Content uploaded by Jelena Ristic
Author content
All content in this area was uploaded by Jelena Ristic on Jan 26, 2024
Content may be subject to copyright.
Social Attention as a General Mechanism? Demonstrating the Influence of
Stimulus Content Factors on Social Attentional Biasing
Effie J. Pereira
1, 2
, Elina Birmingham
3
, and Jelena Ristic
2
1
Department of Psychology, University of Waterloo
2
Department of Psychology, McGill University
3
Faculty of Education, Simon Fraser University
Humans spontaneously attend to faces and eyes. Recent findings, however, suggest that this social attentional
biasing may not be driven by the social value of faces but by general factors, like stimulus content, visual
context, or task settings. Here, we investigated whether the stimulus content factors of globalluminance, fea-
tural configuration, and perceived attractiveness may independently drive social attentional biasing. Six
experiments were run. In each, participants completed a dot-probe task where the presentation of a face, a
house, and two neutral images was followed by the presentation of a response target at one of those locations.
Experiments 1 and 2 assessed social attentional biasing when the face had higher overall global luminance.
Experiments 3 and 4 assessed social attentional biasing when the face (but not the comparison house)
retained the typical canonical configuration of internal features. Experiments 5 and 6 examined social atten-
tional biasing when the face was more attractive than the house. Experiments 1, 3, and 5 measured manual
responses when participants were instructed to maintain fixation. Experiments 2, 4, and 6 measured both
manual and oculomotor responses when no instructions about eye movements were provided. The results
indicated no reliable social attentional biasing in Experiments 1 to 5, however, a reliable saccadic bias toward
the eyes of attractive upright faces was found in Experiment 6. Together, these results show that perceived
facial attractiveness may beanimportant general factorin social attentional biasing.
Public Significance Statement
It is commonly understood that humans attend to faces preferentially. Recent work has challenged the
notion that this effect is attributable to the inherent social value of faces by showing that spontaneous
attending to faces is abolished when nonsocial factors—specifically, content within faces (e.g., lumi-
nance, configuration, attractiveness), contexts within which faces are presented in (e.g., background in-
formation), and task requirements (e.g., method of response)—are systematically controlled. Here, we
show that attending to faces may be biased by the content factor of perceived facial attractiveness and
not other factors like global luminance or featural configuration. This suggests that perceived facial
attractiveness may be a key factor in instantiating social attentional biasing.
Keywords: attentional biasing, attractiveness, faces, social attention, stimulus content
Supplemental materials: https://doi.org/10.1037/xhp0000984.supp
The answer to the question “are faces special”is often an
obvious one. Routine behaviors like looking for a friend in a café
anecdotally support the notion that faces are a special type of
stimulus conveying information about others’gaze, emotions, or
intentions (Bruce & Young, 1986;Darwin, 2013;Willis &
Todorov, 2006). However, the answer to the question “do faces
This article was published Online First March 17, 2022.
Effie J. Pereira https://orcid.org/0000-0002-2494-6592
Jelena Ristic https://orcid.org/0000-0002-6046-9682
All authors were involved in developing the initial study concept and
design. Effie J. Pereira implemented the study and performed data
collection. All authors were involved in analyses, article preparation, and
final approval of the article.
This work was supported by the Canada First Research Excellence Fund
(CFREF) Healthy Brains for Healthy Lives (HBHL) initiative and a Natural
Sciences and Engineering Research Council of Canada (NSERC)
fellowships to Effie J. Pereira, grants from NSERC and the Social Sciences
and Humanities Research Council of Canada (SSHRC) to Elina Birmingham
and Jelena Ristic, and a William Dawson fund to Jelena Ristic. Many thanks
to S. Afara, E. Bossard, C. Larche, C. Li, J. Ryan-Lortie, M. Salim, and K.
Stadel. The authors declare no conflicts of interest. The datasets analyzed for
this study can be found on the Open Science Framework: osf.io/2qey6.
Correspondence concerning this article should be addressed to EffieJ.
Pereira, Department of Psychology, University of Waterloo, PAS Building,
200 University Avenue West, Waterloo, ON N2L 3G1, Canada. Email:
effie.pereira@uwaterloo.ca
289
Journal of Experimental Psychology:
Human Perception and Performance
©2022 American Psychological Association 2022, Vol. 48, No. 4, 289–311
ISSN: 0096-1523 https://doi.org/10.1037/xhp0000984
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
engage perceptual and attentional processes in a unique manner”
is a less obvious one.
Within the perceptual domain, face processing has been domi-
nated by two views that differ on whether faces are processed in a
specialized manner. The domain-specific view postulates that
faces are a unique stimulus that depends on specific visual proc-
essing (Allison et al., 2000;Perrett et al., 1988,1992;Tsao et al.,
2006), engage distributed face-specific brain networks (Bentin et
al., 1996;Gauthier et al., 2000;Haxby et al., 1994;Kanwisher &
Yovel, 2006;Nummenmaa & Calder, 2009;Perrett et al., 1985,
1992;Puce et al., 1998;Yovel et al., 2003), and afford specific be-
havioral advantages (Farah et al., 1998;Frank et al., 2009;Simion
& Giorgio, 2015;Tanaka & Simonyi, 2016;Yin, 1969). In con-
trast, the domain-general view maintains that faces are not unique
but a stimulus category for which humans have gained high per-
ceptual expertise, thus resulting in enhanced processing, behav-
ioral, and neural advantages for this category of stimuli (Eimer,
2018;Gauthier et al., 1999;Gauthier, Skudlarski, et al., 2000;
Gauthier, Tarr, et al., 2000;Tarr & Gauthier, 2000).
Within the attentional domain, spontaneous attentional biasing
toward faces (or social attention) has been less contentious, as
numerous studies have so far demonstrated that faces and their
features, especially eyes, bias attention both covertly (i.e., atten-
tional shifts independent of eye movements; Jonides, 1981) and
overtly (i.e., attentional shifts accompanied by eye movements;
Posner, 1980). Covertly, attentional effects are indexed by manual
performance facilitation for targets that appear following social
(e.g., a face) compared with nonsocial (e.g., a house) cues. Here,
the data show preferential attention to faces across a wide array of
attentional tasks (e.g., dot-probe, Bindemann et al., 2007; go/no-
go, Bindemann et al., 2005; RSVP, Ariga & Arihara, 2018; visual
search, Lavie et al., 2003; change detection, Ro et al., 2001; inat-
tentional blindness, Devue et al., 2009). Overtly, attentional effects
are indexed by examining the number and duration of eye move-
ments made toward faces relative to comparison stimuli. Here as
well, participants preferentially look at faces and facial features,
including eyes, relative to other nonsocial objects (Yarbus, 1967).
This finding has also been replicated across free-viewing naturalis-
tic tasks (Birmingham et al., 2008a,2008b;Cerf et al., 2009;Laid-
law et al., 2012), saccadic choice tasks (Crouzet et al., 2010),
cuing tasks (Theeuwes & Van der Stigchel, 2006), and oculomotor
capture tasks (Devue et al., 2012).
Thus, while prevailing research suggests that faces engage per-
ceptual processes in either a domain-specific or domain-general
manner, past attentional work has been contextualized within the
notion that faces and eyes engage attentional processes in a man-
ner that is theoretically and conceptually consistent with domain-
specificity. However, recent findings have started to cast doubt on
this conclusion by reporting no evidence of social attentional bias-
ing once the face stimuli and the task are controlled for nonsocial
extraneous factors.
In one of the first studies to show this result, Pereira et al. (2020)
used the dot-probe procedure to present participants with images of
a face, house, and neutral cues (i.e., scrambled face and house
images), which were followed by a response target that occurred
equiprobably at one of these possible locations. Importantly, the
authors controlled the stimuli and task for three types of extraneous
factors that are independent of face information, but are known to
play a powerful role in attentional biasing –(a) stimulus content
factors, which are tied to the internal characteristics of the stimuli,
(b) visual context factors, which impact overall perception of stim-
uli, and (c) task settings, which are external to the stimuli but may
still bias performance. To control for stimulus content, the face and
the house image cues were positioned equidistant from fixation,
equated for overall global luminance, configuration of internal fea-
tures (i.e., the spatial arrangement of two eyes and a mouth for the
face mapped on to the spatial arrangement of two windows and a
door for the house), and perceived attractiveness. To control for vis-
ual context, a single image of a face and a house was used, with all
background information removed and all stimuli presented against
a uniform gray screen. To control for task settings, the identical
task was used to measure social attentional biasing in manual and
oculomotor measures, neither cue was spatially or semantically in-
formative about the target, and the response keys and response
types were not confounded with the cue position, target position, or
target type. When the stimuli and task were controlled in this man-
ner, the data surprisingly revealed no evidence of spontaneous
attentional biasing toward faces in manual responses and a numeri-
cally small, but statistically reliable, oculomotor bias toward the
eye region of the face. Perhaps critically, once extraneous factors
were reintroduced by using the stimuli and task structure of a previ-
ously published work (Bindemann et al., 2007), robust attentional
biasing effects toward faces emerged.
Further studies reported similar evidence in support of this con-
clusion. Pereira et al. (2019) examined whether the removal of the
visual context factor of background information was a determining
element in the abolishment of social attentional biasing. Using the
same dot-probe procedure and manual and oculomotor measures,
the data once again indicated no reliable evidence of spontaneous
attentional biasing toward faces or facial features in manual
responses and an infrequent but reliable eye movement bias toward
the eyes of the face. Similarly, Pereira et al. (2022) demonstrated
that the visual context factor of face novelty did not impact manual
responses but affected eye movement biasing toward the eyes of
infrequently presented faces. This work dovetails with findings
showing that visual context factors like self-relevance and valence
(McCrackin et al., 2021;McCrackin & Itier, 2018,2021)andtask
settings like instructions and task demands (Burra et al., 2018;Võ
et al., 2012) can modulate the strength and/or impact the presence
of social attentional biasing. As such, social attentional biasing may
in part be based on the influence of stimulus content, visual context,
or task settings, and not on the intrinsic social value of faces them-
selves, highlighting a critical need for more studies to delineate the
specific impact of these factors on attentional mechanisms.
The Present Study
Here, we examined the role of stimulus content factors in social
attentional biasing. This is a critical question to address because the
removal of stimulus content information, via equating global lumi-
nance, featural configuration, and perceived attractiveness in past
work (Pereira et al., 2020), may have inadvertently also removed
essential visual components that signal social information in faces.
Importantly, each of these visual attributes has also been docu-
mented to engage spatial attention, irrespective of the social value
of stimuli (Cerf et al., 2008;Eastwood et al., 2001;Hedger et al.,
2019;Itier et al., 2006;Rousselet et al., 2014). Although some past
work has controlled for certain extraneous factors, no study to our
290 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
knowledge has equated all factors within the same task. For exam-
ple, Bindemann et al. (2007;Bindemann & Burton, 2008)com-
pared attentional effects for social and nonsocial cues, but they did
not equate these cues for potential luminance differences, featural
configuration, or perceived attractiveness. Sui and Liu (2009) con-
trolled for global luminance but did not account for differences in
featural configuration between their face distractor and target stim-
uli. While controlling for stimulus size and distance, Langton et al.
(2008) did not account for differences in perceived attractiveness
between their face distractors and target object stimuli. Instead, to
index global stimulus differences in perceptual processing for faces,
some investigators opted to control for potential differences in stim-
ulus content across social and nonsocial stimuli by contrasting per-
formance between upright and inverted faces (Frank et al., 2009;
Simion & Giorgio, 2015;Yin, 1969). Although this is a generally
well-accepted and reasonable comparison that can account for some
visual attribute differences (e.g., edge density, local luminance con-
trasts; Maurer et al., 2002;Sekuler et al., 2004), there are other
attributes (e.g., perceived attractiveness) that may survive face
inversion and not be as well controlled for by this common
approach (Leder et al., 2017). Thus, in addition to the control of
corresponding visual context and task factors and the typical control
between upright and inverted stimuli, direct manipulation of the
individual stimulus content factors of global luminance, featural
configuration, and perceived attractiveness are needed to determine
the guiding role that these factors may play in social attention bias-
ing (Bindemann et al., 2005;Laidlaw et al., 2012;Nummenmaa &
Calder, 2009;Olk & Garay-Vado, 2011).
To this aim, we ran six experiments that examined the impact of
specific stimulus content factors—global luminance, featural config-
uration, and perceived attractiveness—on social attentional biasing.
In each experiment, participants completed a dot-probe task in
which the presentation of face, house, and comparison (scrambled
face and house) cue images were followed by the presentation of a
response target at either the prior location of the eyes or mouth of
the face, the top or bottom of the house, or the upper and lower com-
parison cue. While holding visual context and task factors constant,
each experiment assessed the fate of social attentional biasing when
only one stimulus content factor was examined. That is, in Experi-
ments 1 and 2, overall global luminance was higher for the face rela-
tive to the house cue; in Experiments 3 and 4, the face cue displayed
typical configuration of internal features while the comparison house
cue did not; and in Experiments 5 and 6, the face cue was perceived
as more attractive than the house cue. In addition, and paralleling
past work (Pereira et al., 2019,2020,2022), the experiments meas-
ured both manual and oculomotor responses. In Experiments 1, 3,
and 5, we instructed participants to maintain central fixation and
measured their manual responses to the target. In Experiments 2, 4,
and 6, we did not provide participants with any instructions about
eye movements, and in addition to manual responses, we also meas-
ured their natural oculomotor responses during the task.
To understand potential perceptual processing differences
across stimulus content manipulations, we also controlled for other
properties of the task by presenting cue stimuli in both upright and
inverted orientations (Frank et al., 2009;Simion & Giorgio, 2015;
Yin, 1969) and systematically manipulating whether the faces
appeared in the left or right visual field (Kanwisher et al., 1997;
Kanwisher & Yovel, 2006;Puce et al., 1998;Rossion et al., 2003;
Yovel et al., 2003). To assess any potential differences in the time
course of social attentional biasing, presentation time between the
onset of the cue and target varied across short and long intervals.
If a stimulus content factor—global luminance, featural configu-
ration, or perceived attractiveness—played a significant role in
social attentional biasing, we expected to find reliable attentional
effects toward faces and/or eyes when that individual factor was
manipulated. Such a pattern of data would suggest that attentional
biasing for faces may at least partly be driven by general stimulus
properties that broadly impact attentional mechanisms. If, how-
ever, no reliable attentional biasing effects toward faces and/or
eyes are observed across these manipulations, it would suggest
that these individual stimulus content factors likely do not play a
determining role in social attentional effects.
Experiment 1
Experiment 1 examined the role of global facial luminance in
social attentional biasing in manual responses when participants
were instructed to maintain central fixation.
Global luminance, represented by the average intensity or bright-
ness of a stimulus, is a salient attentional cue (Johannes et al., 1995;
Smith, 1998;Turatto & Galfano, 2000). Past work has demonstrated
the impact of luminance information, both across an entire image
and within stimuli, on perceptual and cognitive processing (Bene-
detto et al., 2014;Cherng et al., 2020;Henderson et al., 2008;Wang
et al., 2021), and studies have further demonstrated effects within
the attention domain as well. For example, increased overall lumi-
nance (Posner, 1980;Smith, 1998;Yantis & Hillstrom, 1994)and
heightened luminance contrast differences between the luminance of
a stimuli compared with its background (Badcock et al., 2005;Bell
& Badcock, 2008;Itti & Koch, 2000;Spehar & Owens, 2012)are
known to reliably capture attention. Within faces specifically, local
luminance information from luminance contrast differences in facial
features like eyes (Ando, 2002,2004) and between the eyes and
mouth compared with the rest of the face (Etcoff et al., 2011;Rus-
sell, 2003) is also found to contribute to global luminance and holis-
tic information about the face (Doherty et al., 2015;Lee et al., 2013;
Lewis & Edmonds, 2003). Together, these findings suggest that
global face luminance incorporates relevant information about both
overall and local facial features, which can reliably bias attention.
To examine this question, in Experiment 1, we preserved the typi-
cal luminance profile of the face and house cues (see Figure 1), which
resulted in the face cue containing higher global luminance than the
house cue. All other stimulus content, visual context, and task factors
were controlled between the face and house stimuli. If global lumi-
nance differences between the cues facilitate social attentional biasing,
we expected to find faster responses for targets occurring at the previ-
ous location of the face relative to the house and neutral cues.
Method
Participants
Thirty volunteers (25 women, 5 men, M
age
=20.2years,SD
age
=
1.1 years), with normal or corrected-to-normal vision, participated.
This sample size reflects an a priori power analysis (Ftest family,
ANOVA: repeated measures; G*Power; Faul et al., 2007), which
indicated that data from six to 38 participants were needed to detect
effects ranging from .65–.15, respectively (as estimated from h
p
2
SOCIAL ATTENTION AND GENERAL MECHANISMS 291
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
based on relevant prior studies investigating social attentional bias-
ing; Bindemann & Burton, 2008;Bindemann et al., 2007;Langton
et al., 2008;Ro et al., 2001), with corresponding power values from
.95–.97. We considered this range of effects because estimated
magnitudes of attentional biasing for faces from past research typi-
cally utilize a variety of face stimuli and do not directly overlap
with the manipulations used in the current study. The closest over-
lap comes from Pereira et al. (2020, Experiment 4), wherein a sam-
ple size of 20 participants was sufficient to detect effects of .44 (as
estimated from h
p
2
) and yielded post hoc power of .96.
Informed written consent was obtained from all participants and
they received course credits upon study completion. The study was
conducted in accordance with the Declaration of Helsinki, and all
protocol and procedures were approved by the University research
ethics board.
Apparatus
All stimuli were presented on a 16”CRT monitor at an approxi-
mate viewing distance of 60 cm, with the stimulus presentation
sequence controlled by MATLAB’s Psychophysics toolbox (Brai-
nard, 1997).
Stimuli
Figure 1 illustrates the cue screen and all possible target locations.
All stimuli (cues and targets) were set against a uniform 60% gray
background to control for potential luminance contrast differences
between the cues/target and the background (Badcock et al., 2005;
Bell & Badcock, 2008;Spehar & Owens, 2012). The fixation screen
included a white fixation cross measuring 1° 31° of visual angle,
which was positioned at the center of the screen. The cue screen (1a)
consisted of the fixation cross and gray-scale photographs of (a) a
female face looking straight ahead with a neutral expression and the
hairline removed, (b) a house with no contextual background, and (c)
a neutral image consisting of a fused overlay of the face and house
photographs scrambled using 22-pixel blocks.
1
House cues were
used as a comparison stimuli due to the overlap in visual category
attributes they share with face cues, for example, they are both
exemplars of an overarching basic category, have consistent place-
ment of internal features, and relative familiarity (Filliter et al., 2016;
Summerfield et al., 2006). Neutral cues were included because they
are often beneficial in revealing the magnitude of social attentional
biasing, that is, whether differential facilitation exists for social ver-
sus nonsocial information in relation to a common comparison stimu-
lus (Birmingham & Kingstone, 2009). Each image measured 4.2° 3
6° and was centrally positioned 6.3° away from the fixation cross,
such that the central location of the eyes, mouth, top house, and bot-
tom house were all equidistant from the fixation cross, regardless of
cue orientation or face position manipulation.
To manipulate global luminance, we used luminance-uncorrected
images for the face and house cues. These images were preferred over
computationally manipulated ones to preserve the natural luminance
within the face and house images. In this manner, average gray-scale
luminance, computed using the MATLAB SHINE toolbox (Willen-
bockel et al., 2010) and ranging from 0–1, was numerically higher for
the face than the house cue (Face = .63, House = .58, Neutral = .61),
with similar numerical differences existing between the upper and
lower halves of each cue (Eyes = .63, Mouth = .62, Top House = .58,
Bottom House = .58). Furthermore, when segmenting each cue into 1°
31° blocks, higher average gray scale luminance was found for the
face versus the house cue, t(158) = 4.70, p,.05, d= .74, two-tailed.
In addition, all other stimulus content factors remained equated
between the face and house cue. That is, featural configuration was
matched by ensuring that the face and house cues had a consistent
placement of internal configuration of features, and perceived attrac-
tiveness was matched by using a face and house cue that received
equivalent attractiveness ratings
2
(Face M=2.89,SD =1.68,range=
Figure 1
Cue and Target Screens for Experiment 1
Note. An illustration of (a) the cue screen for Experiment 1, where the face cue contained
greater global luminance than the house cue, and (b) the target screen (square target dis-
played) depicting all six possible target locations. The depicted face image is shown as an
example and was not used in the present study. See the online article for the color version
of this figure.
1
Cue images were obtained from Pereira et al. (2020).
2
Twenty-eight additional naïve participants were presented with 64
different face and house photographs from the Glasgow Unfamiliar Face
Database (Burton et al., 2010). The photographs were presented on a
computer screen, one at a time, and participants were asked to rate each
image on perceived attractiveness using a Likert scale ranging from 1 =
very unattractive to 6 = very attractive. In the online supplemental
materials, we illustrate the range of individual perceived attractiveness
ratings for the face and house images used in the current set of studies.
292 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
1–6; House M= 2.96, SD =.96,range=1–5), which did not differ
reliably, t(27) = .17, p=.87,d
z
= .03, two-tailed, paired.
The target screen (1b) consisted of the fixation cross and a sin-
gle target (yellow circle or square, measuring .3° 3.3° each) posi-
tioned 7.2° away from the fixation cross, ensuring that all target
properties (i.e., size, position, and common uniform background)
were equated and controlled across the experiment.
Thus, aside from a difference in overall luminance between the
face and house cues, all other stimulus content, visual context, and
task parameters (i.e., stimulus size, distance from fixation, back-
ground information, as well as task and response properties)
remained equated.
Design
The dot-probe target discrimination task was a repeated meas-
ures design with five equiprobable factors: Cue orientation
(upright, inverted), Face position (left visual field, right visual
field), Target location (eyes, mouth, top house, bottom house,
upper neutral, lower neutral), Target identity (circle, square), and
Cue-target interval (250, 360, 560, 1,000 ms).
Cue orientation varied between upright and inverted images
(i.e., the face, house, and comparison neutral cues could be pre-
sented either all upright or all inverted). Given the general process-
ing and behavioral preferences for upright faces (Frank et al.,
2009;Simion & Giorgio, 2015;Yin, 1969), this factor was manip-
ulated to examine whether any effects of social attentional biasing
were specific to faces in an upright orientation. Face position var-
ied between the left and right visual fields, with the house image
always placed in the opposite visual field. This factor was manipu-
lated to examine any possible advantageous processing effects of
lateralized social information processing in the right hemisphere
of the brain (Kanwisher et al., 1997;Kanwisher & Yovel, 2006;
Puce et al., 1998;Rossion et al., 2003;Yovel et al., 2003). Target
location varied between the previous spatial location occupied by
the eyes, the mouth, the top of the house, the bottom of the house,
or the center of the upper or lower neutral image. This key manip-
ulation was included to capture any performance differences for
targets occurring at the previous location of the face and its facial
features relative to the comparison stimuli. Target identity varied
between a yellow circle and a yellow square to collect both
response time and response accuracy. Cue-target interval varied
between 250, 360, 560, and 1,000 ms to assess any differences in
the time course of social attentional biasing (Bindemann et al.,
2007;Pereira et al., 2019,2020,2022).
All factor combinations were presented equally often through-
out the task sequence. The cues were spatially uninformative
about the target location and its identity, as each target was
equally likely to occur at any of the possible target locations.
Conditions were intermixed and presented in a randomized
order, so participants had no incentive induced by the task to
attend to any particular cue.
Procedure
At the start of the experiment, participants were instructed to
maintain central fixation. After the initial presentation of the fixa-
tion display for 600 ms, participants were presented with the cue
display for 250 ms. This was followed by the presentation of the
fixation display for 0, 110, 310, or 750 ms (constituting 250-, 360-,
560-, and 1,000-ms cue-target intervals, respectively). Then, a sin-
gle response target was presented at the location previously occu-
pied by the eyes, mouth, top house, bottom house, upper neutral,
or lower neutral image. The target remained visible until response
or until 1,500 ms had elapsed. Participants were instructed to iden-
tify the target quickly and accurately by pressing the ‘b’or ‘h’
keys on the keyboard. Target identity-key response assignment
was counterbalanced between participants.
Participants were informed about the task sequence, that the tar-
get was equally likely to be a circle or a square, that the target
could appear in any of the possible locations, and that there was
no spatial relationship between the cue content, cue orientation,
cue placement, target location, or target identity. The experiment
consisted of 960 trials divided equally across five testing blocks.
Ten practice trials were run at the start. In total, the experiment
took 60 minutes to complete.
Results
First, we examined the data for errors. Trials with response
anticipations (response times [RTs] ,100 ms; .1% of all trials),
timeouts (RTs .1,000 ms; 3.0%), and incorrect key presses
(key press other than ‘b’or ‘h’; .1%) were removed from analy-
ses. Then, accuracy for each trial was calculated based on
whether participants correctly responded to the identity of the
target. Overall, response accuracy was high at 92%. All further
analyses for manual response time were conducted on correct tri-
als only.
Based on previous findings (Pereira et al., 2019,2020,2022),
which repeatedly and convincingly indicated no reliable social
attentional biasing for upright or inverted faces, as well as a lack of
meaningful interactions with this key main effect, we first examined
the data in each experiment using an a priori hypothesis to test for
the presence of an overall social attentional bias. To perform these
analyses, we compared mean correct RTs using one-way repeated
measures ANOVAs across Face, House, and Neutral target loca-
tions for Upright and Inverted cues.
If no evidence of social attentional biasing was found, we fol-
lowed up the absence of this effect with Bayesian analyses to
assess the relative strength of our null findings (i.e., BF
10
, which
provides evidence in favor of the alternative hypothesis; Dienes,
2011;Leppink et al., 2017).
3
To do so, we used a two-tailed Gaus-
sian prior distribution centered around a mean of 17.67 ms and SD
of 7.55 ms, reflecting the magnitude of social attentional biasing
reported in previous literature (Bindemann et al., 2007, Experi-
ments 1a and 1b). While Bayes factor values are best interpreted
on a scale rather than as a cut-off, a BF
10
,.33 is typically taken
as evidence supporting the null and a BF
10
.3.00 as evidence
supporting the alternative hypothesis. If on the other hand signifi-
cant attentional biasing was found, that is, the ANOVA indicated
faster RTs for targets occurring at the location of the Face relative
to targets occurring at the House, we then examined the contribu-
tion of all factors by running a repeated measures ANOVA with
Cue orientation (upright, inverted), Face position (left visual field,
right visual field), Target location (eyes, mouth, top house, bottom
3
Bayes calculator: http://www.lifesci.sussex.ac.uk/home/Zoltan_Dienes/
inference/bayes_factor.swf.
SOCIAL ATTENTION AND GENERAL MECHANISMS 293
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
house, upper neutral, lower neutral), and Cue-target interval (250,
360, 560, 1,000 ms).
4
Across manual RT analyses, Greenhouse–Geiser corrections
were applied for any violations of sphericity. Paired two-tailed t-
tests were used for any post hoc comparisons, which were corrected
for multiple comparisons using the Holm-Bonferroni procedure
(Holm, 1979) and are shown below as corresponding adjusted
pvalues (a
FW
=.05;Ludbrook, 2000).
As shown in Figure 2, which plots mean correct RTs as a
function of target position for Upright (2a) and Inverted (2b)
cues, no overall social attentional biasing effects were found.
Specifically, we found a main effect of Target location for both
Upright (Mauchly’s test of sphericity, v
2
(2) = 12.14, p,.01),
F(1.48,42.91) = 157.34, p,.01, h
p
2
= .84, and Inverted cues,
F(2, 58) = 83.32, p,.01, h
p
2
= .74, reflecting overall slower
responses to targets occurring at the location of the Neutral cues
relative to targets occurring at the Face or House cues (Upright
ts.12.67, ps ,.01, d
z
s.2.31; Inverted ts.9.99, ps ,.01,
d
z
s.1.82). No significant differences were found for targets
occurring at the previous location of the Face versus House
(Upright, 571 ms versus 570 ms, respectively; t[29] = .82, p=
.42, d
z
= .15; Inverted, 571 ms versus 569 ms, respectively;
t[29] = .93, p=.36,d
z
=.17).
Bayesian analyses supported these results, returning a BF
10
value of .01 for the Face versus House contrast for Upright cues
and a BF
10
of .02 for Inverted cues.
Discussion
Experiment 1 examined whether social attention biasing
occurred when overall luminance within the face cue was higher,
thus preserving its natural appearance, than overall luminance
within the comparison house cue. We found no evidence for social
attentional biasing in manual responses across both null hypothesis
significance testing and Bayesian analyses. Therefore, when eye
movements are restricted, increased global luminance of a face
does not appear to drive preferential social attentional biasing
when other stimulus content and visual context factors are held
constant.
Next, we examined whether this finding held when no instruc-
tions were provided to participants regarding maintaining central
fixation.
Experiment 2
Experiment 2 examined the role of global facial luminance in
social attentional biasing in both manual and oculomotor
responses when no instruction about eye movements was given.
That is, in addition to measuring manual responses, Experiment 2
also assessed participants natural oculomotor behavior during the
task using an eye tracker.
If global luminance differences between the cues facilitated
social attentional biasing toward the face when eye movements
were not restricted, we expected to find faster responses for targets
occurring at the previous location of the face relative to the house
and neutral cues and greater proportion of eye movements directed
toward the face and/or eyes.
Method
Thirty new volunteers (24 women, 6 men, M
age
= 20.9 years,
SD
age
= 1.6 years) participated. All apparatus, stimuli, design, and
procedures were identical to Experiment 1, except: (a) eye move-
ments were tracked using a remote EyeLink 1000 eye tracker (SR
Research; Mississauga, ON) recording with a sampling rate of 500
Hz and a spatial resolution of .05°. Although viewing was binocu-
lar, only the right eye was tracked, with saccades defined as eye
movements with an amplitude of at least .5°, an acceleration
threshold of 9,500°/s
2
, and a velocity threshold of 30°/s; (b) partic-
ipants were not given any instructions about restricting or initiat-
ing eye movements, which allowed us to examine their natural
oculomotor behavior during the task; and (c) a nine-point calibra-
tion procedure was performed at the start of the experiment to
ensure high eye tracking accuracy, with spatial error rechecked
before every trial using a single-point central calibration dot. Av-
erage spatial error was no greater than .5°, with maximum error
not exceeding 1°. With the addition of eye tracking, the experi-
ment took 90 minutes in total to complete.
Results
Manual RT
As with Experiment 1, we first examined the data for errors and
accuracy. Anticipations (.03%), timeouts (2.0%), and incorrect
key presses (.03%) were removed from analyses. Overall response
accuracy was 96%. Manual RTs were assessed as in Experiment 1
using the same analytic criteria.
Like Experiment 1, manual data for Experiment 2, illustrated in
Figure 3, showed slower overall RTs for targets occurring at the
location of the Neutral cues relative to the targets occurring at the
Face or House cues for both Upright, F(2, 58) = 78.60, p,.01,
h
p
2
= .73; ts.9.47, ps,.01, d
z
s.1.73, and Inverted conditions,
F(2, 58) = 91.49, p,.01, h
p
2
= .76; ts.10.10, ps,.01, d
z
s.
1.84. Once again, no significant differences were found for targets
occurring at the previous location of the Face versus House
(Upright, 565 ms versus 572 ms, respectively; t(29) = 1.49, p=
.15, d
z
= .27; Inverted, 567 ms versus 565 ms, respectively;
t(29) = .87, p= .39, d
z
= .16). BF
10
for the Face versus House con-
trast for Upright cues once again supported these results with a
value of .61 (BF
10
= .02 for Inverted).
Eye Movement Data
Because no instructions about eye movements were given, ocu-
lomotor behavior was not response relevant and thus we only
examined eye movements occurring during the cue period (i.e.,
250 ms). Following from previous work indicating a small but reli-
able oculomotor preference for faces and eyes (Pereira et al.,
2019,2020,2022), we analyzed the proportion of first saccades
that were launched from the central fixation cross in the direction
of one of the cues during the 250 ms cue time (i.e., saccades did
not have to terminate on the cues, but be launched in the direction
of the cue). To perform this analysis, as illustrated in Figure 4,we
4
For completeness, in the online supplemental materials, we present all
omnibus analyses for mean correct RTs, which expectedly yielded
corresponding effects.
294 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
first defined regions of interest (ROIs) around the cues, which
encompassed 30° radial windows for each of the Eyes, Mouth,
Top house, and Bottom house cues, and 70° radial windows for
each of the Upper neutral and Lower neutral cues, spanning an av-
erage of 43° radial window for all ROIs. Then, for each partici-
pant, we examined the trials that contained a first saccade made
from the fixation cross to one of the ROIs during this cue period.
Proportion of saccades toward each ROI for each participant was
calculated by tallying the number of trials that contained first sac-
cades toward each ROI divided by the number of trials when first
saccades occurred during the cue period. Furthermore, to account
for size differences in the radial windows between the Eyes,
Mouth, Top house, and Bottom house ROIs (30° windows for
each) versus the Upper neutral and Lower neutral ROIs (70° win-
dows for each), as per prior work (Pereira et al., 2020), proportion
of saccades toward the Upper and Lower neutral ROIs were cor-
rected for the window size to ensure that these regions did not cap-
ture a greater proportion of saccades simply due to their larger
radial window (i.e., proportion of saccades were scaled by 3/7th).
On average, participants saccaded away from the fixation cross
during the cue presentation period rarely, on only 6% of trials
(SD = 9%, range = 1–48%). On these trials, saccades were
launched toward one of the ROIs 97% of the time.
5
Mean saccadic
RT, defined as the time between the onset of the cue and the start
of the saccade, was 150 ms (SD = 54 ms).
Like manual RT analyses, proportion of saccades were exam-
ined for the presence of overall social attentional biasing across
Face, House, and Neutral ROIs for Upright and Inverted cues.
Data were followed by Bayesian analyses if null effects were
found or omnibus repeated measures ANOVAs with Cue orienta-
tion (upright, inverted), Face position (left visual field, right visual
field), and ROI (eyes, mouth, top house, bottom house, upper neu-
tral, lower neutral) if social attentional biasing was present. Green-
house–Geiser corrections were applied for sphericity violations,
paired two-tailed t-tests were used for post hoc comparisons, and
multiple comparisons were corrected using the Holm-Bonferroni
procedure with corresponding adjusted pvalues shown below.
Mean overall proportion of saccades is illustrated in Figure 5 as
a function of ROI. The ANOVA indicated main effects of ROI for
both Upright, F(2, 58) = 7.65, p,.01, h
p
2
= .21, and Inverted
cues, F(2, 58) = 6.97, p,.01, h
p
2
= .19. For Upright cues, a
greater proportion of saccades were directed toward the Face cue
relative to both House and Neutral cues (.17 versus .10 versus .07,
respectively; ts.2.51, ps,.04, d
z
s..46; all other p= .12, d
z
=
.29). For Inverted cues, an overall higher proportion of saccades
were directed to both Face and House cues relative to Neutral cues
(.17 versus .18 versus .07, respectively; ts.3.18, ps,.01, d
z
s.
.58; all other p= .82, d
z
= .04).
Because the data indicated an overall oculomotor bias toward
faces, we next examined how proportion of breakaway saccades var-
ied as a function of Cue orientation (upright, inverted), Face position
(left visual field, right visual field), and ROI (eyes, mouth, top house,
bottom house, upper neutral, lower neutral). Figure 6 illustrates the
mean proportion of saccades as a function of all ROIs.
We found a main effect of Cue orientation,F(1, 29) = 4.80, p=
.04, h
p
2
= .14, reflecting an overall greater proportion of saccades
when cues were Inverted compared with Upright. There was also a
main effect of ROI (Mauchly’s test of sphericity, v
2
(14) = 43.31,
p,.01), F(3.06,88.81) = 6.86, p,.01, h
p
2
= .19, with an overall
lower proportion of saccades directed toward the Lower Neutral cue
than the Eyes, Mouth, Top House, and Bottom House regions (ts.
3.34, ps,.03, d
z
s..61). No overall significant differences emerged
in the proportion of saccades directed toward the Eyes, Mouth, Top
House, and Bottom House cues (ts,2.80, ps..09, d
z
s,.51).
Two interactions were significant. The first was between ROI
and Cue orientation (Mauchly’s test of sphericity, v
2
(14) = 76.50,
Figure 2
Experiment 1 Manual RT Results
Note. Mean correct RTs as a function of overall Target position for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs.
5
In the online supplemental materials, Tables S1,S2, and S3 (for
Experiments 2, 4, and 6, respectively) show the number of trials containing
saccades during the cue period for each participant, in total, and as a
function of ROI (eyes, mouth, top house, bottom house, upper neutral,
lower neutral).
SOCIAL ATTENTION AND GENERAL MECHANISMS 295
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
p,.01), F(2.54,73.81) = 3.27, p= .03, h
p
2
= .11 A greater propor-
tion of saccades were directed toward the Eyes versus the Lower
Neutral cue for both Upright, t(29) = 3.47, p= .03, d
z
= .63 (all
other ps..09, d
z
s,.54), and Inverted conditions, t(29) = 3.95,
p= .01, d
z
= .72. Further, when the cues were Inverted, a greater
proportion of saccades were also directed toward the Top House
cue compared with the Bottom House, Upper Neutral, and Lower
Neutral cues (ts.3.11, ps,.05, d
z
s..57; all other ps..14,
d
z
s,.49). However, no differences were found in proportion of
saccades toward the Eyes, Mouth, Top House, and Bottom House
(ts,2.38, ps..22, d
z
s,.43).
The second interaction was between ROI and Face position
(Mauchly’s test of sphericity, v
2
(14) = 77.72, p,.01), F(2.45,71.04) =
3.62, p=.02,h
p
2
= .11, which revealed that when the face was pre-
sented in the left visual field, a greater proportion of saccades were
launched toward the Eyes versus the Lower Neutral cue, t(29) =
3.37, p=.03,d
z
= .62 (all other ps..06, d
z
s,.58). When the face
was presented in the right visual field, a lower proportion of sac-
cades were launched toward the Lower Neutral cue compared with
the Eyes, Top House, and Bottom House cues (ts.3.19, ps,.05,
d
z
s,.58; all other ps..09, d
z
s,.52). Similar to the previous
interaction, no differences were found in proportion of saccades to-
ward the Eyes, Mouth, Top House, and Bottom House cues (ts,
2.69, ps..13, d
z
s,.49). No other effects or interactions were sig-
nificant (Fs,1.93, ps..14, h
p
2
,.06).
Discussion
Experiment 2 examined social attention biasing when overall
luminance within the face cue was higher than the comparison house
cue and when participants were not instructed to maintain central
fixation. Manual data replicated Experiment 1, with no evidence for
social attentional biasing. Oculomotor data similarly showed that
participants rarely disengaged from central fixation to look at the
cues during the cue presentation time (i.e., on only 6% of all trials);
however, when they did, they looked more frequently toward the
face. As revealed by the comparison of upright and inverted cues,
this effect was not specific to differences across the face and house
cues and was also not specific to upright faces. That is, while the
overall a priori analysis indicated greater overall number of oculo-
motor breakaways toward the face relative to the house cue, the fol-
low-up ANOVA indicated that this effect was not specific to upright
faces. As such, this effect may have been driven by an overall larger
number of breakaway saccades for the eye region relative to the neu-
tral cue when the face was shown in the left visual field and likely
reflects overall difference in low level visual features in the stimuli
rather than any specific bias toward the facial region (Turatto & Gal-
fano, 2000). Therefore, when participants’natural oculomotor
behavior is preserved, increased global luminance within the face
does not lead to typical reinstantiation of social attentional biasing
Figure 4
Regions of Interest (ROI)
Note. ROIs were defined by a radial window, including the area of inter-
est; red = eyes, yellow = mouth, dark blue = top house, light blue = bot-
tom house, dark gray = upper neutral, light gray = lower neutral. See the
online article for the color version of this figure.
Figure 3
Experiment 2 Manual RT Results
Note. Mean correct RTs as a function of overall Target position for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs.
296 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
when other stimulus content and visual context factors are held con-
stant; however, it may lead to general oculomotor biasing toward
more overall luminant region of the display.
Next, we examined whether the presence of social attention
biasing may depend on similar internal configuration of the com-
parison stimulus.
Experiment 3
Experiment 3 examined the role of internal canonical organiza-
tion of faces in social attentional biasing in manual responses
when participants are instructed to maintain central fixation.
Featural configuration represents the spatial relationship
between the two eyes on top and one mouth centrally located on
the bottom of faces. This spatial arrangement of features can affect
facial processing and social attention at an early stage (Dakin &
Watt, 2009;Goffaux & Dakin, 2010;Maurer et al., 2002;Pachai
et al., 2013). Studies have demonstrated that face perception
depends on the canonical representation of internal face features,
such that upright faces are easier to perceive and identify than
individual facial features or inverted faces (Frank et al., 2009;
Hochberg & Galper, 1967;Simion & Giorgio, 2015;Yin, 1969),
with additional studies demonstrating preferential oculomotor
biasing toward faces with more consistent internal configuration
Figure 6
Experiment 2 Oculomotor Results
Note. Mean proportion of trials containing a breakaway saccade during the cue presentation period that was
directed towards regions of interest (ROIs) for (a) Upright and (b) Inverted cues. Error bars represent 95% CIs.
Summation of values across both Upright and Inverted cues reveals the total proportion of trials with break-
away saccades directed towards ROI regions.
Figure 5
Experiment 2 Oculomotor Results
Note. Mean proportion of trials containing a breakaway saccade during the cue presenta-
tion period that was directed towards a region of interest (ROI) for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs. Summation of values across both Upright and
Inverted cues reveals the total proportion of trials with breakaway saccades directed
towards ROI regions (i.e., 0.76 proportion of trials directed to ROI regions [0.34 for
Upright, 0.42 for Inverted] versus 0.24 to non-ROI regions).
SOCIAL ATTENTION AND GENERAL MECHANISMS 297
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
(Johnson et al., 1991;Mondloch et al., 1999). Often, houses are
used as comparison stimuli to faces as they display similar canoni-
cal configural structure but lack social content (Bruce & Young,
1986;Farah et al., 1998;Kanwisher & Yovel, 2006;O’Craven et
al., 1999;Tanaka & Farah, 1993). However, keeping the internal
configuration between face and houses on par in past work (Pe-
reira et al., 2019,2020,2022) may have resulted in comparison
house cues appearing too face-like, thus biasing attentional results
toward null effects.
To examine the role of internal configuration in social attention
biasing, in Experiment 3, we used a house cue that had a different
configuration of internal features relative to the face cue. As illus-
trated in Figure 7, the house cue contained one door that was
placed off to the side and only one central window. As before, the
images were equated on all other factors, that is, size, distance
from fixation, average global luminance, perceived attractiveness,
uniform background, and task and response settings. Therefore, if
unique featural configuration of faces is a key factor in social
attentional biasing, we expected to find typical social attentional
biasing effects indicating faster responses for targets occurring at
the previous location of the face and eyes relative to the compari-
son house cue.
Method
Thirty new volunteers participated (24 women, 6 men, M
age
=
20.3 years, SD
age
= 1.3 years). None had participated in any previ-
ous experiments.
All parameters were identical to Experiment 1 except for the
cue stimuli, which are illustrated in Figure 7. To manipulate fea-
tural configuration, the placement of the windows and door of the
house cue did not match the internal spatial arrangement of the
eyes and mouth of the face cue. All other stimulus content factors
remained equated. That is, global luminance was equated across the
face and house cues using the MATLAB SHINE toolbox (Face =
.60, House = .61, Neutral = .60; split-half luminance, Eyes = .60,
Mouth = .60, Top House = .60, Bottom House = .62; 1° 31° lumi-
nance segmented block analysis for face versus house, t[158] =
1.54, p=.13,d= .24, two-tailed), and perceived attractiveness was
matched by utilizing face and house images that received equivalent
attractiveness ratings (see Footnote 1; Face M=2.93,SD =.77,
range = 1–4; House M= 3.11, SD = 1.47, range = 1–6; t[27] = .57,
p=.57,d
z
= .11, two-tailed, paired).
Results
Anticipations (.3%), timeouts (3.6%), and incorrect key presses
(.3%) were removed from analyses. Overall response accuracy
was 92%.
As illustrated in Figure 8, which shows mean correct RTs for
Upright (8a) and Inverted (8b) cues, there was once again no over-
all response advantage for targets occurring at the location of the
face relative to the house cue. That is, the ANOVA showed overall
slower RTs for targets occurring at the location of the Neutral cues
relative to the targets occurring at the Face or House cues for
Upright (Mauchly's test of sphericity, v
2
(2) = 9.46, p= .01),
F(1.55,45.08) = 75.82, p,.01, h
p
2
= .72; ts.9.02, ps,.01,
d
z
s.1.65 and Inverted cues, F(2, 58) = 84.48, p,.01, h
p
2
= .74;
ts.10.07, ps,.01, d
z
s.1.84, with no significant differences
for targets occurring at the previous location of the Face relative to
the House (Upright, 583 ms versus 584 ms, respectively; t(29) =
.28, p= .78, d
z
= .05; Inverted, 584 ms versus 581 ms, respec-
tively; t(29) = 1.34, p= .19, d
z
= .24). Supporting this result, the
Bayes analysis for Upright Face versus House contrasts yielded a
BF
10
of .03 (BF
10
= .02 for Inverted).
Discussion
Experiment 3 examined whether equating the face and house
stimuli on internal configuration of features impacted social atten-
tion bias. We hypothesized that if this variable was one of the driv-
ing factors of social attentional biasing, once the factor was
reinstated, there should be reliable attentional effects toward faces.
The data did not support this hypothesis, as we found no evidence
of spontaneous social attentional biasing in manual responses
across both null hypothesis significance testing and Bayesian anal-
yses when participants were instructed to maintain central fixation.
The next experiment examined whether this finding was consist-
ent when eye movements were not restricted and participants’nat-
ural oculomotor behavior was preserved.
Experiment 4
Experiment 4 examined whether social attentional biasing, as
assessed via manual and oculomotor responses, depended on the
internal canonical organization of faces when participants were
provided with no instruction about eye movements.
If featural configuration of faces facilitates social attentional
biasing, we expected to find faster responses for targets occurring
at the previous location of the face and eyes relative to the compar-
ison house cue, along with greater proportion of eye movements
directed toward the face and eyes.
Method
Thirty additional volunteers (25 women, 5 men, M
age
= 20.4
years, SD
age
= 1.5 years) participated. The task and the stimuli
were identical to Experiment 3, whereas the eye tracking parame-
ters were identical to Experiment 2.
Figure 7
Cue Screen for Experiment 3
Note. An illustration of the cue screen for Experiment 3, where the in-
ternal featural configuration of the face cue did not match the internal fea-
tural configuration of the house cue.
298 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Results
Manual RT
Anticipations (.02%), timeouts (1.2%), and incorrect key
presses (.01%) were removed from analyses. Overall response ac-
curacy was 96%.
Once again, and as depicted in Figure 9, no reliable social atten-
tional biases were found. Significant main effects for Upright, F(2,
58) = 63.57, p,.01, h
p
2
= .69, and Inverted cues, F(2, 58) =
72.81, p,.01, h
p
2
= .72, indicated overall slower RTs for targets
occurring at the previous location of the Neutral cues relative to
the previous location of the Face and House cues (Upright, ts.
9.89, ps,.01, d
z
s.1.81; Inverted, ts.10.39, ps,.01, d
z
s.
1.90), with no significant differences for targets occurring at the
previous location of the Face relative to the House (Upright, 557
ms versus 563 ms, respectively; t(29) = 1.26, p= .22, d
z
= .23;
Inverted, 562 ms versus 564 ms, respectively; t(29) = .40, p= .70,
d
z
= .07). BF
10
for this analysis was .48 for Upright cues (BF
10
=
.08 for Inverted).
Eye Movement Data
Eye movements were analyzed as in Experiment 2. As before,
during the cue period, saccadic breakaways from the central fixa-
tion cross were rare, occurring on 9% of trials (SD = 16%, range =
1–67%). Of these trials, saccades were launched toward an ROI
96% of the time. Mean saccadic RT was 155 ms (SD = 52 ms).
Mean proportion of first saccades away from the fixation cross is
illustrated in Figure 10 as a function of ROI for Upright (10a) and
Inverted (10b) cues.
A main effect of ROI was significant for Upright (Mauchly’s
test of sphericity, v
2
(2) = 7.93, p= .02), F(1.60,46.52) = 9.84, p,
.01, h
p
2
= .25, and Inverted cues, F(1.88,54.56) = 5.35, p= .01,
h
p
2
= .16, denoting a greater proportion of saccades directed toward
the Face relative to both House and Neutral (Upright, .19 versus
.08 versus .08, respectively; ts .3.04, ps ,.01, d
z
s..55; all
other p= .76, d
z
= .06; Inverted, .19 versus .10 versus .08, respec-
tively; ts .2.48, ps ,.04, d
z
s..45; all other p= .58, d
z
= .10).
Because the data indicated increased frequency of eye move-
ments toward the Face region, we examined proportion of break-
away saccades as a function of Cue orientation (upright, inverted),
Face position (left visual field, right visual field), and ROI (eyes,
mouth, top house, bottom house, upper neutral, lower neutral).
These data are illustrated in Figure 11.
The analysis indicated a main effect of ROI,F(5, 145) = 5.67,
p,.01, h
p
2
= .16, showing an overall greater proportion of sac-
cades directed toward the Eyes compared with the Top House,
Bottom House, Upper Neutral, and Lower Neutral cues (ts.3.18,
ps,.04, d
z
s..58; all other ps..23, d
z
s,.45).
We also found a reliable interaction between ROI and Face
position (Mauchly’s test of sphericity, v
2
(14) = 29.05, p= .01),
F(3.49,101.11) = 2.74, p= .04, h
p
2
= .09. When the face was pre-
sented in the left visual field, a greater proportion of saccades were
launched toward the Eyes compared with the Top House, Bottom
House, Upper Neutral, and Lower Neutral cues (ts.3.65, ps,
.01, d
z
s..67). Furthermore, there were also a greater proportion
of saccades directed toward the Mouth compared with the Top
House, Bottom House, and Lower Neutral cues (ts.3.13, ps,
.04, d
z
s..57; all other ps..13, d
z
s,.46). No such relationship
was found when the face was presented in the right visual field (all
ps..99, d
z
s,.35). However, this oculomotor biasing effect did
not appear to be specific to Upright faces, as no interactions
involving Cue Orientation were found, ROI 3Cue Orientation;
F(5, 145) = 1.77, p= .12, h
p
2
= .06; ROI 3Face Position 3Cue
Orientation,F(5, 145) = .85, p= .52, h
p
2
= .03. No other effects
reached significance (Fs,.49, ps..49, h
p
2
,.02).
Discussion
In Experiment 4, we examined whether social attentional biasing
would occur when the internal configuration of features between
the face and house stimuli were not equated and eye movements
were not controlled.
Similar to Experiment 3, we found no evidence of spontaneous
social attentional biasing in manual responses. Although oculomo-
tor breakaway data indicated a greater proportion of first saccades
Figure 8
Experiment 3 Manual Response Time (RT) Results
Note. Mean correct RTs as a function of overall Target position for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs.
SOCIAL ATTENTION AND GENERAL MECHANISMS 299
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
directed toward the eyes of faces, similar to Experiment 2, this
result was not specific to upright faces. That is, we found a nonspe-
cific increased frequency of saccadic breakaways toward the eye
region of the face relative to the house and neutral cues; however,
this effect was not unique to upright faces, and as such could reflect
overall differences in low-level visual properties of the stimuli
rather than any specific social biasing by face cues. Thus, the results
from Experiment 4 do not lend support to the hypothesis that the in-
ternal configuration of face stimuli may be a driving factor behind
social attentional biasing as reported in previous literature.
Next, we examined the role of perceived facial attractiveness in
social attentional biasing.
Experiment 5
Experiment 5 examined whether perceived attractiveness of the
face influenced social attentional biasing in manual responses
when participants were instructed to maintain central fixation.
Facial attractiveness, defined as a representation of aesthetically
pleasing information, is a powerful attentional cue. Since attrac-
tiveness appears to be processed rapidly (Locher et al., 1993;
Olson & Marshuetz, 2005), it can play an important role in social
attentional biasing. Indeed, past work shows that eye movements
are more strongly biased toward attractive relative to unattractive
faces (Aharon et al., 2001;Maner et al., 2007), while attentional
Figure 9
Experiment 4 Manual Response Time (RT) Results
Note. Mean correct RTs as a function of overall Target position for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs.
Figure 10
Experiment 4 Oculomotor Results
Note. Mean proportion of trials containing a breakaway saccade during the cue presenta-
tion period that was directed towards a region of interest (ROI) for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs. Summation of values across both Upright and
Inverted cues reveals the total proportion of trials with breakaway saccades directed
towards ROI regions (i.e., 0.72 proportion of trials directed to ROI regions [0.35 for
Upright, 0.37 for Inverted] versus 0.28 to non-ROI regions).
300 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
work shows that attractive faces bias manual responses in a cuing
task even when they are manipulated as task-irrelevant (Sui & Liu,
2009). Although houses may not have proportional attractiveness
when compared with faces, studies have found that houses can dif-
fer in terms of their likeability and typicality (Filliter et al., 2016),
which may be akin to the generalized information processing
mechanisms used to judge attractiveness for faces (Halberstadt &
Rhodes, 2003). Therefore, we reasoned that comparing measures
of perceived attractiveness for a face that is rated as highly attrac-
tive and a house that is not rated as highly attractive would provide
a good platform for such a comparison.
To examine this question in Experiment 5, as illustrated in Fig-
ure 12, we used a face cue that was perceived as more attractive
than the comparison house cue. If perceived attractiveness was a
key driving factor for social attentional biasing, we expected to
find faster responses for targets occurring at the previous location
of the face and eyes compared with the previous location of the
house.
Method
Thirty new naïve volunteers participated (26 women, 4 men,
M
age
= 21.0 years, SD
age
= 2.2 years).
All factors were kept identical to Experiments 1 and 3 except for
the stimuli, illustrated in Figure 12. Here, we used a face identity
cue that received the highest attractiveness rating (Face M = 5.71,
SD =.71,range=3–6), whereas the house image used was the
same as in Experiment 1, which received an average attractiveness
rating (see Footnote 1; House M=2.96,SD =.96,range=1–5).
The attractiveness ratings between the face and the house image dif-
fered reliably, t(27) = 11.24, p,.01, d
z
= 2.12, two-tailed, paired.
All other stimulus content factors, that is, global luminance (Face =
.60, House = .58, Neutral = .60; split-half luminance, Eyes = .60,
Mouth = .60, Top House = .58, Bottom House = .58; 1° 31° lumi-
nance segmented block analysis for face versus house, t(158) =
1.22, p=.22,d= .19, two-tailed) and featural configuration, visual
context factors (uniform background information), and task param-
eters (target and response settings) remained equated.
Results
Anticipations (.4%), timeouts (2.9%), and incorrect key presses
(.4%) were removed from analyses. Overall response accuracy
was 92%.
Mean correct RTs are illustrated in Figure 13 for Upright (13a)
and Inverted (13b) cues, showing once again slowest RTs for tar-
gets occurring at the Neutral cue locations (Upright, F(2, 58) =
53.54, p,.01, h
p
2
= .65; ts.7.95, ps,.01, d
z
s..1.45;
Inverted, F(2, 58) = 63.46, p,.01, h
p
2
= .69; ts.9.90, ps,.01,
d
z
s.1.81), and no difference in overall RTs for targets occurring
at the locations of the Face or House cues (Upright, 558 ms versus
561 ms, respectively; all other p= .25, d
z
= .22; Inverted, 561 ms
versus 563 ms, respectively; all other p= .61, d
z
= .09). Bayes
Figure 11
Experiment 4 Oculomotor Results
Note. Mean proportion of trials containing a breakaway saccade during the cue presentation period that was
directed towards regions of interest (ROIs) for (a) Upright and (b) Inverted cues. Error bars represent 95% CIs.
Summation of values across both Upright and Inverted cues reveals the total proportion of trials with break-
away saccades directed towards ROI regions.
Figure 12
Cue Screen for Experiment 5
Note. An illustration of the cue screen for Experiment 5, where the face
cue had a higher rating of perceived attractiveness than the house cue.
The depicted face image shown received the highest attractiveness rating
and was used in the present study.
SOCIAL ATTENTION AND GENERAL MECHANISMS 301
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
factor analysis for Upright Face versus House contrasts yielded a
value of .11 (BF
10
= .06 for Inverted).
Discussion
In Experiment 5, we examined whether social attentional biasing
was affected by facial attractiveness by presenting a face cue that
had received the highest perceived attractiveness ratings. When par-
ticipants were instructed to maintain central fixation, no overall
social attentional bias was found, such that manual responses for
targets occurring at the previous location of the face did not differ
from when targets occurred at the previous location of the house.
In the next experiment, we examined whether these results held
when examining participants’natural oculomotor behavior during
the task.
Experiment 6
Experiment 6 examined whether social attentional biasing
measured via manual and oculomotor responses was influenced by
the perceived attractiveness of the face when no instruction about
eye movement was given. If perceived attractiveness impacted
social attentional biasing, we would expect faster manual
responses for targets occurring at the previous location of the face
and/or increased oculomotor breakaways toward the face cue.
Method
Thirty new volunteers participated (24 women, 6 men, M
age
=
20.6 years, SD
age
= 1.7 years). The stimuli were identical to Experi-
ment 5. All other parameters were identical to Experiments 2 and 4.
Results
Manual RT
Anticipations (.2%), timeouts (1.2%), and incorrect key presses
(.2%) were removed from analyses. Overall response accuracy
was 97%.
Figure 14 shows these data. There were significant main effects
of Target position for both Upright, F(2, 58) = 96.44, p,.01,
h
p
2
= .77, and Inverted cues, F(2, 58) = 131.19, p,.01, h
p
2
= .82,
denoting a presence of an overall attentional bias toward faces.
That is, targets occurring at the previous location of the Face cue
were responded to faster relative to targets occurring at the previ-
ous location of the House cue for both Upright (546 ms versus 554
ms, respectively; t(29) = 2.52, p= .02, d
z
= .46) and Inverted cues
(547 ms versus 553 ms, respectively; t(29) = 2.28, p= .03, d
z
=
.42). Of lesser interest, there were also slower overall responses
for targets occurring at the previous location of the Neutral cues
versus the Face and House cues (Upright, ts.10.49, ps,.01,
d
z
s.1.92; Inverted, ts.12.65, ps,.01, d
z
s.2.31).
Next, we subjected the mean correct RTs to a repeated measures
ANOVA with Cue orientation (upright, inverted), Face position (left
visual field, right visual field), Target location (eyes, mouth, top
house, bottom house, upper neutral, lower neutral), and Cue-target
interval (250, 360, 560, 1,000 ms). However, as illustrated in Figure
15, the omnibus ANOVA returned no reliable main effects or interac-
tions supporting social attention biasing nor indicating facilitation for
targets occurring at the location of the Eyes or Mouth relative to those
occurring at the location of the Top or Bottom House (548 ms versus
545 ms versus 553 ms versus 554 ms, respectively; ts,2.89, ps.
.05, d
z
s,.53).Further,noeffectswerespecific to upright faces and
there were no effects or interactions involving Cue orientation, Cue
orientation 3Target location,F(5, 145) = .83, p=.53,h
p
2
= .03; Cue
orientation 3Face position 3Target location,F(5, 145) = .78, p=
.56, h
p
2
=.03;Cue orientation 3Cue-target interval 3Target loca-
tion,F(15, 435) = .77, p= .71, h
p
2
=.03;Cue orientation 3Face posi-
tion 3Cue-target interval 3Target location,F(15, 435) = .76,
p= .72, h
p
2
=.03.
Instead, of lesser theoretical interest, the omnibus analysis indi-
cated a significant main effect of Cue-target interval,F(3, 87) =
43.56, p,.01, h
p
2
= .60, with overall slower RTs for shorter ver-
sus longer cue-target intervals (250 ms versus all, ts.6.91, ps,
.01, d
z
s.1.26; all other ps..25, d
z
s,.33). This finding demon-
strates the typical foreperiod effect found within attentional dot-
Figure 13
Experiment 5 Manual Response Time (RT) Results
Note. Mean correct RTs as a function of overall Target position for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs.
302 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
probe tasks (Bertelson, 1967;Hayward & Ristic, 2013) and
reflects an increased response preparation with a lengthening of
the time between the cue and the target. There was also a signifi-
cant main effect of Target location (Mauchly’s test of sphericity,
v
2
(14) = 34.58, p,.01), F(3.53,102.42) = 68.86, p,.01, h
p
2
=
.70, reflecting overall slower RTs for targets occurring at the previ-
ous location of the Neutral cues versus all other cues (ts.9.28,
ps,.01, d
z
s.1.69). No other effects were reliable (Fs,1.40,
ps..24, h
p
2
,.05).
Therefore, even though manual RTs suggested the presence of
an overall attentional bias for faces relative to house and neutral
target locations, this effect did not persist for specific target loca-
tions and for upright cues.
Eye Movement Data
As in previous experiments, participants saccaded away from
central fixation on 9% of trials during the cue presentation (SD =
15%, range = 1–75%). Of these trials, saccades were launched to-
ward an ROI on 95% of trials. Mean saccadic RT was 156 ms
(SD = 53 ms). Mean proportion of saccades are illustrated in Figure
16 as a function of ROIs for Upright (16a) and Inverted (16b) cues.
There were reliable main effects of ROI for both Upright
(Mauchly’s test of sphericity, v
2
(2) = 14.86, p,.01), F(1.42,41.08) =
12.21, p,.01, h
p
2
= .30, and Inverted conditions, F(2, 58) = 3.65,
p=.03,h
p
2
= .11, indicating a greater proportion of saccades directed
toward the Face versus the House and Neutral cues for Upright (.22
versus .10 versus .06, respectively; ts.3.00, ps,.01, d
z
s..55; all
other t(29) = 1.52, p=.14,d
z
= .28) but not Inverted cues (.17 versus
.10 versus .08, respectively; ts,2.18, ps..11, d
z
s,.40).
Thus, an omnibus ANOVA examined the proportion of break-
away saccades as a function of Cue orientation (upright, inverted),
Face position (left visual field, right visual field), and ROI (eyes,
mouth, top house, bottom house, upper neutral, lower neutral).
The means are illustrated in Figure 17
Figure 14
Experiment 6 Manual Response Time (RT) Results
Note. Mean correct RTs as a function of overall Target position for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs.
Figure 15
Experiment 6 Manual Response Time (RT) Results
Note. Mean correct RTs as a function of all Target positions for (a) Upright and (b) Inverted cues. Error bars
represent 95% CIs.
SOCIAL ATTENTION AND GENERAL MECHANISMS 303
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
There was a main effect of ROI (Mauchly’s test of sphericity,
v
2
(14) = 86.98, p,.001), F(2.03,58.99) = 16.00, p,.01, h
p
2
=
.36, with an overall greater proportion of first saccades directed to-
ward the Eyes versus all other regions (ts.3.68, ps,.01, d
z
s.
.67) and an overall lower proportion of saccades directed toward
the Lower Neutral versus the Top House and Upper Neutral cues
(ts.3.00, ps,.05, d
z
s..55; all other ps..06, d
z
s,.53).
This main effect was qualified by an interaction between ROI
and Cue orientation (Mauchly’s test of sphericity, v
2
(14) = 30.77,
p= .01), F(3.35,97.16) = 4.85, p,.01, h
p
2
= .14. When cues were
Upright, a greater proportion of saccades were directed toward the
Eyes compared with all other regions (ts.3.93, ps,.01, d
z
s.
.72; all other ps..06, d
z
s,.54). When cues were Inverted,
greater proportion of saccades were directed toward the Eyes ver-
sus Bottom House and Lower Neutral cues (ts.3.66, ps,.01,
d
z
s..67) and toward the Top House versus Bottom House cue,
t(29) = 3.81, p= .01, d
z
= .70 (all other ps..05, d
z
s,.56).
An interaction between ROI and Face position was also signif-
icant (Mauchly’s test of sphericity, v
2
(14) = 60.42, p,.01),
F(2.79,80.77) = 3.10, p= .04, h
p
2
= .10. It further revealed that
when the face was presented in the left visual field, an overall
greater proportion of saccades were launched toward the Eyes
versus all other regions (ts.3.87, ps,.01, d
z
s..71) and a
greater proportion of saccades toward the Mouth versus the
Figure 16
Experiment 6 Oculomotor Results
Note. Mean proportion of trials containing a breakaway saccade during the cue presenta-
tion period that was directed towards a region of interest (ROI) for (a) Upright and (b)
Inverted cues. Error bars represent 95% CIs. Summation of values across both Upright and
Inverted cues reveals the total proportion of trials with breakaway saccades directed
towards ROI regions (i.e., 0.74 proportion of trials directed to ROI regions [0.38 for
Upright, 0.36 for Inverted] versus 0.26 to non-ROI regions).
Figure 17
Experiment 6 Oculomotor Results
Note. Mean proportion of trials containing a breakaway saccade during the cue presentation period that was
directed towards regions of interest (ROIs) for (a) Upright and (b) Inverted cues. Error bars represent 95% CIs.
Summation of values across both Upright and Inverted cues reveals the total proportion of trials with break-
away saccades directed towards ROI regions.
304 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Lower Neutral cue, t(29) = 3.72, p= .01, d
z
= .68 (all other ps.
.11, d
z
s,.48). When the face was presented in the right visual
field, a greater proportion of saccades were launched toward the
Eyes compared with the Mouth, Bottom House, and Lower Neu-
tral cues (ts.3.24, ps,.04, d
z
s..59), and a greater propor-
tion of saccades were launched toward the Top House versus
Lower Neutral cue, t(29) = 3.67, p= .01, d
z
= .67 (all other ps.
.11, d
z
s,.50). No other effects were found (Fs,.87, ps..36,
h
p
2
,.03).
Discussion
Experiment 6 examined whether perceived facial attractiveness
impacted social attentional biasing when eye movements were not
restricted. Within manual response data, there was a nonspecific
overall social attentional bias toward the face, but this effect was
not specific to upright faces or individual target locations. Within
oculomotor data during the cue period, more robust social atten-
tional biasing effects were found. When we examined spontaneous
first saccades launched toward the cues, we found an increased
proportion of saccades toward the eye region of the face, and par-
ticularly when faces were presented in an upright orientation and
in the left visual field. Therefore, even though oculomotor biasing
occurred on a small subset of all trials (i.e., 9%), a reliable number
of saccades were preferentially launched toward the eyes of an
attractive face. Together, the results from Experiment 6 identify
perceived facial attractiveness as a potential key driving factor of
social attention biasing.
General Discussion
When answering the question about whether faces bias attention
preferentially, the field of attention has traditionally been situated
within a domain-specific view, uncovering data consistent with the
notion that faces and eyes engage attention preferentially due to
their social nature. However, recent work (Pereira et al., 2019,
2020,2022) has suggested that faces and facial features may
instead bias attention in a manner that is better explained by gener-
alized mechanisms, wherein extraneous factors such as stimulus
content, visual context, and/or task settings may be the key gating
components that drive such social attentional biases.
The present series of experiments examined the role of face
stimulus content, namely global luminance, featural configuration,
and perceived attractiveness, in spontaneous social attentional
biasing by assessing performance in both manual (Ariga & Ari-
hara, 2018;Bindemann et al., 2005,2007;Lavie et al., 2003;Ro et
al., 2001;Sato & Kawahara, 2015) and oculomotor measures (Bir-
mingham et al., 2008a,2008b;Laidlaw et al., 2012;Langton et al.,
2008;Theeuwes & Van der Stigchel, 2006;Yarbus, 1967). Using
the dot-probe paradigm, in a series of six experiments, we pre-
sented participants with displays containing images of face, house,
and neutral cues, and measured their speed and accuracy to dis-
criminate targets that occurred at one of the previous locations of
the face (eyes, mouth), house (top, bottom), or neutral (upper,
lower) cues. We manipulated stimulus content information
between the face and house stimuli by assessing if differences in
global luminance (Experiments 1 and 2), imbalance of featural
configuration (Experiments 3 and 4), and higher attractiveness
(Experiments 5 and 6) affected the resulting social attentional bias.
When measuring manual RT under instruction to maintain eye fix-
ation (Experiments 1, 3, and 5), we found no evidence of atten-
tional biasing toward upright faces across all experiments. This
result was supported by both null hypothesis testing and Bayesian
methods. However, when measuring oculomotor biasing in condi-
tions when eye movements were not restricted (Experiments 2, 4,
and 6), when the face cue was perceived as more attractive than
the nonsocial cue, we found a reliable indication of a social atten-
tion bias that was specific to upright faces and specific to the eyes
of faces as well. Taken together, the results of these experiments
show that global luminance and internal configuration of features
likely contribute little to social attentional biasing, but that per-
ceived attractiveness potentially plays a critical role in social atten-
tional biasing. These results raise several points for further
discussion.
Perceived Facial Attractiveness Is an Important Factor
in Oculomotor Social Attentional Biasing
First, when examining the effect of perceived facial attractive-
ness on social attention when eye movements were not restricted
in Experiment 6, we found evidence for social attentional biasing
in both manual and oculomotor data. In manual effects, there was
an overall bias to detect targets occurring at the location of the
face that was not specific to upright faces or any facial feature. It
is possible that this finding may indicate a nonspecific manual bias
for targets occurring at the location of the face, as recent data has
shown that attractiveness may survive face inversion and poten-
tially even enhance it as a result of the loss of distinctive facial
characteristics with inversion effects (Leder et al., 2017); however,
more studies are needed to investigate whether this nonspecific
effect reflects social attentional biasing. In oculomotor data, our
findings indicated a saccadic bias toward the eyes of the face,
which was specific to upright faces and when faces were presented
in the left visual field. This finding furthers behavioral studies that
suggest that assessing facial attractiveness occurs automatically
(Olson & Marshuetz, 2005;Willis & Todorov, 2006) and is diffi-
cult to inhibit (Sui & Liu, 2009), and dovetails with past work
showing a general preference for upright faces and a processing
advantage for faces presented in the left visual field (Frank et al.,
2009;Kanwisher et al., 1997;Kanwisher & Yovel, 2006;Puce et
al., 1998;Rossion et al., 2003;Simion & Giorgio, 2015;Yin,
1969;Yovel et al., 2003). Of note here is that nonspecific effects
were found for both upright and inverted faces within manual
measures, whereas specific effects were found for upright faces
within oculomotor measures. This suggests that comparing upright
and inverted stimuli without controlling for and isolating specific
visual and/or categorical variables may not be sufficient to capture
potential differences across all extraneous factors, highlighting the
need to specifically account for stimulus content variables when
studying social attention, above and beyond inversion effects. As
such, the findings from Experiment 6 provide evidence for social
attentional biasing that may be reflected across both manual and
oculomotor data.
Thus, perceived facial attractiveness may be an important factor
in social attention. This point is particularly revealing given that
oculomotor effects occurred even though saccadic breakaways
from fixation occurred rarely (i.e., on 9% of trials). This suggests
that even with a low proportion of eye movements, perceived
SOCIAL ATTENTION AND GENERAL MECHANISMS 305
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
attractiveness instantiated statistically robust oculomotor biasing
toward the eyes of the face. Furthermore, our findings also show
that the attractive face used in the current study and the controlled
face used in previous work (Pereira et al., 2020) both resulted in
similar percentage of trials with saccadic breakaways, but that the
attractive face resulted in numerically greater proportion of sac-
cades directed toward the eyes (i.e., 3.4% in the current study vs.
1.9% in Pereira et al., 2020). Although these comparisons repre-
sent numerical differences alone, they suggest that perceived
attractiveness may regulate the degree of oculomotor social bias-
ing for faces and eyes rather than acting to enhance overall eye
movements. Low proportions of saccadic breakaways within the
current study prevented more complex analyses from being con-
ducted to examine whether trials on which saccadic breakaways to
faces and eyes occurred also resulted in faster manual RTs for tar-
gets appearing in these locations. Future studies can utilize similar
manipulations of perceived attractiveness while making eye move-
ments relevant to the task to uncover possible combinatory effects
of oculomotor and manual performance when examining atten-
tional biasing toward attractive faces.
An additional point worth noting is that the eyes of attractive
faces were the specific feature that biased eye movements, above
and beyond any oculomotor effects for the mouth. This finding
dovetails with past work demonstrating that the eye region plays a
central role in social attentional effects (Birmingham et al., 2007;
Capozzi & Ristic, 2018;Laidlaw et al., 2012;Langton et al.,
2000). For example, it is well-established that information con-
tained within the eyes (i.e., eye gaze) is capable of orienting atten-
tion even when this information runs counter to task instructions
and settings (Friesen & Kingstone, 2003;Itier et al., 2007;Mans-
field et al., 2003). Our results further extend these findings by
showing that this oculomotor effect was not driven by any specific
global luminance or featural configuration differences within this
region since these factors were equated between our cue stimuli
for Experiment 6. However, the present study did utilize a differ-
ent task paradigm (i.e., dot-probe vs. gaze cuing) and different
gaze stimuli (i.e., direct vs. averted gaze) compared with this prior
work, and more comparisons will be needed to assess whether dif-
ferences in stimulus content factors also affect attentional orient-
ing when elicited by eye gaze. Past work has also found that
perception of direct and averted gaze is subserved by different
brain mechanisms (Bayliss et al., 2011;Frischen et al., 2007;
George & Conty, 2008) and serves different communicative pur-
poses (i.e., communicative intent vs. attentional orienting). Thus,
it is possible that the mechanisms invoked by the perception of
gaze may not be the same as those invoked by attentional orienting
in response to gaze direction. This question remains for further
research.
Another key question from our findings is the degree to which
social attentional biasing can be modulated by subjective ratings
of attractiveness. That is, in the current study, we utilized faces
that were aggregately rated as more attractive by an independent
group of participants. However, it may be possible for oculomotor
effects to be heightened if faces are perceived as more or less
attractive on an individual level. Future studies could employ a
similar task design while utilizing face stimuli of high and low
attractiveness or nonsocial stimuli that may be more personally-
relevant or socially-equivalent to faces (e.g., avatars, pareidolic
faces; Henschel et al., 2021;Liu et al., 2014;Takahashi &
Watanabe, 2013) as a within-subject factor to clarify the role of
this stimulus content factor in oculomotor biasing effects toward
the eyes.
Together, the current results suggest that past studies that have
shown robust social attentional biasing in oculomotor measures
(Birmingham et al., 2008a,2008b;Laidlaw et al., 2012;Langton
et al., 2008;Theeuwes & Van der Stigchel, 2006;Yarbus, 1967)
may have also captured the influence of perceived facial attractive-
ness due to its ability to quickly engage social attention.
No Social Attentional Biasing Across Stimulus Content
Factors in Manual Measures
Second, and in contrast to oculomotor data from Experiment 6,
other manipulations of stimulus content factors did not result in
reliable social attentional biases in manual responses when partici-
pants’eye movements were controlled. This finding is consistent
with recent work showing that controlling stimulus content, visual
context, and task settings abolishes social attentional biasing in
manual performance (Pereira et al., 2019,2020,2022), and adds to
the growing body of literature demonstrating null or conditional
social attentional biasing effects (Besner et al., 2021a,2021b;
Burra et al., 2018;McCrackin et al., 2021;McCrackin & Itier,
2018,2021;Ricciardelli et al., 2013;Võ et al., 2012).
One possibility for these emergent null effects is the notion that
spontaneous social attentional biasing may depend on a combina-
tion of stimulus content and visual context factors rather than
being specific to a single extraneous variable. For example, it may
be possible that a combination of factors that have resulted in
attentional biasing in previous and current work (e.g., background
context and perceived attractiveness) may be necessary for manual
effects to occur. It is also possible that social biasing toward faces
and eyes may be dependent on task settings, or that social atten-
tional biasing occurs purposefully based on internal and external
demands. Some evidence supports this notion. For example, Võ et
al. (2012) have demonstrated that attentional selection of faces
and facial features can be differentially elicited based on estab-
lished priorities from the task (e.g., see also Smilek et al., 2006).
More recently, Burra et al. (2018) demonstrated that both behav-
ioral and neural measures of social attentional biasing are influ-
enced by task relevancy by showing modulations in gaze
processing depending on whether the face was relevant to the task.
The present results dovetail with these findings and highlight the
need for future investigations geared toward understanding how
components of stimulus content, visual context, and task factors
lead to robust social attentional biasing.
Another possibility is that our study design or stimulus manipu-
lations contributed to the lesser social attentional biasing effects.
From a theoretical perspective, preferential spontaneous effects for
faces should be resilient to these relatively simple manipulations
of task factors; however, it is possible that having such a tightly
controlled design with specific binary stimulus content manipula-
tions may have biased the experiment against finding potential
subtle differences between conditions. For example, it is possible
that utilizing a simplified study design with different levels of
stimulus content factors manipulated as within-subjects variables
may reveal that these factors play a role in the magnitude of atten-
tional biasing for faces. Similarly, utilizing a study design that
increases the global luminance of the house cue or rearranges the
306 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
internal featural configuration of the face cue may reveal whether
similar behavior and oculomotor effects exist for social and nonso-
cial information. In addition, it is also possible that the study
design may have resulted in participants responding strategically
to most frequent target locations, owing to the higher proportion
of targets appearing in the middle region as compared with the
upper and lower regions of the screen. Although future study
designs with fully balanced target locations can be beneficial in
examining whether upper, middle, and lower regions of the screen
can impact reaction times, it is worth noting that within the current
studies, the number of targets appearing at the locations of the face
and the house cues were equal, and as such, this design feature
should not have affected the primary question of interest about
potential attentional biases invoked by faces.
Although studies of this nature can shed light on the threshold
that needs to be met for stimulus content factors to moderate atten-
tional biasing, a truer test of social attention necessitates a direct
contrast of social versus nonsocial information (Birmingham &
Kingstone, 2009). Although this may at times present nonequiva-
lent and dissimilar contrasts (e.g., by comparing stimuli such as
faces and houses), this key manipulation is critical in determining
whether faces contain fundamental social properties that result in
spontaneous and robust attentional biasing. If this were the case,
then contrasting two highly dissimilar stimuli like faces and
houses should result in exponentially greater social attentional
biasing owing to the heightened social relevance of the face com-
pared with the lesser relevance of the house; however, if instances
of controlling for simple extraneous factors between stimuli is
able to rob faces of their attentional relevance, resulting in null
effects, this speaks to the factors that may have driven the origi-
nally reported effects. In this manner, the current set of studies are
compelling specifically because of their ability to reveal modula-
tions of social attentional biasing or the lack thereof in these care-
fully designed contrasts.
Dissociations in Data Across Manual and Oculomotor
Measures
Third, the differential results found when eye movements were re-
stricted versus when eye movements were allowed to occur highlight
recent results showing dissociations of covert and overt measures of
social attention, respectively (Gobel et al., 2015;Kuhn et al., 2016;
Laidlaw et al., 2015;Risko et al., 2016). Namely, these studies sug-
gest that covert and overt social attention may diverge based on the
utilization of gaze cues in real life to either signal social information
or reciprocate that information back. In this manner, covert and overt
social attention may serve different purposes, as covert social atten-
tion can be used to gather information surreptitiously (i.e., by shifting
the mind’s eye toward a location of interest), whereas overt social
attention can be used to directly communicate social cues (i.e., by
shifting the eyes to a location of interest). In addition to providing
evidence in favor of this distinction, the present set of studies also
point to factors that may give rise to covert-overt dissociations in a
spontaneous manner. Specifically, facial attractiveness was the only
stimulus content factor that resulted in differential covert and overt
effects, such that no manual biases were found when participants
were instructed to maintain central fixation (Experiment 5), and a
nonspecific manual bias toward faces and a specific oculomotor bias
toward the eyes was found when participants were allowed to freely
move their eyes (Experiment 6). As such, this factor may provide a
particularly illuminating real-world example of the necessity for sep-
arate investigations of the factors that may drive covert and overt
social attention, further pointing to the utility of reconceptualizing
attentional control as an integrative system that can be influenced by
stimulus factors, task information, internal preferences, and personal
experiences (Awh et al., 2012;Ristic & Enns, 2015).
An important caveat to note however is that the manipulations
contained within the current set of studies do not fully overlap with
typical conceptualizations of covert and overt attention. Specifically,
Experiments 1, 3, and 5 did not provide a pure measure of covert
attention since participants were verbally instructed to maintain fixa-
tion without fixation monitoring. Conversely, Experiments 2, 4, and
6 did not provide a typical measure of overt attention because eye
movements were not task-relevant, as in typical free-viewing oculo-
motor tasks. However, despite these differences, there is evidence to
suggest convergence across our effects and available covert/overt
data given that past work confirms that verbal instructions result in
participants’compliance with fixation (Friesen et al., 2004;Pereira et
al., 2020;Posner, 1980) and that eye movements occurred spontane-
ously within the short period of cue presentation (i.e., 250 ms). As
such, the present manipulations provided generally consistent results
within each measure and replicated the effects of previous work.
This finding lends parallel evidence to the notion that humans may
use covert and overt attentional processes differently in various envi-
ronments, such as in situations where we use covert attention to dis-
creetly gather information around us without revealing our
immediate intentions to others or when we need overt attention to ex-
plicitly convey our own internal thoughts and emotions to others.
Bridging Social Attention Within a Generalized
Framework
Finally, the current set of results appear to lend support for social
attention being subsumed at least partly by generalized attentional
mechanisms in which faces do not hold a special status, but instead
bias attentional mechanisms by virtue of their stimulus or task char-
acteristics. However, our results also provided patterns that are in-
dicative of typical perceptual processing for faces, such as a general
preference for upright faces and a processing advantage for faces
presented in the left visual field. We also found that some stimulus
content factors, like global luminance and featural configuration,
produced generalized biasing effects, independent of face orienta-
tion. As such, our results suggest that the links between perceptual
and attentional mechanisms for faces may be more nuanced than
originally thought. One potential neural structure which could play
an important role in this interaction is the right temporoparietal junc-
tion (TPJ), which is typically activated when attention is engaged in
a spontaneous manner (Corbetta & Shulman, 2002). The TPJ is also
known to be important for attentionally orienting toward behavior-
ally relevant stimuli (Geng & Vossel, 2013;Joseph et al., 2015;Kin-
cade et al., 2005;Ristic & Giesbrecht, 2009;Serences et al., 2005)
and for higher level sociocognitive processing, such as theory of
mind (Corbetta et al., 2008;Decety & Lamm, 2007;Mars et al.,
2013). Recent work from Capozzi and Ristic (2018) has proposed
that connections between the TPJ and adjacent face processing
regions may be critical in understanding how attentional systems are
linked with visual processing hubs for social information at a neural
level. Although more research is needed to determine the specific
SOCIAL ATTENTION AND GENERAL MECHANISMS 307
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
gating mechanisms between social attention and face perception, the
current set of studies suggest that nonsocial generalized mechanisms
may play a strong role in modulating these links.
Conclusions
In summary, the present set of studies investigated how stimulus
content factors, namely global luminance, internal configuration of
features, and perceived attractiveness, influenced social attentional
biasing. Although the data showed no robust effects of social
attentional biasing across any of the stimulus content factors when
eye movements were restricted, they indicated that perceived fa-
cial attractiveness elicited social attentional biasing when eye
movements were allowed to occur. As such, these data point to
perceived attractiveness as an important factor in social attentional
biasing and further highlights the need for future work to delineate
the contributions of other generalized factors of content, context,
and task factors to social attention.
References
Aharon, I., Etcoff, N., Ariely, D., Chabris, C. F., O’Connor, E., & Breiter,
H. C. (2001). Beautiful faces have variable reward value: fMRI and be-
havioral evidence. Neuron,32(3), 537–551. https://doi.org/10.1016/
S0896-6273(01)00491-3
Allison, T., Puce, A., & McCarthy, G. (2000). Social perception from vis-
ual cues: Role of the STS region. Trends in Cognitive Sciences,4(7),
267–278. https://doi.org/10.1016/S1364-6613(00)01501-1
Ando, S. (2002). Luminance-induced shift in the apparent direction of
gaze. Perception,31(6), 657–674. https://doi.org/10.1068/p3332
Ando, S. (2004). Perception of gaze direction based on luminance ratio.
Perception,33(10), 1173–1184. https://doi.org/10.1068/p5297
Ariga, A., & Arihara, K. (2018). Attentional capture by spatiotemporally
task-irrelevant faces: Supportive evidence for Sato and Kawahara
(2015). Psychological Research,82(10), 859–865. https://doi.org/10
.1007/s00426-017-0869-3
Awh, E., Belopolsky, A. V., & Theeuwes, J. (2012). Top-down versus bot-
tom-up attentional control: A failed theoretical dichotomy. Trends in
Cognitive Sciences,16(8), 437–443. https://doi.org/10.1016/j.tics.2012
.06.010
Badcock, D. R., Clifford, C. W. G., & Khuu, S. K. (2005). Interactions
between luminance and contrast signals in global form detection. Vision
Research,45(7), 881–889. https://doi.org/10.1016/j.visres.2004.09.042
Bayliss, A. P., Bartlett, J., Naughtin, C. K., & Kritikos, A. (2011). A direct
link between gaze perception and social attention. Journal of Experi-
mental Psychology: Human Perception and Performance,37(3),
634–644. https://doi.org/10.1037/a0020559
Bell, J., & Badcock, D. R. (2008). Luminance and contrast cues are inte-
grated in global shape detection with contours. Vision Research,48(21),
2336–2344. https://doi.org/10.1016/j.visres.2008.07.015
Benedetto, S., Carbone, A., Drai-Zerbib, V., Pedrotti, M., & Baccino, T.
(2014). Effects of luminance and illuminance on visual fatigue and
arousal during digital reading. Computers in Human Behavior,41,
112–119. https://doi.org/10.1016/j.chb.2014.09.023
Bentin, S., Allison, T., Puce, A., Perez, E., & McCarthy, G. (1996). Elec-
trophysiological Studies of Face Perception in Humans. Journal of Cog-
nitive Neuroscience,8(6), 551–565. https://doi.org/10.1162/jocn.1996.8
.6.551
Bertelson, P. (1967). The time course of preparation. The Quarterly Jour-
nal of Experimental Psychology,19(3), 272–279. https://doi.org/10
.1080/14640746708400102
Besner, D., McLean, D., & Young, T. (2021a). Do eyes and arrows elicit
automatic orienting? Three mutually exclusive hypotheses and a test. Quar-
terly Journal of Experimental Psychology: Human Experimental Psychol-
ogy,74(7), 1164–1169. https://doi.org/10.1177/1747021821998572
Besner, D., McLean, D., & Young, T. (2021b). On the determination of
eye gaze and arrow direction: Automaticity reconsidered. Canadian
Journal of Experimental Psychology/Revue Canadienne de Psychologie
Expérimentale,75(3), 261–278. https://doi.org/10.1037/cep0000261
Bindemann, M., & Burton, A. M. (2008). Attention to upside-down faces:
An exception to the inversion effect. Vision Research,48(25),
2555–2561. https://doi.org/10.1016/j.visres.2008.09.001
Bindemann, M., Burton, A. M., Hooge, I. T. C., Jenkins, R., & de Haan,
E. H. F. (2005). Faces retain attention. Psychonomic Bulletin & Review,
12(6), 1048–1053. https://doi.org/10.3758/BF03206442
Bindemann, M., Burton, A. M., Langton, S. R., Schweinberger, S. R., &
Doherty, M. J. (2007). The control of attention to faces. Journal of
Vision,7(10), 15. https://doi.org/10.1167/7.10.15
Birmingham, E., & Kingstone, A. (2009). Human social attention: A new
look at past, present, and future investigations. Annals of the New York
Academy of Sciences,1156(1), 118–140. https://doi.org/10.1111/j.1749
-6632.2009.04468.x
Birmingham, E., Bischof, W., & Kingstone, A. (2008a). Gaze selection in
complex social scenes. Visual Cognition,16(2–3), 341–355. https://doi
.org/10.1080/13506280701434532
Birmingham, E., Bischof, W. F., & Kingstone, A. (2008b). Social attention
and real-world scenes: The roles of action, competition and social con-
tent. Quarterly Journal of Experimental Psychology: Human Experi-
mental Psychology,61(7), 986–998. https://doi.org/10.1080/17470210
701410375
Birmingham, E., Bischof, W., & Kingstone, A. (2007). Why do we look at
people’s eyes? Journal of Eye Movement Research,1(1), 1–6. https://doi
.org/10.16910/jemr.1.1.1
Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision,10(4),
433–436. https://doi.org/10.1163/156856897X00357
Bruce, V., & Young, A. (1986). Understanding face recognition. British
Journal of Psychology,77(3), 305–327. https://doi.org/10.1111/j.2044
-8295.1986.tb02199.x
Burra, N., Framorando, D., & Pegna, A. J. (2018). Early and late cortical
responses to directly gazing faces are task dependent. Cognitive, Affec-
tive & Behavioral Neuroscience,18(4), 796–809. https://doi.org/10
.3758/s13415-018-0605-5
Burton, A. M., White, D., & McNeill, A. (2010). The Glasgow Face
Matching Test. Behavior Research Methods,42(1), 286–291. https://doi
.org/10.3758/BRM.42.1.286
Capozzi, F., & Ristic, J. (2018). How attention gates social interactions.
Annals of the New York Academy of Sciences,1426(1), 179–198. https://
doi.org/10.1111/nyas.13854
Cerf, M., Frady, E. P., & Koch, C. (2009). Faces and text attract gaze inde-
pendent of the task: Experimental data and computer model. Journal of
Vision,9(12), 10. https://doi.org/10.1167/9.12.10
Cerf, M., Harel, J., Einhäuser, W., & Koch, C. (2008). Predicting human
gaze using low-level saliency combined with face detection. In C. J.
Platt, D. Koller, Y. Singer & S. Roweis (Eds.), Advances in neural in-
formation processing systems (pp. 241–248). MIT Press.
Cherng, Y.-G., Baird, T., Chen, J.-T., & Wang, C.-A. (2020). Background
luminance effects on pupil size associated with emotion and saccade
preparation. Scientific Reports,10(1), 15718. https://doi.org/10.1038/
s41598-020-72954-z
Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stim-
ulus-driven attention in the brain. Nature Reviews Neuroscience,3(3),
201–215. https://doi.org/10.1038/nrn755
Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system
of the human brain: From environment to theory of mind. Neuron,
58(3), 306–324. https://doi.org/10.1016/j.neuron.2008.04.017
308 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Crouzet, S. M., Kirchner, H., & Thorpe, S. J. (2010). Fast saccades toward
faces: Face detection in just 100 ms. Journal of Vision,10(4), 16.
https://doi.org/10.1167/10.4.16
Dakin, S. C., & Watt, R. J. (2009). Biological “bar codes”in human faces.
Journal of Vision,9(4), 2. https://doi.org/10.1167/9.4.2
Darwin,C.(2013).The expression of the emotions in man and animals.
Cambridge University Press. https://doi.org/10.1017/CBO9781139833813
Decety, J., & Lamm, C. (2007). The role of the right temporoparietal junc-
tion in social interaction: How low-level computational processes con-
tribute to meta-cognition. The Neuroscientist,13(6), 580–593. https://
doi.org/10.1177/1073858407304654
Devue, C., Belopolsky, A. V., & Theeuwes, J. (2012). Oculomotor guid-
ance and capture by irrelevant faces. PLoS ONE,7(4), e34598. https://
doi.org/10.1371/journal.pone.0034598
Devue, C., Laloyaux, C., Feyers, D., Theeuwes, J., & Brédart, S. (2009).
Do pictures of faces, and which ones, capture attention in the inatten-
tional-blindness paradigm? Perception,38(4), 552–568. https://doi.org/
10.1068/p6049
Dienes, Z. (2011). Bayesian versus orthodox statistics: Which side are you
on? Perspectives on Psychological Science,6(3), 274–290. https://doi
.org/10.1177/1745691611406920
Doherty, M. J., McIntyre, A. H., & Langton, S. R. H. (2015). Developmen-
tally distinct gaze processing systems: Luminance versus geometric cues.
Cognition,137,72–80. https://doi.org/10.1016/j.cognition.2015.01.001
Eastwood, J. D., Smilek, D., & Merikle, P. M. (2001). Differential atten-
tional guidance by unattended faces expressing positive and negative
emotion. Perception & Psychophysics,63(6), 1004–1013. https://doi
.org/10.3758/BF03194519
Eimer, M. (2018). What do associations and dissociations between face
and object recognition abilities tell us about the domain-generality of
face processing? Cognitive Neuropsychology,35(1-2), 80–82. https://doi
.org/10.1080/02643294.2017.1414691
Etcoff, N. L., Stock, S., Haley, L. E., Vickery, S. A., & House, D. M.
(2011). Cosmetics as a feature of the extended human phenotype: Modu-
lation of the perception of biologically important facial signals. PLoS
ONE,6(10), e25656. https://doi.org/10.1371/journal.pone.0025656
Farah, M. J., Wilson, K. D., Drain, M., & Tanaka, J. N. (1998). What is
“special”about face perception? Psychological Review,105(3),
482–498. https://doi.org/10.1037/0033-295X.105.3.482
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). GPower 3: A
flexible statistical power analysis program for the social, behavioral, and
biomedical sciences. Behavior Research Methods,39(2), 175–191.
https://doi.org/10.3758/BF03193146
Filliter, J. H., Glover, J. M., McMullen, P. A., Salmon, J. P., & Johnson, S. A.
(2016). The DalHouses: 100 new photographs of houses with ratings of
typicality, familiarity, and degree of similarity to faces. Behavior Research
Methods,48(1), 178–183. https://doi.org/10.3758/s13428-015-0561-8
Frank, M. C., Vul, E., & Johnson, S. P. (2009). Development of infants’
attention to faces during the first year. Cognition,110(2), 160–170.
https://doi.org/10.1016/j.cognition.2008.11.010
Friesen, C. K., & Kingstone, A. (2003). Covert and overt orienting to gaze
direction cues and the effects of fixation offset. NeuroReport,14(3),
489–493. https://doi.org/10.1097/00001756-200303030-00039
Friesen, C. K., Ristic, J., & Kingstone, A. (2004). Attentional effects of
counterpredictive gaze and arrow cues. Journal of Experimental Psy-
chology: Human Perception and Performance,30(2), 319–329. https://
doi.org/10.1037/0096-1523.30.2.319
Frischen, A., Bayliss, A. P., & Tipper, S. P. (2007). Gaze cueing of atten-
tion: Visual attention, social cognition, and individual differences. Psy-
chological Bulletin,133(4), 694–724. https://doi.org/10.1037/0033-2909
.133.4.694
Gauthier, I., Skudlarski, P., Gore, J. C., & Anderson, A. W. (2000). Exper-
tise for cars and birds recruits brain areas involved in face recognition.
Nature Neuroscience,3(2), 191–197. https://doi.org/10.1038/72140
Gauthier, I., Tarr, M. J., Anderson, A. W., Skudlarski, P., & Gore, J. C.
(1999). Activation of the middle fusiform ‘face area’increases with ex-
pertise in recognizing novel objects. Nature Neuroscience,2(6),
568–573. https://doi.org/10.1038/9224
Gauthier, I., Tarr, M. J., Moylan, J., Skudlarski, P., Gore, J. C., &
Anderson, A. W. (2000). The fusiform “face area”is part of a network
that processes faces at the individual level. Journal of Cognitive Neuro-
science,12(3), 495–504. https://doi.org/10.1162/089892900562165
Geng, J. J., & Vossel, S. (2013). Re-evaluating the role of TPJ in atten-
tional control: Contextual updating? Neuroscience and Biobehavioral
Reviews,37(10, Pt. 2), 2608–2620. https://doi.org/10.1016/j.neubiorev
.2013.08.010
George, N., & Conty, L. (2008). Facing the gaze of others. Clinical Neuro-
physiology,38(3), 197–207. https://doi.org/10.1016/j.neucli.2008.03.001
Gobel, M. S., Kim, H. S., & Richardson, D. C. (2015). The dual function
of social gaze. Cognition,136(Supplement C), 359–364. https://doi.org/
10.1016/j.cognition.2014.11.040
Goffaux, V., & Dakin, S. C. (2010). Horizontal information drives the be-
havioral signatures of face processing. Frontiers in Psychology,1,
143–143. https://doi.org/10.3389/fpsyg.2010.00143
Halberstadt, J., & Rhodes, G. (2003). It’s not just average faces that are
attractive: Computer-manipulated averageness makes birds, fish, and
automobiles attractive. Psychonomic Bulletin & Review,10(1),
149–156. https://doi.org/10.3758/BF03196479
Haxby, J. V., Horwitz, B., Ungerleider, L. G., Maisog, J. M., Pietrini, P.,
& Grady, C. L. (1994). The functional organization of human extrastri-
ate cortex: A PET-rCBF study of selective attention to faces and loca-
tions. The Journal of Neuroscience,14(11 Pt 1), 6336–6353. https://doi
.org/10.1523/JNEUROSCI.14-11-06336.1994
Hayward, D. A., & Ristic, J. (2013). Measuring attention using the Posner
cuing paradigm: The role of across and within trial target probabilities.
Frontiers in Human Neuroscience,7, 205. https://doi.org/10.3389/
fnhum.2013.00205
Hedger, N., Garner, M., & Adams, W. J. (2019). Do emotional faces cap-
ture attention, and does this depend on awareness? Evidence from the
visual probe paradigm. Journal of Experimental Psychology: Human
Perception and Performance,45(6), 790–802. https://doi.org/10.1037/
xhp0000640
Henderson, J. M., Brockmole, J. R., & Gajewski, D. A. (2008). Differential
detection of global luminance and contrast changes across saccades and
flickers during active scene perception. Vision Research,48(1), 16–29.
https://doi.org/10.1016/j.visres.2007.10.008
Henschel, A., Bargel, H., & Cross, E. S. (2021). Faces do not attract more
attention than non-social distractors in the Stroop task. Collabra. Psy-
chology,7(1), 18521. https://doi.org/10.31234/osf.io/pbfny
Hochberg, J., & Galper, R. E. (1967). Recognition of faces: An exploratory
study. Psychonomic Science,9(12), 619–620. https://doi.org/10.3758/
BF03327918
Holm, S. (1979). A simple sequential rejective multiple test procedure.
Scandinavian Journal of Statistics,6,65–70.
Itier, R. J., Latinus, M., & Taylor, M. J. (2006). Face, eye and object early
processing: What is the face specificity? NeuroImage,29(2), 667–676.
https://doi.org/10.1016/j.neuroimage.2005.07.041
Itier, R. J., Villate, C., & Ryan, J. D. (2007). Eyes always attract attention
but gaze orienting is task-dependent: Evidence from eye movement
monitoring. Neuropsychologia,45(5), 1019–1028. https://doi.org/10
.1016/j.neuropsychologia.2006.09.004
Itti, L., & Koch, C. (2000). A saliency-based search mechanism for overt
and covert shifts of visual attention. Vision Research,40(10-12),
1489–1506. https://doi.org/10.1016/S0042-6989(99)00163-7
Johannes, S., Münte, T. F., Heinze, H. J., & Mangun, G. R. (1995). Lumi-
nance and spatial attention effects on early visual processing. Cognitive
Brain Research,2(3), 189–205. https://doi.org/10.1016/0926-6410(95)
90008-X
SOCIAL ATTENTION AND GENERAL MECHANISMS 309
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Johnson, M. H., Dziurawiec, S., Ellis, H., & Morton, J. (1991). Newborns’
preferential tracking of face-like stimuli and its subsequent decline. Cog-
nition,40(1-2), 1–19. https://doi.org/10.1016/0010-0277(91)90045-6
Jonides, J. (1981). Voluntary versus automatic control over the mind’s
eye’s movement. In J. B. Long & A. D. Baddeley (Eds.), Attention and
performance (Vol. IX, pp. 187–203). Erlbaum.
Joseph, R. M., Fricker, Z., & Keehn, B. (2015). Activation of frontoparie-
tal attention networks by non-predictive gaze and arrow cues. Social
Cognitive and Affective Neuroscience,10(2), 294–301. https://doi.org/
10.1093/scan/nsu054
Kanwisher, N., & Yovel, G. (2006). The fusiform face area: A cortical
region specialized for the perception of faces. Philosophical Transac-
tions of the Royal Society of London. Series B, Biological Sciences,
361(1476), 2109–2128. https://doi.org/10.1098/rstb.2006.1934
Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The fusiform face
area: A module in human extrastriate cortex specialized for face percep-
tion. The Journal of Neuroscience,17(11), 4302–4311. https://doi.org/
10.1523/JNEUROSCI.17-11-04302.1997
Kincade, J. M., Abrams, R. A., Astafiev, S. V., Shulman, G. L., &
Corbetta, M. (2005). An event-related functional magnetic resonance
imaging study of voluntary and stimulus-driven orienting of attention.
The Journal of Neuroscience,25(18), 4593–4604. https://doi.org/10
.1523/JNEUROSCI.0236-05.2005
Kuhn, G., Teszka, R., Tenaw, N., & Kingstone, A. (2016). Don’tbefooled!
Attentional responses to social cues in a face-to-face and video magic
trick reveals greater top-down control for overt than covert attention.
Cognition,146,136–142. https://doi.org/10.1016/j.cognition.2015.08.005
Laidlaw, K. E. W., Badiudeen, T. A., Zhu, M. J. H., & Kingstone, A.
(2015). A fresh look at saccadic trajectories and task irrelevant stimuli:
Social relevance matters. Vision Research,111(Pt. A), 82–90. https://doi
.org/10.1016/j.visres.2015.03.024
Laidlaw, K. E. W., Risko, E. F., & Kingstone, A. (2012). A new look at
social attention: Orienting to the eyes is not (entirely) under volitional
control. Journal of Experimental Psychology: Human Perception and
Performance,38(5), 1132–1143. https://doi.org/10.1037/a0027075
Langton, S. R. H., Law, A. S., Burton, A. M., & Schweinberger, S. R.
(2008). Attention capture by faces. Cognition,107(1), 330–342. https://
doi.org/10.1016/j.cognition.2007.07.012
Langton, S. R. H., Watt, R. J., & Bruce, I. (2000). Do the eyes have it?
Cues to the direction of social attention. Trends in Cognitive Sciences,
4(2), 50–59. https://doi.org/10.1016/S1364-6613(99)01436-9
Lavie, N., Ro, T., & Russell, C. (2003). The role of perceptual load in
processing distractor faces. Psychological Science,14(5), 510–515.
https://doi.org/10.1111/1467-9280.03453
Leder, H., Goller, J., Forster, M., Schlageter, L., & Paul, M. A. (2017).
Face inversion increases attractiveness. Acta Psychologica,178,25–31.
https://doi.org/10.1016/j.actpsy.2017.05.005
Lee, D. H., Susskind, J. M., & Anderson, A. K. (2013). Social transmission
of the sensory benefits of eye widening in fear expressions. Psychological
Science,24(6), 957–965. https://doi.org/10.1177/0956797612464500
Leppink, J., O'Sullivan, P., & Winston, K. (2017). Evidence against vs. in
favour of a null hypothesis. Perspectives on Medical Education,6(2),
115–118. https://doi.org/10.1007/s40037-017-0332-6
Lewis, M. B., & Edmonds, A. J. (2003). Face detection: Mapping human
performance. Perception,32(8), 903–920. https://doi.org/10.1068/p5007
Liu, J., Li, J., Feng, L., Li, L., Tian, J., & Lee, K. (2014). Seeing Jesus in
toast: Neural and behavioral correlates of face pareidolia. Cortex,53,
60–77. https://doi.org/10.1016/j.cortex.2014.01.013
Locher, P., Unger, R. K., Sociedade, P., & Wahl, J. (1993). At first glance:
Accessibility of the physical attractiveness stereotype. Sex Roles,28(11-
12), 729–743. https://doi.org/10.1007/BF00289990
Ludbrook, J. (2000). Multiple inferences using confidence intervals. Clini-
cal and Experimental Pharmacology & Physiology,27(3), 212–215.
https://doi.org/10.1046/j.1440-1681.2000.03223.x
Maner, J. K., Gailliot, M. T., Rouby, D. A., & Miller, S. L. (2007). Can’t
take my eyes off you: Attentional adhesion to mates and rivals. Journal
of Personality and Social Psychology,93(3), 389–401. https://doi.org/10
.1037/0022-3514.93.3.389
Mansfield, E., Farroni, T., & Johnson, M. H. (2003). Does gaze perception
facilitate overt orienting? Visual Cognition,10(1), 7–14. https://doi.org/
10.1080/713756671
Mars, R. B., Sallet, J., Neubert, F.-X., & Rushworth, M. F. S. (2013). Con-
nectivity profiles reveal the relationship between brain areas for social
cognition in human and monkey temporoparietal cortex. Proceedings of
the National Academy of Sciences of the United States of America,
110(26), 10806–10811. https://doi.org/10.1073/pnas.1302956110
Maurer, D., Grand, R. L., & Mondloch, C. J. (2002). The many faces of
configural processing. Trends in Cognitive Sciences,6(6), 255–260.
https://doi.org/10.1016/S1364-6613(02)01903-4
McCrackin, S. D., & Itier, R. J. (2018). Is it about me? Time-course of
self-relevance and valence effects on the perception of neutral faces
with direct and averted gaze. Biological Psychology,135,47–64. https://
doi.org/10.1016/j.biopsycho.2018.03.003
McCrackin, S. D., & Itier, R. J. (2021). Feeling through another’s eyes:
Perceived gaze direction impacts ERP and behavioral measures of posi-
tive and negative affective empathy. NeuroImage,226, 117605. https://
doi.org/10.1016/j.neuroimage.2020.117605
McCrackin, S. D., Lee, C. M., Itier, R. J., & Fernandes, M. A. (2021).
Meaningful faces: Self-relevance of semantic context in an initial social
encounter improves later face recognition. Psychonomic Bulletin &
Review,28(1), 283–291. https://doi.org/10.3758/s13423-020-01808-6
Mondloch, C. J., Lewis, T. L., Budreau, D. R., Maurer, D., Dannemiller,
J. L., Stephens, B. R., & Kleiner-Gathercoal, K. A. (1999). Face percep-
tion during early infancy. Psychological Science,10(5), 419–422.
https://doi.org/10.1111/1467-9280.00179
Nummenmaa, L., & Calder, A. J. (2009). Neural mechanisms of social
attention. Trends in Cognitive Sciences,13(3), 135–143. https://doi.org/
10.1016/j.tics.2008.12.006
O’Craven, K. M., Downing, P. E., & Kanwisher, N. (1999). fMRI evidence
for objects as the units of attentional selection. Nature,401(6753),
584–587. https://doi.org/10.1038/44134
Olk, B., & Garay-Vado, A. M. (2011). Attention to faces: Effects of face
inversion. Vision Research,51(14), 1659–1666. https://doi.org/10.1016/
j.visres.2011.05.007
Olson, I. R., & Marshuetz, C. (2005). Facial attractiveness is appraised in a
glance. Emotion,5(4), 498–502. https://doi.org/10.1037/1528-3542.5.4.498
Pachai, M. V., Sekuler, A. B., & Bennett, P. J. (2013). Masking of individ-
ual facial features reveals the use of horizontal structure in the eyes.
Journal of Vision,13(9), 411. https://doi.org/10.1167/13.9.411
Pereira, E. J., Birmingham, E., & Ristic, J. (2019). Contextually-based
social attention diverges across covert and overt measures. Vision,3(2),
29. https://doi.org/10.3390/vision3020029
Pereira, E. J., Birmingham, E., & Ristic, J. (2020). The eyes do not have it
after all? Attention is not automatically biased towards faces and eyes.
Psychological Research,84(5), 1407–1423. https://doi.org/10.1007/
s00426-018-1130-4
Pereira, E. J., Birmingham, E., & Ristic, J. (2022). Infrequent faces bias
social attention differently in manual and oculomotor measures. Atten-
tion, Perception, & Psychophysics. Advance online publication. https://
doi.org/10.3758/s13414-021-02432-9
Perrett, D. I., Hietanen, J. K., Oram, M. W., Benson, P. J., & Rolls, E. T.
(1992). Organization and functions of cells responsive to faces in the
temporal cortex. Philosophical Transactions of the Royal Society of
London. Series B, Biological Sciences,335(1273), 23–30. https://doi
.org/10.1098/rstb.1992.0003
Perrett, D. I., Mistlin, A. J., Chitty, A. J., Smith, P. A. J., Potter, D. D.,
Broennimann, R., & Harries, M. (1988). Specialized face processing
and hemispheric asymmetry in man and monkey: Evidence from single
310 PEREIRA, BIRMINGHAM, AND RISTIC
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
unit and reaction time studies. Behavioural Brain Research,29(3),
245–258. https://doi.org/10.1016/0166-4328(88)90029-0
Perrett, D. I., Smith, P. A. J., Potter, D. D., Mistlin, A. J., Head, A. S.,
Milner, A. D., & Jeeves, M. A. (1985). Visual cells in the temporal cor-
tex sensitive to face view and gaze direction. Proceedings of the Royal
Society of London, Series B: Biological Sciences,223(1232), 293–317.
Posner, M. I. (1980). Orienting of attention. The Quarterly Journal of
Experimental Psychology,32(1), 3–25. https://doi.org/10.1080/0033
5558008248231
Puce, A., Allison, T., Bentin, S., Gore, J. C., & McCarthy, G. (1998). Tem-
poral cortex activation in humans viewing eye and mouth movements.
The Journal of Neuroscience,18(6), 2188–2199. https://doi.org/10
.1523/JNEUROSCI.18-06-02188.1998
Ricciardelli, P., Carcagno, S., Vallar, G., & Bricolo, E. (2013). Is gaze fol-
lowing purely reflexive or goal-directed instead? Revisiting the automa-
ticity of orienting attention by gaze cues. Experimental Brain Research,
224(1), 93–106. https://doi.org/10.1007/s00221-012-3291-5
Risko, E. F., Richardson, D. C., & Kingstone, A. (2016). Breaking the
fourth wall of cognitive science. Current Directions in Psychological
Science,25(1), 70–74. https://doi.org/10.1177/0963721415617806
Ristic, J., & Enns, J. T. (2015). The changing face of attentional develop-
ment. Current Directions in Psychological Science,24(1), 24–31.
https://doi.org/10.1177/0963721414551165
Ristic, J., & Giesbrecht, B. (2009). The role of the ventrolateral frontopari-
etal attention network in social attention. Journal of Vision,9(8), 102.
https://doi.org/10.1167/9.8.102
Ro, T., Russell, C., & Lavie, N. (2001). Changing faces: A detection
advantage in the flicker paradigm. Psychological Science,12(1), 94–99.
https://doi.org/10.1111/1467-9280.00317
Rossion, B., Joyce, C. A., Cottrell, G. W., & Tarr, M. J. (2003). Early later-
alization and orientation tuning for face, word, and object processing in
the visual cortex. NeuroImage,20(3), 1609–1624. https://doi.org/10
.1016/j.neuroimage.2003.07.010
Rousselet, G. A., Ince, R. A., van Rijsbergen, N. J., & Schyns, P. G.
(2014). Eye coding mechanisms in early human face event-related
potentials. Journal of Vision,14(13), 7. https://doi.org/10.1167/14.13.7
Russell, R. (2003). Sex, beauty, and the relative luminance of facial fea-
tures. Perception,32(9), 1093–1107. https://doi.org/10.1068/p5101
Sato, S., & Kawahara, J. I. (2015). Attentional capture by completely task-
irrelevant faces. Psychological Research,79(4), 523–533. https://doi
.org/10.1007/s00426-014-0599-8
Sekuler,A.B.,Gaspar,C.M.,Gold,J.M.,&Bennett,P.J.(2004).Inversion
leads to quantitative, not qualitative, changes in face processing. Current
Biology,14(5), 391–396. https://doi.org/10.1016/j.cub.2004.02.028
Serences, J. T., Shomstein, S., Leber, A. B., Golay, X., Egeth, H. E., &
Yantis, S. (2005). Coordination of voluntary and stimulus-driven atten-
tional control in human cortex. Psychological Science,16(2), 114–122.
https://doi.org/10.1111/j.0956-7976.2005.00791.x
Simion, F., & Giorgio, E. D. (2015). Face perception and processing in
early infancy: Inborn predispositions and developmental changes. Fron-
tiers in Psychology,6, 969. https://doi.org/10.3389/fpsyg.2015.00969
Smilek, D., Birmingham, E., Cameron, D., Bischof, W., & Kingstone, A.
(2006). Cognitive ethology and exploring attention in real-world scenes.
Brain Research,1080(1), 101–119. https://doi.org/10.1016/j.brainres
.2005.12.090
Smith, P. L. (1998). Attention and luminance detection: A quantitative anal-
ysis. Journal of Experimental Psychology: Human Perception and Per-
formance,24(1), 105–133. https://doi.org/10.1037/0096-1523.24.1.105
Spehar, B., & Owens, C. (2012). When do luminance changes capture
attention? Attention, Perception, & Psychophysics,74(4), 674–690.
https://doi.org/10.3758/s13414-011-0266-8
Sui, J., & Liu, C. H. (2009). Can beauty be ignored? Effects of facial
attractiveness on covert attention. Psychonomic Bulletin & Review,
16(2), 276–281. https://doi.org/10.3758/PBR.16.2.276
Summerfield, C., Egner, T., Mangels, J., & Hirsch, J. (2006). Mistaking a
house for a face: Neural correlates of misperception in healthy humans.
Cerebral Cortex,16(4), 500–508. https://doi.org/10.1093/cercor/bhi129
Takahashi, K., & Watanabe, K. (2013). Gaze cueing by pareidolia faces.
Perception,4(8), 490–492. https://doi.org/10.1068/i0617sas
Tanaka, J. W., & Farah, M. J. (1993). Parts and wholes in face recognition.
Quarterly Journal of Experimental Psychology A: Human Experimental
Psychology,46(2), 225–245. https://doi.org/10.1080/14640749308401045
Tanaka, J. W., & Simonyi, D. (2016). The “parts and wholes”of face rec-
ognition: A review of the literature. Quarterly Journal of Experimental
Psychology: Human Experimental Psychology,69(10), 1876–1889.
https://doi.org/10.1080/17470218.2016.1146780
Tarr, M. J., & Gauthier, I. (2000). FFA: A flexible fusiform area for subor-
dinate-level visual processing automatized by expertise. Nature Neuro-
science,3(8), 764–769. https://doi.org/10.1038/77666
Theeuwes, J., & Van der Stigchel, S. (2006). Faces capture attention: Evi-
dence from inhibition of return. Visual Cognition,13(6), 657–665.
https://doi.org/10.1080/13506280500410949
Tsao, D. Y., Freiwald, W. A., Tootell, R. B. H., & Livingstone, M. S.
(2006). A cortical region consisting entirely of face-selective cells. Sci-
ence,311(5761), 670–674. https://doi.org/10.1126/science.1119983
Turatto, M., & Galfano, G. (2000). Color, form and luminance capture
attention in visual search. Vision Research,40(13), 1639–1643. https://
doi.org/10.1016/S0042-6989(00)00061-4
Võ, M. L.-H., Smith, T. J., Mital, P. K., & Henderson, J. M. (2012). Do the
eyes really have it? Dynamic allocation of attention when viewing mov-
ing faces. Journal of Vision,12(13), 3. https://doi.org/10.1167/12.13.3
Wang, C.-A., Nguyen, K. T., & Juan, C.-H. (2021). Linking Pupil Size
Modulated by Global Luminance and Motor Preparation to Saccade
Behavior. Neuroscience,476,90–101. https://doi.org/10.1016/j
.neuroscience.2021.09.014
Willenbockel, V., Sadr, J., Fiset, D., Horne, G. O., Gosselin, F., & Tanaka,
J. W. (2010). Controlling low-level image properties: The SHINE tool-
box. [journal article]. Behavior Research Methods,42(3), 671–684.
https://doi.org/10.3758/BRM.42.3.671
Willis, J., & Todorov, A. (2006). First impressions: Making up your mind
after a 100-ms exposure to a face. Psychological Science,17(7),
592–598. https://doi.org/10.1111/j.1467-9280.2006.01750.x
Yantis, S., & Hillstrom, A. P. (1994). Stimulus-driven attentional capture:
Evidence from equiluminant visual objects. Journal of Experimental
Psychology: Human Perception and Performance,20(1), 95–107.
https://doi.org/10.1037/0096-1523.20.1.95
Yarbus, A. L. (1967). Eye movements & vision. Plenum Press. https://doi
.org/10.1007/978-1-4899-5379-7
Yin, R. K. (1969). Looking at upside-down faces. Journal of Experimental
Psychology,81(1), 141–145. https://doi.org/10.1037/h0027474
Yovel, G., Levy, J., Grabowecky, M., & Paller, K. A. (2003). Neural corre-
lates of the left-visual-field superiority in face perception appear at mul-
tiple stages of face processing. Journal of Cognitive Neuroscience,
15(3), 462–474. https://doi.org/10.1162/089892903321593162
Received December 5, 2020
Revision received November 3, 2021
Accepted November 8, 2021 n
SOCIAL ATTENTION AND GENERAL MECHANISMS 311
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
A preview of this full-text is provided by American Psychological Association.
Content available from Journal of Experimental Psychology Human Perception & Performance
This content is subject to copyright. Terms and conditions apply.
