categorical perception of facial gender information: behavioural evidence and the face-space...

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Categorical perceptionof facial genderinformation: Behaviouralevidence and the face-space metaphorS. Campanella a , A. Chrysochoos a & R.Bruyer aa Cognitive Neuropsychology Unit (NECO),University of Louvain-la-Neuve (UCL),Belgium

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To cite this article: S. Campanella, A. Chrysochoos & R. Bruyer (2001):Categorical perception of facial gender information: Behavioural evidenceand the face-space metaphor, Visual Cognition, 8:2, 237-262

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Categorical perception of facial gender information:Behavioural evidence and the face-space metaphor

S. Campanella, A. Chrysochoos, and R. BruyerCognitive Neuropsychology Unit (NECO), University of Louvain-la-Neuve

(UCL), Belgium

Categorization is a fundamental property of the human brain. We used an image-morphing procedure to investigate the categorical perception of facial genderinformation. Three experiments, an identification and two matching tasks, werereported. First, we showed that, even when facial image information changes lin-early across unfamiliar male and female faces, gender is perceived categorically.This holds only when faces are presented in an upright orientation. Second, sub-jects discriminated more easily two unknown morphed faces presenting a genderchange as compared to two unknown morphed faces belonging to the same gen-der, even when the physical distance between the pairs was identical. We discussthe results in terms of how representations of faces are encoded and stored inlong-term memory.

The human brain is not able to process all the stimuli present in the environ-ment. Processing can be simplified, however, by grouping different stimuli,which share common properties, into a single category (Rosch, Mervis, Gray,Johnson, & Boyes-Braem, 1976). This categorization process can operate atseveral levels of information processing. For example, we can establish a setincluding the items “wife”, “children”, “dog”, and “money”. This set is notdefined by the common physical attributes of its members but rather by itsabstract meaning such as “what we have to save if our house is on fire”. Theabstract meanings of the stimuli are needed to operate this categorizationwhereas physical attributes are not: This is a form of “semantic categorization”.

Please address all correspondenc e to S. Campanella, Faculté de Psychologie—Unité NECO,Place du Cardinal Mercier, 10, 1348 Louvain-la-Neuve, Belgium.Email: [email protected] e

We are grateful to Glyn Humphreys, Michael Lewis, and two anonymous reviewers for theirhelpful comments and suggestion s on a previous draft of this manuscript . This study was sup-ported by the grant no. 95/00-189 (“Action de Recherche Concertée”) from the Government of theFrench-speakin g Community. The first author was supported by the Belgian Fund of the Scien-tific Research (FNRS).

Ó 2001 Psychology Press Ltdhttp://www.tandf.co.uk/journals/pp/13506285.html DOI:10.1080/13506280042000072

VISUAL COGNITION, 2001, 8 (2), 237–262D

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Categorization processes are also used at a perceptual level, as is illustrated byour perception of colour. Colours can be defined on a physical continuum by agradual variation of light wavelengths. Nevertheless, we perceive chunks ofcolours in spite of linear changes in the physical signal. Moreover, Bornsteinand Korda (1984) showed that if we consider two pairs of equidistant light fre-quencies, subjects discriminate more easily the pair which is constituted by twostimuli belonging to two different categories (green-yellow) than the pairdefined by two stimuli belonging to the same category (two different tones ofyellow). Categorization processes can thus modulate the way we perceive thephysical attributes of a stimulus: This is “perceptual categorization”. More pre-cisely, the advantage for inter- over intra-categorical discriminations (thebetter discrimination between two stimuli belonging to different categories rel-ative to stimuli from the same category) is known as “the categorical percep-tion effect” (Harnad, 1987). This latter type of perceptual categorizationdefines the scope of this paper.

The categorical perception effect was initially observed on unidimensionalstimuli such as speech sounds and colours (Liberman, Harris, Hoffman, &Griffith, 1957; Bornstein & Korda, 1984). However, recent developments andapplications of computer image-manipulation techniques have made the inves-tigation of multidimensional stimuli, such as the human face, possible. This isof interest because even though the ability to recognize specific individualsmust be learned and the continua between individual faces are not naturallyoccurring, there might be general constraints on category formation that alsoapply to individual face recognition (Harnad, 1987). Thus, during the last fewyears, several studies have been published showing categorical perception offamiliar identities (Beale & Keil, 1995; Stevenage, 1998). Beale and Keil(1995) used stimuli morphed between two familiar identities (i.e., PresidentsKennedy and Clinton). Subjects were confronted with both identification andmatching tasks. The identification task allows the identification of the categori-cal boundary of a continuum, whereas the matching task shows a better dis-crimination of faces straddling this categorical boundary as compared to facesstemming from the same category. The results strongly suggested that therewas categorical perception of familiar facial identities. In other words, subjectsdiscriminated more easily the identities of two faces belonging to two differentpeople than the identities of two faces belonging to the same person, even whenthe physical distance between the stimuli within each pairs was kept constant.Moreover, Stevenage (1998) performed an experiment where she used photo-graphs of twin faces (Rosie and Elizabeth). Subjects had to rate the similarity ofpairs of photographs (same: Rosie–Rosie; Elizabeth–Elizabeth; different:Rosie–Elizabeth) before and after a category learning session of the two dis-tinct faces. She found evidence for: (1) a “compression effect”, i.e., subjectsjudged the same-twin pairs as more similar after than before the learning ses-sion; and (2) an “expansion or separation effect”, i.e., subjects judged the

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different-twin pairs as more different after than before the category learningphase. These data provide some evidence about the mechanisms responsiblefor categorical perception effects. Indeed, a categorical perception effect couldarise from acquired equivalence or distinctiveness (Goldstone, 1994a;Livingston, Andrews, & Harnad, 1998). According to acquired equivalence,there is an increase of perceptual sensitivity to similarities (among instances ofa same category) that are relevant for a categorization (Nosofsky, 1986). Thismechanism would be responsible for the within-categorical compressioneffect. According to acquired distinctiveness, there is an increase in perceptualsensitivity to differences that are relevant for a categorization (Gibson, 1969;Nosofsky, 1986). This mechanism would be responsible for the between-cate-gorical separation effect. Therefore, the categorical perception effect observedfor familiar identities is due to the way faces are stored in memory, such thatdifferences and similarities can be extracted through comparisons betweenstored exemplars, or relative to a facial prototype (Valentine, 1991). Accord-ingly, categorical perception is correlated with face familiarity (Beale & Keil,1995) and should not be observed with unfamiliar faces (Goldstone, 1998).

Although identity is an important dimension of facial information, it is notthe only dimension used in face recognition (Bruce & Young, 1986). Recentlymost of the published studies on categorical perception of faces have concen-trated on facial expressions (Bruyer & Granato, 1999; Calder, Young, Perrett,Etcoff, & Rowland, 1996; de Gelder, Teunisse, & Benson, 1997; Etcoff &Magee, 1992; Granato, Bruyer, & Révillon, 1996; Young et al., 1997). Thesedata are particularly important because they allow us to define the perceptualbasis of how emotions are recognized. Strong evidence has been reportedshowing that facial expressions are perceived as belonging to qualitatively dis-crete categories and not as varying continuously along certain underlyingdimensions (Ekman, 1982; Woodworth & Schlosberg, 1954).

A further dimension of faces is gender. Contrary to the case with facialexpressions (which can be accounted for by six emotional categories, seeEkman, 1994) or facial identities (which are potentially defined by an infinitenumber), the categories implied in the gender discrimination process are lim-ited to two. Moreover, we can imagine that, from a sexual reproduction view-point, the categories “attractive/unattractive” might be better psychologicalconstructs than “male/female”. With this in mind, it could be that the male/female distinction could as easily be continuous rather than categorical.Accordingly, we can wonder whether subjects confronted with facial genderinformation that varies linearly will perceive it categorically or not. This wasinvestigated here. By means of a morphing procedure, we generated continuaof facial stimuli in which gender information was varied linearly. The aim ofthis paper was to evaluate whether a categorical perception effect can be evi-denced for facial gender information. Categorical perception needs two stagesto be assessed: (1) an identification task, which has to show non-linear

GENDER CATEGORICAL PERCEPTION 239D

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responses to linearly manipulated stimuli and to define boundaries within eachcontinuum; and (2) a delayed matching task, which has to evidence anenhanced discriminability for between- as compared to within-category pairsof morphed faces. Both pieces of evidence were collected in the present studyin three separate experiments.

EXPERIMENT 1

The goal of Experiment 1 was to show, by means of an identification task, thateven if subjects are confronted with upright morphed faces in which genderinformation varies linearly, they will perceive this gender information in dis-crete categories. However, it is possible that this categorical effect was: (1) anartefact due to experimentator instructions, which forced subjects to classifymorphed faces into two pre-defined categories (male/female); or (2) a “techni-cal” artifact linked to the use of a morphing procedure. To overcome theseobjections, the same experiment was run with a new set of subjects but withfaces presented upside-down. Inversion has frequently been used in research onface perception as a control for the role of non-face-specific properties of thematerial due to the fact that inversion is supposed to alter the perception of theconfigurational information conveyed by faces (de Gelder et al., 1997; Valen-tine, 1988). Indeed, it is nowadays well-accepted that humans are experts in therecognition of faces (Carey, 1992). We are also experts in the gender recogni-tion of male and female faces. Experts differ from novices in their enhancedsensitivity to the configural properties of a stimulus (Tanaka & Gauthier,1997). Then, if inversion “disturbs” the categorical perception effect evidencedwith upright faces, the information relevant to induce this effect on uprightfaces should be carried by configural information and it does not represent theresult of the experimentator’s instructions or the morphing technique. How-ever, if the same categorical results are obtained in the upright and invertedconditions, it would mean that the categorical perception effect is unrelated toconfigural cues and may rather be due to author’s instructions or to technicalartefacts due to the use of the morphing procedure.

Method

Subjects. Thirty-two volunteers (sixteen females) of the Department ofPsychology (Louvain-la-Neuve) took part in this experiment. Sixteen (eightfemales) were given the identification task with upright faces; the other halfreceived inverted faces (180°) to identify. All were aged between 18 and 25years, reported no neurological disease, and had normal or corrected-to-normalvision.


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Stimuli. Three unfamiliar male faces (M1, M2, and M3) and three unfa-miliar female faces (F1, F2, and F3) were photographed (Figure 1). Nine con-tinua of male/female pairs were possible (M1/F1, M1/F2, M1/F3, M2/F1, M2/F2, M2/F3, M3/F1, M3/F2, and M3/F3). In this way, each male face was pairedto each female face, and vice versa.

Five morphed images were created for each continuum. These were pre-pared by blending two faces in proportion 90:10 (i.e., 90% M and 10% F),70:30, 50:50, 30:70, and 10:90. We will refer to these as 90%, 70%, 50%, 30%,and 10% morphs along the appropriate continuum (see Figure 2 forillustration).

The preparation of each continuum involved five stages. First, photographicquality images (digital camera) of faces were chosen as source-images. Modelswere selected as being devoid of beard, moustache, and glasses. All faces weretaken from a frontal view and with a neutral facial expression. Second, thesephotographs were downloaded onto a Macintosh computer where they were

GENDER CATEGORICAL PERCEPTION 241

Figure 1. Photographed source faces of three unfamiliar females (F1, F2, and F3) and three unfamiliarmales (M1, M2, and M3).

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edited by Adobe Photoshop 4.0.1 to remove backgrounds, everything belowthe chin, hair, and ears. Coloured-scale images were created, matched for skintone and colouration, and scaled to 150 × 191 pixels. Third, morphed stimuliwere generated using the Morph 2.5 program. One hundred and fifty pointswere located manually onto the sources. The locations of these points werespecified in terms of facial features such as corners of the mouth, tip, and rest ofthe nose, outlines of the eyes, and various anatomical landmarks. The samemethod was applied to each source so that there was a correspondence of the150 points for all sources. Fourth, a vector equation for each of the 150 pointswas computed on the sources to determine which position a point on, say, M1’sface, would have on the morphed image after moving to 10, 30, 50, 70, or 90%of the distance to the position of the corresponding point on, say, F1’s face.Fifth, the Morph program used a warping procedure to move from one source to

242 CAMPANELLA, CHRYSOCHOOS, BRUYER

Figure 2. Illustration of the morphed faces for continuum M2–F3 with, from upper left, M2 90%/F310%, M2 70%/F3 30%, M2 50%/F3 50%, M2 30%/F3 70%, and M2 10%/F3 90%.

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the other by allowing the shift of the 150 control points from their initial posi-tion (in one source) to their final position (in the other) along linear changes.For example, in the 90% M2 /10% F3 morphed face, the pixel intensities havedeformed the M2’s face 10% toward the F3’s face and the F3’s face 90%toward the M2’s face. In total, 45 images were drawn (5 from each of the 9 con-tinua) and were prepared in upright and upside-down (180°) orientations.

Design and procedure. The 45 morphed faces were displayed for genderidentification. Upright faces were used in the upright condition, whereas upsidedown faces were used in the reversed or inverted condition. The imagesappeared one at a time, in random order, on a 256-colour scale 15" Macintoshmonitor. The viewing distance was 1 m and every stimulus had a size of 60 × 78mm. The task involved a two forced-choice decision: The subjects had to makea gender decision for each displayed image. Responses were made by pressingwith the right index finger one of two buttons which were labelled accordingly.The labelling of these two buttons was randomized across subjects. Each trialinvolved: the display of a fixation cross (300 ms), then a blank (300 ms), andfinally the morphed image, which remained in view until a button was pressedor there was a delay of 3400 ms. No feedback was given about the subjects’responses. Choice of gender and latency were recorded.

Each subject was shown randomly 10 blocks of 27 images. These 270 trialswere formed with the 45 morphed faces repeated 6 times each. An additionalpre-experiment block of 15 random stimuli was discounted as practice. Notethat the source-faces (Figure 1) were never shown in the experiment. To ensurethat the source-faces were correctly referred to their gender, 10 additional sub-jects (5 females) had to take a gender decision for each of the 6 source-faces. Allfaces were correctly referred to their gender category with a mean latency of427 ms for F1, F2, and F3 and 426 ms for M1, M2, and M3.

Results

Figure 3 illustrates the mean frequencies with which subjects identified eachmorphed image as male or female in each condition (upright vs. inverted).

These percentages were computed from 4320 data points (16 subjects × 6occurrences of each 5 morphs from the 9 continua) recorded from a two-waychoice. An ANOVA was computed for percentages of “female” responses withmorphs (90%, 70%, 50%, 30%, and 10%) as a within-factor and orientation(upright vs. inverted) as between-factor. One subject in the inverted conditionwas rejected as an outlier (70% of the responses were out of time). The analysesshowed a significant main effect of morphs, F(4, 116) = 929, 6, p < .0001, and asignificant interaction morphs × orientation, F(4, 116) = 30, 3, p < .0001,whereas orientation was not significant, F(1, 29) = 0, 679, n.s. The main effectsindicate that the percentages of male and female responses were modulated by


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the intensity of the morphing defining the images, whereas orientation had noeffect on how subjects identified the gender on these morphed faces. Moreinterestingly, the interaction morphs × orientation indicates that the morphingeffect changed for upright and inverted faces (Table 1). Post hoc tests werecomputed using one-way ANOVAs with a within-subjects factor of morph(with five levels). There was a clear effect of the morphs for both the uprightcondition, F(4, 60) = 982, 4, p < .0001; and the inverted, F(4, 56) = 237, 7, p <.0001, condition. However, polynomial tests showed that linear, quadratic, andcubic contrasts were significant in the upright condition, linear, F(1, 15) =3680, 7, p < .0001, quadratic, F(1, 15) = 4, 976, p = .041; cubic: F(1, 15) = 197,9, p < .0001; whereas quadratic and cubic contrasts were not significant in theinverted condition, linear, F(1, 14) = 530, 5, p < .0001; quadratic: F(1, 14) = 1,748, n.s.; cubic, F(1, 14) = 4, 1, n.s.

In the upright condition, the 10%, 30%, 70%, and 90% morphed faces werereferred to their correct gender on at least 85% of the occasions. Only the 50%


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Figure 3. Mean frequency of responses (%) in the identification task for subjects of the upright condi-tion and subjects of the inverted condition.

TABLE 1Mean percentages of female responses (SD) to morphed faces

composed of 10%, 30%, 50%, 70%, and 90% of femaleinformation along the nine continua “male–female” (Exp. 1)

10% 30% 50% 70% 90%

Upright 4 11 53 85 93(1,56) (1,98) (2,89) (2,46) (1,58)

Inverted 12 31 53 70 86(1,61) (2,04) (2,98) (2,54) (1,64)

%

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morphed images gave rise to ambiguous responses. Indeed, the significantcubic function suggests the existence of two clear regions, one where the end-points of the continuum (10%, 30%, 70%, and 90%) were clearly referred totheir sources, and another around the mid-point (50%) of the continnum, whichled to an abrupt shift from one gender decision to the other. This is consistentwith a categorical perception effect. However, the frequencies of the responsesin the inverted condition did not delineate clearly similar regions. Now the 10%and 90% morphed faces were correctly referred to their gender but gender deci-sions were difficult for 30% and 70% morphed faces. Here performance seemsto vary continuously, as a function of the linear shifts in facial images.

The presence of categorical perception can also be assessed statistically byconsidering response latencies (Figure 4).

Latencies for each condition and for each continuum were collapsed intothose for morphs closest to the sources (10% and 90% = distance 1), morphsfurther from the sources (30% and 70% = distance 2), and morphs furthest fromthe sources (50% = distance 3). A 3 × 2 ANOVA with distance (1, 2, 3) as awithin-subject factor and orientation (upright, inverted) as a between-subjectfactor showed significant main effects of orientation, F(1, 29) = 4, 351, p =.046, and distance, F(2, 58) = 24, 7, p < .0001, along with a significant interac-tion, F(2, 58) = 5, 482, p = .007. The main effect of orientation showed that sub-jects identified more easily the gender of upright morphed faces than the genderof reversed faces. Moreover, the main effect of distance indicated that the dis-tance from the sources had a definite cost on the ability to categorize themorphed images. Subjects categorized more easily: (1) the 10%, 30%, 70%,and 90% morphed faces as male or female relative to the 50% morphed images,(upright: t15 = 3, 985; p = .001, inverted: t14 = 3, 319; p = .005, and (2) the 10%


Figure 4. Mean response latencies (ms) in the identification task for subjects of the upright conditionand subjects of the inverted condition.

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and 90% morphed faces relative to the 30% and 70% morphed faces, upright:t15 = 4, 765; p < .0001, inverted: t14 = 3, 916, p = .002. The distance × orienta-tion interaction was assessed by analysing the data separately for upright andinverted faces. In the upright condition, there was a significant main effect ofdistance, F(2, 30) = 16, 456, p < .0001, with the linear polynomial contrast andthe quadratic polynomial contrast also being significant, respectively, F(1, 15)= 17, 617; p = .001, and F(1, 15) = 5, 066, p = .04. The same analysis for theinverted condition showed a significant main effect of distance and a signifi-cant linear polynomial contrast, respectively, F(2, 28) = 12, 532, p < .0001, andF(1, 14) = 14, 61, p = .002, but the quadratic polynomial contrast was not signif-icant, F(1, 14) = 2, 551, n.s. This suggests that the difference between morphsof distance 3 and 2 was more marked on RTs than the difference betweenmorphs of distance 2 and 1, but only in the upright condition (Table 2).

Discussion

The results of Experiment 1 show the following. First, both response frequen-cies and latencies in the upright condition suggest that each continuum betweenmale and female faces can be defined by two clear regions: one (near the end-points) where morphed faces are clearly referred to their gender, and another(around the mid-point) where morphed faces trigger ambiguous responses.Nevertheless, in the upright condition, 30% and 70% morphed faces wereassigned 85% of the time to the gender that predominantly constituted theimages, such as 10% and 90% morphed faces were referred to their sources.However, this tendency to associate 30% and 70% morphed faces to theirsources was less clear in the inverted condition, decreasing towards 70% forinverted morphed faces.

Second, analyses of response latencies showed that, in the upright condition,subjects identified more easily the gender of morphs of distance 1 than morphsof distance 2, and morphs of distance 2 more easily than morphs of distance 3,but the difference between morphs of distances 3 and 2 was more marked thanthe difference between morphs of distances 2 and 1. This was not the case for


TABLE 2Mean latencies (SD) to morphed faces of distance 1

(10% and 90%), distance 2 (30% and 70%), and distance3 (50%) (Exp.1)

Distance 1 Distance 2 Distance 3

Upright 747 851 1043(60) (72) (93)

Inverted 1034 1109 1150(62) (74) (96)

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the inverted condition: Indeed, for inverted faces, the difference betweenmorphs of distances 1 and 2 and morphs of distances 2 and 3 was notsignificant.

Taken together, these data indicate that, for the upright condition, despite thefact that a linear continuum of gender information has been created, there wassome tendency towards categorical perception. This tendency was reduced forinverted faces. In the inverted condition, the difficulty of the gender decisionincreased linearly as a function of the linear manipulations affecting the genderinformation in the morphed faces. The data in the inverted condition also showthat the information relevant for the categorical perception effect is carried byfacial configuration and not the result of a methodological (instructions, morphprocedure) artefact (see also de Gelder et al., 1997).

It is interesting to note that these data link to the notions of how categoriza-tion develops with expertise. Humans are experts in the recognition of faces(Carey, 1992) and face recognition is disproportionately impaired by inversion(Yin, 1969) as compared to other objects. Accordingly, using a manipulation ofexpertise level with face stimuli, Rhodes, Tan, Brake, and Taylor (1989)showed that the effect of inversion was larger for faces of the subjects’ own racethan for different race faces. These results can be accounted for by the facts that(1) inversion is supposed to alter the configurational information present infaces (Valentine, 1988), and (2) novices use a feature-based strategy andexperts use a holistic (configurational) strategy. Accordingly, for normal faces,subjects recognized parts better in the whole face than in isolation, althoughthis is not the case when faces are inverted (Tanaka & Farah, 1993). Applied tothe current context, we may presume that people are experts in recognizing(upright) male and female faces. The present data suggest that: (1) when pro-cessed configurally (in the upright condition), face gender is perceived categor-ically; and (2) when processed featurally (in the inverted condition), facegender is perceived linearly. This fits with there being a principal role forconfigural information in perceptual expertise and suggests that configura-tional cues are important for gender category formation.

In sum, Experiment 1 achieved a triple goal: (1) the first stage, to assess cate-gorical perception of gender information (i.e., subjects giving non-linearresponses to linearly manipulated stimuli) was fulfilled; (2) the upright condi-tion allows us to define on the basis of the identification task the categoricalboundary of each continuum individually (see later); and (3) the inverted con-dition assessed the validity of these results.

In Experiment 2, we assessed categorical perception of gender informationusing a matching task. The hallmark of categorical perception is better discrim-ination across category boundaries than within categories (Harnad, 1987;Young et al., 1997). We tested whether there was an enhanced discriminabilityfor stimuli crossing the categorical gender boundary in a delayed “same–differ-ent” matching task.


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EXPERIMENT 2

Experiment 2 used a delayed “same–different” matching task on two morphedimages (A, B) successively shown to subjects who had to decide whether B wasphysically identical or not to A. This task shares the same goal as the usual ABXdiscrimination task used in the categorical perception literature, with theadvantage that the memory load component is reduced. Categorical perceptionis defined as an enhanced discriminability of between-category relative towithin-category stimuli (Young et al., 1997). We asked whether the discrimina-tion of morphs crossing the subjective categorical boundary (as defined byExperiment 1) is facilitated relative to the discrimination of morphs that remainwithin the same category, even if the physical differences between each pair iskept constant. If there is categorical perception, then responses for “differentpairs” will be better for “between-category” (two stimuli crossing the bound-ary) than for “within-category” pairs (two stimuli being closer to the source),the difference between A and B being held constant (20%) in the twoconditions.

Method

Subjects. Fourteen new volunteers (seven females) of the Department ofPsychology took part in the experiment. All were aged between 18 and 25years, reported no neurological disease, and had normal or corrected-to-normalvision.

Stimuli. Data of Experiment 1 were used to define boundaries betweencategories. For example, Figure 5 shows the percentages of “male” and“female” responses for each stimuli (10%, 30%, 50%, 70%, and 90%) of onecontinuum (M1–F1). The intersection of the two curves (upright condition)indicates the point where half of the subjects would respond “male” and theother half “female” (48% in this example). This point was taken as the subjec-tive categorical boundary of the continuum M1–F1. The same procedure wasapplied to each of the nine continua in order to obtain their own categoricalboundary. For the nine continua, categorical boundaries were always situatedbetween 44% and 56%.

Subsequently, between-category pairs and within-category pairs of equalphysical distance (20%) were created, in order that the between-categoricalpairs straddled the categorical boundary of the continuum from which they areissued. For instance, for the continuum M1–F1, the pair “38%–58%” crossedthe boundary (48%), while the pair “8%–28%” was formed with stimulibelonging to the same category. “Same-pairs” (20%–20%) were also generatedfor methodological reasons in order that subjects have the same chance torespond “same” or “different” (Figure 6). In this way, four between-gender


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pairs (in this example, “36%–56%”, “38%–58%”, “42%–62%”, “44%–64%”),four within-gender pairs (in this example, “8%–28%”, “12%–32%”, “68%–88%”, “72%–92%”), and eight same pairs (”10%–10%”, “20%–20%”, “30%–30%”, “40%–40%”, “60%–60%”, “70%–70%”, “80%–80%”, “90%–90%”)were created for the continuum M1–F1. Each pair was repeated two times, oncein order A–B and once in the order B–A. The same procedure was applied to theother eight continua by considering their respective categorical boundary. Sub-jects were thus confronted with 288 pairs (144 “same” and 144 “different” with72 “between-” and 72 “within-gender pairs”).

Design and procedure. These 288 pairs constituted 12 blocks of 24 pairsand were used in a delayed “same–different” matching task. Each trial wasformed with a central fixation cross (300 ms), a blank interval (800 ms), the firstmorphed face (400 ms), a blank interval (800 ms), the second morphed face(400 ms), and finally a blank interval of 1200 ms. The subject’s task was tomake a button-press response (right hand) to indicate whether the second imagewas exactly the same as the first or not. Subjects had 1600 ms from the onset ofthe second morphed face to respond. No feedback was given. Responses andlatencies were recorded.

The 12 blocks of 24 pairs were presented in random order. The assignmentof buttons (same/different) was counterbalanced across subjects. Stimuli werepresented at a distance of 1 m on a 256-colour scale 15" Macintosh colour mon-itor using Superlab software. All stimuli were the same size (60 × 78 mm).


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Figure 5. Frequency of responses (%) in the identification task for subjects of the upright condition forthe continuum M1–F1. The categorical boundary was situated at 48%.

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Figure 6. Pairs of stimuli that crossed (between) or not (within) the boundary of the continuum M1–F1 were generated. Pairs of identical stimuli (same) were also created for methodological purpose.

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Before starting the task, subjects were confronted with 15 practice trials to befamiliarized with the procedure.

Results

Both accuracy and correct latencies were analysed. Experiment 2 was aimed atshowing that judgements of difference are easier for between-category pairsthan for within-category pairs, even if the physical difference between eachpair was kept constant. Table 3 illustrates the mean correct latencies and themean percentages of correct responses. These data were computed from 72between-category pairs, 72 within-category pairs, and 144 same-pairs submit-ted to each of the 14 subjects. Same-pairs generated 77% correct responses witha mean correct latency of 860 ms. Only different pairs were submitted to analy-ses. A clear pattern of categorical perception emerged, i.e., there was anenhanced discrimination for between- versus within-category pairs.

Indeed, subjects made fewer errors, t13 = –3, 944, p = .002, and had shortercorrect latencies, t13 = –2, 360, p = .035, for between- than for within-categorypairs. Moreover, subjects’ performance for within-, t13 = –2, 996, p = .027, andbetween-, t13 = –8, 655, p < .0001, category pairs was significantly abovechance.

Discussion

The data from Experiment 2 showed a clear pattern of categorical perception.In fact, subjects discriminated more easily (less errors and faster correct laten-cies) between-gender pairs than within-gender pairs, even if the physical differ-ence between the pairs is identical. Nevertheless, we note that, to create acontinuum varying from one gender to the other one, we had to use a male face,that represents a particular individual (for instance, M1) and a female face, rep-resenting another particular individual (for instance, F1). That is, we could notavoid that the transition between one gender and the other one be confoundedwith the transition between one identity and another one. However, even if this


TABLE 3Mean percentages of correct responses (SD)and mean correct latencies (SD) for between-,

within-, and same-category pairs (Exp. 2)

% Correct Correct latencies

Between 70 867(8,615) (141)

Within 59 904(13,385) (138)

Same 77 860(9,95) (144)

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possible confound has to be stressed, we suggest that, in the present study, thefacilitation to discriminate between-gender pairs as compared to within-genderpairs would only be due to gender information and not to identity information.1

We argue this for two reasons.First, the stimuli used in our experiments are generated from faces that are

totally unfamiliar to the subjects. By using familiar faces, Beale and Keil(1995) showed that subjects discriminated more easily two morphed facesbelonging to different identities than two morphed faces belonging to the sameone. More importantly, they showed that this categorical perception effect wascorrelated with face familiarity. Indeed, a strong categorical perception effectemerged for pairs of faces rated as highly familiar (for instance, Kennedy/Clinton), although this effect disappeared for pairs of faces rated as relativelyunfamiliar (Burns/Harris). Tanaka, Giles, Kremen, and Simon (1998)explained these results by the fact that for between-categorical pairs, themorphed faces are “attracted” by two different stored representations, whereasfor the within-categorical pairs, the two faces are “attracted” by a single repre-sentation. Then, on the basis of the literature (Beale & Keil, 1995; Goldstone,1998; Stevenage, 1998), no categorical perception effect should be obtained byusing unfamiliar faces, due to the fact that, by definition, unfamiliar faces arenot represented in memory.

Second, we suggest that if subjects cannot rely on stored information aboutfaces’ identity in order to discriminate more easily between-categorical thanwithin-categorical pairs, they will focus on the available gender information,which is the same in within-categorical pairs but differs in between-categoricalpairs. This postulate is based on the diagnosticity principle (Schyns, 1998),which can be considered as one of the key components for successful categori-zation performance. According to this principle, subjects attend to the featuresof a stimulus that have classificatory significance (Nosofsky, 1986). Thus, inthe present study, the information available from the faces and the nature of thediscrimination task demands influence the diagnosticity of specific cues, insuch a way that gender cues become particularly useful (i.e., diagnostic) for thetask at hand as compared to identity cues.

In keeping with these considerations, we report a third experiment in whichwe compared the performance of subjects confronted with pairs of faces: (1)moving from one gender (unfamiliar male) to the other one (unfamiliarfemale); and (2) moving from one unfamiliar face to another one, but with thesame gender (two males or females). Indeed, if the transition between anunknown identity and another one plays a role in the good discrimination per-formance obtained for between-gender pairs in Experiment 2, we should also


1Note that all stimuli were matched for other cues, such as size, skin tone and colouration , age,

and emotional expression (i.e., neutral) , so that only gender and identity could vary in the pre-sented pairs.

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observe a good discrimination performance if subjects are confronted withpairs of morphed faces varying only on the identity dimension (and not on gen-der). Conversely, if the discrimination performance was bad for these between-identity pairs (i.e., at chance level), this would mean that the identity dimensionis not reliable to perform the discrimination task and that the gender representsthe useful “diagnostic” (Schyns, 1998) cues.

EXPERIMENT 3

As mentioned previously, a possible confound could be advanced due to thefact that the passage through one gender to the other one is necessarily corre-lated to the passage from one identity to another one. Nevertheless, faces areunknown to subjects so that no stored representations are available. Thus, wesuggest that the categorical perception effect found in the present study is onlydue to gender information.

The goal of Experiment 3 was to show, by means of a delayed same–differ-ent matching task, a sharper discrimination when subjects are confronted withpairs of unfamiliar faces showing an identity and a gender changes as comparedto pairs of unfamiliar faces showing only an identity change.

Method

Subjects. Twelve new volunteers (six females) of the Department of Psy-chology took part in the experiment. All were aged between 23 and 28 years,reported no neurological disease, and had normal or corrected-to-normalvision.

Stimuli. Six continua moving from one unfamiliar identity to another one,without gender change (M1/M2, M2/M3, M1/M3, F1/F2, F2/F3, and F1/F3),were created (see Figure 7 for examples). The six continua of male/female pairsused in Experiment 1 (M1/F1, M2/F2, M3/F3, M1/F2, M2/F3, M3/F1) wereemployed again. This created six continua of faces moving from one unfamiliarface to another one, the two faces being of the same gender (identity condition),and six continua of faces moving from one unfamiliar male (or female) face toanother female (or male) one (sex condition).

Subsequently, between-category pairs of equal physical distance (20%)were created for the sex and identity conditions. The pairs “35%–55%”, “40%–60%” and “45%–65%” were used. “Same-pairs” (35%–35%) were also gener-ated for methodological reasons in order that subjects have the same chance torespond “same” or “different” (Figure 8). Thus, three sex between-pairs(“35%–55%”, “40%–60%”, and “45%–65%”), three identity between-pairs(“35%–55%”, “40%–60%”, and “45%–65%”), and six same-pairs (”35%–35%”, “40%–40%”, “45%–45%”, “55%–55%”, “60%–60%”, and “65%–


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65%”) were created for each of the 12 continua. Each pair was repeated twotimes, once in order A–B and once in order B–A. Subjects were thus confrontedwith 144 pairs (72 “same” and 72 “different” with 36 belonging to the sex con-dition and 36 belonging to the identity condition).

Design and procedure. These 144 pairs constituted 6 blocks of 24 pairsand were used in a delayed “same–different” matching task. For details, seeExperiment 2.

Results

Both accuracy and correct latencies were analysed. Experiment 3 was aimed atshowing a sharper discrimination when subjects are confronted with pairs ofunknown faces presenting a gender change as compared to pairs of unknownfaces of the same gender (even if the physical difference between each pair isidentical). Figure 9 illustrates the mean correct latencies and the mean percent-ages of correct responses. A clear pattern of results emerged, i.e. a better dis-crimination in the sex condition as compared to the identity condition.

Subjects made fewer errors, t11 = 3, 182, p = .009, and had shorter correctlatencies, t11 = 2, 93, p = .014, for “different” pairs in the sex condition com-pared with the ones in the identity condition. The results did not vary for the“same” pairs of the sex and identity conditions, neither for accuracy t11 = 0,953, n.s., nor for correct latencies t11 = 0, 695, n.s. Moreover, performance wassignificantly above chance for the sex condition, t11 = –3, 453, p = .005, but notfor the identity condition, t11 = –0, 547, n.s.


Figure 7. Illustration for the continua F2–F3 and M2–M1, with, from left, the morphed faces 10%/90%, 30%/70%, 50%/50%, 70%/30%, and 90%/10%.

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Figure 8. Pairs of different morphed faces used in the sex and identity conditions.

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Discussion

The results of Experiment 2 suggest that people discriminated more easilyunfamiliar morphed faces belonging to two different gender categories thanmorphed faces belonging to the same gender category. However, a possibleconfound could be due to the fact that moving from one gender to the other onenecessarily implies the passage through one identity to another one. Thus, theenhanced discriminability of between-gender pairs as compared to within-gen-der pairs could be accounted for as by the passage through one gender to theother one as well as by the passage through one unfamiliar identity to anotherone. We argued that, as unfamiliar faces have not available stored representa-tions in memory, subjects rely on diagnostic cues (Schyns, 1998), i.e., the gen-der cues, to operate the discrimination task.

The results of Experiment 3 show that when subjects were confronted withpairs of faces belonging to two different unknown identities but sharing thesame gender, their discrimination performance was not significantly differentfrom chance. However, when subjects were confronted with pairs of facesbelonging to two unknown identities but presenting a gender change, their per-formance was enhanced and significantly above chance (mean of 68%). Theseempirical data suggest (1) that the boundaries across different-sex faces aresharper than those across unfamiliar facial identities, and (2) that the results ofExperiment 2 were really illustrative of a categorical perception effect due togender change and not to the transition from one unknown identity to anotherone.

The question is to determine whether these data can provide new informa-tion about how faces are encoded. This will be discussed in the General Discus-sion where it is suggested that the multidimensional space (MDS) framework


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Figure 9. Mean correct latencies and mean performance (n = 12) for the sex and identity conditions.

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(Valentine, 1991) offers an adequate conceptual background to interpret theseresults (see Burton & Vokey, 1998; Cabeza, Bruce, Kato, and Oda, 1999, fordiscussions of the limitations of the approach).

GENERAL DISCUSSION

The MDS

A useful framework for considering face recognition is the face-space meta-phor. Valentine (1991) suggested that faces are stored as points in a n-dimen-sional Euclidean space where (1) dimensions are not explicitly specified butcorrespond to physical properties of faces, and (2) the origin of the dimensionsdetermines the most typical or average face in the population (norm face) insuch a way that typical faces are close to the central tendency while distinctivefaces are far from it.2 In such a framework, the density of points in the multidi-mensional space decreases with the distance from the origin (prototype). TheMDS framework does not, however, necessarily require the existence of a pro-totype and, as a matter of fact, two different models have been proposed toaccount for recognition of individual faces—one requiring the existence of ageneral prototype, and the other not. In the former, the norm-based codingmodel, Rhodes, Brennan, and Carey (1987) and Valentine (1991) assume thatfaces are encoded in terms of their deviation from a single general face norm(prototype) representing the central tendency. To recognize a face, subjectshave to (1) encode the stimulus as a dimensional vector (with the central ten-dency point as the origin), and (2) proceed to a similarity decision for knowingwhether the stimulus matched a previously stored vector. In the latter, the exem-plar-based coding model, Valentine (1991) assumes that faces are encoded aspoints rather than vectors and thus, according to Valentine (1991, p. 168), “theorigin of the multidimensional space plays no part in encoding stimuli, itmerely indicates the point of maximum exemplar density”. Therefore, the simi-larity between two faces is judged by the distance separating representations ofthe faces (points) in the MDS.

This framework has given rise to several recent investigations (e.g.,Johnston, Kanazawa, Kato, and Oda, 1997), and it provides a good account of


2In Valentine’s (1991) framework, the density of face representation s are normally distributed

around the norm face such that (1) the density of points is high near the norm and (2) the more thedistance between the norm and a target face is high, the more this face is atypical (distinctive) . Wehave to note that Burton and Vokey (1998) discussed some of these points, showing that it is notthe case that most faces will cluster around the norm and suggesting to (1) discriminate the con-cepts of local and global densities of points in a space, (2) specify that typicality has not to beequated with local points density, and (3) specify the dimensions of the Euclidean space in orderthat distance from the norm can function as a definition of typicality .

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“effects of distinctiveness, inversion and race” (Valentine, 1991). In such amodel, the recognition of familiar faces is optimal when a face stimulusmatches a stored exemplar or a stored vector. Nevertheless, the recognition sys-tem is able to identify a familiar face across deviations in face input, as forexample changes due to age (Bruck, Cavanagh, and Ceci, 1991), orientation(Hill, Schyns, and Akamatsu, 1998), viewpoint (Newell, Chiroro, and Valen-tine, 1999; Perrett, Oram, & Ashbridge, 1998), and caricatures (Lewis &Johnston, 1999a; Rhodes et al., 1987). These behavioural data lead to the pro-posal of an attractor field model (Tanaka et al., 1998). According to thisapproach, a face representation is activated by any stimulus falling within theboundaries of its attractor field.3 It is suggested that this conceptual frameworkcan help to interpret the results obtained in the present experiments.

The MDS and the results of Experiment 1

By considering the norm-based coding model of the MDS (Valentine, 1991),one can imagine memory representations of two distinct “male” and “female”prototypes, which respectively average all the male and female faces encoun-tered across life. In the present Experiment 1, subjects saw unfamiliar male orfemale faces and these faces could be encoded in relation to their respectivegender prototypes. Indeed, as suggested by the results of Experiment 3, theidentity dimension is not pertinent (to achieve the purpose of the discriminationtask) due to the fact that all faces are totally unknown to subjects. Then, forexample, the presentation of a morphed face “M1–90%” will be encoded in theMDS in such a way that: (1) the distance from the prototype will depend on itsdegree of gender typicality; and (2) the vector distance between this representa-tion and the male prototype was shorter than the vector distance between thispoint and the female prototype. This will occur if there is enough male informa-tion in these faces to be more attracted by the male than the female prototype.However, 50% morphed faces were as close to the female than the male proto-type, and consequently, they give rise to ambiguous and slow responses. Onsuch a view, the categorization of unfamiliar male and female faces is consid-ered to be grounded on the similarity between a prototype and face inputs4.


3The problem is to define these boundaries . For example, Tanaka et al. (1998) showed that the

attractor field of an atypical face is larger than the one of a typical face. Moreover, Lewis andJohnston (1999b) provide a method for defining the boundaries of attractor fields.

4Goldstone (1994b) investigate d the role of similarity on category formation. There are some

arguments to consider similarity as too unconstraine d and not sufficientl y sophisticated to groundmost categories . Nevertheless , Goldstone concluded that if similarity is too unconstraine d to pro-vide a firm basis for categories , it can provide a useful ground for an important subset of catego-ries. We think that this is the case for male/female categories .

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Conversely, a similar account can be proposed in terms of the exemplar-based coding model (Valentine, 1991). Indeed, we can imagine that subjectshave in memory several exemplars of familiar males and females. Then, forexample, the presentation of a morphed face “M1–90%” will be encoded insuch a way that it will be attracted by a stored familiar male while a morphedface “F1–90%” will be attracted by a stored familiar female. In such a view, cat-egorization of unfamiliar male and female faces is considered to be groundedon the similarity between stored exemplars and face inputs.

The MDS and the results of Experiment 2 and 3

Experiment 2 showed that between-gender differences were more easily dis-criminated than within-gender differences. On the basis of the literature, thisresult could be unexpected because the faces used in the present study aretotally unfamiliar to subjects. Since no stored representations of these identitiesare available in memory, subjects cannot rely on the discrimination betweentwo different identity representations when confronted with between-categori-cal pairs, while a unique representation is activated by the within-categoricalpairs. This statement was assessed by results of Experiment 3, showing thatsubjects cannot discriminate two morphed faces belonging to two differentunknown identities. The better performance in the discrimination of between-categorical pairs as compared to within-categorical pairs found in Experiment2 cannot thus be explained by referring to the fact that between-categoricalpairs are defined by two morphed faces issued from two different models,whereas within-categorical pairs are defined by two morphed faces issued fromthe same model.

We suggest that the gender information gave rise to the obtained categoricalperception effect, i.e., an enhanced discriminability for between-categoricalpairs as compared to within-categorical pairs.

According to the norm-based coding model, one can hold that a within-cate-gory pair activated a unique and identical prototype (male or female) whereas abetween-category pair activated both prototypes. Subjects may then be led toconsider within-category pairs as similar because the two stimuli are attractedby the same prototype. This will make differentiation between these two stim-uli more difficult, relative to between-category pairs for which subjects can relyon different prototypes.

Conversely, according to the exemplar-based coding model, within-cate-gory pairs should activate the same stored male (female) exemplar or the samepart of the “exemplar-space” model, whereas between-categorical pairs acti-vate both male and female stored exemplars or two different regions of the“exemplar-space” model. Subjects discriminated between-category pairs moreeasily because differential gender information was activated, although thesame representation is activated for within-category pairs.


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CONCLUSIONS

The present results support the idea that there is categorical perception of gen-der information for unfamiliar faces. By using a morphing procedure, we artifi-cially created faces represented in the MDS by points which are movinglinearly from a point situated close to the male prototype or to a male exemplarto another point situated close to the female prototype or to a female exemplar.As already shown for phonemes (Liberman et al., 1957), colours (Bornstein &Korda, 1964), facial expressions (Calder et al., 1996; de Gelder et al., 1997;Etcoff & Magee, 1992; Young et al., 1997), and familiar facial identities (Beale& Keil, 1995), we showed that two unknown faces belonging to different gen-der are easier to discriminate than two unknown faces belonging to the sameone. It would be interesting that further researches tried to understand whetherthis categorical perception effect was due to acquired similarity or distinctive-ness. However, it was already interesting to note that the nature of the phenom-enon of categorical perception of unknown facial gender information seems tobe different than the nature of classical categorical perception effect describedfor phonemes or colours. In fact, the phenomenon that we evidenced requires(1) visual analysis of faces, (2) encoding in the MDS, (3) comparison to a proto-type or exemplars, and (4) decision making, whereas, for instance, categoricalperception of colour does not need (2) and (3). It is suggested that the mecha-nisms implied in categorical perception of facial gender information are thusdifferent than those implied in the categorical perception of colours or pho-nemes. Moreover, results of the present study (Experiment 2) suggested inter-actions between the information demands of specific categorization tasks andthe perceptual information available from the input stimulus. This stressed theimportance of considering the principles governing the formation of categoriesas tightly anchored with the perceptual aspects of recognition (Goldstone,1994a; Schyns, 1998).

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categorical perception of facial gender information: behavioural evidence and the face-space...

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