Developmental Science 14:5 (2011), pp 1176–1184

DOI: 10.1111/j.1467-7687.2011.01067.x

PAPER
Developing cultural differences in face processing
David J. Kelly,1 Shaoying Liu,2 Helen Rodger,3 Sébastien Miellet,3Liezhong Ge2 and Roberto Caldara3,4
1 . Department of Psychology, Royal Holloway, University of London, UK
2 . Department of Psychology, Zhejiang Sci-Tech University, Hangzhou, PR China
3 . Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, UK
4 . Department of Psychology, University of Fribourg, Switzerland

Abstract
Perception and eye movements are affected by culture. Adults from Eastern societies (e.g. China) display a disposition to process
information holistically, whereas individuals from Western societies (e.g. Britain) process information analytically. Recently,
this pattern of cultural differences has been extended to face processing. Adults from Eastern cultures fixate centrally towards
the nose when learning and recognizing faces, whereas adults from Western societies spread fixations across the eye and mouth
regions. Although light has been shed on how adults can fixate different areas yet achieve comparable recognition accuracy, thereason why such divergent strategies exist is less certain. Although some argue that culture shapes strategies across development,
little direct evidence exists to support this claim. Additionally, it has long been claimed that face recognition in early childhood islargely reliant upon external rather than internal face features, yet recent studies have challenged this theory. To address theseissues, we tested children aged 7–12 years of age from the UK and China with an old ⁄ new face recognition paradigm while
simultaneously recording their eye movements. Both populations displayed patterns of fixations that were consistent with adults
from their respective cultural groups, which ‘strengthened’ across development as qualified by a pattern classifier analysis.
Altogether, these observations suggest that cultural forces may indeed be responsible for shaping eye movements from earlychildhood. Furthermore, fixations made by both cultural groups almost exclusively landed on internal face regions, suggestingthat these features, and not external features, are universally used to achieve face recognition in childhood.

Introduction
The ability to accurately remember and identify conspecifics is a requisite skill for all social species. Humans
primarily achieve this feat through face recognition,
which requires rapid scanning of facial features in orderto encode a new identity or to recognize whether anindividual has been encountered previously or not. The
pioneering work of Yarbus (1965) first demonstrated that
adults display a distinct and ordered pattern of eye
movements during face encoding and recognition with
fixations primarily landing on the eyes and mouth
forming a triangular scanpath. Further studies replicatedthis finding (Groner, Walder & Groner, 1984; Henderson, Williams & Falk, 2005), which leads to the presumption that a triangular scanpath represents auniversal strategy employed by all individuals and is themost efficient way to extract individuating information.
However, this hypothesis was challenged by Blais, Jack,
Scheepers, Fiset and Caldara (2008) who found that incontrast to adults from Western societies (e.g. the USA),
individuals from Eastern (e.g. China) cultural back-grounds predominantly fixate the centre of the face andalmost completely avoid fixating the eyes, a finding
recently corroborated by another group in Japaneseobservers (Kita, Gunji, Inagaki, Kaga, Nakagawa &Hosokawa, 2010).
The strategy used by Eastern populations is particularly intriguing as available evidence suggests that the
information required to accurately recognize faces iscontained in the eye region (e.g. Gosselin & Schyns, 2001;
Caldara, Schyns, Mayer, Smith, Gosselin & Rossion,2005). Furthermore, there is insufficient variation within
the central nose region to achieve reliable face recognition (Goldstein, 1979a, 1979b; Caldara & Abdi, 2006).
Caldara, Zhou and Miellet (2010) explored this paradox
by testing East Asian (EA) and Western Caucasian (WC)
adults using a gaze-contingent moving aperture method.
In their study, the visual information available to participants was restricted by Gaussian apertures (termed
spotlights) sized 2, 5 or 8. In both the 2 and 5 conditions, the aperture was large enough for any single
facial feature (e.g. eye or nose) to be viewed, but it was
not large enough for the eyes and mouth to be visible

Address for correspondence: David J. Kelly, Department of Psychology, Royal Holloway, Egham Hill, Egham, Surrey, TW20 0EX, UK; e-mail:david.kelly@rhul.ac.uk

 2011 Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.

Developing cultural differences in face processing 1177

when fixating the nose. In the larger 8 condition, however, the aperture was sufficiently large for participants
to fixate centrally on the nose region and view the mouthand eyes simultaneously. As predicted by Caldara andcolleagues, the differences reported by Blais et al. (2008)
were abolished in the restrictive 2 and 5 aperture conditions. In both of these conditions, EA and WC participants predominantly directed their fixations to theeye region. By contrast, in the 8 condition the EA
participants reverted to their preferred central landing
position while the WC participants retained their familiar triangular scanpath. Thus, it appears probable thatthe cognitive mechanisms operating to reliably encode
and subsequently recognize the faces of conspecifics areinvariant, but the manner in which this information is
extracted is subject to environmental modulation.
If this interpretation of events is correct, then one canpredict that the distinct eye movement patterns displayedby adults should emerge at a currently unknown timepoint and subsequently strengthen across ontogeny.
Furthermore, it seems reasonable to hypothesize that allindividuals may initially attend to the same facial information early in life before culture-specific patterns
emerge as environmental forces are exerted. Currently
though, it is unknown which of the strategies observed in
adults might be found in developing populations orwhether such clear strategies even exist in infancy andchildhood. However, understanding the developing
visual system can provide clues that permit a certain
degree of speculation.
Based on the properties of the human newborn visualsystem, we can speculate that the pattern of eye movements observed at this age is more likely to resemble arudimentary WC adult scanpath than an EA adultscanpath. The visual system of newborn infants isextremely limited relative to adults. At birth, an infant’svisual acuity is approximately 40 times poorer thanadults and is limited to the processing of spatial frequencies no greater than 1cpd (cycle per degree). Furthermore, newborns’ sensitivity to contrast is around 30
times poorer than adults’. Consequently, newborns’ recognition of faces is achieved using low spatial frequency
information (de Heering, Turati, Rossion, Bulf, Goffaux& Simion, 2008) and therefore their recognition of faces
is dependent upon large-scale differences between faces
as they are unable to exploit fine-grained information.
Thus, early in life newborns and infants will be drawn tofacial areas of high variation and high contrast, suggesting that they will be more attracted to the eye andmouth (if the teeth are visible) regions. The limited
available data suggest that this is indeed the case, with
infants increasing fixations directed at the face from theexternal contour to the eye region between 3 to 11 weeks
of age (Haith, Bergman & Moore, 1977) and 4-monthold infants directing the majority of their looks towards
internal face features (Gallay, Baudouin, Durand, Lemoine & Lcuyer, 2006). In Gallay et al.’s study, across afamiliarization trial with a single face, infants appear to 2011 Blackwell Publishing Ltd.

shift their gaze from the eye region to other facial features (i.e. nose and mouth) and then back again. Whether infants show greater interest in the nose or mouth
area is not clear at present as Gallay and colleagues
collapsed the fixation points from these two regions intoa single area of interest for analysis. Regardless, it canstill be stated that very early in life fixations are dispersed
around the internal facial features when faces are displayed in their canonical upright orientation.
Alternatively, other properties of the infant visualsystem mean that a case can be made for potentiallyobserving a central fixation landing position. Retinal celldensity and visual acuity decrease steeply towards theperipheral visual field, which might make the centre of
the face an optimal spatial position to capture facial
feature information holistically. Currently, such a patternof looking has only been reported in Chinese adults,
making a WC adult-like pattern of eye movements more
likely to be observed, but owing to the lack of developmental eye-tracking studies using faces, the possibility
that similar behaviour might be seen in developing
populations remains open to investigation. A way tostraightforwardly address this issue is to test children
across a range of age groups. If culture is responsible forshaping the reported differences in adults, then we can
expect to observe them emerge across ontogeny.
A recent study conducted with Chinese infants aged 4
to 9 months of age has provided some clues concerning
the origins of differential face scanning strategies. Liu,
Quinn, Wheeler, Xiao, Ge and Lee (2011) sequentiallypresented videos of a Chinese or Caucasian adult female
to 23 Chinese infants. Their analyses found no significant
differences for fixations to the eyes or mouth between
own- and other-race faces, but a significant race of faceby age interaction was found for fixations to the nose.
While the high frequency of fixations to the nose wasmaintained for own-race faces, they decreased with age
for other-race faces. Although these findings might suggest that a predilection to fixate the central face region
develops within the first year of life in Chinese infants,
making this conclusion would be premature. As only one
population was tested and the stimulus set used was
relatively limited, we cannot be certain that the pattern ofresults reported by Liu et al. is evidence of the same
strategic eye movement differences found in adults.
Nevertheless, the results from Liu et al. warrant further
investigation with different cultural and older age groups.
In addition to attempting to identify the emergence of
cultural differences in eye movements, the current study
will also enable us to explore more general aspects of faceprocessing development. In particular, analysis of fixation locations will inform the inner ⁄ outer face featuredebate. Earlier behavioural studies reported that children
aged 5 to 13 years rely more on external face features
relative to internal face features when recognizing
famous faces (Campbell, Coleman, Walker, Benson,
Wallace, Michelotti & Baron-Cohen, 1999) and 5- to
9-year-olds show the same external advantage for1178 David J. Kelly et al.

unfamiliar adult faces (Want, Pascalis, Coleman &Blades, 2003). However, later studies have reported an
inner face advantage in children from 5 years of age
when recognizing familiar adult faces (Wilson, Blades &Pascalis, 2007). In terms of children recognizing children’s faces, the results are similarly mixed. While one
study has reported an external face advantage at 7 years
shifting to an internal face advantage at 9 years(Campbell, Walker & Baron-Cohen, 1995), a second
study found an internal advantage from 7 years of age(Bonner & Burton, 2004). A recent study further
explored this issue by testing children with their classmates’ faces and found an internal advantage in 4-yearold children. The authors conclude that previous reports
of a reliance on external face features are attributable toexperience with faces rather than ontogenetic shifts inprocessing strategy (Ge, Anzures, Wang, Kelly, Pascalis,
Quinn, Slater, Yang & Lee, 2008). However, it is notablethat in contrast to all the other studies described above, Geand colleagues tested a non-Western (Chinese) population. This raises the possibility that strategic differences inface processing may exist between Eastern and Westerncultural groups and that the findings of Ge et al. are
attributable to cultural differences rather than experiential
differences. The current study will add clarity to this issue
by testing both Eastern and Western children across a
range of age groups with unfamiliar faces from both races.
To begin to explore the origins of cultural differencesin eye movements when encoding and recognizing
human faces and potential cultural divergence in generalface processing strategies, we recruited children aged 7 to
12 years of age from the UK and China. Children were
tested with East Asian and Western Caucasian adultfaces with an old ⁄ new face recognition paradigm, analogous to the adult study (Blais et al., 2008), while wesimultaneously recorded their eye movements. With thisbalanced design, we predicted that the patterns of eye
movements displayed in both cultural groups might bedifferent in even the youngest children (based on thefindings of Liu et al., 2011), but will further diverge tomore fully resemble their respective adult cultural norms
in older age groups.

Methods
Participants
In total, 42 WC children and 42 EA children comprised
the final sample. Within each cultural population, there
were three separate age groups: 7–8 years, 9–10 years
and 11–12 years. There were 14 children of each culturalgroup in each age group: 7–8 years (WC: eight female,age range = 7.2–8.8; EA: six female, age range =7.4–8.6), 9–10 years (WC: seven female, age range =9.1–10.9; EA: seven female, age range = 9.4–10.10),
11–12 years (WC: seven female, age range = 11.2–12.11;
EA: six female, age range = 11.3–12.9).
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The WC participants were recruited from local schools
near to the University of Glasgow. Letters providing
information about the study were distributed to theschools and subsequently sent home for parents. Parents
were then able to contact us to arrange a convenient
testing time. Written consent was obtained from parents
and testing only occurred if the child was willing toparticipate. Remuneration comprised travel expenses forparents and gift vouchers for children.
The EA participants were recruited from schools in
Hangzhou, PR China. Testing took place in the schools
where parents had already provided consent for theirchildren to participate in studies affiliated to Zheijiang SciTech University. Children were reimbursed for their participation with stationary sets. All participants from both
populations had normal or corrected to normal vision.
Materials
Face stimuli were obtained from the KDEF (Lundqvist,
Flykt & hman, 1998) and AFID (Bang, Kim & Choi,
2001) databases and consisted of 12 East Asian and 12
Western Caucasian identities holding neutral facial
expressions and contained equal numbers of adult males
and females. The images were 390 · 382 pixels in size,
subtending 15.6 degrees of visual angle horizontally and15.3 degrees of visual angle vertically, which represents
the size of a real face (approximately 19 cm in height).
All images were cropped around the face to remove
clothing and were devoid of distinctive features (scarf,
jewellery, facial hair, etc.). All images were mounted on awhite background and viewed at a distance of 70 cm.
This reflects a natural distance during human face-toface interaction (Hall, 1966) and has been successfully
used in previous studies (Blais et al., 2008; Caldara et al.,2010; Kelly, Miellet & Caldara, 2010). Luminance wasnormalized for all images and they were presented on a
800 · 600 pixel grey background displayed on a 19¢¢
CRT monitor with a refresh rate of 170 Hz.
Eye tracking (UK)
Eye movements were recorded at a sampling rate of1000 Hz with the SR Research Desktop-Mount EyeLink
2K eyetracker (with a chin ⁄ forehead-rest), which has anaverage gaze position error of about 0.25. Only thedominant eye of each participant was tracked althoughviewing was binocular. The experiment was implemented
in Matlab (R2006a), using the Psychophysics (PTB-3)
and EyeLink Toolbox extensions (Brainard, 1997; Cornelissen, Peters & Palmer, 2002). Calibrations of eye
fixations were conducted at the beginning of the experiment using a nine-point fixation procedure as implemented in the EyeLink API (see EyeLink Manual) andinitiated using Matlab software. Calibration was validated with the EyeLink software and repeated whennecessary until the optimal calibration criterion wasreached.

Developing cultural differences in face processing 1179

Eye tracking (China)
Binocular eye movements were recorded at a sampling
rate of 60 Hz with a Tobii T120 eyetracker which has anaverage gaze position error of about 0.5. The experiment
was implemented using Tobii Studio software. Calibration of eye fixations was conducted at the beginning of
the experiment using a nine-point fixation procedure in
Tobii Studio software. Calibration was validated andrepeated when necessary until the optimal calibration
criterion was reached.
Eye tracking – hardware differences
Naturally, it would have been preferable for all participants to have been tested with identical eye-tracking systems. To combat this difference, prior to testing we defined
fixations so they were comparable across systems andsubsequently analyzed all data using custom written codewith an independent platform (MATLAB 2006a) to ensure that all data output was treated equally. Furthermore,
we also administered a control task to demonstrate thatany differences observed between populations were not an
artifact resulting from hardware differences. For the control task, we selected six new faces (three EA, three WC)
from the face database described above and presented
them sequentially for 5 seconds each to five children fromeach population while eye movements were recorded. For
half the face trials, children were asked to look at the eyes
and the mouth and for the remaining trials children were
instructed to fixate centrally on the nose. Eye movements
were analyzed separately for the ‘eye ⁄ mouth’ and ‘nose’
conditions and revealed no differences between culturalgroups (see Figure S1 in Supplementary Materials). Thus,
any differences observed between cultural groups are aconsequence of genuine strategic variations and not
attributable to the different hardware devices used.
Procedure
All participants completed both EA and WC face stimulus conditions. The order of conditions was counterbalanced across participants. Participants began eachstimulus condition with a training session, which comprised four examples of the images that would be displayed in that condition. Importantly, these images wereobtained from the original databases from which thefinal stimulus sets were taken, but they did not form partof the final sets and were not displayed again subsequently. The purpose of the training session was simply
to familiarize the participants with the stimuli, but they
were not required to perform any behavioural task during this phase and eye movements were not recorded.
Participants were informed that they would be presented with a series of images to learn and subsequently
recognize. They were also told that they would complete
two testing blocks in total. In each block, participants
were required to learn six images. After a 30 second
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pause, a series of 12 images (six targets from the learning
phase plus six foils) were presented and participants wereasked to indicate as quickly and as accurately as possible
whether each stimulus was a target or foil by pressing
designated keys (a, l) on the keyboard with the index
fingers of their left and right hands. Response buttons
were counterbalanced across participants.
Each test trial started with the presentation of a central
fixation cross that was displayed until the participant
held a stable fixation on the cross. Following this, astimulus was presented on the computer screen. All
stimuli were presented for 5 seconds’ duration in thelearning phase and until the participant made a key press
response in the recognition phase. To prevent anticipatory strategies, images were randomly presented at different locations of the computer screen. Each stimulus
was subsequently followed by the fixation cross, as
described above, which preceded the next stimulus.
Data analyses
Analysis was conducted using iMap (Caldara & Miellet,
in press) methods and other custom written MATLAB
software. Fixation distribution maps were computed
individually for WC and EA participants, for eachstimulus condition and separately for the learning andrecognition phases. The fixation maps were computed bysumming, across all (correct) trials, the fixation location
coordinates (x, y) across time. Since more than one pixel
is processed during a fixation, we smoothed the resulting
fixation distributions with a Gaussian kernel with a sigma of 15 pixels. Then, the fixation maps of all the participants belonging to the same cultural group weresummed together separately for each face condition,
resulting in group fixation maps.
We Z-scored the group fixation maps by assuming
identical WC and EA eye movement distributions for aparticular face race as the null hypothesis. Consequently,
we pooled the fixation distributions of participants forboth groups and used the mean and the standard deviation for each stimulus condition to separately normalize
the data. Finally, to clearly reveal the difference of fixation patterns across participants of different cultures, we
subtracted the group fixation maps of the EA participantsfrom the WC participants and Z-scored the resulting
distribution. To establish significance, we used a robust
statistical approach correcting for multiple comparisonsin the fixation map space, by applying a two-tailed Pixel
test (Chauvin, Worsley, Schyns, Arguin & Gosselin, 2005;
Zcrit > |4.64|; p < .05) on the differential fixation maps.

Results
Accuracy
A 2 (Culture of Observer: British or Chinese) · 2 (Race ofFace: WC or EA) · 3 (Age: 7–8 years, 9–10 years or 11–

1180 David J. Kelly et al.

12 years) ANOVA was conducted on participants’ recognition accuracy. The ANOVA yielded a main effect ofRace of Face (F(1, 82) = 11.550, p < .001, gp2 = .069)
and a main effect of Age (F(2, 81) = 6.510, p < .002,
gp2 = .077). Post-hoc analysis revealed that accuracy was
superior for WC faces (86.41%) relative to EA faces(80.46%) (t(83) = 3.691, p < .001) and that recognition
accuracy increased with age (7–8 years: 79.61%; 9–10
years: 83.33%; 11–12 years: 87.35%) with a significant
difference between 7–8-year-olds and 11–12-year-olds(t(55) = 3.702, p < .001). Furthermore, WC participants
were significantly more accurate at recognizing WC faces
relative to EA faces (t(41) = 3.954, p < .001), whereas
EA participants’ recognition accuracy did not differ
between face categories. Accuracy results are displayed in
Figure 1a.
Reaction timeA 2 (Culture of Observer: British or Chinese) · 2 (Race ofFace: WC or EA) · 3 (Age: 7–8 years, 9–10 years or
11–12 years) ANOVA was conducted on participants’recognition reaction times. The ANOVA yielded a main(a)effect of Culture of Participant (F(1, 82) = 10.724,
p < .001, gp2 = .064) only. Post-hoc analysis revealed
that WC children responded faster (1.932 secs) than EA
children (2.196 secs) (t(83) = 3.242, p < .002). Reaction
time results for correct trials are displayed in Figure 1b.
Number of fixations
A 2 (Culture of Observer: British or Chinese) · 2 (Condition: Learning or Recognition) · 3 (Age: 7–8 years,
9–10 years or 11–12 years) ANOVA was conducted on
the number of fixations made by participants. The
number of fixations made increased with age (7–8 years:
8.31; 9–10 years: 9.353; 11–12 years: 10.450) with asignificant difference between 7–8-year-olds and 11–12year-olds (t(55) = 2.836, p < .006). A main effect ofCondition (F(1, 82) = 10.431, p < .002, gp2 = .063) was
also found with more fixations made during learning(mean = 10.45) than recognition (mean = 8.45).
Eye movements
Children from the UK predominantly direct their fixations toward the eyes and mouth regions whereas children from China fixate more centrally on the nose
region. These strategic group differences, as qualified bya two-tailed pixel test (Zcrit > |4.64|, p < .05), are clearly
illustrated in Figure 2. Areas fixated above chance aredelimited by white borders and depict the relative fixation biases following map subtraction (WC ) EA).
Classifier(b)

Figure 1 (a) Accuracy (% correct responses) with standard
error bars from the recognition phase of the old ⁄ new task forWestern Caucasian (WC) and East Asian (EA) faces in all age
groups from both populations. (b) Reaction Times for correct
trials only with standard error bars from the recognition phaseof the old ⁄ new task for all age groups for Western Caucasian(WC) and East Asian (EA) faces in all age groups from both
populations.
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In order to measure any strategic changes in fixation
patterns across development, we classified children’s
fixation maps by contrasting these with adults’ fixation
maps obtained from a previous study, Kelly et al. (2010).
Critically, the materials and methods used by Kelly andcolleagues were identical to the current study, making thedata templates perfectly suited for comparison with the

Figure 2 Fixation maps: group differences. Maps display
Western Caucasian (WC) participant fixation strategies minus
East Asian (EA) fixation strategies at each age group. Areas ofsignificance are delimited by white borders (red indicates
Western Caucasian bias, blue indicates East Asian bias).

Developing cultural differences in face processing 1181

current results. We used the Z-scored EA and WC participants’ group fixation maps from Kelly et al. (2010) as‘Eastern’ and ‘Western’ templates. Subsequently, eachchild’s fixation map was compared against each of thetemplates. Four comparisons were computed separately
for each individual participant, which comprised thelearning and recognition phases for each race of face (i.e.
EA faces and WC faces). A correlation coefficient wasthen computed for each comparison to determine whichof the adults’ strategies the participants’ strategy wasclosest to. Since correlation coefficients are not additive,
they were then Z-normalized (Chung, Kim, Kelley,
Robbins, Evans & Davidson, 2005), using Fisher’stransform Z ¼ 0:5  loge 1þr
1r . A 2 (Culture of Observer:
British or Chinese) · 2 (Condition: Learning or Recognition) · 3 (Age: 7–8 years, 9–10 years or 11–12 years)
ANOVA was conducted to assess eye movement strategy
differences between groups and across development. The
ANOVA yielded a main effect of Culture of Observer only
(F(1, 82) = 43.778, p < .001, gp2 = .219), demonstratingthat significant strategic differences exist between the two
populations. Although a main effect of Age was notfound (F(1, 82) = 2.092, p = .130, gp2 = .051), we didobserve a non-significant trend in the predicted direction. Figure 3 displays the Z-normalized WC templatecomparison values minus the Z-normalized EA templatecomparison values. Inspection of these values reveals
that for both cultural groups, older children’s fixation
strategies more closely resemble their respective adultfixation patterns.
Inner ⁄ outer fixations
In order to assess the number of fixations directed
towards internal and external features, two Areas ofInterest (AOIs) were established. One AOI covered
the internal facial features only and the second AOIFigure 3 Results from classifier analysis. Z-normalised Western Caucasian template comparison values minus the East
Asian template comparison values with standard error bars.
Positive values indicate ‘Western-like’ fixation strategies.
Negative values indicate ‘Eastern-like’ fixation strategies.
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comprised the rest of the pixel space. The number offixations that fell within each of these two AOIs was thencalculated individually for each participant. A 2 (Cultureof Observer: British or Chinese) · 2 (Condition: Learning
or Recognition) · 3 (Age: 7–8 years, 9–10 years or 11–
12 years) · 2 (AOI: Internal or External) ANOVA was
conducted on the number of fixations made by participants yielding a main effect of AOI only (F(1,82) = 24235.06, p < .0001, gp2 = .987). Inspection of themean number of fixations showed that participants
almost exclusively directed their fixations towards internal features (98.56%) rather than external features(1.44%).

Discussion
The subtracted group fixation maps show that the patterns of fixations displayed by children in all age groups
are highly similar to those of adults from their respective
cultural groups reported in previous studies (Blais et al.,2008; Caldara et al., 2010; Kelly et al., 2010) when
encoding and recognizing human faces. The culturespecific patterns observed in EA and WC adults wereeven present in the youngest age group tested. Thisobservation was qualified by the classification procedure
conducted using templates from Kelly et al. (2010).
Furthermore, fixation strategies appear to become more‘adult-like’ across development, although this trend
failed to reach statistical significance. Our findings
clearly show that culture-specific fixation strategies arepresent by 7 years of age and are maintained throughout
later childhood. The non-significant trend observed for
culture-specific strategies to become more ‘adult-like’
across childhood implies that these cultural differences
may increase with age, although the current data do notprovide definitive support for this conclusion. In relation
to the study of Liu et al. (2011), the findings from thepresent study demonstrate that the ‘tuning’ of culturespecific eye movement patterns continues long after
infancy. Furthermore, Liu and colleagues found that atendency to fixate the nose region decreased for otherrace faces. In our study culture-specific strategies were
present for both own- and other-race faces (see Figure S2 in Supplementary Materials), which might indicate that the face system has reached a more robust
calibration in the eye movement strategy used to process
faces. Further eye-tracking studies with infants andyoung children are necessary to identify the precisechanges that occur in early childhood, and precisely
identify when similar eye movement strategies are
deployed for all human faces.
A slightly unexpected auxiliary finding is that EA
children did not display an own-race bias in face recognition, while the WC children did. We cannot fully
account for this result as previous studies have foundevidence for the other-race effect emerging during
infancy (e.g. Kelly, Quinn, Slater, Lee, Ge & Pascalis,

1182 David J. Kelly et al.

2007; Kelly, Liu, Lee, Quinn, Pascalis, Slater & Ge,2009). EA children did take significantly longer to
respond relative to WC children, which could account for
their high accuracy. Alternatively, the increase in exposure to Western media such as Hollywood movies andthe internet in China could have eradicated the effectin this population. Future studies may well shed light on
this finding.
As cultural differences in fixation strategies wereobserved during development, it is critical to question
what aspect of culture is responsible for producing distinct strategies during face processing tasks. At present,
the analytical versus holistic cultural framework of perceptual and attentional processing styles by Nisbett andMiyamoto (2005) provides the most plausible explanation for the pattern of results observed. According totheir work, individuals from Western cultural backgrounds display a tendency to process information analytically by focusing on salient objects and using
categorical rules when organizing their visual environment. People from Eastern cultures, on the other hand,seem to process information in a more holistic manner byshowing interest in context and grouping objects
according to relationships. Miyamoto, Nisbett andMasuda (2006) have argued that the reported variations
have arisen as a consequence of the physical environment and historical differences between these distinct
societies (e.g. individualist versus collectivist; see Miyamoto et al., 2006, for a fuller account and Kelly
et al., 2010, for further discussion on this issue). The
critical, but as yet unanswered, question that remains iswhether it is these same forces that impact face recognition and whether a direct link between cultural
upbringing and strategies to extract information fromthe environment can be established. The suggestion thatsuch a link might exist would have been considered
controversial until quite recently; however, as evidence
from the cultural framework of perception and attention increases we are challenged to reconsider thisposition.
In a recent review of cross-cultural studies, Henrich,
Heine and Norenzayan (2010) endorse the view thatmuch of what we consider to be universal in psychology,
including ‘classic’ effects with visual illusions, is in fact
culture specific. Perhaps counter-intuitively to membersof the Western psychology community, Henrich et al.
claim that not only do pronounced differences inthought, behaviour and perception exist between culturalgroups, but the most commonly tested population (i.e.
white, middle-class, psychology students) might be theoutliers in relation to most other populations. However,Henrich and colleagues also emphasize that culturaldifferences are not always found, and highlight areas
where universality prevails (e.g. mate preferences andpersonality structure). It is necessary to be mindful of
this fact and rather than seeking out cultural differences
alone, we should also attempt to understand what

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differences exist and how to account for them. In thepresent study, cultural variations were clearly demonstrated in eye movements at the individual feature level(i.e. looking at eyes versus nose), but no differences were
found at the internal ⁄ external features level. This result
adds further weight to the argument proposed by Caldara et al. (2010), who suggested that the cognitive
mechanisms involved in face processing are identicalacross all peoples, but the strategies employed for
information extraction vary across populations. Future
developmental work will be crucial to aid our understanding of how cultural differences arise across populations, which cognitive processes are subject toenvironmental modulation and when they occur. For
example, testing children younger than 7 years of age
with age-appropriate methods is likely to provide significant insights into early development of these processes.
In relation to the internal ⁄ external feature debate, thefindings from this study offer strong support for the
reliance of internal feature use for face encoding andrecognition during childhood as all age groups almost
exclusively directed fixations towards the internal features. Although this finding is at odds with some early
work in this area (Campbell et al., 1999; Want et al.,2003), the pattern of results is consistent with recent
studies (Bonner & Burton, 2004; Ge et al., 2008; Liuet al., 2011; Wilson et al., 2007). It is important toemphasize that the current study can only inform on
which facial information overt visual attention is directed
towards during recognition and not how accurate recognition is achieved. On the basis of the fixations patterns observed it is clear that if external face information
is being used to recognize faces, it is done using
extrafoveal vision as fixations were not directed to theseregions. Therefore, it seems probable that face recognition in childhood does not require the use of the detailed,foveated information that would be gained by landing
fixations on external features. This reliance on internalfeature information accords with recent studies that
contrast with earlier evidence of internal ⁄ external information use biases and ontogenetic shifts. Notably, in thecurrent study the face stimuli represented unfamiliar
adults and were displayed as full faces. Based on thefindings of earlier studies, one might have predicted thatthe unfamiliarity of faces would have led to an externalfeature advantage, at least in the younger age groups. But
our data do not support this view. One possible explanation for the discrepancies between studies is that the
typical method of displaying faces that have been divided
into internal ⁄ external features induces artificial learning
strategies. To establish whether this is correct, it will be
important for future studies to consider this point and touse naturalistic full faces whenever possible. Nonetheless,we believe the current study provides an important
contribution to this literature and demonstrates thatexternal face features are not relied upon by children

Developing cultural differences in face processing 1183

aged 7–12 years when encoding and recognizing unfamiliar faces.
In conclusion, cultural differences in eye movements
were found in children as young as 7 years of age during
face encoding and recognition. Furthermore, the strategies displayed by both WC and EA children wereconsistent with those previously reported in adults (Blais
et al., 2008; Caldara et al., 2010; Kelly et al., 2010).
Although it cannot be definitively stated that cultural
factors are responsible for shaping the distinct eye
movement patterns observed, the culture-specific adultlike fixation strategies displayed at 7 years of age and theapparent strengthening of strategies across ontogeny
implies that experiential factors influence the way information is extracted from the visual world.

Acknowledgements
DK was supported by the Economic and Social ResearchCouncil (RES-000-22-3338); SM was supported by the
Economic and Social Research Council and Medical
Research Council (ESRC ⁄ RES-060-25-0010); RC byboth funding bodies.

References
Bang, S., Kim, D., & Choi, S. (2001). Asian Face Image
Database PF01. Intelligent Multimedia Lab, Pohang University of Science and Technology: http://nova.postech.ac.kr/.
Blais, C., Jack, R.E., Scheepers, C., Fiset, D., & Caldara, R.
(2008). Culture shapes how we look at faces. PLoS ONE, 3,
e3022.
Bonner, L., & Burton, M.A. (2004). 7–11-year-old children
show an advantage for matching and recognizing the internalfeatures of familiar faces: evidence against a developmental
shift. Quarterly Journal of Experimental Psychology, 57,
1019–1029.
Brainard, D.H. (1997). The psychophysics toolbox. Spatial
Vision, 10, 433–436.
Caldara, R., & Abdi, H. (2006). Simulating the ‘other-race’
effect with autoassociative neural networks: further evidence in favor of the face-space model. Perception, 35, 659–
670.
Caldara, R., & Miellet, S (in press). iMap: a novel method forstatistical fixation mapping of eye movement data. Behavior
Research Methods.
Caldara, R., Schyns. P.G., Mayer, E., Smith, M., Gosselin, F.,& Rossion, B. (2005). Does prosopagnosia take the eyes outof face representations? Evidence for a defect in representing
diagnostic facial information following brain damage. Journal of Cognitive Neuroscience, 17, 1652–1666.
Caldara, R., Zhou, X., & Miellet, S. (2010). Putting culture
under the ‘spotlight’ reveals universal information use forface recognition. PLoS ONE, 5, e9708.
Campbell, R., Coleman, M., Walker, J., Benson, P.J., Wallace,S., Michelotti, J., & Baron-Cohen, S. (1999). When does theinner-face advantage in familiar face recognition arise andwhy? Visual Cognition, 6, 197–216.
 2011 Blackwell Publishing Ltd.

Campbell, R., Walker, J., & Baron-Cohen, S. (1995). The
development of differential use of inner and outer face features in familiar face identification. Journal of Experimental
Child Psychology, 59, 196–210.
Chauvin, A., Worsley, K.J., Schyns, P.G., Arguin, M., &Gosselin, F. (2005). Accurate statistical tests for smoothclassification images. Journal of Vision, 5, 659–667.
Chung, M.K., Kim, D.M., Kelley, D.J., Robbins, S., Evans,
A.C., & Davidson, R.J. (2005). Partial correlation mapping of
anatomical and behavioral measures and its application to
autism. Madison, WI: University of Wisconsin-Madison.
Cornelissen, F.W., Peters, E.M., & Palmer, J. (2002). The
Eyelink Toolbox: eye tracking with MATLAB and the Psychophysics Toolbox. Behavioral Research Methods, Instruments & Computers, 34, 613–617.
de Heering, A., Turati, C., Rossion, B., Bulf, H., Goffaux, V.,& Simion, F. (2008). Newborns’ face recognition is based on
spatial frequencies below 0.5 cycles per degree. Cognition,
106, 444–454.
Gallay, M., Durand, K., Baudouin, J.-Y., Lemoine, C., &Lcuyer, R. (2006). Qualitative differences in the explorationof upright and upside-down faces in four-month-old infants:
an eye-movement study. Child Development, 77, 984–996.
Ge, L., Anzures, G., Wang, Z., Kelly, D.J., Pascalis, O., Quinn,
P.C., Slater, A.M., Yang, Z., & Lee, K. (2008). An inner faceadvantage in children’s recognition of familiar peers. Journalof Experimental Child Psychology, 101, 124–136.
Goldstein, A.G. (1979a). Race-related variation of facial features: anthropometric data I. Bulletin of the Psychonomic
Society, 13, 187–190.
Goldstein, A.G. (1979b). Facial feature variation: anthropometric data II. Bulletin of the Psychonomic Society, 13, 191–
193.
Gosselin, F., & Schyns, P.G. (2001). Bubbles: a technique toreveal the use of information in recognition tasks. Cognition,
41, 2261–2271.
Groner, R., Walder, F., & Groner, M. (1984). Looking at faces:
local and global aspects of scanpaths. In A.G. Gale & F.
Johnson (Eds.), Theoretical and applied aspects of eye movement research (pp. 523–533). Amsterdam: Elsevier.
Haith, M.M., Bergman, T., & Moore, M.J. (1977). Eye contact
and face scanning in early infancy. Science, 198, 853–855.
Hall, E.T. (1966). The hidden dimension. New York: Doubleday.
Henderson, J.M., Williams, C.C., & Falk, R.J. (2005). Eye
movements are functional during face learning. Memory andCognition, 33, 98–106.
Henrich, J., Heine, S.J., & Norenzayan, A. (2010). The weirdest
people in the world? Behavioral and Brain Sciences, 33, 61–135.
Kelly, D.J., Liu, S., Lee, K., Quinn, P.C., Pascalis, O., Slater,
A.M., & Ge, L. (2009). Development of the other-race effectduring infancy: evidence towards universality? Journal of
Experimental Child Psychology, 104, 105–114.
Kelly, D.J., Miellet, S., & Caldara, R. (2010). Culture shapes
eye movements for visually homogeneous objects. Frontiers in
Psychology, 1. doi: 10.3389/fpsyg.2010.00006.
Kelly, D.J., Quinn, P.C., Slater, A.M., Lee, K., Ge, L., &Pascalis, O. (2007). The other-race effect develops during
infancy: evidence of perceptual narrowing. Psychological
Science, 18, 1084–1089.
Kita, Y., Gunji, A., Inagaki, M., Kaga, M., Nakagawa, E., &Hosokawa, T. (2010). Scanning strategies do not modulate
face identification: eye-tracking and near-infrared spectroscopy study. PLoS ONE, 5, e11050.

1184 David J. Kelly et al.

Liu, S., Quinn, P.C., Wheeler, A., Xiao, N., Ge, L., & Lee, K.
(2011). Similarity and difference in the processing of sameand other-race faces as revealed by eye-tracking in 4- to
9-month-olds. Journal of Experimental Child Psychology, 108(1), 180–189.
Lundqvist, D., Flykt, A., & hman, A. (1998). The Karolinska
Directed Emotional Faces. Karolinska Institute (Ed.).
Stockholm.
Miyamoto, Y., Nisbett, R.E., & Masuda, T. (2006). Culture
and the physical environment: holistic versus analytic perceptual affordances. Psychological Science, 17, 113–119.
Nisbett, R.E., & Miyatomo, Y. (2005). The influence of culture: holistic versus analytic perception. Trends in Cognitive
Sciences, 9, 467–473.
Want, S.C., Pascalis, O., Coleman, M., & Blades, M. (2003).
Recognizing people from inner or outer parts of their faces:developmental data concerning ‘unfamilar’ faces. Journal of
Developmental Psychology, 21, 125–135.
Wilson, R.R., Blades, M., & Pascalis, O. (2007). What dochildren look at in an adult face with which they are personally familiar? British Journal of Developmental Psychology, 25, 375–382.
Yarbus, A.L. (1965). Role of eye movements in the visual process.
Moscow: Nauka.

 2011 Blackwell Publishing Ltd.

Received: 11 November 2010
Accepted: 14 March 2011

Supporting Information
Additional Supporting Information may be found in the online
version of this article:
Figure S1 Fixations maps generated for Western Caucasianand East Asian children in the control task where explicit
instructions to look to either the ‘eyes and mouth’ or the ‘nose’
were provided.
Figure S2 Fixation maps displaying fixation patterns separately for WC and EA faces in each age group. The subtracted
maps show small but non-significant differences between fixation
patterns for own- and other-race faces in both populations. Figure
2a displays Western Caucasian participants’ fixation strategies.
Figure 2b displays East Asian participants’ fixation strategies.
Please note: Wiley-Blackwell are not responsible for thecontent or functionality of any supporting materials suppliedby the authors. Any queries (other than missing material)
should be directed to the corresponding author for the article.