Putting Culture Under the ‘Spotlight’ Reveals Universal
Information Use for Face Recognition
Roberto Caldara1*, Xinyue Zhou2, Sébastien Miellet1
1 Department of Psychology and Centre for Cognitive Neuroimaging, University of Glasgow, Glasgow, United Kingdom, 2 Department of Psychology, Sun Yat-Sen
University, Guangzhou, China

Abstract
Background: Eye movement strategies employed by humans to identify conspecifics are not universal. Westerners
predominantly fixate the eyes during face recognition, whereas Easterners more the nose region, yet recognition accuracy iscomparable. However, natural fixations do not unequivocally represent information extraction. So the question of whether
humans universally use identical facial information to recognize faces remains unresolved.
Methodology/Principal Findings: We monitored eye movements during face recognition of Western Caucasian (WC) andEast Asian (EA) observers with a novel technique in face recognition that parametrically restricts information outside central
vision. We used ‘Spotlights’ with Gaussian apertures of 2u, 5u or 8u dynamically centered on observers’ fixations. Strikingly, inconstrained Spotlight conditions (2u and 5u) observers of both cultures actively fixated the same facial information: the eyes
and mouth. When information from both eyes and mouth was simultaneously available when fixating the nose (8u), as
expected EA observers shifted their fixations towards this region.
Conclusions/Significance: Social experience and cultural factors shape the strategies used to extract information from faces,
but these results suggest that external forces do not modulate information use. Human beings rely on identical facial
information to recognize conspecifics, a universal law that might be dictated by the evolutionary constraints of nature andnot nurture.
Citation: Caldara R, Zhou X, Miellet S (2010) Putting Culture Under the ‘Spotlight’ Reveals Universal Information Use for Face Recognition. PLoS ONE 5(3): e9708.
doi:10.1371/journal.pone.0009708
Editor: Jan Lauwereyns, Kyushu University, Japan
Received January 14, 2010; Accepted February 20, 2010; Published March 18, 2010
Copyright: ß 2010 Caldara et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by The Economic and Social Research Council and Medical Research Council (ESRC/RES-060-25-0010). The funders had norole in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: r.caldara@psy.gla.ac.uk

paradigms: scene perception (e.g., [11]) and description (e.g., [12]),perceptual categorization (e.g., [13]) and eye movement for scene
affordance [14]. All these studies converge into a similar pattern ofresults, revealing that distinct cultural mechanisms influence visual
perception and categorization. Western cultures focus on salient
objects or features and use analytical categorization rules toorganize the environment. By contrast, Easterners focus moreglobally on relationships and similarities among objects whenorganizing the environment. Our previous eye movement data [2]suggest that Western Caucasian observers deploy an analyticalperceptual strategy to integrate facial information by using featureby-feature fixations, whereas East Asian observers focused on theregion that is optimal and economical to integrate information
globally: the center of the face (i.e., the nose region). The nose
region is the most advantageous spatial position to capture facial
feature information globally (see Figure 1 - 8u condition), since
retinal cell density and visual resolution decrease steeply towards
the peripheral visual field. One of the most prominent, despite
debatable, position in the cultural framework posits the roots of thediversity in cultural perceptual strategies in the organization of thesocial systems in which people develop and live (for a review see[15,16]). Western societies are individualistic, encouraging thedevelopment of individual goals, which would favor the perceptionof focal object in a context [17]. By contrast, Eastern societies are

Introduction
As noted by Galton over one century ago [1], the humancapacity for face recognition is remarkable compared to therecognition of other objects. This critical biological function is abasic requirement for efficient social interactions, for all humans
within all cultures. We recently questioned the universality of how
face recognition is achieved by recording eye movements [2]. We
showed that Westerners predominantly fixate the eye region tolearn and recognize faces, a well established finding in the eye
movement literature on faces [3,4,5,6,7,8,9]. However, contrary to
all prior knowledge, Easterners consistently focus more on thenose, yet recognition accuracy was comparable. Such cultural
diversity in eye movements was robust over time and generalized
across different face processing tasks (learning, recognition andcategorization by race).
These observations demonstrate that face processing does notarise from a universal series of perceptual events. Instead, thestrategies employed to extract visual information from faces varies
across cultures. We mainly attributed eye movement diversity inface processing to genuine systematic cultural perceptual differences observed between Westerners and Easterners. A growing
body of literature (for a review see [10]) has reported systematicdifferences across cultures in a variety of perceptual tasks and
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Figure 1. Area covered by Spotlights with Gaussian apertures of 2u, 5u and 8u, centered respectively on the left eye and the nose
region. Note that information from both eyes and the mouth is available from the nose region only in the 8u condition.
doi:10.1371/journal.pone.0009708.g001

observers by using ‘Spotlights’ with Gaussian apertures dynamically
centered on observers’ fixations of 2u (foveal vision only), 5u and 8u(both expanding on extrafoveal vision). Crucially, in the 2u and 5u
conditions, the Spotlight apertures covered an entire eye, but the eyes
and the mouth were not visible when fixating the nose (Figure 1 andsee also Supporting Movie S1). The 8u condition was the closest tonatural viewing conditions; information from both eyes and themouth was simultaneously available when fixating the nose.
Observers from both cultures were randomly allocated to one ofthese conditions and learned two series of 14 of Western Caucasianand East Asian faces with neutral, happy or disgusted expressions
presented for 10 seconds each. After a 30 second interval, observers
indicated which of 28 faces (14 faces from the learning phase – 14
new faces) was familiar or not. The emotional expression of thefamiliar faces was changed between the learning and the recognition
stage to avoid trivial image matching strategies. In order to rule out
the possibility of an inherent bias in East Asian faces that would
drive the typical central eye movement strategy used by Easterners(i.e., the presence of more information on the nose region in East
Asian faces compared to Western Caucasian faces), we also carriedout a pixel-based statistical analysis on the face images used in theexperiment.
Our results show that when the eyes and the mouth were notvisible when fixating the nose (constrained 2u and 5u Spotlights
conditions – Figure 1), Westerners and Easterners observers relyon the very same information to recognize faces, by actively
deploying triangular fixations mainly over the eyes and partiallythe mouth. The eye movement strategies of Westerners were notmodulated by any of the Spotlight size apertures. By contrast,
Easterners shifted their eye movement strategy in the condition
closest to naturalistic viewing conditions (8u – Figure 1), with
fixations landing at their preferred location: the center of the face.
In line with previous findings [36,37,38], our analysis on the face
images showed that the modulations in the fixation strategies
deployed by observers from different cultures cannot be accounted
by any obvious difference that would rely on differences in facial
feature information between faces from different race.

collectivistic, in which the group holds greater importance than theindividual, favoring perception biases towards the relationshipbetween objects (but see [18]).
Beyond the theoretical interpretations of our previous findings,
it remains puzzling and necessary to explain how East Asianobservers achieve face recognition by not focusing on the eyes.
Indeed, the abundant literature on face recognition testing
Western Caucasian observers in the recognition of Western
Caucasian faces (e.g., [19,20,21]), with response classification
techniques in normal healthy adults (e.g., [22,23]) and brain
damaged patients [24], and computational modeling (e.g., [25,26])
have robustly shown in Westerners that the critical information forface recognition is located in the eyes and partially the mouth, but
not the nose. These findings question the genuine use of
information from the nose region in Easterner observers, or atleast it remains to be unambiguously demonstrated that Easterners
use only information from this region to recognize faces. Given thateye movements in natural viewing conditions do not provide
unequivocal evidence on the measure of the visual information
being used by observers [27], it is possible that information fromthe eyes is extracted without focal fixations. For instance, Kuhn
and Tatler [28] have shown that people detecting successfully amagic trick do not necessarily fixate at the location on which thetrick is taking place, demonstrating that a natural fixation does notstraightforwardly translate information use. As a consequence, thequestion of whether humans universally use similar facial
information to recognize faces, despite cultural variance in eye
movements, remains unresolved.
To directly address this issue, we monitored eye movements ofthirty Western Caucasian and thirty East Asian (i.e., Chinese)
observers during the recognition of Western Caucasian and East
Asian faces, using a gaze-contingent paradigm [29], a techniquethat has been extensively used in reading and scene perception
literature (for a review see [30]). In gaze-contingent paradigms thestimulus display is continuously updated as a function of theobservers’ current gaze position. Therefore, the gaze-contingent
technique is a powerful method to control for the visual information
feeding the visual system and to isolate information use. In thelanguage domain this method has been successfully used in natural
reading to map out the perceptual span (moving window paradigm:
e.g., [31,32]), the nature of the extrafoveal information extracted
during a fixation, for instance orthographic and phonologicalinformation (boundary paradigm: e.g., [29,33,34]) or the relative
influence of attention versus acuity drop-off in the perceptual span(parafoveal magnification paradigm: e.g., [35]). Here, we adapted
the gaze-contingent method to reveal the information actively usedby observers to achieve face recognition. To this aim, weparametrically restricted the facial information available to the
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Results
Behavior
The race of the faces did not interact with the culture of theobserver in terms of accuracy (F(1, 54) = .49, P = .48) and response
times (F(1, 54) = 2.71, P = .10), even in the condition with thelargest aperture size: 8u (accuracy — F(1, 18) = 1.25, P = .27);
response times — F(1, 18) = 1.75, P = .2). For this reason, we
collapsed the data across faces (Figure 2).
Regardless of their culture, observers showed an increase offace recognition accuracy (F(2, 54) = 43.8, P,0.001) and faster2

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Figure 2. Percentages of correct responses (left y axis) and response times (right y axis) for the different Spotlight conditions. WC =Western Caucasian; EA = East Asian. Note the relationship for those variables, the increase of accuracy with larger Spotlight apertures was also
accompanied by faster response times (WC: plain lines; EA: dashed lines).
doi:10.1371/journal.pone.0009708.g002

eye region (2u and 5u) and partially the mouth (5u) when the
Spotlight constrained the available information, similarly toWesterners, as revealed by the absence of significant differencesin the differential fixation maps (i.e., WC - EA Z-scored group
fixation maps) for those conditions. Post-hoc analyses directlycomparing the fixation maps during face learning in the 2u and 5u
Spotlight conditions with the 8u condition for each cultural groupseparately, confirmed: i) the use of similar eye movement strategies
in Westerners regardless of the Spotlight size aperture and ii) the
presence of a genuine central fixation bias in Easterners uniquelywith a Gaussian aperture of 8u, as well as fixations in the eyeregion in the 2u and 5u conditions (Figure 5 – similar results wereobserved during face recognition).
Analyses performed in the 2u condition for incorrect responses
during face recognition (which roughly included a comparable
number of trials and, therefore, a comparable variance with correct
face recognition responses) show consistent information use fromthe eye region in both groups of observers (Figure 6, top and middle)
and no significant differences in fixation strategies across observers
from different cultures (Zcrit.|4.25|, P,.05) (Figure 6, bottom).
Only trials leading to correct identification (hit and correct
rejections) were taken into account for the face recognition stage inthe 5u and 8u Spotlight conditions. When the eyes and the mouth
regions were simultaneously accessible using extrafoveal vision(Figure 1 - 8u), East Asian observers shifted their fixations towards
their preferred landing location during both face learning andrecognition: the nose region (Figure 4 - 8u Spotlight). To determine
the magnitude of the fixation biases across cultures, for eachobserver we extracted the average of the Z-scored values within theareas showing significant differences in the differential fixation maps
(i.e., average Z-scored fixation duration of the eye and nose regions
per observer). Then we carried out a two-way mixed design
ANOVA on the averaged Z-score values with Face regions as awithin-subject factor and Culture of the observer as a between-subjects

response times (F(2, 54) = 15.63, P,0.001) as Spotlight aperture size
increased. Western Caucasian and East Asian observers were as
accurate (F(1, 54) = 2.18, P = .14) and fast (F(1, 54) = .014, P = .9)
at recognizing faces. The interaction for accuracy (F(2, 54) = .6,
P = .55) and response times (F(2, 54) = .58, P = .56) between the
Culture of the observer and the Spotlight aperture size factors failed
to reach significance.

Number of fixations
We did not observe an interaction between the Culture of theobserver and the Spotlight aperture sizes on the average number offixations deployed during the learning (F(2, 54) = .99, P = .37) andthe recognition stage (F(2, 54) = .13, P = .87) (Figure 3).
During learning, however, Western Caucasian observers usedsignificantly more fixations (M = 28.8) than East Asian observers(M = 27) (F(1, 54) = 6.38, P = .014) and the number of fixations
increased for both group of observers as Spotlight aperture size
increased (F(2, 54) = 9.23, P,.001) (see Figure 1). During
recognition, Western Caucasian observers (M = 18.6) performed
significantly less fixations than East Asian observers (M = 20.6)(F(1, 54) = 4.06, P = .048). The number of fixations was notmodulated by Spotlight aperture size within this condition (F(2,54) = 1.27, P = .28).

Eye movements
The novel result comes from the eye movement data: Figure 4
shows the regions (weighted by the fixation durations) significantly
fixated above chance level with Spotlights of 2u, 5u and 8u during
face learning and recognition respectively (Zcrit.|4.25|, P,.05).
Western Caucasian observers systematically fixated the eyeregion and partially the mouth, regardless of Spotlight size. By
contrast, East Asian observers’ eye movement strategies wereclearly altered by the information available. East Asians fixated the
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Figure 3. Number of average fixations employed by Western Caucasian (WC) and East Asian (EA) observers to adapt to facelearning and recognition across the different Spotlight apertures sizes.
doi:10.1371/journal.pone.0009708.g003

To finely track the appearance of such cultural fixation biases inprocessing faces, we computed the frequency of fixations over time
for the fixations landing on the significant area around the eye andnose regions during face learning and recognition respectively.
Western Caucasian observers showed a general bias towards theeye region over the entire time course during both tasks, withsignificant more fixations over the eyes compared to East Asianobservers in particular time windows. By contrast, East Asianobservers showed a general bias towards the nose region over theentire time course during both tasks, and significant morefixations

factor. This statistical analysis revealed significant interactions for
those factors in both conditions: learning (F(1, 18) = 40.08, P,.001,
gp2 = .69) and recognition (F(1, 18) = 33.56, P,.001, gp2 = .65)
(Figure 7).
Western Caucasian observers had significantly more fixations
landing in the eye region, while East Asian observers had more
fixations on the nose region, as revealed by independent two-tailed
t-tests (P,.001). Cultural fixation biases on facial features werereliable and robust, as highlighted by the large magnitude ofCohen’s d effect size values.

Figure 4. Fixation maps of Western Caucasian (WC) and East Asian (EA) observers for each Spotlight condition during WC and EA
face learning (left) and recognition (right). Fixation biases for WC (red) and EA (blue) observers are highlighted by subtracting WC and the EA Zscored group fixation maps. Areas fixated above chance are delimited by white borders. Note the shift of eye movement fixations in the EA observers
in the 8u Spotlight condition for both tasks.
doi:10.1371/journal.pone.0009708.g004

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recognition (e.g., [19,20,21,22,23,24,25,26]). Consistent with ourprevious observations in natural viewing conditions [2], East Asianobservers changed their eye movement strategy and fixated thenose region in the 8u condition, since information from the eye
and mouth region was extractable extrafoveally from this location.
Regardless of their culture, within their respective Spotlight
conditions (Figure 9) observers did not change their viewing
strategies for faces from different races, which is consistent with
our previous eye movement findings [2]. Additionally, we did not
find differences in terms of recognition performance acrossobservers from different cultures, nor as a function of the race ofthe faces. As might be expected, artificially restricting information
outside central vision impacted on the sensitivity of the face system
and its performance, as the greater ability humans have inrecognizing same- compared to other-race faces was abolished(e.g. [24,39,40,41,42]). In the present experiment we adopted an
ecologically-valid approach by using different pictures of the same
identify to tap into genuine face identification mechanisms(therefore ruling out potential face recognition mechanisms basedon picture matching strategies). This experimental control
represents a taxing constraint for the face system and might
partially account for the present observations, as the vast majorityof studies on the other-race effect have relied on the use ofidentical pictures to assess face recognition performance. It is
worth noting that this observation is not critical for the purpose of
the present study, as the eye movement data showed significant,consistent and robust fixation patterns for face recognition in bothgroups of observers. Restricting information available in extrafoveal vision also dramatically increased the number of fixations
used by the observers to adapt to the present tasks at handcompared to natural viewing conditions (i.e., 5 fixations on
average with natural vision during face recognition [2], compared
to 18 here), with a series of first fixations directed towards locating
regions of interest. It is worth noting, that most of those fixations
were performed to precisely adjust fixations towards the location ofinterest and incidentally increased information sampling aroundthe area. Importantly, those observations do not impact on themain aim of the present study, which was to isolate theinformation used by the observers to solve a face recognition
task. Although both cultures were at chance level in the 2u
condition, observers did not deploy random eye movement
strategies: Westerners and Easterners consistently and significantly
relied on the eyes to perform under those strong task constraints,
even during erroneous face recognition (Figure 6). Western
Caucasian and East Asian observers focused on similar facial
areas (i.e., the eye and mouth regions) with a Spotlight of 5u toachieve above chance face recognition performance. The use ofidentical facial information in Western Caucasian and East Asianobservers with constrained extrafoveal information (2u and 5u)
suggests that the two groups of observers use the same facial
information under natural viewing conditions (i.e., when thestimulus is a whole face) (Figure 4 and 5). Indeed, the Spotlighttechnique identifies precisely the information used by observers
under constrained (i.e., foveated) and unconstrained (i.e., extrafoveated) conditions. Compared to response classification techniques (e.g., [22,23]) the Spotlight technique offers the advantage ofcontrolling and providing active dynamic information use with avery limited number of trials. However, the technique shares acomparable disadvantage with response classification techniques
which relies in altering the information available compared tonatural vision (i.e., full face).
Finally, our observations in the 8u condition report again a stark
contrast between cultures. Observers from different cultures
reached a comparable level of performance by deploying differential

Figure 5. Fixation biases specific to the 8u Spotlight. Top left:differential fixation maps computed by subtracting the fixation map forWestern Caucasian (WC) observers obtained in the 2uSpotlight condition
with the 8u Spotlight. Bottom left: differential fixation maps computed bysubtracting the fixation map for Western Caucasian (WC) observers
obtained in the 5uSpotlight condition with the 8u Spotlight. Top andBottom right: report the same comparisons, in their respective conditions,for the East Asian (EA) observers. Note that significant differences were
only observed for East Asian observers, which deployed a central fixation
bias only in the 8uSpotlight condition and focused on the eye region in
the 2u and 5u constrained Spotlight conditions.
doi:10.1371/journal.pone.0009708.g005

over the nose compared to Western Caucasian observers inparticular time windows (Figure 8).
Regardless of the race of the input faces, fixation strategies
deployed by both groups of observers during learning andrecognition were consistent, as highlighted by the lack of significant
difference in the differential fixation maps (Zcrit.|4.25|, P,.05)(Figure 9).

Face images
We calculated the standard deviation of the face images used in
the present experiment, separately for each race. To identify
region of the faces that would be significantly different across both
populations, we subtracted these values and used a two-tailed pixel
test on the differential fixation maps (Zcrit.|4.25|, P,.05)(Figure 10).
This analysis failed to reveal any significant difference. There
was no region in the faces from different race containing different
information at the pixel level.

Discussion
The gaze-contingent Spotlight technique showed that, independently of culture, observers rely on identical information torecognize faces. The Spotlight results with limited perceptual spans(2u and 5u) provide direct evidence on information use, as withlimited extrafoveal information observers are constrained to actively
focus on the diagnostic information required for face recognition.
Notably, Westerners and Easterners showed similar eye movement
scanpaths in these conditions, with extended fixations towards theeye region and partially the mouth, abolishing previously
established cultural diversity in eye movements [2]. These findings
are consistent with the triangular pattern of fixations reported inmany previous eye movement studies using Western Caucasianobservers [3,4,5,6,7,8,9] and overall they are fully in line withprevious findings pointing to the eyes as a critical feature for face
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Figure 6. Fixation maps of Western Caucasian (WC) and East Asian (EA) observers for the 2u Spotlight condition during facerecognition for incorrect and correct trials. Areas fixated above chance are delimited by white borders. Observers significantly fixated more on
the eye region than the rest of the face regardless their accuracy (about 28 trials per condition); on those maps the darker blue represents 0. Right:
Note the absence of significant differences in the fixation strategies as a function of correct and incorrect trials in both groups of observers. Bottom:
differential fixation biases for Western Caucasian (WC - red) and East Asian (EA - blue) observers are highlighted by subtracting the WC and the EA Zscored group fixation maps for incorrect and correct trials respectively. No significant cultural differences were found for this comparison.
doi:10.1371/journal.pone.0009708.g006

also hypothesize that even if observers from different cultures use
the same facial information, the spatial relations involving the nose
region are more useful to elaborate such representations to East
Asian than Western Caucasian observers. Note, that we intentionally decided to use here the term global 2 and not the term holistic as
widely used in the cultural literature 2 to relate cultural differencesin perception and eye movements by East Asian observers to avoid
confusion with the term holistic used in the framework of faceprocessing. Future studies are necessary to clarify whether and how
such mechanisms are related (see [45]).
We previously suggested an alternative explanation forinterpreting the central fixation strategy employed by EA
observers [2], which relied on a social norm. Direct gazing at
people during social interaction is considered to be rude in East
Asian societies [46] and therefore this cultural force might haveshaped the eye movement strategies used by East Asian observers.
Interestingly, we recently investigated facial expressions of emotion
categorization across cultures [47]. We found that Western
Caucasian and East Asian observers deploy distinct, culturespecific fixation strategies to decode the same basic set of six facial
expressions, plus neutral (using faces from both cultures). While
Western Caucasian observers distribute their fixations evenly
across the face (i.e. mainly to the eyes and mouth), East Asian

fixation patterns. WC observers persistently reproduced the wellestablished triangular pattern of fixation over the eyes and themouth [3,4,5,6,7,8,9]. Westerners tend to engage analytic strategies
for processing the visual environment [16] and consequently their
triangular facial feature-by-feature strategy [2] was not affected by
Spotlight sizes. Uniquely in this 8u condition information from the eyeregion was extractable from the face center and EA observers
shifted their fixation towards the nose region [2] (Figure 4, 5 and 7).
This central location is optimal to integrate information globally [2]and satisfies with the constraints of the cultural perceptual tuning
typical of East Asian observers [16]. Interestingly, such cultural
diversity in facial feature fixation (i.e., WC towards the eye region;
EA towards the nose region) is not restricted to a particular time
period. The analysis of the time course of the frequency of facial
feature fixations demonstrated that this oculo-motor behavior ismore deeply rooted in the entire strategy deployed to process faces(Figure 8), confirming the robustness of this cultural perceptual bias.
It is worth noting that both WC and EA observers have beenshown to perceive faces holistically (e.g., [41,43,44]). Therefore, eyemovement scanpaths cannot rule out the possibility that WCs’feature-by-feature fixations might be used to construct a whole-face
representation, while a similar representation might be elaborated
from central fixations on the nose region by EA observers. We could
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Figure 7. Average Z-score (left y axis) and Cohen’s d effect size values (right y axis) for the eye and nose regions during face learningand recognition. WC = Western Caucasian; EA = East Asian. Error bars report standard errors of the mean. Significant differences between
observers from different cultures for each of the facial features are reported at the bottom of the bars (*** = P,.001).
doi:10.1371/journal.pone.0009708.g007

observers persistently sample the eye region. Beside firstly showing
cultural diversity in eye movements for expression categorization,these data show that East Asian do gaze on the eye region when it
is necessary. Secondly, they demonstrate that the central fixation
used by East Asian observers during face recognition relates to task
specific perceptual mechanisms. In addition, we have recently
shown that the central fixation deployed by East Asian observers
expand on the recognition of non-facial visually homogenous
objects [45], suggesting a more fundamental explanation may berequired to clarify cultural diversity in eye movements. Futurestudies are necessary to clarify the effective use of extrafoveal
information in Easterners, assess the extent to which their eye
movement strategy is regulated by social norms and identify thecultural roots shaping their perceptual strategies in vision.
Behavioral [11,12] and eye movement [14,48] differences acrosspeople from different cultures have been also reported during scene
affordance. Yet, this view has been recently challenged by a series ofeye movement studies pointing out to a similar use of fixation
strategies across observers from different cultures [49,50,51], widely
opening a debate on this question. However, the eye movement
sampling strategies for faces cannot be straightforwardly comparedwith previous studies in scene perception. For instance, the visual
scenes are composed by many objects and cover a larger visual
angle compared with faces (for a detailed discussion on this point,see [2]). But also, there is abundant evidence in the literature
showing that human faces are a homogenous visual category thattaps into cognitive and neural mechanisms that are distinct fromthose engaged in object or scene perception (for a review, see[52,53]). The data reported here show universality (2u and 5u) anddiversity (8u) for eye movements when people from different culture
look at faces, but do not allow to conclude on the generalization of
the fixation strategies that would be deployed for processing othertypes of visual information (i.e., scenes, objects, etc.).
It is also worth noting that the Spotlight technique we used here
precisely identifies the information use under constrained (i.e.,
foveated) and unconstrained (i.e., extra-foveated) conditions. This
Spotlight opens a wide range of possibilities to investigate several
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questions aiming to identify the precise nature of the visual
information selected by eye movements and the visual scanstrategy during face processing in normal and clinical populations(e.g., autistic, schizophrenic, prosopagnosic and agnosic patients),
paving the way to dynamic information integration modeling.
Understanding how humans share basic perceptual mechanisms is
as important as understanding human diversity. Face recognition isroutinely and effortlessly achieved in every culture. Social experienceand cultural factors shape the way humans think about the world[16] and regulate the strategies used to extract information from faces[2,47]. However, these external forces do not modulate theinformation used to solve this critical biological feat: all human beings
rely on the eye region to recognize conspecifics. Human eyes have
evolved with a unique morphology among primate species, with asclera surrounding the highly-contrasted iris [54]. Such a morphological structure maximizes the transmission of gaze [54] andexpression signals [55], which are both critical for social interaction,and eye region information processing has dedicated neural bases(for a review, see [56]). Newborns (e.g., [57]) and neurons devoted to
face processing (e.g., [58]) show also a notable tuning towards theupper part of high-contrasted non face stimuli [59,60] – a visual
contrast mapping into eye region. Monkeys deprived after birth ofexperience with faces also show remarkably preserved facerecognition abilities, compared to other visual object recognition[61], suggesting the existence of an experience-independent ability
for face processing. Despite these studies pointing to a particular
status of the eye region in face recognition, there is no obvious
diagnostic information in this region to allow face recognition, at leastby using a univariate statistical analysis approach with the present face
database (Figure 10). It could be possible that diagnostic informationfrom the eyes are revealed by using a statistical threshold lower thanthe probability threshold criterion routinely used in scientific studies(i.e., P,.05) and by using a multivariate combinatory statisticalinformation coding approach. Future studies are necessary to clarify
the extent to which the evolutionary constraints of nature (whichhave shaped eyes’ morphology to have an high visual contrast andoptimally transmit social signals) or decoding experience in social
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Figure 8. Time course of the frequency of fixations for the facial regions showing a cultural bias during face learning (left) andrecognition (right). Top: the eye region; bottom: the nose region. Note that since the response times varied across trials within- and betweenobservers, the time was normalized for this condition only. Observers from different culture showed a larger number of fixations towards theirrespective preferred regions throughout the entire time course. Significant differences at each time point across the two groups of observers arereported by an *. Shaded areas report the 95% confidence interval (Western Caucasian – red; East Asian – blue).
doi:10.1371/journal.pone.0009708.g008

signals from this region of the face (which is culture dependent) areresponsible for the universal information use from the eyes during
face recognition in humans.

Materials
Stimuli were obtained from the KDEF [62] and AFID [63]databases and consisted of 56 East Asian and 56 Western Caucasian
identities containing equal numbers of males and females. The
images were 3826390 pixels in size, subtending 15.6u degrees ofvisual angle vertically and 15.3u degrees of visual angle horizontally,
which represents the size of a real face (approximately 19 cm inheight). Faces from the original databases were aligned by theauthors on the eye and mouth positions; the images were rescaled tomatch those facial features position and normalized for luminance.
Images were viewed at a distance of 70 cm, reflecting a natural
distance during human interaction [64]. All images were cropped
around the face to remove clothing and were devoid of distinctive
features (scarf, jewelry, facial hair etc.). Faces were presented on a
8006600 pixel grey background displayed on a Dell P1130 190
CRT monitor with a refresh rate of 170 Hz.

Methods
Participants
Thirty Western Caucasian (11 males, 19 females) and thirty East
Asian (11 males, 19 females) young adults (mean age 25.23 years
and 23.9 years respectively) participated in this study. Fifteen East
Asian participants were newly enrolled international students
attending the University of Glasgow, being born in East Asia andarriving in a Western country (Glasgow, UK) for the first time. The
average duration of residence in the UK upon testing was less than 6months within the East Asian group from Glasgow. The 15 other
East Asian participants were students at the Sun Yat-Sen University,
Guangzhou, China. All participants had normal or corrected vision
and were paid £6 or equivalent per hour for their participation. All
participants gave written informed consent and the protocol wasapproved by the ethical committee of the Faculty of Informationand Mathematical Sciences of the University of Glasgow andthe ethical committee of the Department of Psychology of the
University of Sun Yat-Sen.
PLoS ONE | www.plosone.org

Eye tracking
Eye movements were recorded at a sampling rate of 1000 Hz
with the SR Research Desktop-Mount EyeLink 2K eyetracker(with a chin/forehead rest), which has an average gaze position
error of about 0.25u, a spatial resolution of 0.01u and a linear
output over the range of the monitor used. The dominant eye of
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Culture and Face Recognition

Figure 9. Caucasian (WC) and East Asian (EA) group fixation maps for learning and recognition trials. Face areas fixated with above
chance frequency are delimited by white borders. As revealed by the lack of significant differences in the differential fixation maps (3rd and 6th row),
fixation strategies of both cultural groups were consistent as a function of the race of the faces within their respective Spotlight conditions.
doi:10.1371/journal.pone.0009708.g009

each participant was determined by using a variation of the Porta
test [65,66,67]. Observers were asked to extend one arm and alignthe pointer finger of the extended hand vertically with the cornerof the room, with both eyes open. Then, observers were instructed
to close one eye or the other alternately and reported which eye
closure caused the largest alignment change. Only the dominant
eye was tracked, although viewing was binocular. The experiment
was implemented in Matlab (R2006a), using the Psychophysics(PTB-3) and EyeLink Toolbox extensions [68,69]. Calibrations ofeye fixations were conducted at the beginning of the experiment
PLoS ONE | www.plosone.org

using a nine-point fixation procedure as implemented in the
EyeLink API (see EyeLink Manual) and using Matlab software.
Calibrations were then validated with the EyeLink software andrepeated when necessary until the optimal calibration criterion
was reached. At the beginning of each trial, participants were
instructed to fixate a dot at the center of the screen to perform adrift correction. If the drift correction was more than 1u, a new
calibration was launched to insure an optimal recording quality.
The eyetracker, software and setting used in Glasgow and Sun
Yat-Sen universities were identical.
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Culture and Face Recognition

Figure 10. Standard deviation from the mean of the pixel values (gray level: 1-256) of the Western Caucasian (WC - left) and East
Asian (EA - middle) faces used in the experiment. Right: Pixel information biases for WC (red) and EA (blue) faces. Note the absence of any
significant differences in the pixel space across faces for faces from different culture (Zcrit.|4.25|, P,.05), indicating the absence of evident diagnostic
information for observers.
doi:10.1371/journal.pone.0009708.g010

anced across observers. Response buttons were counterbalanced
across participants.
Each trial started with the presentation of a central fixation
cross. Then four crosses were presented, one in the middle of eachof the four quadrants of the computer screen. These crosses
allowed the experimenter to check that the calibration was still
accurate, tolerating a maximum error 0.5 degrees of visual angle.
A final central fixation cross, which served as a drift correction,
was then followed by a face presented in a random location on thecomputer screen. If a fixation failed to land on any of the crosses
during the firsts 2 seconds, a new calibration was started. In thatway, we validated the calibration between each trial. Faces were
presented in a black frame for 10 seconds duration in the learning
phase and until the observer responded in the recognition
phase. To prevent anticipatory strategies, images were randomly
presented on different locations of the computer screen. Each face
was subsequently followed by the 6 fixation crosses which
preceded the next face stimulus.

The Spotlight was either 2u, 5u or 8u degrees of visual angle with azero alpha value at the centre. The alpha value is the value of thealpha channel we used to create the Gaussian apertures combinedwith an image with as background to create the appearance ofpartial transparency. The alpha values increased with distancefrom center of gaze according to a Gaussian function and reached
1 (complete opacity) at the border of the aperture. The image
outside the Spotlight was black and the background gray. The
display contingent to gaze position updating required 1 ms toreceive a sample from the eye-tracker, less than 7 ms to calculate
the texture including the background and the Gaussian mask andbetween 0 and 6 ms to refresh the screen. Therefore, the display
was updated depending on observers’ looking position every 11 ms
on average (between 8 and 14 ms), eliminating any impression offlickering for the observers (see also Supporting Movie S1).
In the 2u and 5u conditions, the Spotlight apertures covered an
entire eye, but the eyes and the mouth were not visible when
fixating the nose (Figure 1 and see also Supporting Movie S1). The
8u condition was the closest to natural viewing conditions;information from both eyes and the mouth was simultaneously
available when fixating the nose.

Data analyses
We implemented saccade detection in our Matlab routines
analyzing eye movement, by using the same filter parameters as
the EyeLink software: saccade velocity threshold = 30u/sec;
saccade acceleration threshold = 4000u/sec. To detect a saccade,for each data sample, the parser thus computes velocity andacceleration and compares these to the velocity and accelerationthresholds. Sometimes, a large saccade is followed by a small
corrective saccade or vice versa. As a result, two or more
temporally (,20 ms) and spatially (,.30u) contiguous saccades
could be merged. Additionally, a blink is defined as a period ofsaccade detector activity with the pupil data missing for three ormore samples in a sequence. A fixation event is defined as any
period that is not a blink or saccade.
Fixation distribution maps were extracted individually forWestern Caucasian and East Asian observers and face race, forthe learning and recognition tasks separately. The data from East
Asian observers from China and from those newly arrived in
Glasgow were analyzed separately. A two-tailed Pixel test (Zcrit|4.25|; p,.05 – see below for statistical details) showed nodifferences across both groups of East Asian observers (seeSupporting Figure S1). Therefore the data from both groups ofEast Asian observers were collapsed together. The fixation maps
were computed by summing, across all (correct) trials, the fixation
location coordinates (x, y) across time. This procedure directly

Procedure
Ten observers from each cultural group were randomly
assigned to one of the three Spotlight conditions, with Gaussian
apertures of 2u, 5u or 8u degrees. To ensure that observers would
deploy a reliable strategy with such strong visual constraints, they
performed the entire experiment with the same Spotlight aperturesize. Participants started with a training session in order tofamiliarize them with the gaze contingent display. Then they were
informed that they would be presented with a series of faces tolearn and subsequently recognize. They were also informed thatthey would be given two face recognition blocks per race. In eachblock, observers were instructed to learn 14 face identities
displaying randomly either neutral, happy or disgust expressions(7 females). After a 30 second pause, a series of 28 faces (14 faces
from the learning phase – 14 new faces; 7 females) were presented
and observers were instructed to indicate as quickly and as
accurately as possible whether each face was familiar or not bypressing keys on the keyboard with the index of their left and righthand. Response times and accuracy were collected and analyzed
for the purpose of the present experiment. Faces from each
cultural group were presented in separate blocks, with the order ofpresentation for same- and other-race blocks being counterbalPLoS ONE | www.plosone.org

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Culture and Face Recognition

weights the importance of a fixation as a function of its duration,
thereby representing the time spent fixating a particular location.
Since more than one pixel is processed during a fixation, wesmoothed the resulting fixation distributions with a Gaussian
kernel with a sigma of 10 pixels. Then, the fixation maps of all theobservers belonging to the same cultural group were summed
together separately for each face condition, resulting in group
fixation maps.
We then Z-scored the resulting group fixation maps by
assuming identical Western Caucasian and East Asian eye
movement distributions for a particular face race as the null
hypothesis. Consequently, we pooled the fixation distributions ofobservers for both groups and used the mean and the standard
deviation for Western Caucasian and East Asian faces toseparately normalize the data. To clearly reveal the difference offixation patterns across observers of different cultures, we
subtracted the group fixation maps of the East Asian observers
from the group Western Caucasian and we Z-scored the resulting
distribution. To establish significance, we used a robust statistical
approach correcting for multiple comparisons in the fixation map
space, by applying a one-tailed Pixel test [70] (Zcrit.4.64; p,.05) for
the group fixation maps and a two-tailed Pixel test (Zcrit |4.25|;
p,.05) on the differential fixation maps. Finally, for each condition
we extracted the average Z-score values for each observer
individually, within each region of interest showing significancein the differential fixation maps. Cohen’s d effect sizes [71] and partial
eta squares were calculated from a two-way mixed design
ANOVAs on the average Z-scores with the Region of the face
and the Culture of the observer as factors carried out for thelearning and recognition conditions separately.
To isolate the time course of fixations landing in regions
showing a cultural bias, we computed the frequency of fixations
over time during face learning and recognition. The frequency was
extracted at each time point sample and was normalized by thearea covered by the regions of interest. The regions of interest
were defined by selecting all the pixels falling within areas showing
significant differences across cultures (i.e., nearby the eye region
for WC observers; nearby the nose region for EA observers – see
Figure 4). Given the rather heterogeneous, asymmetrical nature of
the distributions of frequency of fixations over time, we also
carried out percentile bootstrap analyses. We sampled observers
with replacement, computing the mean frequency across participants independently for each condition. This process was
repeated 5000 times, leading to a distribution of bootstrapped
estimates of the mean frequency for each group of observers,
averaged across subjects. Then the 95% percent confidence
interval was computed (alpha = 0.05). Finally, the difference
between the two sample means was considered significant if the
95% confidence interval did not include zero. Note that thisbootstrap technique, relying on an estimation of H1, tends to havemore power than other robust methods like permutation tests andrelated bootstrap methods that evaluate the null hypothesis H0.

Finally, to identify whether eye movement strategies weremodulated by the race of the faces, we computed a differential
fixation map, by subtracting the eye movement patterns forWestern Caucasian and East Asian faces in both groups ofobservers. Significance was established by using a two-tailed Pixel
test (Zcrit |4.25|; p,.05).

Image analyses
In order to assess for the presence of obvious facial diagnostic
information that would be inherently present in faces fromdifferent race, we carried out a statistical analysis in pixel space ofthe faces images we used. We averaged the grey level values(1-256) of all Western Caucasian and East Asian faces separately
and calculated the average and standard deviation of the images.
The standard deviation from the mean would represent the
information available to discriminate across face exemplars, as thisformally contains the information (pixels) that differs acrossexemplars (the average being the common information). Thus,
we calculated a differential map across faces from different race,by subtracting the standard deviation of Western Caucasian face
images from the standard deviation of East Asian face images. To
establish significance, we used a two-tailed Pixel test (Zcrit |4.25|;
p,.05).

Supporting Information
Figure S1 Fixation maps for the EA participants tested in
Glasgow and those tested in China with the different Spotlight
apertures conditions. No significant difference was found in theeye movement strategies deployed by these two groups of East
Asian observers, so the data were collapsed together. Note, thatthese data also show that short term experience in a Westerncountry does not modulate eye movements for faces in Easterners.
Found at: doi:10.1371/journal.pone.0009708.s001 (5.39 MB TIF)
Movie S1 QuickTimeTM movie of the eye movement strategy

deployed by a Western Caucasian observer during the 10 seconds
face learning with a 5u Spotlight aperture size.
Found at: doi:10.1371/journal.pone.0009708.s002 (1.98 MB
MOV)

Acknowledgments
We are grateful to Anne-Sarah Caldara and Lingnan He for theirinvaluable help in acquiring the eye movement data and David J. Kelly
and Helen Rodger for their comments on a previous version of the paper.

Author Contributions
Conceived and designed the experiments: RC SM. Performed theexperiments: XZ SM. Analyzed the data: SM. Contributed reagents/
materials/analysis tools: RC SM. Wrote the paper: RC.

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