The classification of ‘fear’ from faces is associated with face recognition skill in women

Neuropsychologia 40 (2002) 575–584

The classification of ‘fear’ from faces is associated with facerecognition skill in women

Ruth Campbell a,*, Kate Elgar b, Jonna Kuntsi c, Rebecca Akers b, Janneke Terstegge d,Michael Coleman a, David Skuse b

a Department of Human Communication Science, Uni�ersity College London, Chandler House, 2 Wakefield Street, London WC1N 1 PF, UKb Department of Beha�ioural Science, Institute of Child Health, Uni�ersity College London, London, UK

c SGDP Research Centre, Institute of Psychiatry, Kings College, London, UKd Psychonomics Department, Uni�ersity of Utrecht, Utrecht, The Netherlands

Received 15 January 2001; received in revised form 30 July 2001; accepted 30 July 2001

Abstract

Two experiments were conducted to explore the relationship between the discrimination of the facial expression of ‘fear’ in facesand facial recognition. On the basis of the reported role of the amygdala in both processes in patients, we hypothesised that thetwo skills would be correlated in normal adults. In Experiment 1, a series of tests of facial expression categorisation, of facematching and of familiar and unfamiliar face recognition was conducted on normal young women, for whom psychometric scoreswere also obtained (n=23). Accuracy of categorisation of fear from faces predicted variance in face recognition accuracy—espe-cially in tasks of unfamiliar face recognition (immediate old–new discrimination). No other correlations between face processingand expression classification were significant. Experiment 2 repeated the expression classification tests and an unfamiliar facerecognition test on a new sample of men (n=13) and women (n=16). While there were no sex differences in face recognition,the correlation between ‘fear’ and face recognition was replicated only for women. These data indicate that the amygdala supportsboth the specific apprehension of fear in faces and face recognition in adult human females, but that the association may not holdfor men. Sex differences in the structure of the amygdala–hippocampal complex suggest a likely cortical substrate for the observeddifferences. We speculate that social learning, which involves identifying the faces of potentially salient others, and also theirattitude to the observer, engages the amygdala more readily in women than in men. © 2002 Elsevier Science Ltd. All rightsreserved.

Keywords: Facial expression; Face recognition; Amygdala; Sex differences; Face processing

www.elsevier.com/locate/neuropsychologia

1. Introduction

The role of the amygdala in the apprehension offearful emotion from facial pictures is reliably attestedthrough human lesion studies [1–4,13,31,37]. It is alsoevident from patterns of brain activation in normalsubjects [26,27]. The amygdala has a role as a crucialcomponent of a neural ‘warning system’ [25], and it canbe activated even when displays of facial emotion fail toreach conscious awareness [35]. Its role goes beyondthis, however. It appears to be an essential component

of a system for the evaluation of salience and value ofevents [14,15], which may modulate social perception[11,12] in a subtle manner, implicating ‘face-readings’[7,8,13] quite specifically.

In this context it is not surprising that another face-specific deficit has been noted in relation to amygdalafunction. Patients with lesions of the amygdala canshow face recognition impairments [4,5,10,21,36]. Suchcases are, however, rare, and it is unclear to what extentdeductions concerning normal human behaviouralfunction may be grounded in reports of patients withrare lesions related to neuropathologies.

Caution is indicated for another reason. From astudy of around 150 subjects including many withcortical lesions, Rapcsak et al. [28] conclude that, since

* Corresponding author. Tel.: +44-207-679-4232; fax: +44-207-713-0861.

E-mail address: [email protected] (R. Campbell).

0028-3932/02/$ - see front matter © 2002 Elsevier Science Ltd. All rights reserved.PII: S 0 0 2 8 -3932 (01 )00164 -6

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R. Campbell et al. / Neuropsychologia 40 (2002) 575–584576

‘fear’ is the hardest facial display to discriminate, it isalso the most sensitive to impairment in visual classifi-cation—whatever the brain sites involved. On this ac-count, the amygdala plays no special role in thecategorisation of fear in faces and in face recognition:task difficulty is the determinant of the conjointdifficulties experienced by patients with lesions of theamygdala. Not all the neurological findings can beaccommodated to this thesis: It cannot explain why theamygdala should be preferentially activated in normalviewing of fearful faces—especially in subthreshold dis-plays. It is nevertheless important to note that anassociation between visual classification of ‘fear’ andrecognition accuracy may be predicted on the basis oftask difficulty, and to take steps to account for this.

In the first study reported here, a group of adultwomen with no clinical anomalies performed a numberof face processing tasks including: (a) the classificationof facial expression; (b) face matching tasks where morethan one image of a face was present simultaneouslyand the task was to assess whether the image was of thesame or different individuals (the Benton Face Discrim-ination test is one such task); and (c) some face recogni-tion tasks (including the Warrington Test of FaceRecognition) which required encoding, memorial stor-age and decoding of facial images over time. On thebasis of the reported association between ‘fear’ identifi-cation and face recognition in patients with lesions tothe amygdala, we hypothesised that individual recogni-tion of fear in faces may correlate with face-recognitionskill. This would reflect individual variability in amyg-dala activation when face stimuli are processed. Wefurther hypothesised that, if activation of the amygdalaunderlies such associations, these should be specific—both to the expression perceived (fear—and not other‘hard-to-discriminate’ emotional displays) and to theface processing task (recognition memory, but notdifficult simultaneous matching tasks). Young et al. [33]report that a patient with bilateral amygdalectomyshowed no deficit in a range of face-matching tasks, butdid show impaired unfamiliar face recognition andimpaired recognition of fear from faces.

2. Methods

2.1. Participants

A total of 23 female volunteers (aged between 19 and35 years) were recruited from Great Ormond StreetHospital, the Institute of Child Health and UniversityCollege London, as part of a project related to investi-gations of Turner’s syndrome. Subjects were excluded ifthey had known neurological or psychiatric disease or ifthey had lived in the UK for less than 3 years.

2.2. Tests

2.2.1. Facial expression categorisationThe Ekman-Friesen Test of Affect Recognition was

administered as a paper test. Subjects were shown 60black and white pictures of faces with emotional ex-pressions The set consists of 10 individuals, each posingthe six basic emotions: happiness, surprise, fear, sad-ness, disgust and anger. The six emotion labels arepresented below each face and participants are asked todecide what the individual is feeling. Z scores for theidentification of each emotion were calculated usingequivalent identification rates derived from the originalnorms [17].

2.2.2. Tests of general �isuospatial functionThe Picture Completion, Block Design and Digit

Symbol sub-tests of the WAIS-R (Weschler, 1981) wereadministered and scores pro-rated to provide an esti-mate of Performance IQ [33].

2.2.3. Verbal IQA total of four subtests of the WAIS were used:

Information, Digit Span (which is also related to verbalmemory), Arithmetic and Similarities.

2.2.4. Test of �erbal memoryIn the words sub-test of The Recognition Memory

Test (Warrington) [34] participants examined 50 words,each shown for 3 s, and rated them as pleasant orunpleasant. Before being shown the words, subjects aretold that it is a ‘test of memory for words’. Immediatelyafter the full presentation, participants are shown 50pairs of words, half of which are new, half previouslyseen, for forced-choice old–new decision.

2.2.5. Tests of face matching and configural processingThe Benton Test of Facial Recognition provides a

standardised objective procedure for assessing the ca-pacity to identify and discriminate photographs of un-familiar human faces. The test consists of three parts:matching of identical front view photographs, matchingof front view with three-quarter view photographs andmatching of front-view photographs under differentlighting conditions. Participants match a target face tothe face(s) of the same identity, presented amongst atleast three distracter faces. The short form was usedand results were adjusted to give estimated long formscores [9].

2.3. Experimental tasks of face processing highlightingconfigurational aspects (computer-based)

2.3.1. Face orientation: upright and in�ertedface-matching

In this task a face image appeared on the computerscreen for matching to an aftercoming target paired

R. Campbell et al. / Neuropsychologia 40 (2002) 575–584 577

with a foil (X-AB forced choice procedure). The orien-tation of the image varied unpredictably from trial totrial, but was always the same for presentation andrecognition.

Stimuli were derived from 32 grey-scale images offaces comprising 16 pairs, matched for sex, age, image-luminance, image-contrast and general appearance.Each pair appeared 4 times in the upright conditionand 4 times in the inverted condition, giving 128 trials.Image size was approximately 8cm by 6cm on thecomputer monitor used in testing.

Each trial proceeded as follows: A fixation crossappeared for 250 ms followed by a face image for 250ms. This was followed by a laterally arranged pair offace images, one of which was the previously seenimage. The participant pressed the key (m or z) on theside at which the target appeared. The computer wasprogrammed to collect and collate response type (accu-racy) and time per trial. The first 24 trials (half upright,half inverted) were practice and were not scored. Nocorrective feedback was given. The dependent variableswere the mean number and speed of correct choices forthe upright and the inverted face conditions, for eachparticipant.

2.3.2. Whole and part-face matchingThis task examined accuracy at matching whole full-

face images compared with matching just the upper-face or just the lower-face. A similar procedure to thatoutlined above (X-AB recognition paradigm) was used.Material comprised 12 matched pairs of faces and threepresentation conditions, giving 96 trials. Initial presen-tation was always of a whole, upright face. The pair ofitems presented for recognition could be whole face,upper face only or lower-face only. The type of recogni-tion trial was unpredictable from trial to trial. Partici-pants again chose the left or right image in therecognition array by pressing the ‘z ’ or ‘m ’ key of thecomputer keyboard. The dependent variables were themean number of correct responses and speed, for eachof the three recognition conditions: whole-face, upper-face and lower-face.

3. Tests of face recognition

3.1. Warrington face recognition task

This followed the same procedure as the Warringtonword recognition task [34] but the stimuli presentedand tested at recognition are unfamiliar grey-scalemale faces (head and shoulder views). The facerecognition task was administered directly after thewords sub-test of the Warrington recognition memorytest.

3.2. Familiar face recognition

This test was computer administered. First, a be-havioural study established a set of 50 people whom atleast 17 out of 20 female participants (age range 18–36years) named accurately on sight. The images of thesefaces were downloaded from a variety of copyright-free sites on the world-wide web and manipulatedusing ‘Paint Shop Pro’ computer software to generateimages of similar size and general appearance (allgreyscale).

In the experiment proper, the participant was askedto name the individual within 20 seconds. Responseswere scored correct if the image was named, or distinc-tive information about the individual was given (i.e. aspecific role played by a TV actor).

3.3. Incidental face recognition

This test was also computer administered. The stimu-lus set comprised 22 grey-scale face images seen in theearlier computer tasks (Part/whole and Face inversion)and 22 new faces. The new and old faces appearin a random order. As the single face image appearedon the computer screen, the participant indicatedwhether it was one she had seen earlier in the experi-ment (‘old’) or if it was a new face (‘new’). The depen-dent variable was accuracy of recognition (hits andcorrect rejections)

4. Results

4.1. Psychometric data and experimental taskperformance

Psychometric scores are shown in Table 1. Theseshow a reasonable and representative range of IQscores in these participants.

Table 2 shows the distribution of scores for othertasks not explicitly discussed further below. ‘Recogni-tion d ‘ ’ is the d ’ measure for the incidental facerecognition task.

4.2. Expression categorisation

Accuracy of expression identification scores is shownin Fig. 1. One-way ANOVA (SPSS GLM repeatedmeasures procedure) confirmed that these scores dif-fered from each other (F(5,110)=9.74, P�0.001).Post-hoc tests (Scheffe) confirmed that ‘fear’, ‘anger’,‘sadness’ and ‘disgust’ were not different from eachother: All were significantly poorer than ‘happiness’(P�0.01). ‘surprise’ was also significantly better than‘anger’ (P=0.05).


Table 1Experiment 1 psychometric data

Count Mean Range Standard deviation Minimum Maximum

Age at testing (years) 23 25.30 16.00 4.53 19.00 35.0023 16.35 16.00WAIS digit span raw score 3.97 9.00 25.00

WAIS arithmetic raw score 23 11.43 13.00 2.78 6.00 19.0023 20.39 11.00 3.23 15.00 26.00WAIS similarities raw score23 15.48 9.00WAIS picture completion raws 2.47 10.00 19.0023 37.30 21.00WAIS block design raw score 6.71 28.00 49.0023 66.83 34.00WAIS digit symbol raw score 9.40 50.00 84.00

WAIS performance IQ 23 105.70 41.00 11.44 84.00 125.0023 99.57 54.00WAIS verbal IQ 11.64 79.00 133.00

WAIS full-scale IQ 23 102.30 47.00 11.58 86.00 133.00

Table 2Experiment 1: experimental task data (and see figures)

Count Mean Median Standard deviation Maximum Minimum

23 3.47 3.48Recognition d � 0.89 5.16 1.4623 90.96Famous face recognition—accuracy of naming whole faces 96.00 9.96 100.0 64.0023 6.00 6.00Benton face recognition—score for items 1–6 0.00 6.00 6.00

Benton face recognition—score for items 7–13 23 17.09 18.00 1.76 20.00 13.0023Total time taken over Benton pages 1–13 in seconds 149.6 141.7 39.67 254.0 77.00

4.3. Face recognition scores

Warrington Face and Word recognition scores wereanalysed by paired-t-test. This showed a significantdifference in favour of words (t=5.73 (22), P�0.001)(faces, mean=42.5, words: 48.6). Box plots of thesedata are shown in Fig. 2.

4.4. Face matching performance

Fig. 3 shows the performance on two tasks of facematching. Upright faces were matched more accuratelythan inverted ones (t(22)=27.01, P�0.001). Uprightfaces were also matched significantly more quickly(t(22)=16.11, P�0.001).

Similarly, whole faces were matched more accuratelythan either or both of the part-face images, (SPSS,GLM repeated measures: F(2,44)=18.62, P�0.001).Posthoc tests (Scheffe) confirmed that the part-facetasks did not differ significantly from each other.

Participants performed in an age-appropriate man-ner, showing sensitivity both to orientation and topart-of-face in simple matching tasks, and confirmingthat face image processing was ‘configural’ in nature.

4.5. A deri�ed measure of configural face processingand its relations to other task performance

Did individual differences in configurational faceprocessing account for performance on the recognitiontasks, or expression naming? A composite measure offace configuration sensitivity was derived by calculating

the sum of the difference scores for the inversion exper-iment (Upright–Inverted) and the whole-part test(whole-(eyes+mouth)/2) for each participant. Thismeasure (DIFF) was entered into correlations withother face processing tasks (expression, memory). Itfailed to account for the variance in any of them (nocorrelations approached significance).

4.6. Correlations of experimental tasks with expressionnaming

Pearson correlations were calculated between expres-

Fig. 1. Experiment 1: Facial expression accuracy (raw scores/10):Means and standard deviations.


Fig. 2. Experiment 1: Distribution of scores on Warrington’s (1986)tests of immediate recognition memory, mean accuracy for words andfor faces.

of tasks. The most consistent finding was that‘fear’, and that expression alone, correlated signifi-cantly with performance on various face recognitionmeasures.

Concerning other relations between task and expres-sions, a significant correlation was that of WAIS Block-design performance with ‘surprise’ (r=0.54, P=0.01).Similar significant and specific correlations with ‘sur-prise’ were observed for WAIS picture completiontasks.

On the Benton face recognition task, which is pri-marily a test of face discrimination, no correlationsapproached significance. While performance on the firstpart of the test was at ceiling, long-form scores incorpo-rating the second half of the test were used in thecorrelation tests (see Table 2). All correlations werebelow �0.2. Similarly, correlations between expressionaccuracy and performance on the whole and part,upright and inverted face-matching tasks did not evenapproach significance.

The significance of the correlations between ‘fear’and face memory scores was not reduced by partiallingfor configural face processing style, using the derivedDIFF scores (see above).

4.7. Regression analysis: does ‘fear’ predict �ariance onrecognition scores?

While correlations offer a descriptive account of therelationships between variables, regression analysis onrecognition scores can provide a test of hypotheticallypredicted associations. Although subject numberswere too few to enable multiple independent variablesto be tested, regression analysis (SPSS linear re-gression) on Warrington face recognition (raw) scores,using ‘fear’ (raw) scores as the independent variableshowed a significant amount of the variance was ac-counted for by this single predictor (R2 change=0.54,F(1,21)=24.7, P�0.001, standard coefficient beta=0.74, P�0.01). A similar pattern obtained for theprediction of famous-face recognition performancefrom ‘fear’ scores (R2 change=0.24, F(1,21)=6.52,P�0.02, standard coefficient beta=0.49, P�0.02).No other expression scores accounted for significantamounts of the variance in regression on these facerecognition tasks. ‘fear’ did not account for a signifi-cant amount of the variance on the incidental facerecognition task.

No expression score accounted for significantamounts of variance on the Warrington word recogni-tion task.

4.8. Experiment 2

Experiment 1 showed a strong correlation betweenthe classification of ‘fear’ in faces and face recognition

Fig. 3. Experiment 1: Simultaneous matching tasks, boxplots showingmean accuracy distribution. Upper panel: Upright and Inverted faces.Lower panel: Whole and part-face matching.

sion scores1 and each of the experimental and psycho-metric tests. ‘Happiness’, which was reported at ceilingaccuracy, was not entered into these analyses.

Fig. 4 shows the pattern of correlations betweenspecific expression scores and performance on a range

1 Analyses using raw scores are reported, but similar analyses usingZ-scores gave identical results. Non-parametric correlation analysis(Spearman) gave identical results to those summarised here.


Fig. 4. Experiment 1: Pearson product-moment correlations between expression scores, recognition memory tasks and block-design subtest of theWAIS. Similar patterns obtain for all face recognition tasks. Fear shows a positive correlation with recognition accuracy, reaching significance(r=0.77, P�0.01, two-tailed) for the Warrington face recognition, and famous face naming tasks (r=0.54), and approaches significance for theincidental face recognition task (one-tailed, P=0.05). By contrast, no other expressions are positively correlated with these tasks, while theWarrington word recognition task shows a positive correlation (P�0.05, two-tailed) with ‘sadness’. The negative correlation of face recognitionmemory with ‘surprise’ is significant for the Warrington face recognition task (P�0.05, two-tailed).

which did not appear to extend to other expressions orto other face processing skills. Before discussing thesignificance of this finding, we wished to tests its ro-bustness and reliability. To this end a second experi-ment simply tested performance on a face recognitiontask and on facial expression classification in a newgroup of adult participants.

Sex differences in the efficiency of processing of facialexpression have been reported [20,23]. Brain scans showamygdala volume is relatively larger in men thanwomen [18,19]. Brain imaging studies of developmentalchanges in responses to facial expressions of fearshowed activation of the amygdala to be moderated byage and sex of the respondent [22,24,32].

For these reasons, this replication study examinedthe relationship between face recognition, using theWarrington task, and expression categorisation, usingthe Ekman classification task, in both male and femaleadults. The Warrington test was chosen not just be-cause it was the most strongly related to ‘fear’ scores inthe previous experiment but also because the amygdalaappears to be more involved in the learning of newfaces than in accessing those which have become famil-iar through repeated exposure [16].

4.9. Participants

29 new volunteers (13 male) between the ages of 18and 33 were recruited for this study which lasted fortwenty minutes.

4.10. Tests

Two tests were administered: the Warrington recog-nition test (words and faces), and the Ekman facecategorisation task.

5. Results

Figs. 5 and 6 summarise the performance of partici-pants. Relevant means and tests for sex differences areshown in Table 3.

Once more, the Warrington task generated poorerscores for faces than for words (P�0.01), but thispattern was not moderated by sex. Facial expressionscores were analysed by repeated-measures ANOVA,with expression (within-subjects, six levels) and gender(between-subjects) as factors. This showed a main effectof expression (F=9.61 (5,27), P�0.01), which post-


Fig. 5. Experiment 2: Immediate recognition scores, Warrington Test,for male (n=13) and female (n=16) participants.

visuospatial skill. Moreover, in further analyses, therewas no correlation between ‘surprise’ and ‘fear’ ineither men or women, while ‘fear’ correlated with clas-sification of ‘fear’ from vocal segments in women.There were no further cross-modality, same-expressioncorrelations.

6. Discussion

In two experiments with young adults, the classifica-tion of six facial expressions was assessed. In contrastto ‘happiness’ which was accurately recognised, theother expressions showed a decrement but one whichdid not distinguish reliably between the expressions.2

In line with our speculations based on the functionsof the amygdala, marked correlations obtained between‘fear’ and face recognition scores in three face recogni-tion tasks in Experiment 1, in which 23 women partici-pated. These were: (1) explicit immediate recognition ofunfamiliar faces; (2) familiar face naming; and (3) a testof incidental unfamiliar face recognition. In regressionanalysis, ‘fear’ scores alone predicted a significantamount of the variance of face recognition on theWarrington face-recognition test.

By contrast, performance on tasks of face-matching,including the Benton Test of Facial Recognition, didnot correlate with accuracy of ‘fear’ classification. Face-matching tasks however, confirmed that these womenshowed the expected sensitivity to facial inversion andto wholes over parts, suggesting their configural pro-cessing skills were appropriate. An unexpected findingwas that ‘surprise’ correlated with psychometrictest variables that tap visuospatial ability (Block designand picture completion subtests of the WAIS), and thatthis was the only expression so to do. ‘Surprise’ corre-lated negatively with face recognition in both experi-ments.

It seems unlikely that the relationship between ‘fear’classification and face recognition reflects a generalised‘difficulty with faces’, as suggested by Rapcsak et al[28]. Had it been so, ‘fear’ scores would be expected torelate to measures of face-matching performance aswell as recognition. Moreover, ‘fear’ scores in thissample were not significantly depressed in relation toother face-expression scores (excluding ‘happiness’),

Fig. 6. Experiment 2: Facial expression accuracy. Means (/10).

hoc contrasts showed to be as follows: ‘happy’(= ‘surprise’ = ‘anger’)� ‘sad’, and ‘fear’= ‘sad’�‘happy’.

Men were poorer than women at expression categori-sation (F=12.15 (1,27) P�0.01), significantly so for‘disgust’, ‘anger’ (P�0.02 on Mann-Whitney pairedcomparisons). The ANOVA interaction term (expres-sion*sex) failed to reach significance (F=2.39) Correla-tions between immediate memory for faces (Warringtontask) and expression categorisation were performedseparately for men and women, and the results aresummarised in Fig. 7.

Just two correlations were significant, both of themin women. ‘Fear’ correlated with face recognition accu-racy (r=0.62, P�0.01, one-tailed), and ‘surprise’ cor-related negatively with recognition accuracy(r= −0.51, P�0.05). This pattern reiterates thatfound in Experiment 1, where it was associated with

2 One interesting question to be answered by current and furtherresearch is whether this pattern may be supported when vocalemotions are discriminated [6,25]. For the six ‘universal facialexpressions’ in the Ekman series, there are more with negative thanpositive affect (anger, fear, disgust, sadness compared with happinessand surprise)—and the hardest discriminations are between nega-tively balanced emotions. For vocal expressions, this may not be thecase.


Table 3Experiment 2: means, distributions (above) and nonparametric tests for sex differences (below)

Sex N Mean Standard Standard errormeandeviation

Female 16 42.5625 4.5894 1.1473Warrington recognition memory forfaces—raw

13 44.0000 4.2230 1.1712Male16 9.9375 .2500Ekman-Freisen—happy rawscore 6.250E−02Female13 10.0000 .0000 0.0000Male16Ekman-Freisen—sad raw score 7.9375Female 1.6112 0.402813 7.6923 2.2130 0.6138Male16 9.3750 .7188 0.1797Ekman-Freisen—surprise rawscore Female13 9.1538 1.4632 0.4058Male

FemaleEkman-Freisen—anger rawscore 16 9.3750 .8851 0.221313 8.4615 1.0500 0.2912Male

FemaleEkman-Freisen—disgust rawscore 16 9.3125 0.8732 0.218313 7.5385 1.8081 0.501’)Male16 8.6250 1.0247 0.2562FemaleEkman-Freisen— fear raw score13 7.8462 2.2303 0.6186Male

Surprise Sad Disgust AngerHappy Fear Warrington facesMann-Whitney U 97.500 97000 103.000 41.000 51.500 90.500 83.000

233000 194.000 132.000 142.500233.500 181.500Wilcoxon W 219.000−0.901Z −343 −0.045 −2.863 −2.426 −0.608 −0.927

732 0.964 0.004 0.015 0.543 0.354Asymp. Sig. (2-tailed) 0.367A A a aa aExact Sig. [2*(1-tailed Sig.)] a0.779a 0.983a 0.005a0.779a 0.020a 0.559a 0.374a

a Not corrected for ties.

and did not correlate with face-matching scores at theindividual level.

These findings confirm the predictions, based on casestudies of patients with (bilateral) amygdalectomy, thatthere is a strong association between the classificationof ‘fear’ in faces and the ability to recognise unfamiliarfaces. However, it is not always the case that suchpatients show clinical levels of deficit in both thesetasks specifically. Adolphs & Tranel’s developmentalpatient SM [2] showed specific impairment in identify-ing fear in faces, but her face recognition ability wasreportedly within normal range, though low. Neverthe-less, most studies show the association [10,21,36,37].

Why should the amygdala moderate both tasks?While the amygdala is associated generally with learn-ing, and hence to a variety of reinforcers, positive andnegative [9], new faces may involve the amygdala to theextent that the task may engage relatively more, andpossibly more aversive, emotional processing than doesmemorising a printed word [1]. Individual differences inthe extent to which facial images have emotionalsalience to the observer may then be crucial in learningand categorising faces, and Experiment 2 demonstratedone aspect of this.

With 29 new participants, Experiment 2 replicatedthe pattern of accuracy in facial expression classifica-tion. Once again, ‘fear’ was not particularly difficult todiscriminate from other expressions. The major finding

of a strong and specific correlation between judgementsof ‘fear’ from faces and unfamiliar face recognitionaccuracy was upheld-but only for women and not formen. There were also sex differences in the classification

Fig. 7. Experiment 2: Spearman correlations between face recognitionaccuracy (Warrington scores) and facial expression scores. In women,the correlation between recognition and ‘fear’ is significant (r=0.62,P�0.02), as is that between recognition and ‘surprise’(r= −0.51,P�0.05). No correlations are significant for men.


of ‘disgust’ and ‘anger’, leading to a sex difference inoverall accuracy of face expression classification.

The amygdala is one of several brain structureswhich show sexual dimorphism, probably as a result ofits sensitivity to sex-steroid levels throughout develop-ment [19]. Structural imaging studies to date confirmthat relative sizes of the amygdala and the hippocam-pus show sex differences. In men, the amygdala may berelatively larger, while in women, the hippocampus maybe relatively larger [18,19]. This in turn suggests thatthe functional balance between the two structures, espe-cially with regard to learning and memory [29] mayvary with sex. Moreover, recent functional brain imag-ing reports confirm that sex differences in amygdalaactivation for facial expressions of emotion are reliable.Where sex differences are reported, it is men who showreduced activation of the amygdala for several facialdisplays, including that of fear [22,32].

Overall performance on both ‘fear’ judgement andface recognition accuracy was similar in men and inwomen, so there appear to be different ways to achievenormal recognition of faces, and to categorise ‘fear’ infaces, too. However, women were somewhat better atidentifying facial expressions generally, in this study, asin others [20,23]. Heightened sensitivity to events ofemotional significance is also reported to be greater inwomen’s autobiographical memory [30], suggesting thatsex may moderate memorial processes via relative dif-ferences in experienced affect. At all events, womenmay make greater use of such emotional learning cir-cuitry in recognising faces than do men. The categorisa-tion of fearful facial expressions may then be implicatedto a differing degree within each sex in specific learningtasks: In women it is a good predictor, while in men itis not. A final speculation, therefore, is that sociallearning may recruit the amygdala more reliably anddirectly in women than in men.

Acknowledgements

DS, JK and KE were supported by the WellcomeTrust. RC and JT were supported with facilities fromthe Belle van Zuylen Foundation, University ofUtrecht. Grace Adlam, Rebecca Shah helped in dataacquisition; Andy Young provided access to the facialexpression tasks. Andy Calder offered useful advice.We are grateful to all for their help.

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The classification of ‘fear’ from faces is associated with face recognition skill in women

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