A, Stanley D, Kanwisher N (1999) The parahippocampal place area: recognition, navigation, or encoding? Neuron
23:115--125.
Farah MJ (1990) Visual agnosia: disorders of object recognition and what
they tell us about normal vision. Cambridge, MA: MIT Press.
Farah, MJ, Levinson, KL, Klein, KL (1995) Face perception and withincategory discrimination in prosopagnosia. Neuropsychologia
33:661--674.
Friston KJ, Frith CD, Turner R, Frackowiak RS (1995) Characterizing
evoked hemodynamics with fMRI. Neuroimage 2:157--165.
Galuske RA, Schmidt KE, Goebel R, Lomber SG, Payne BR (2002) The
role of feedback in shaping neural representations in cat visualcortex. Proc Natl Acad Sci USA 99:17083--17088.
Gauthier I, Behrmann M, Tarr MJ (1999) Can face recognition really bedissociated from object recognition? J Cogn Neurosci 11:349--370.
Gauthier I, Tarr MJ, Moylan J, Skudlarski P, Gore JC, Anderson AW (2000)
The fusiform ‘face area’ is part of a network that processes faces at
the individual level. J Cogn Neurosci 12:495--504.
Grill-Spector K, Malach R (2001) fMR-adaptation: a tool for studying thefunctional properties of human cortical neurons. Acta Psychol
107:293--321.
Grill-Spector K, Kushnir T, Edelman S, Avidan G, Itzchak Y, Malach R(1999) Differential processing of objects under various viewing conditions in the human lateral occipital complex. Neuron 24:187--203.
Grill-Spector K, Knouf N, Kanwisher N (2004) The fusiform face areasubserves face perception, not generic within-category identiﬁcation. Nat Neurosci 7:555--562.
Halgren E, Dale AM, Sereno MI, Tootell RB, Marinkovic K, Rosen BR(1999) Location of human face-selective cortex with respect toretinotopic areas. Hum Brain Mapp 7:29--37.
Haxby JV, Hoffman EA, Gobbini IA (2000) The distributed neural system
for face perception. Trends Cogn Sci 4:223--233.

Henson RN (2003) Neuroimaging studies of priming. Prog Neurobiol
70:53--81.
Henson R, Shallice T, Dolan R (2000) Neuroimaging evidence fordissociable forms of repetition priming. Science 287:1269--1272.
Ishai A, Ungerleider LG, Martin A, Haxby JV (2000) The representationof objects in the human occipital and temporal cortex. J Cogn
Neurosci 12 (suppl 2) :35--51.
Kanwisher N, McDermott J, Chun MM (1997) The fusiform face area:a module in human extrastriate cortex specialized for face perception. J Neurosci 17:4302--4311.
Kim M, Ducros M, Carlson T, He S, Ugurbil K, Kim D-S (2004) Loop andlinear connections in high-order human occipito-temporal cortex.
Soc Neurosci Abstr 300. 14.
Kourtzi Z, Kanwisher N (2000) Cortical regions involved in perceiving
object shape. J Neurosci 20:3310--3318.
Kress T, Daum I (2003) Developmental prosopagnosia: a review. Behav
Neurol 14:109--121.
Laeng B, Caviness VS (2001) Prosopagnosia as a deﬁcit in encoding
curved surface. J Cogn Neurosci 13:556--576.
Lamme VA, Roelfsema PR (2000) The distinct modes of vision offered by
feedforward and recurrent processing. Trends Neurosci 23:571--579.
Landis T, Regard M, Bliestle A, Kleihues P (1988) Prosopagnosia andagnosia for noncanonical views. An autopsied case. Brain
111:1287--1297.
Le Grand R, Mondloch CJ, Maurer D, Brent HP (2001) Early visualexperience and face processing. Nature 410:890.
Lee TS, Mumford D, Romero R, Lamme VA (1998) The role of the
primary visual cortex in higher level vision. Vis Res 38:2429--2454.
Levine DN, Calvanio R (1989) Prosopagnosia: a defect in visual
conﬁgural processing. Brain Cogn 10:149--170.
Malach R, Reppas JB, Benson RR, Kwong KK, Jiang H, Kennedy WA,
Ledden PJ, Brady TL, Rosen BR, Tootell RB (1995) Object-related
activity revealed by functional magnetic resonance imaging inhuman occipital cortex. Proc Natl Acad Sci USA 92:8135--8139.
Mayer E, Fistarol P, Valenza N (1999) Prise en charge neuropsychologique d’une patiente prosopagnosique. In: La reducation en
neuropsychologie: etudes de cas (Azouvi P, Perrier, D, Van der
Linden, M, ed.). Marseille: Solal.
Mechelli A, Price CJ, Henson RN, Friston KJ (2003) Estimating efﬁciency
a priori: a comparison of blocked and randomized designs. Neuroimage 18:798--805.
Morton J, Johnson MH (1991) CONSPEC and CONLERN: a two-process
theory of infant face recognition. Psychol Rev 98:164--181.
Mumford D (1992) On the computational architecture of the neocortex.
II. The role of cortico-cortical loops. Biol Cybern 66:241--251.
Ogawa S, Lee TM, Kay AR, Tank DW (1990) Brain magnetic resonanceimaging with contrast dependent on blood oxygenation. Proc Natl
Acad Sci USA 87:9868--9872.
Oldﬁeld RC (1971) The assessment and analysis of handedness: theEdinburgh inventory. Neuropsychologia 9:97--113.
Price CJ, Friston KJ (1999) Scanning patients with tasks they can
perform. Hum Brain Mapp 8:102--108.
Price CJ, Friston KJ (2002) Degeneracy and cognitive anatomy. Trends
Cogn Sci 6:416--421.
Rolls ET (1992) Neurophysiological mechanisms underlying faceprocessing within and beyond the temporal cortical visual areas.
Philos Trans R Soc Lond B Biol Sci 335:11--20; discussion 20--11.
Rolls ET, Deco G (2001) Computational neuroscience of vision. Oxford:
Oxford University Press.
Rossion B, Dricot L, De Volder A, Bodart J-M, Crommelinck M, de Gelder
B., Zoontjes R (2000) Hemispheric asymmetries for whole-based andparts-based face processing in the human fusiform gyrus. J Cogn
Neurosci 12:793--802.
Rossion B, Schiltz C, Robaye L, Pirenne D, Crommelinck M (2001) How
does the brain discriminate familiar and unfamiliar faces? A PET studyof face categorical perception. J Cogn Neurosci 13:1019--1034.
Rossion B, Caldara R, Seghier M, Schuller AM, Lazeyras F, Mayer E (2003)
A network of occipito-temporal face-sensitive areas besides the right
middle fusiform gyrus is necessary for normal face processing. Brain
126:2381--2395.

Cerebral Cortex April 2006, V 16 N 4 585

Rotshtein P, Henson RN, Treves A, Driver J, Dolan RJ (2005) Morphing
Marylin into Maggie dissociates physical and identity face representation in the brain. Nat Neurosci 8:107--113.
Sergent J, Signoret JL (1992) Varieties of functional deﬁcits inprosopagnosia. Cereb Cortex 2:375--388.
Sergent J, Ohta S, MacDonald B (1992) Functional neuroanatomy of faceand object processing. A positron emission tomography study. Brain
115:15--36
Sorger B, Schiltz C, Caldara R’ Kriegeskorte N, Mayer E, Rossion B,
Goebel R (2004) Functional neuroanatomy of the visual system ina prosopagnosic. OHBM Abstr 369.
Sugase Y, Yamane S, Ueno S, Kawano K (1999) Global and ﬁne
information coded by single neurons in the temporal visual cortex.
Nature 400:869--873.

586 Face Discrimination in Acquired ProsopagnosiadSchiltz et al.

Talairach G, Tournoux P (1988) Co-planar stereotaxic atlas of thehuman brain. New York: Thieme Verlag.
Tanaka JW (2001) The entry point of face recognition: evidence for faceexpertise. J Exp Psychol Gen 130:534--543.
Tononi G, Sporns O, Edelman GM (1999) Measures of degeneracy andredundancy in biological networks. Proc Natl Acad Sci USA
96:3257--3262.
Uttner I, Bliem H, Danek A (2002) Prosopagnosia after unilateral rightcerebral infarction. J Neurol 249:933--935.
Warrington EK (1984) Recognition memory test. Windsor: NFER-Nelson.
Winston JS, Henson RNA, Fine-Goulden, MR, Dolan RJ (2004). fMRIadaptation reveals dissociable neural representations of identity andexpression in face perception. J Neurophysiol 92:1830--1839.
Young MP, Yamane S (1992) Sparse population coding of faces in theinferotemporal cortex. Science 256:1327--1331.