Does Prosopagnosia Take the Eyes Out of Face
Representations? Evidence for a Defect inRepresenting Diagnostic Facial Information
following Brain Damage
Roberto Caldara1, Philippe Schyns1, Eugène Mayer2, Marie L. Smith1,Frédéric Gosselin3, and Bruno Rossion4

Abstract& One of the most impressive disorders following brain
damage to the ventral occipitotemporal cortex is prosopagnosia, or the inability to recognize faces. Although acquired
prosopagnosia with preserved general visual and memory
functions is rare, several cases have been described in theneuropsychological literature and studied at the functional andneural level over the last decades. Here we tested a braindamaged patient (PS) presenting a deficit restricted to thecategory of faces to clarify the nature of the missing and preserved components of the face processing system when it isselectively damaged. Following learning to identify 10 neutral
and happy faces through extensive training, we investigatedpatient PS’s recognition of faces using Bubbles, a responseclassification technique that sampled facial information acrossthe faces in different bandwidths of spatial frequencies[Gosselin, F., & Schyns, P. E., Bubbles: A technique to reveal

INTRODUCTION
In humans, faces convey at a glance a great deal of
information (e.g., person’s identity, gender, mood, ethnical origin, age) that is crucial for efficient social
interactions. A long-standing goal of the face processing
research agenda has been to identify which cues are
extracted from a face in order to categorize it (according
to its gender, expression, identity, race, etc.). In otherwords, what is the diagnostic (i.e., most useful) information that is extracted from faces, and how does it vary
according to the task at hand? To address this issue,
various methods have been used, such as categorizing
faces presented with masked or isolated facial features(e.g., Bruce, Burton, et al., 1993), with surface and shapeproperties separated (Hill, Bruce, & Akamatsu, 1995),
with only information from the principal components ofa face set (e.g., Calder, Burton, Miller, Young, & Akamatsu,

1
3

University of Glasgow, 2Hôpitaux Universitaires de Genève,
Université de Montréal, 4University of Louvain

D 2005 Massachusetts Institute of Technology

the use of information in recognition tasks. Vision Research,
41, 2261–2271, 2001]. Although PS gradually used lessinformation (i.e., the number of bubbles) to identify faces
over testing, the total information required was much larger
than for normal controls and decreased less steeply withpractice. Most importantly, the facial information used to
identify individual faces differed between PS and controls.
Specifically, in marked contrast to controls, PS did not use theoptimal eye information to identify familiar faces, but instead
the lower part of the face, including the mouth and theexternal contours, as normal observers typically do whenprocessing unfamiliar faces. Together, the findings reported
here suggest that damage to the face processing system ischaracterized by an inability to use the information that is
optimal to judge identity, focusing instead on suboptimal
information. &2001), and, more recently, by sampling facial information at a fine grain to derive the information subset associated with categorization judgments (Smith,
Cottrell, Gosselin, & Schyns, 2005; Sekuler, Gaspar, Gold,& Bennett, 2004; Schyns, Bonnar, & Gosselin, 2002;
Gosselin & Schyns, 2001).
Humans are generally considered face processing
experts because they efficiently extract the diagnostic
cues allowing face categorization, identification, andgeneralization (Tanaka, 2001; Diamond & Carey, 1986).
Yet, several observations illustrate the complexity anddifficulty of face categorization. First, the ‘‘expert’’ human face processing system of adults undergoes quite
a long development, not reaching full maturity before puberty (Campbell, Coleman, et al., 1999; Taylor,
McCarthy, Saliba, & Degiovanni, 1999; Carey, 1992). Secondly, the face processing system is not so efficient at
processing unfamiliar faces. This is demonstrated by
the striking difference between our excellent ability togeneralize across different images of familiar faces andour relatively poor performance when performing the

Journal of Cognitive Neuroscience 17:10, pp. 1652–1666

same task on unfamiliar faces (e.g., Bruce, Henderson,
et al., 1999; Burton, Wilson, Cowan, & Bruce, 1999; Young,
McWeeny, Hay, & Ellis, 1986), suggesting that the efficiency of face processing arises from robust long-term
representations of others’ faces.
Possibly the most striking evidence that the extraction of diagnostic information from faces is nontrivial
is the observation of patients who have lost this ability, despite no other obvious impairments of the visual system (at least as far as neuropsychologicaltests demonstrate) and a preserved ability to recognize
people through other modalities (e.g., voice). This
deficit in face recognition is a spectacular impairment,
and despite its rarity (it occurs in less than 1% of braindamaged patients, Sergent & Villemure, 1989), it has
attained considerable notoriety in the neuropsychological literature since the first clinical observations(see Grüsser & Landis, 1991; Quaglino, 1867; Wigan,1844) and the introduction of the term prosopagnosia
by Bodamer (1947) (English translation by Ellis &Florence, 1990).
Prosopagnosia generally follows brain damage to bilateral occipitotemporal areas (e.g., Sergent & Signoret,
1992; Farah, 1990; Landis, Regard, Bliestle, & Kleihues,
1988; Damasio, Damasio, & Van Hoesen, 1982). Althoughable to detect a face among objects (‘‘face detection’’),prosopagnosic patients typically lose the ability to identify
familiar faces, including famous persons, friends, andrelatives, or even their own face (Damasio, 1985). Despite
the rarity of prosopagnosic patients with well-preserved
visual perception and memory, a number of such braindamaged cases have been described over the last decades(e.g., Sergent & Signoret, 1992; Farah, 1990; for more
recent cases, see Laeng & Caviness, 2001; Gauthier,Behrmann, & Tarr, 1999).
The clinical and anatomical conditions of prosopagnosia have been of great interest to cognitive
neuroscientists willing to clarify the neurofunctional
mechanisms of normal face processing. Several key
findings have been presented. Anatomical descriptions of
prosopagnosia support the critical role of the righthemisphere in the occipitotemporal pathway of faceprocessing (Bouvier & Engel, 2004; Sergent & Signoret,
1992; Landis et al., 1988). The double dissociations reported between the ability to perceive unfamiliar andfamiliar faces (Malone, Morris, Kay, & Levin, 1982),
between the recognition of facial expression and facial
identity (e.g., Tranel, Damasio, & Damasio, 1988; Bruyer
et al., 1983), or between lip reading and face identification (Campbell, Landis, & Regard, 1986) have helped inisolating the different subfunctions in a cognitive architecture of face processing (Bruce & Young, 1986). The
study of prosopagnosia at the functional level has also
probably initiated (Bodamer, 1947) and fuelled the‘‘never-ending’’ debate about the modularity of faceprocessing (e.g., Gauthier et al., 1999; Farah, Levinson,& Klein, 1995; Damasio et al., 1982).

Despite the theoretical importance of studies of
prosopagnosic patients, an important area of researchremains largely unexplored. In descriptions of clinicalcases, it is usually reported that prosopagnosic patients
who rely on nonfacial cues to recognize people (gait,
voice, clothes, etc.) still attend to and extract information from faces that is used to recognize people. Yet,these patients appear to have lost the ability to
extract and/or build diagnostic representations of otherpeople’s faces. What is then the nature of the facial
information that brain-damaged prosopagnosic patients
extract when processing faces? To put it differently,
what is the nature of the missing and preserved components of the face processing system when it is selectively damaged? Answering this question would
undoubtedly contribute to functionally characterizing
the selective face impairment that is prosopagnosia,
and from there on providing a better understanding offunctional aspects of the normal, ‘‘expert,’’ face processing system.
However, several limitations may hamper a better
understanding of the functional aspects of face processing in prosopagnosia. First, cases of prosopagnosia
described in the literature usually suffer from many
low-level and high-level visual deficits besides theirface impairments: loss of visual acuity, visual field defects (hemianopia, upper visual field problems, or left
quadrantopsia generally; for reviews, see Barton, 2003;
Goldsmith & Liu, 2001), achromatopsia (about 60%
of overlap, Bouvier & Engel, 2004), or difficulties at
general configural processing and object recognition(e.g., Gauthier et al., 1999; Sergent & Signoret, 1992;
Levine & Calvanio, 1989). Consider, for instance, LH,
a patient initially presented with a disproportionately large deficit with face compared to object processing, performing even in the normal range forsubtle discrimination tasks on nonface objects suchas pairs of glasses (Farah, Levinson, et al., 1995).
Other studies revealed that LH had clear deficits at
performing visual discrimination tasks on complex
patterns and at recognizing nonface objects (e.g.,
Farah, McMullen, & Meyer, 1991; Levine & Calvanio,
1989; Levine, Calvanio, & Wolf, 1980). Crucially, his
recognition failures proved to be more pronounced
for certain categories than others (e.g., living vs.
nonliving, Farah, McMullen, et al., 1991), and previous
studies had concluded that the deficits were due togeneral factors such as the loss of configural information processing (Levine & Calvanio, 1989). Althoughthese deficits may not explain fully the face recognition impairment observed in these patients, they arelikely to affect and modify the strategies that thepatient uses when processing faces. A trivial example
is that of a prosopagnosic suffering from achromatopsia, who will be unable to use eyes or hair color torecognize or discriminate between people. For thesereasons, it is inherently difficult to establish the

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functional aspects that are specific to the face impairment in prosopagnosia when associated deficits arelikely to present confounding factors.
Any attempt to clarify the components (missing andpreserved) of prosopagnosia is confronted with the
problem of defining the information cues to perform
various (face) categorization tasks. A typical strategy is
to hypothesize a priori that certain facial cues are notproperly processed in prosopagnosia and test thishypothesis by selectively manipulating these cues. Thisapproach may provide interesting outcomes but isinherently limited because faces vary according toa large number of dimensions (Valentine, 1991). By
selecting a priori a subset of this information for
testing, one could miss important components of theface recognition impairment or disclose processing
differences between the damaged and normal faceprocessing systems that are not central to prosopagnosia. Moreover, by selectively manipulating the typeof information that is diagnostic for the task at handover a number of trials, subjects may be forced torely on this information (e.g., the mouth) and learn
strategies to dramatically improve their performance(Barton, Press, Keenan, & O’Connor, 2002; Barton,
Cherkasova, & O’Connor, 2001). Thus, a better approach to determine the information used and notused is to bias as little as possible the tested information. To this end, we trained and tested a single
patient (PS ) suffering from a remarkably selective
deficit at processing faces following brain damage(Rossion et al., 2003) with Bubbles (Gosselin & Schyns,
2001), a low-bias sampling technique that can deter-mine the specific visual information used to categorize
a visual stimulus.
PS is a 54-year-old woman who sustained a closed
head injury in 1991. After several months of spontaneous recovery and neuropsychological reeducation, she
was left with massive prosopagnosia, being unable torecognize famous and familiar people. Despite large
occipital and occipitotemporal lesions (see Figure 1 in
Rossion et al., 2003), PS’s low-level vision is almost
perfect, her visual acuity being 8/10 in both eyes (August2003), with a full visual field, apart from a small left
paracentral scotoma. She reads normally (althoughslowly) and, crucially, does not present any problem atobject perception and recognition, even for subordinatelevel discriminations (Rossion et al., 2003). Her deficit
truly appears to be restricted to the category of faces.
With faces, PS is able to categorize a face as a face,discriminate faces from objects and from a complex scene
background, even at brief presentations (100 msec;
Schiltz et al., in press). Her gender and expression
performances are relatively well preserved, althoughslightly below normal range (Rossion et al., 2003). This
is in stark contrast with her inability to recognize previously seen or familiar faces and to match unfamiliar
faces (see Methods section). In sum, PS is unable to derive an individual representation of a face that is both
selective and invariant (robust) enough so that it canbe discriminated from other faces and be associatedwith the same or other views of the same face (Rossion
et al., 2003).
Given the restriction of her deficit to the face category and that PS is alert, cooperative, and without

Figure 1. Application of Bubbles technique to the three-dimensional space composed of a two-dimensional face and spatial scales on thethird dimension. (A) The original image is decomposed into five different scales. (B) The bubbles were randomly positioned at each scaleand covered approximately the same area across scales. (C) The bubbles were integrated with the decomposed pictures and summed toresult in a ‘‘bubbleized’’ face.

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any learning difficulties (Caldara et al., submitted), she
may represent an ideal case to isolate the nature of the
facial information extracted by an impaired face processing system, relative to normals. Moreover, althoughrelying also on nonfacial cues to identify faces, PS
reports using facial cues in general and does not avoid
looking at people’s faces. Her performance at matchingtasks is under normal range, but generally better thanchance (Caldara et al., submitted; Schiltz et al., in press;
Rossion et al., 2003). Hence, her face processing system,
although inefficient at recognizing individual faces, is notcompletely disrupted, as supported by the significant
face-sensitive activations observed in her right hemisphere in the fusiform gyrus (Rossion et al., 2003) andalso in the superior temporal sulcus and the dorsolateralprefrontal cortex (Sorger et al., 2004).
To specify PS’s use of facial information, we used
Bubbles (Gosselin & Schyns, 2001), a response classification technique sampling the information in 3-D
space (2-D image  spatial frequencies). Bubbles samples an input space to present sparse versions of thefaces as stimuli (see Figure 1). PS and normal controls must categorize the sparse stimuli, and Bubbles
keeps track of the samples of information that leadto correct and incorrect identification responses. From
this information, we can establish how each region of
the input space contributed to face identification performance and depict the selective use with an effective
stimulus.

In the present study, we applied this technique to PS
and a group of control participants, who identified a setof previously learned unfamiliar faces displaying two
possible expressions (neutral or happy) (see Methods)(Schyns et al., 2002).

RESULTS
The proportion of the search space, revealed at eachtrial, was adjusted on-line to maintain accuracy at
75% correct by adjusting the total number of bubbles
sampling the input (see Methods and Gosselin &Schyns, 2001). Following the experiment, independently for each subject and session of trials, we averaged
across trials the number of bubbles required to resolve
the task.
Overall, PS required many more bubbles (mean =157; SD = 30) than controls (mean = 38; SD = 17,
Z = 7.04, p < .001; Figure 2), meaning that PS needed
more facial cues, on average, to achieve the same
performance level. Even her lowest number of bubbles,
recorded on her last session (116), was much larger
than that of controls (mean = 25; SD = 6; Z = 14.89,
p < .001), even though PS was allowed to perform
approximately twice as many trials as the controls(Figure 2, see Methods section). Another striking
measure is the proportion of decrease in number of
bubbles between the first three and the last three

Figure 2. Mean number of
bubbles per session used by
PS and seven controls tocorrectly adapt to the task
(AM = age-matched controls;
C = young adult control
subjects). The performancefor all the participants was
automatically kept to a 75%
correct identification.

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sessions, which was 54% (SD = 8%) for controls, but
only 42% for PS (Z = 2.16, p < .01).
These descriptive results illustrate not only that theface processing system of PS is not as efficient as that ofnormal subjects, but also that PS can still extract somediagnostic information to identify faces at 75% correct.
To address the critical question of the nature of thisdiagnostic information, we compared PS’s effective stimulus with the average of controls ( p < .05, see Methods
and Figure 3). PS does not use information from theupper part of faces (i.e., the eyes) to identify them, butinstead relies mainly on the lower part of faces (i.e.,the mouth). In contrast, all controls used the eyesand some of the mouth, with a bias toward the upper
part of the face (see also Schyns et al., 2002; Gosselin& Schyns, 2001).
From the diagnostic information, we also compared
the relative use of spatial frequency information between PS and controls. To this end, independently foreach spatial frequency (SF) band sampled, we pooled
the ProportionPlanes of all controls and Z scored them.
To evaluate PS’s relative use of SF bands in a normative
context (the performance context of controls), for eachSF bands we averaged PS’s Z scores computed using themean and standard deviation of controls. Figure 4 reveals that PS used the high spatial frequency bands toencode the mouth, in contrast to controls who usedsignificantly more high spatial frequencies to encode theeyes. Finally, we derived a fine-grain, pixel-per-pixel
evaluation of PS’s use of information in a direct comparison with controls. Independently for each SF band,
we took the logarithm of the division of the ProportionPlane of PS with the average ProportionPlane of controls. We then summed these logarithms to derive ameasure of sensitivity to information (see Methods andSmith et al., 2005). This measure provides an accountof the relative sensitivity of PS to all aspects of the face,on a pixel-per-pixel basis, in the identity task. To readthe figure, red (vs. blue) values indicate a higher (vs.
lower) sensitivity of PS with respect to controls. The
results clearly show that for face identification, PS uses
suboptimally the eyes (particularly the left one) and she
has a clear bias to the outline contours and the lower
part of the face, including the mouth (see Figure 5). To
further specify theses biases, we isolated the Z scores
over the eyes and the mouth regions for PS and forthe average performance of controls. We then built the
distributions of Z scores across scales, subtracted theZ scores between controls and PS, and depicted the resulting Z score distributions (Figure 5, right). PS usedsignificantly less the eyes (negative values) than themouth (positive values) to achieve correct identifications (Z > 1.65; p < .05). Conversely, controls used lessthe mouth than the eyes to perform the task efficiently.

DISCUSSION
Our general goal was to shed light on the nature of themissing and preserved components of the face processing system when it is selectively—albeit not entirely—
damaged. The first observation was that the prosopagnosic patient PS and controls dramatically differed in
the amount of information needed (i.e., number of
bubbles) to recognize an individual face. Furthermore,
PS improved throughout the recognition sessions, using progressively less information. Her ‘‘learning curve’’
was, however, less steep than normal controls, including age-matched subjects. Of particular interest, PS andcontrols differed on the type of information used torecognize faces. PS relied much less on information
contained in the upper part of the face (the eye

Figure 3. Top: diagnostic
information used by PS
and the average for thecontrols. Bottom: diagnostic
information for each control
subject (AM = age-matched;C = young adult control
subjects). Note that PS is the
only participant that did not
use the eyes to adapt
to the task.

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Figure 4. Top and middle:
diagnostic information used
to resolve the identification
task at each independent scale
for PS and the controls. Notethat three control subjects
did not use any significant
information for the scale goingfrom 16 to 8 cycles per face.
Bottom: patient PS’s Z score
distributions in the use of
spatial frequency bands.
The dashed line indicates a
Z score of 1.65 ( p < .05).
PS used significantly less highspatial frequency information(128–64 and 64–32 cycles perface) when compared to thecontrol group. Note that no
meaningful information was
found at the fifth frequency(coarsest scale) for PS or
the controls.

region), but in stark contrast with controls, she used
the lower part, particularly the mouth. She also presented a bias to use of the outline contour of the faces.
Finally, PS was more impaired in extracting informationin high spatial frequencies, but did not differ fromnormals for low spatial frequency bands. We discussthese findings in turn.
Quantitative Assessment of Visual Information
The observation that PS required a larger number of
bubbles than normal controls can be considered asanother illustration of her dramatic face processing
impairment. In previous behavioral experiments, she
was less accurate and/or slower when having to discriminate and recognize faces at the individual level (Rossion
et al., 2003). Remember that PS was extensively trainedwith full-face stimuli before the Bubbles sessions toreach the same level of faultless performance as con-trols. In the present study, her recognition performancewith faces revealed through the Bubbles apertures wasmaintained at the same threshold as normals (75%)
throughout the whole experiment. In other words, she
required more information to reach the same level of
performance as controls. Whereas normal observers can
extract information from a relatively degraded image tomatch their internal representation of a given face, sheneeded more information. This result cannot be accounted for by a general learning problem (face–nameassociations) because PS has no known learning or
memory deficits (Mayer, Fistarol, & Valenza, 1999). In
fact, she can name common objects normally and evenlearn arbitrary associations between shapes and names
rapidly (Rossion et al., 2003).
Although the fact that a prosopagnosic can learn andrecognize 10 face–name associations might be paradoxical at first glance, one must point out that she needed
3 hr to be flawless, whereas controls achieved thisCaldara et al.

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Figure 5. Left: optimality of the information used by PS compared to the control group. Dark blue regions correspond to negative values andillustrate a suboptimal use of information. Light blue regions correspond to values close to 0, a comparable use of information. The red and yellow
areas correspond to positive values, reflecting the bias of PS in the task. Right: distribution of the performances in the Eyes and Mouth regions, after
the subtraction of PS’s Z score distributions from the controls. Z scores >1.65 indicates when these particular features were significantly ( p < .05)
used as diagnostic information. A positive value indicates a bias for PS; a negative value indicates a bias for the controls. Note that PS was more
efficient for the Mouth (Z > 1.65; p < .05) than the Eyes region. The reverse pattern is observed for the controls.

ceiling performance in about 10 min. Furthermore, previous studies of prosopagnosic patients have reported
that they are able to learn up to 12 new face–nameassociations, and retrieve them consciously (Sergent &Signoret, 1992; Dixon, Bub, & Arguin, 1998) or unconsciously (de Haan, Young, & Newcombe, 1987; Bruyer
et al., 1983), although this learning is slow and does
not generalize well to new views (e.g., three quarters
to full front and vice versa) of the same faces (Sergent& Signoret, 1992). Even when the exact same picture isused for learning and testing, prosopagnosic patientsusually perform well below normal range (Sergent &Signoret, 1992).
Given that she had as much time as she wished during
the recognition tests with Bubbles, the observation that
she needed more information in the degraded (‘‘bubbleized’’) faces to recover the facial attributes necessary
to match against her stored representations suggeststhat these are poorer than in normals. This observation
does not necessarily mean that PS’s prosopagnosia liesin the associative level and that her perception of faces isnormal (i.e., a ‘‘pure associative prosopagnosia’’). In
fact, her inability to match normal face pictures presented under identical or different viewpoints and thelocus of her lesions (Schiltz et al., in press; Rossion et al.,2003) point to a face deficit of high level visual processes. However, as pointed out previously, disruption at theperceptual level of the face processing system maydisable a set of face processes, making it impossible toencode rich facial representations in memory (Sergent &Signoret, 1992; Farah, 1990).

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Qualitative Assessment of Visual Information
In what respects then, are PS’s internal representationsof faces poorer than normals? Behavioral and neurophysiological evidence suggest that faces are represented both in terms of individual features (e.g., eyes,
nose, mouth, etc.) and also as undissociated wholes(Tanaka & Farah, 1993; Perrett, Hietanen, Oram, &Benson, 1992; Perrett, Rolls, & Caan, 1982). Behavioral
studies have also pointed to the importance of themetric distances between face features (e.g., betweeneyes and nose), the so-called second-order relations(Diamond & Carey, 1986), to recognize faces (for areview on the different types of configural processing,see Maurer, Grand, & Mondloch, 2002). In the present
experiment, it may well be that normal controls requireless information than PS because their internal representations are more detailed at the level of critical single
features such as the eyes. Alternatively, normal controls’
featural representations may be better integrated into
holistic facial templates (Tanaka & Farah, 1993), allowing
one to reconstruct full facial representations from smaller fragments of the face than PS. An analysis of thequality of PS’s internal representation of the faces, thatis, which parts of the face are and/or are not represented, may help to clarify this question.
A striking feature of PS’s diagnostic information is that
it is weighted less on the upper part of the face (eyes/
eyebrows) than on the lower part (mouth area). Admittedly, the dominant reliance of PS on the mouth area
may not hold for all the faces of the set,1 and there is a

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certain amount of interindividual variability for the
average diagnostic image in normal controls (Figure 3).
Yet, the general pattern of respective diagnostic facial
information observed is clear: Whereas the region of theeyes dominated the picture for normal subjects, PS
weighted strongly the area around the mouth of theface. This finding suggests that PS’s internal representations of the faces contain mostly information in themouth area, whereas the normal face processing systemrelies largely on the eyes (see also Schyns et al., 2002;
Gosselin & Schyns, 2001).
There is considerable evidence supporting the viewthat the eyes are dominant in the recognition of facial
identity. Human adults can recognize and remember
faces from the eyes only (McKelvie, 1976) and experiments designed to measure the relative importance ofdifferent facial features for individual face recognition
have consistently shown the dominance of the eye/eyebrow combination, followed by the mouth and then
the nose (Tanaka & Farah, 1993; Fraser, Craig, & Parker,
1990; Haig, 1985, 1986; Sergent, 1984; Walker Smith,
1978; Davies, Ellis, & Shepherd, 1977). In fact, recent
evidence even suggests that the eyebrows alone convey
critical information to recognize faces (Sekuler et al.,
2004; Vinette, Gosselin, & Schyns, 2004; Sadr, Jarudi, &Sinha, 2003).
Given these considerations, there are several possible
explanations regarding the decreased reliance on theeyes area following prosopagnosia, as found in PS.
First, given that the eye area contains more information in high spatial frequencies (HSFs), it may bethought that PS’s lesser reliance on the eyes reflects ageneral deficit with HSFs. This observation would be inagreement with previous reports of reduced contrast
sensitivity in the high-frequency range for nonfacial
stimuli in prosopagnosic patients (Barton, Cherkasova,
Press, Intriligator, & O’Connor, 2004; Rizzo, Corbett,Thompson, & Damasio, 1986), although there are reports of prosopagnosic patients having a marked deficit
at resolving mostly low spatial frequencies on facestimuli (e.g., Sergent & Villemure, 1989). Critically, inthe present experiment there is clear evidence that PS
uses HSFs for the mouth and that the deficit is not
related to HSF processing per se, but to the encoding of
information from the eyes, at any SF.
Second, following her brain damage, PS may have lostthe ability to extract other information than the cues
associated with identity on the eye region (e.g., expression, eye-gaze direction) and would have turned herinterest to different (e.g., the mouth) face cues wheninteracting with others. However, whereas she reports
being unable to recognize people, she does not complain at all about judging people’s expressions, and her
ability to categorize facial expressions on pictures isrelatively preserved as compared to identity (Rossion
et al., 2003). There is no evidence either that she lost her
ability to detect eye gaze direction, although this has notbeen tested previously. Furthermore, PS’s lesions spareentirely the region of the posterior superior temporalsulcus responding to faces (Sorger et al., 2004), which
subtends eye-gaze detection in normals (Hoffman &Haxby, 2000). These behavioral and anatomical observations suggest that her deficit in processing the eyeregion is unlikely to be explained by a general impairment in extracting social cues from the eyes.
A third hypothesis that may account for PS’s decreasein the representation of the eyes is also indirect. Given
her inability to recognize faces, she may have developed
some strategies over time to be able to recognize people
while avoiding the embarrassment caused by staring.
Indeed, it is well known that prosopagnosics report
avoiding looking at people they encounter in the eyes
because they need quite some time and numerous cues
to recognize familiar persons and one cannot afford
staring at people for long periods (Gauthier et al.,1999). According to these views, PS might have overrepresented the mouth area for reasons that have nothing
to do with the structure of the face and the loss of her
face individual recognition abilities per se, but as a resultof the development of new strategies following her
impairment. However, as far as we can tell from interactions with her and from her verbal reports, she does
not avoid eye-to-eye contact in real-life situations. As amatter of fact, she is a very lively and ‘‘social’’ person,
who—as with other prosopagnosics—has developed anumber of strategies to cope positively with her deficit
in real-life situations: Rather than avoiding people, shewill try to anticipate and rely on all possible cues (facial
and nonfacial) to be able to recognize them efficiently
and rapidly, but then will engage in normal social
interactions with these persons. During the experiment,
PS verbally reported information on all face features(eyes, eyebrows, teeth, etc.). She often described thepresented face before giving an answer, suggesting that
she explored the entire image. Moreover, PS’s highest
reliance on the mouth and on external facial features
relative to normals concurs with her verbal reports
about people she encountered after her accident. When
asked about how people she met in the laboratory look
like, for instance, she always refers to the shape of themouth and teeth area, as well as to external contour
information (hair, head size, etc.).
Although the last two hypotheses cannot be completely dismissed, we favor the hypothesis that her
overrepresentation of the mouth area at the expenseof the eyes has to do with the interaction between the
structure of the faces—what type of cues are conveyed
by the eyes—and the expertise of the face processing
system with these cues. Several observations support
this hypothesis. When presented in isolation, the eye
area can be conceived as a visual structure made up of
several (pairs of ) components (i.e., eyebrows, eyelid,
eyelash, eyeball, pupil, and iris). As such, there is muchconfigural information (e.g., distance between the eyes,

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between the eyebrows and the eyes) in this structure,much more so than in other internal facial features suchas the mouth and the nose, as demonstrated in several
experiments by Leder, Candrian, Huber, and Bruce(2001) and Leder and Bruce (2000). These authors
showed that configural information is not limited to
the whole face but consist at least partly of locallyprocessed relations between facial elements, in particular at the level of the eyes. Rakover and Teucher (1997)
also found inversion effects for isolated features andshowed larger effects for the eye area than for themouth, suggesting that the former conveys more configural information. In fact, a large number of studies
showing the important role of configural information in
face perception mostly or exclusively used spatialchanges (e.g., inward/outward or up/down movements)
at the level of the eyes (e.g., Leder et al., 2001; Macho &Leder, 1998; Kemp, McManus, & Pigott, 1990; Hosie,
Ellis, & Haig, 1988; Haig, 1984). Corroborating yet again
the critical role of the eye region in supporting configural information, there is evidence from the whole/partadvantage paradigm that the holistic processing of theface is larger for the eyes than for other features(Donnelly & Davidoff, 1999). Most interestingly, whereas
the whole/part advantage is observed for the mouth on
unfamiliar faces and does not increase with familiarization, this effect appears only for the eyes after substantial training with a face set (Donnelly & Davidoff, 1999).
Thus, the ability to extract and use configural information on the eyes seems to develop over time andconcerns mostly familiar faces. This is also the conclusion of two experiments conducted by O’Donnell andBruce (2001), which tested subjects’ discrimination abilities on pairs of familiar and unfamiliar faces with subtle
differences at the level of one of four features (hair, jaw,eye, and mouth). Strikingly, when faces differed only by
the eyes, the subjects’ performance was excellent forfamiliar faces (above 90%) and below chance for unfamiliar faces. There was no effect of familiarity for theother features, including the mouth. This familiarity
effect restricted to the eyes was found whether the modifications were configural (eye spacing, Experiment 1)
or local (brightness change, Experiment 2). The conclusion of the authors is that details from the upper partof the face may offer particularly salient informationin the initial structuring of categorical knowledge about
individual faces (O’Donnell & Bruce, 2001). This holds
obviously for a normally functioning face processing
system. The present study, contrasting the representations used by normal viewers and a damaged faceprocessing system, indicates that a critical feature of
prosopagnosia is the inability to extract such salient
information, largely conveyed by the eye area, to build
robust representations of faces.
To sum up, we suggest that relative to normals, PS
does not rely on eyes because her face processing
system is not able to extract and store information,

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Journal of Cognitive Neuroscience

perhaps mostly configural, from this area of the face.
One difficulty with this version of Bubbles is that thefeatures of the different faces were presented at thesame locations across the different faces of the set(Gosselin & Schyns, 2001), minimizing the diagnosticity
of configural metric information (Maurer et al., 2002;
Diamond & Carey, 1986) to individualize faces. However, by revealing the face features used by the subjects,
for instance, the eyes, the nose, and the mouth for a face
identification task, Bubbles can reveal the use of the facefeatures that are essential for proper configural processing. The absence of the use of the eyes in patient PS
reflects an inability to extract information that is known
to be critical for configural processing of faces in normal
viewers, although we cannot exclude at this stage that PS
suffers mainly from a deficit at extracting both configuraland local information in this area of the face.
Besides a suboptimal use of the eye region, PS reliedmuch less on internal features than on external features(i.e., contour), relative to normals (Figure 5, left). Thisobservation can also be related to the inner-features
advantage observed for familiar faces in normals, namely, the robust finding that the inner-face parts are more
useful than those of the outer face for recognizing
familiar faces but not unfamiliar faces (Campbell,
Coleman, et al., 1999; Young et al., 1986; Ellis, Shepherd,& Davies, 1979). Because this inner-features advantage
is found only with familiar faces, it is associated withthe ‘‘memorial representation of the known individual’’(Campbell, Coleman, et al., 1999). When encoding faces
in memory, the normal face processing system appears
to give more weight to internal face features. In contrast,
our data show that although PS managed to encode
faces in memory, she relied less than controls on innerfacial features, similarly to her lesser reliance on the eye
area of the face. To our knowledge, the inner-faceadvantage for familiar faces has not been tested inprosopagnosics previously, given their difficulties inrecognizing faces. However, a normal inner-face advantage was found in posterior left- and right-braindamaged patients without prosopagnosia (de Haan &Hay, 1986), suggesting that the lesser reliance oninternal features of faces observed in patient PS may
be specific to the prosopagnosic deficit.
The literature covered above suggests that both thereliance on facial configuration, particularly at the levelof the eyes, and the advantage given to internal featuresreflect important characteristics of the normal adult faceprocessing system, allowing the recognition of individual
familiar faces. Quite interestingly, these features of theface processing system appear to undergo a long developmental course, relative to other aspects of face processing. The inner-face advantage for familiar faces, forinstance, is found only at 15 years old, children before
that age showing an outer-face advantage (Campbell,
Coleman, et al., 1999; see also Carey & Diamond, 1977).
Other evidence suggests that although the early months

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of visual experience may be critical for the normal
development of facial configuration processes (LeGrand, Mondloch, Maurer, & Brent, 2001, 2004), thisability develops relatively slowly compared to the capacity to extract individual features (Mondloch, Le Grand, &Maurer, 2002) and may not be achieved fully until midadolescence (Carey & Diamond, 1994; Ellis & Ellis, 1994;
Carey, 1992).
Considering together the literature and the datareported here, we suggest that the fundamental properties of the face processing system that undergo a longdevelopmental course may also be the most sensitive—that is, the first to be disrupted—when selective damage
occurs to this system. Admittedly, this suggestion needs
complementary evidence, such as showing how PS deals
with various face information on ‘‘familiar’’ and unfamiliar faces relative to normals in simple discrimination
tasks, for instance. Most importantly, it remains to be
seen whether other cases of prosopagnosia with at least
relatively well-preserved non-face recognition processes,
show the lesser reliance on the eyes area and internal
face features in general. As stated in the Introduction,
there is considerable variability between acquired prosopagnosics with respect to lesion localization andextent, performance on various discrimination and recognition tasks, and strategies used to compensate for
their deficit (e.g., Sergent & Signoret, 1992). Yet, common patterns of functional impairments can also befound in such cases despite different lesion localizations,for instance (e.g., Barton, Press, et al., 2002; Damasio
et al., 1982). The investigation reported here is made ona single case and will need complementary evidence
from other patients to be recognized as a key feature ofacquired prosopagnosia. However, if we are correct
about the reasons why PS shows a lesser reliance on
the eyes and internal region of the face, we expect tofind such a pattern of performance in other acquired
cases of prosopagnosia, provided that they have preserved low-level vision and long-term visual memory,allowing them to extract and store diagnostic information from isolated face cues. Recent investigations using
simultaneous discrimination tasks with full face stimuli
on patient LR, a case of prosopagnosia following a lesionin the anterior part of the right temporal lobe, support
this view, showing that he relies mostly on the mouth
area (Bukach, Bub, Gauthier, & Tarr, in press). Interestingly, this patient also presents a deficit restricted to
faces and a remarkably preserved low-level vision. Finally, future studies will also have to determine whether thepresent findings can be generalized to cases of congenital prosopagnosia (CP), the lifelong impairment in faceprocessing that is apparent from birth (for a review, see
Kress & Daum, 2003). Despite an increasing interest in
CP in the last couple of years, many findings remaininconsistent, but recent careful investigations of a groupof congenital prosopagnosics suggest that such patients
have deficits that are not limited to faces and may be due

to a general inability to derive a global configurationfrom local elements (Behrmann, Avidan, Marotta, &Kimchi, 2005). These CP patients have never developed
an expertise at processing faces and thus will probably
have qualitatively different ‘‘facial representations’’ thancases of acquired prosopagnosia, a topic of interest for
future studies.
Conclusions
Testing a single case of acquired prosopagnosia with
Bubbles gives clues about how faces can be represented
by a selectively disrupted face processing system relative
to normals. The data collected show that PS’s internal
representations of ‘‘familiar’’ faces is less robust andspecific than in normals, requiring more informationfrom the percept to be activated and discriminated fromother representations. Qualitatively, PS’s representations appear to be weighted less toward the eyes andthe internal features in general, which are critical components of a normal adult face processing system having
to build and store robust representations of individual
faces. Finally, in the framework of high-level visualneuropsychological diseases, the Bubbles techniquemight represent a promising instrument for identifying
in the patients the preserved visual representations and,as a consequence, exploiting this information for theirrehabilitation.

METHODS
Subjects
Case Report
PS is a case of acquired prosopagnosia with normal
object recognition who has been reported in detailelsewhere (Rossion et al., 2003) and will be only briefly
described here. She is a 53-year-old woman (born in1950) who sustained a closed head injury in 1992,
causing lesions of the lateral part of the occipital andtemporal lobes, bilaterally (see Figure 1 in Rossion et al.,2003). Despite the extent of the lesions in the visualsystem, PS has normal low-level visual processing. PS isranked as highly impaired on the Benton Face Matching
Test (Benton & van Allen, 1972), scoring 27/54 (percentile 1). She is also impaired on the Short Recognition
Memory Test for Faces, a set of the Camden Memory
Tests (Warrington, 1984, 1996), scoring 18/25 (percentile 3). Regarding the recognition of familiar faces, when
PS was confronted with the pictures of 60 famous
people (all known by the patient), she was able toclassify 14 of them as familiar, and correctly classified
all the unfamiliar ones. Nevertheless, when she had toreport the individual names of the faces classified as
familiar, as well as their associated semantic information,
drastically, she was correct for only four of them.
Although much better than controls for individual dis-

Caldara et al.

1661

crimination, PS is not as good as controls at gender andfacial expression judgments but has normal performances of age assessment on faces (Rossion et al., 2003).
She is also able to draw correctly a schematic face andperfectly point out all the single features. Finally, PS has
been tested extensively with simultaneous and delayed
face and nonface (cars and novel objects) matching tasks
in previous studies (Rossion et al., 2003). Although she isconsistently dramatically impaired and slowed down for
the face conditions, her performance with the nonface
objects is in the normal range.
Controls
Five young adults (mean age, 27) and two age- andeducation-level-matched controls (one woman and one
man, ages 54 and 57 years, respectively) voluntarily
participated in the experiment. All the subjects were
healthy and had no neurological or psychiatric history.
Stimuli
Ten unfamiliar faces (5 women, 5 men) displaying two
possible expressions (neutral or happy) were used in theexperiment. All faces had a normalized hairstyle, global
orientation, and lighting (Schyns & Oliva, 1999). Bubbles(Gosselin & Schyns, 2001) was applied to generate thestimuli (see Gosselin & Schyns, 2001, for details). Eachface is first decomposed into six nonoverlapping bandsof spatial frequencies of one octave each. The cutoffs ofthese bands were, respectively, 90, 45, 22.5, 11.25, 5.62,
and 2.81 cycles per face, from the finest to the coarsest
scale. The coarsest band was a constant background andis not illustrated in Figure 1. For each spatial frequency
band, a number of randomly located Gaussian apertures(called Bubbles) sampled facial information independently at each scale to create a sparse stimulus, that is,a subset of the original facial information. With sufficiently many trials, this technique ensures that the entire
face is sampled in the considered spatial frequency
bandwidths, that is, Bubbles is an asymptomaticallyexhaustive, nonbiased sampling.
Procedure
Prior to the Bubbles experiment, all participants received a printed version of all faces and learned themat the individual level (i.e., their names). In a computerverification task that assessed performances, participants
were confronted with each face and instructed to namethem by pressing the corresponding computer keyboard
key. Feedback displaying the correct name informed
subjects of their mistakes. This training procedure ended when subjects performed a perfect identification of
all the faces twice in a row. On average, for the controls,
only 10 min were sufficient to reach this level and start
the experiment. The same procedure was used with the1662

Journal of Cognitive Neurosciencepatient PS. However, for her, a 3-hr training program
split into 2 days was necessary to achieve this level offace identification. In addition, PS performed this verification procedure before starting each of the Bubbles
sessions and had to succeed twice in a row before
starting a Bubbles session.
The experiment ran on a Macintosh PowerBook G3computer using a program written with the Psychophysics (Brainard, 1997; Pelli, 1997) and Pyramid (Simoncelli, 1997) Toolboxes for Matlab and consisted ofsessions of 300 trials, randomly presenting 30 times
the same identity (10 neutral, 10 happy). All trials weretaken into account for the analysis. In each trial, a sparse
face appeared on the screen, and the participants had todetermine its identity by pressing the corresponding
computer keyboard key. The image remained on thescreen until the subject responded, and no feedback wasprovided. Note that PS and the controls were notrequired to answer as fast as possible, and thus were
free to finely examine each stimulus. The number of
bubbles was automatically adjusted to maintain subjects’
performance at 75% correct. PS performed a total of
9300 experimental trials divided into 31 sessions of
300 trials, spanned over 16 weeks. Controls performed
4200 trials divided into 14 sessions within 3 weeks. PS
was tested for twice the number of sessions of thecontrols for several reasons. First, the number of bubbles for PS over the early sessions was less stable than forcontrols, and there was an indication that it could stilldecrease with additional sessions in her case. For instance, PS’s number of Bubbles first increased, thendecreased and was as large after seven sessions than at
the beginning, and then decreased again up to the 12th
session. However, the decrease in number of Bubbles
took place after two sessions for controls to reach aplateau after seven sessions (Figure 2). This parameter
influences the quality of the statistical solutions foundby Bubbles, and thus we chose to conduct more sessions with PS until we obtained a stable pattern ofperformance in terms of number of bubbles. Second,
we expected to observe a reduction of the amount of
information needed by PS over the extra Bubbles session
to get a fine-grained picture of the diagnostic information for her. Finally, although PS agreed to do that many
sessions, totaling 9300 trials, allowing us to get a refined
picture of the diagnostic facial information for her,
there was no need to run controls over 14 sessions,which was enough to characterize their pattern ofdiagnostic information.
Data Analysis
We hypothesize that on any given trial, if the participant could correctly categorize the sparse face on thebasis of the information revealed by the bubbles, that
information was sufficient for that face identification.
Across trials, we therefore kept track of the locations

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of the bubbles leading to correct identification foreach participant. To this end, for each scale we added
the masks with the bubbles leading to correct identifications to create a CorrectPlane [henceforth, CorrectPlane(scale)], where scale information is represented
from 1 to 5, from fine to coarse (see Figure 1 forexamples of masks). CorrectPlane(scale) therefore encapsulates the locations at each scale where samplingof face information (bubbles) led to correct identifications. We also added the masks with bubbles leading
to both correct and incorrect identifications to create
TotalPlane(scale). Thus, TotalPlane(scale) represents,for each scale, the total sampling frequency of face information. From the information in CorrectPlane(scale)and TotalPlane(scale), we determined, for each subject
separately and on a cell-by-cell basis, the ratio of thenumber of times a specific location led to a successful
face identification over the number of times this location
was presented, CorrectPlane(scale)/TotalPlane(scale).
We refer to this ratio as ProportionPlane(scale). Acrosssubjects, the averaged ProportionPlane(scale) weighs
the importance of the regions of each scale for theidentification task. If all regions were equally important,
ProportionPlane(scale) would be uniform across cells,
and equal to the performance criterion—here, .75.
Consequently, regions significantly above (vs. below)
the performance criterion are more (vs. less) diagnostic.
To determine this significance, we built a confidence
interval ( p < .05) around the mean of the ProportionPlane(scale), for each proportion. DiagnosticPlane(scale)
was created by representing diagnostic (significant)proportions with a filtering weight of 1 and nondiagnostic proportions with a filtering weight of 0. These
diagnostic weights were then used to filter the original
stimulus to derive the effective stimulus (see Figure 3),
which depicts the selective use of information in thetask. The effective stimulus is simply obtained by multiplying the face information at each scale in Figure 1 withthe corresponding DiagnosticPlane(scale) convolved
with bubbles of the size used during the experiment.
The importance of the information used at each spatial frequency bands was compared between PS andthe control group (see Figure 4) by normalizing patient PS’s results with those of the control group andselecting a confidence interval ( p < .05) around themean.
The logarithm of a pixelwise division of the ProportionPlane of patient PS with the averaged ProportionPlane of the control group was computed to determine
the optimality/efficiency of information use by the patient compared to the control group (e.g., Smith et al.,2005). Negative and positive values are related to a
suboptimal and an optimal processing, respectively, of
patient PS (Figure 5, left). The 0 value represents acomparable performance between patient PS and thecontrol group. Finally, to reveal the quality of theperformances for the eyes and the mouth facial features,

two separate masks covering these face regions wereapplied to the ProportionPlane of PS and the controls,
disclosing the respective distributions for both facefeatures and groups. Then, PS’s distributions were subtracted from the controls’ distributions for each respective face region, revealing a frequency bias for each facial
feature in both populations (Figure 5, right). A positive
value in Z score distributions indicates that PS’s performances, compared with the controls, occurred more
frequently for a particular Z score bin (Z > 1.65;
p < .05). Conversely, a negative value indicates a bias
for the control group.

Acknowledgments
We are immensely grateful to PS for her patience and motivation during the experiment, to Daniel Bub for sharing stimulating ideas about functional deficits in prosopagnosia, and to
two anonymous reviewers for helpful comments on a previous
version of this manuscript. This work was supported by grant
ARC 01/06-267 (Communauté Française de Belgique—Actions
de Recherche Concertées) and the Belgian National Research
Foundation (Bruno Rossion). Roberto Caldara was supported
by a postdoctoral fellowship provided by the Swiss National
Science Foundation.
Reprint requests should be sent to Roberto Caldara, Department of Psychology, University of Glasgow, 58, Hillhead Street,
Glasgow G12 8QB, UK, or via e-mail: r.caldara@psy.gla.ac.uk.

Notes
1. Although Bubbles would in principle allow an analysis ofdiagnostic features per face, the number of trials per facewould be prohibitively larger (with a patient) to reach statistical significance.

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