Distinct Attention Capture for Self- and Familiar Faces in Visual Search

Distinct Attention Capture for Self- and Familiar Faces in Visual Search | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Distinct Attention Capture for Self- and Familiar Faces in Visual Search Taylor Marcus, Anna Wood, Brianna Hunter, Julie Markant This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8311098/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Faces are salient social stimuli that convey critical information for communication but compete with other inputs for limited attentional resources. Selection among these inputs can be guided by multiple factors, including the perceptual salience of a stimulus, its relevance to task goals, its reward value, or prior learning about it. One’s own face captures attention even when it is neither perceptually salient nor task-relevant. This self-face bias has been proposed to reflect reward value, though others suggest it reflects mere familiarity. Prior studies have compared attention to the self- versus other familiar, but less rewarding, faces, yet findings have been mixed and these inconsistencies may reflect varying task demands (e.g., the goal-relevance of faces across paradigms). The present study used an attention capture paradigm to compare automatic attention orienting to the self-, familiar, and stranger faces that appeared as a task-irrelevant distractor within multi-object search arrays of varying set size. The presence of any face distractor impaired target detection performance, confirming that faces capture attention even when irrelevant to an ongoing task. However, distraction also varied across both face identity and the context of the search array. Faces facilitated target detection at moderate set sizes but interfered at larger set sizes. Moreover, when the target was present, the self-face captured attention most within moderate set sizes, whereas familiar faces did so at the largest set size. These findings demonstrate context-dependent, identity-specific attention capture and suggest that the attention biases to the self- and familiar faces may reflect different mechanisms. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Faces are common stimuli in our environments that provide critical information for communication and social interactions (e.g., Stolzenberg et al., 2022 ; Willis & Todorov, 2006 ). Individuals are strongly biased to attend to faces, even when they are not relevant to current task goals (e.g. Bindemann et al., 2005 ; Riby et al., 2012 ). In particular, individuals are biased to attend to their own face compared to an unfamiliar face (i.e., the self-face attention bias ), indicated by longer looking to the self-face and increased distraction by the self-face when it appears as a distractor in a visual search task (Devue & Bredart, 2008; Devue et al., 2009 ). Some have argued that the self-face bias reflects underlying reward processing, given that the self-face activates neural reward regions (e.g. Ota & Nakano, 2021 ). However, familiarity may also play a critical role, given evidence that close others may also automatically capture attention (Bortolon et al., Zochowska et al, 2023). As a result, the mechanisms contributing to the self-face attention bias remain unclear. The current study addressed this gap by examining whether adults showed differential attention capture by the self-face compared to familiar or unfamiliar faces. We also conducted exploratory analyses examining whether the self-face attention bias is moderated by individual differences in self-esteem, based on past findings linking self-esteem to both reward processing and automatic orienting to the self-face (Izuma et al., 2018 ). Although faces are ubiquitous, they compete with many other stimuli for cognitive processing resources. We cannot simultaneously process all the information available in our cluttered visual environments, and therefore must select inputs that are most relevant to our current goals while filtering irrelevant stimuli (Chun et al., 2011 ). This selection of relevant inputs is mediated by multiple mechanisms including exogenous selection, which is based on the perceptual features of a stimulus, and endogenous selection, which is based on current task goals (Zelinsky & Bisley, 2015 ). Many factors beyond perceptual salience and goal relevance can also drive selective attention (Anderson et al., 2011 ; Awh et al., 2012 ; Carrigan et al., 2019 ; Failing & Theeuwes, 2014 ). For example, stimuli that have been previously associated with a reward robustly capture attention, even when they are not perceptually salient or goal-relevant (Engelmann & Pessoa, 2007 ; Libera & Chelazzi, 2006 ; Munneke et al., 2015 ; Theeuwes & Belopolsky, 2012 ). Theeuwes & Belopolsky ( 2012 ) examined automatic attention capture of stimuli that were associated with either a high or low monetary reward. Participants completed an initial training phase in which they learned to associate certain shapes with either a high or low monetary reward. They next completed an attention capture task in which they searched for a target shape in the presence of task-irrelevant distractors. On some of the trials, one of the task-irrelevant distractors was either the high or low reward stimulus from the training phase. Participants demonstrated stronger attention capture to the high reward distractor than the low reward distractor, even though all distractors were similar in perceptual salience (i.e. red shapes) and irrelevant to the task. Overall, this suggests that reward-associated stimuli capture attention via motivational or value/reward-driven attention , which is independent of exogenous and endogenous selection. Individuals are strongly biased to orient to and sustain attention on faces, even when this disrupts performance on another task (Bindemann et al., 2005 ; Langton et al., 2008 ; Riby et al., 2012 ). Beyond faces in general, attention is also biased toward specific face identities (e.g. Devue & Brédart, 2008 ; Hunter & Markant, 2023b ; Nakamura et al., 2017 ). In particular, individuals show a self-face attention bias , indicated by longer looking times or greater distraction by their own face compared to a stranger’s face (Devue & Bredart, 2008; Devue, Van der Stigchel, et al., 2009 ). Some have argued that this self-face bias reflects reward-based attention mechanisms, as the self-face activates neural reward regions (Alzueta et al., 2019 ; Jublie & Kumar, 2021 , 2022 ; Ota & Nakano, 2021 ; Zhan et al., 2016 ). However, familiarity may also play a critical role, as attention can also be biased to familiar objects (e.g. Diliberto et al., 2000 ; Nelson & Palmer, 2007 ) and regular exposure to the self-face begins in infancy (Sugden & Moulson, 2019 ). As a result, the mechanisms contributing to the self-face attention bias remain unclear. Prior work has addressed this question by using a range of paradigms to investigate differences in attention biases towards the self-and other familiar faces, such as friends and classmates (e.g., Bola et al., 2021 ; Bortolon et al., 2018 ; Bredart et al., 2006; Devue, et al., 2009 ). For example, in a modified Flanker task, participants identified their own name or a classmate’s name in the center of a display while a face appeared on the side. The self-face slowed performance more than familiar faces, suggesting stronger interference (Bredart et al., 2006). Other paradigms have shown similar effects, including a visual search in which participants searched arrays of faces to find the face making an “m" or “o” sound with its mouth (Devue et al., 2009 ) and a head orientation task, in which participants judged the direction of the face (Sui et al., 2006 ). Both of these studies showed stronger biases to the self-face than familiar faces. However, other studies have yielded mixed results. In a dot-probe task, participants see the self- and familiar faces briefly appear on opposite sides of the screen, followed by a target in one of those locations. Faster responses to targets following one face type indicate biased orienting toward that face. Although some work found biased attention to the self-face (Jublie & Kumar, 2022 ), others found no difference in reaction time across the self- and familiar faces (Bola et al., 2021 ; Żochowska et al., 2023 ). Participants similarly showed no difference during a delayed matching task, in which they judged whether two sequentially presented faces matched in identity (Bortolon et al., 2018 ). These inconsistent findings may be a result of task designs in which the self- or familiar faces could serve as endogenous targets. In the dot-probe, faces served as cues that could predict target locations. In the Flanker, the self-face sometimes corresponded to the target name, and in the matching, visual search, and head-orientation tasks, the faces were direct response targets. This overlap between task goals and face relevance may have engaged endogenous, goal-driven attention, obscuring the contribution of motivational salience to the self-face bias. In contrast, the attention capture task isolates automatic, stimulus-driven attention by presenting task-irrelevant distractors unpredictably alongside targets (e.g., Hunter & Markant, 2023b ; Langton et al., 2008 ). Because distractor identity and location are unrelated to the target, the task minimizes endogenous influences. Prior work comparing attention tasks showed that attention capture paradigms are more sensitive than dot-probe or cueing tasks in detecting face-related attention biases (Sigurjónsdóttir et al., 2020 ). However, to our knowledge, no study has compared automatic orienting to self- versus familiar faces using this task. To address this gap, we used an attention capture task to determine whether the self-face interfered with task performance more than a familiar or unfamiliar face when presented as a task-irrelevant distractor. Participants searched for a target among multiple distractors and during some trials the self-face, a familiar face, or a stranger face appeared as one of these distractors. Slower or less accurate target detection indicated increased distraction, reflecting automatic orienting to the face. We predicted that the self-face would capture attention to a greater degree than familiar and stranger faces. Finally, we also conducted exploratory analyses to examine whether self-face attention-capture was moderated by individual differences in self-esteem, or the value one assigns to themselves. Prior work demonstrated links between higher self-esteem and increased neural reward activity in response to the self-face (Izuma et al., 2018 ), as well as stronger attention biases toward the self-face (Salehinejad et al., 2020 ) suggesting that individuals with higher self-esteem may show increased attention capture by the self-face. Methods Participants We tested 66 adults between the ages of 18 to 35 years old (21 M; 42 F; 3 Other; M age = 20.82, SD = 3.63). An a priori power analysis ( a = .05, power = .8) indicated that a minimum sample size of 52 would be needed to observe main effects similar to those previously observed with this task (i.e., h 2 = .18; Riby et al., 2012). All participants had normal or corrected-to-normal vision and hearing and reported no neurological or developmental diagnoses (e.g., autism spectrum disorder, attention defecit hyperactivity disorder). According to self-report, 72.7% of participants were White/Caucasian, 6.1% were Hispanic, 3.0% were Black/African American, 7.6% were Asian, and 10.6% were more than one race. We tested an additional 37 participants who were excluded from analyses because they did not provide usable images for the self-face or familiar face stimuli (see Materials and Procedure; N = 32); their accuracy on the task was < 3 SD below the group mean ( N = 2), the participant knew the identity of the stranger face used in the task ( N = 1), or due to technical errors ( N = 2). All participants provided written informed consent prior to participation and received a $5 gift card or academic credit as compensation for completing the study. All study protocols were approved by the local Institutional Review Board. Materials and Procedure Attention capture task. We measured attention capture by the self-face using a task based on Hunter and Markant (2023). Figure 1 presents a schematic of the task (see Supplemental Figure 1 for all trial types). In this task, participants responded with key presses to indicate whether a target was present or absent in a search array. The target appeared within an array of distractors containing 3, 6, or 9 images (150 x 150 pixels per image) appearing in a 3 x 3 grid (200 x 200 pixels per square). The target images were three unique butterfly images and non-face distractors included flowers, fruits, houses, plants, shells, and shoes. During a subset of trials ( face-present trials ), a face appeared as one of the distractors in the array. The identity of the face varied across the face-present trials, including either the participant’s own face (i.e., “self-face”), a non-romantic friend or acquaintance (i.e. “familiar face”), or a stranger's face that was unfamiliar to the participant (i.e., “stranger face”). Based on participant ratings, the self- and familiar face stimuli were more familiar and preferred compared to the stranger faces, but there were no differences in these ratings across the self- and familiar faces (see Supplementary Materials for details). These ratings thus confirm that the stranger face stimuli used were not known to the participants. Participants provided the self-face and familiar face images prior to the study visit based on the same guidelines for both face types. We instructed participants to provide images that included the face completely in the frame, directly facing the camera with no part of the face cut off, and did not contain glasses, hats, or any accessories that obscured the face. We also asked participants to submit face images that exhibited a neutral expression with a closed mouth and direct eye gaze. Finally, we asked participants to submit photos that were taken within the past 6 months in good lighting and with no filters added. We cropped all face images to an oval shape to remove external features (e.g., hair) and the image background. We used each self-face image as a stranger face for another participant to control for differences in perceptual salience across images. We gender and race-matched the self and stranger faces whenever possible[1]. We did not specify that the familiar images should be race or gender-matched to avoid biasing who the participants selected as their familiar other; however most familiar face images matched the participants’ gender and race[2]. We administered the attention capture task via PsychoPy (Peirce et al., 2019) at our lab using either a desktop computer (1920 x 1080; N = 26) or a laptop (2560 x 1600; N = 40). The experiment began with six practice trials with audiovisual feedback, followed by the primary task. Participants responded using the Z and M keys to indicate the presence or absence of the butterfly target. The corresponding letter and response type (present vs. absent) were counterbalanced across participants to control for differences in handedness. At the start of each trial, an empty grid appeared for 500 ms. Then, the search array appeared and remained visible for up to 3,500 ms or until the participant responded. After each trial, a blank screen appeared for 1000 ms. There were a total of 108 trials, with an equal number of target present and target absent trials (54 target present, 54 target absent), as well as an equal number of face present and face absent trials (54 face present, 54 face absent). Within the face present trials, there were an equal number of trials in which the self-, familiar-, and stranger-face appeared as a distractor (18 self-face present, 18 familiar-face present, 18 stranger-face present), split evenly across the set size 3, 6, and 9 trials (9 self-, familiar- and stranger-faces each). Across the task, the target and face images were counterbalanced so that each face, butterfly, and distractor appeared in all locations an equal number of times. Once target and face locations were determined, non-face distractor images were randomly positioned in the remaining locations and occurred with equal frequency throughout the task. All trial types were preselected, ensuring that each participant observed the identical set of 108 search arrays, presented in a randomized sequence. We assessed participants’ accuracy and response times to detect the butterfly target within each search array. We computed accuracy based on the proportion of trials in which participants correctly indicated the presence or absence of the butterfly target. We computed reaction time by averaging the time it took participants to respond correctly. We calculated reaction time only for accurate trials and excluded any responses that were less than 200ms or more than two standard deviations slower than the participants’ average reaction time. Attention capture by the face distractors is indicated by poorer accuracy and/or slower reaction times to detect the target. Questionnaires. Participants completed two questionnaires to assess individual differences in self-esteem and self-consciousness. However, because these measures were highly correlated, analyses focused on the measure of self-esteem assessed via the Rosenberg Self-Esteem Scale (Rosenberg, 1965). See Supplementary Materials for additional details. [1] We were unable to fully gender- and race-match the self and stranger faces for N = 8 participants. However, the overall pattern of results did not change when we limited analyses to participants (N = 58) with fully gender and race-matched faces. [2] Since participants selected their own familiar images, some of familiar faces were not gender- and race-matched to the participants (N = 7). The overall pattern of results did not change when we limited analyses to participants (N = 59) with fully gender- and race-matched faces. Results Preliminary Analyses Initial analyses indicated that there were no significant effects of gender on any variables of interest ( p ’s > .055). Older participants showed slower overall target response times ( r (66) = .25, p = .041), but this effect of age did not interact with face presence or face type ( p ’s > .233) . As a result, we did not include age or gender in any subsequent analyses. For our primary analyses, we first examined the effects of overall face presence on target detection performance using a repeated-measures ANOVA with within-subject factors of target presence (present, absent), face presence (present, absent), and set size (three, six, nine). Next, we focused on trials in which a face was present and examined effects of face type on target detection performance using a repeated-measures ANOVA with within-subject factors of target presence (present, absent), face type (self, familiar, stranger), and set size (three, six, nine). For all analyses we conducted separate analyses to examine accuracy and response time measures and used Greenhouse-Geisser corrections when necessary to correct for violations of sphericity. Effects of Face Presence Accuracy. Participants were overall less accurate during target present vs. target absent trials, F (1,65) = 92.98, p < .001, h p 2 = .59 ( M Present = .96, SD = .03; M Absent = .99, SD = .01). There was no overall effect of face presence on accuracy, F (1,65) = 1.353, p = .249, h p 2 = .02 ( M Present = .98, SD = .02; M Absent = .98, SD = .02). There was a main effect of set size on accuracy, F (1.71, 111.39) = 4.81, p = .014, h p 2 = .07, such that participants were more accurate during set size 3 trials ( M = .98, SD = .018) compared to set size 6 ( M = .97, SD = .03), t (65) = 2.75, p = .008, d = .34), and set size 9 trials ( M = .97, SD = .03), t (65) = 3.28, p = <.001, d = .40. There was no difference between set size 6 and set size 9 trials ( p = .944). Results also indicated a target presence x set size interaction, F (1.81, 117.40) = 4.39, p = .017, h p 2 = .06, and a face presence x set size interaction, F (2, 130) = 5.630, p = .005, h p 2 = .08, which were further moderated by a target presence x face presence x set size interaction, F (1.79, 116.45) = 10.88, p < .001, h p 2 = .14 (Figure 2). Follow-up analyses revealed a significant face presence x set size interaction only during the target present condition, F (1.81, 117.38) = 9.80, p < .001, h p 2 = .13, but not during the target absent condition ( p = .218). When the target was present, the presence vs. absence of a face distractor had no effect on accuracy during set size 3 trials ( p = .370). However, during set size 6 trials participants responded more accurately when a face distractor appeared ( M = .97, SD = .04) compared to trials without a face distractor, M = .94, SD = .07; F (1, 65) = 6.74, p = .012, h p 2 = .09. During set size 9 trials participants instead responded less accurately when a face distractor appeared ( M = .94, SD = .05) compared to trials without a face distractor, M Absent = .97, SD = .05; F (1, 65) = 8.80, p = .004, h p 2 = .12. Reaction Time. Participants were overall faster to respond during the target present vs. target absent trials, F (1,65) = 159.32, p < .001, h p 2 = .71; M Present = 651.36, SD = 111.42; M Absen t = 795.85, SD = 176.86, and overall slower to respond during the face present vs. face absent trials, F (1,65) = 28.20, p < .001, h p 2 = .30; M Present = 737.88, SD = 151.65; M Absent = 709.33, SD = 131.62. There was also a main effect of set size on reaction time, F (1.25, 81.51) = 182.09, p < .001, h p 2 = .74, such that participants were slower to respond as the number of distractors in the set size increased ( M SetSize3 = 642.91, SD = 110.49; M SetSize6 = 722.95, SD = 138.61; M SetSize9 = 804.95, SD = 179.97; p ’s < .001). Results also indicated a target presence x face presence interaction, F (1,65) = 7.95, p = .006, h p 2 = .11, a target presence x set size interaction F (1.42, 92.17) = 74.62, p < .001, h p 2 = .53, and a face presence x set size interaction F (1.77, 115.33) = 36.83, p < .001, h p 2 = .36. These effects were further moderated by a significant target presence x face presence x set size interaction, F (1.62, 105.05) = 40.77, p < .001, h p 2 = .39 (Figure 3). Follow-up analyses revealed a significant face presence x set size interaction for only the target present condition, F (1.67, 108.31) = 83.03, p < .001, h p 2 = .56, but not the target absent condition ( p = .478). When the target was present, participants were slower to respond during set size 3 trials when a face appeared as a distractor ( M present = 615.95 SD = 109.75) compared to trials without a face distractor, M absent = 689.85 SD = 120.85; F (1, 65) = 9.79, p = .003, h p 2 = .13. Participants showed a similar pattern during set size 9 trials, with slower responses when a face appeared as a distractor ( M Present = 738.19 SD = 160.87) compared to trials without a face distractor, M Absent = 642.41 SD = 115.29; F (1, 65) = 76.51, p < .001, h p 2 = .54. However, during set size 6 trials participants were instead faster to respond when a face appeared as a distractor ( M Presen t = 628.28 SD = 113.46) compared to trials without a face distractor, M Absent = 689.85 SD = 120.85; F (1, 65) = 59.98, p < .001, h p 2 = .47. Summary. Overall, participants demonstrated poorer target detection performance, indicated by poorer accuracy and slower reaction times, during trials with larger set sizes and during target present trials compared to target absent trials. The presence of the face distractors also resulted in poorer target detection performance, as participants showed overall slower reaction times to respond to the target when a face was present in the array. However, the effects of face presence also depended on target presence and set size, such that the presence of face distractors facilitated performance (i.e., improved accuracy and faster reaction times) during target present, set size 6 trials but instead resulted in poorer accuracy and slower reaction times during target present, set size 9 trials. Effects of Face Type Accuracy. Results of the target presence x face type x set size ANOVA indicated that participants were overall less accurate during target present vs. target absent trials, F (1,65) = 55.758, p < .001, h p 2 = .46; M Present = .96, SD = .03; M Absent = .99, SD = .01. There was a main effect of set size on accuracy, F (1.76, 114.42) = 5.07, p = .010, h p 2 = .07, such that participants were more accurate during set size 3 trials ( M = .98, SD = .018) compared to set size 6, M = .97, SD = .03; t (65) = 2.75, p = .008, d = .34, and set size 9 trials, M = .97, SD = .03; t (65) = 3.28, p = <.001, d = .40. There was no difference between set size 6 and set size 9 trials ( p = .944). There was also a marginally significant main effect of face type on accuracy, F (1.75, 113.91) = 3.11, p = .055, h p 2 = .05. Participants were overall less accurate during trials in which the familiar face ( M = .97, SD = .03) or self-face ( M = .97, SD = .04) appeared as a distractor compared to trials in which the stranger face was a distractor, M = .98, SD = .03; t Familiar (65) = -2.61, p = .011, d = -.32; t Self (65) = -2.18, p = .033, d = -0.27. However, there was no difference across the familiar and self-face trials ( p = .842). Results also indicated a face type x set size interaction, F (3.13, 203.61) = 9.44, p < .001, h p 2 = .13, which was further moderated by a target presence x face type x set size interaction, F (3.45, 223.45) = 8.55, p < .001, h p 2 = .12 (Figure 4). Follow-up analyses revealed a significant face type x set size interaction in only the target present condition only, F (3.15, 119.03) = 10.76, p < .001, h p 2 = .14, but not the target absent condition ( p = .476). Within the target present condition, there was no effect of face type during set size 3 trials ( p = .906), but there was a significant effect of face type during both set size 6 trials, F (1.26, 81.98) = 15.30, p < .001, h p 2 = .19, and set size 9 trials, F (2, 130) = 7.03, p = .001, h p 2 = .10. However, the direction of these effects varied across set sizes 6 and 9. During set size 6 trials, participants showed poorer target detection accuracy in the presence of the self-face distractor ( M = .93, SD = .12) compared to trials with either the familiar face distractor, M = .98, SD = .05; t (65) = 3.41, p < .001, d = 0.42, or the stranger face distractor, M = .99, SD = .02; t (65) = 4.67, p < .001, d = 0.58. Participants also showed poorer accuracy in the presence of the familiar face distractor compared to the stranger face distractor, t (65) = 2.14, p = .036, d = 0.26. In contrast, during set size 9 trials, participants showed better target detection accuracy in the presence of the self-face distractor ( M = .98, SD = .08) compared to both the familiar face distractor, M = .91, SD = .12; t (65) = 3.68, p < .001, d = 0.45, and the stranger face distractor, M = .94, SD = .10; t (65) = 2.01, p = .049, d = 0.25. There was no difference in accuracy when the familiar and stranger faces appeared as distractors, t (65) = 1.80, p = .076, d = 0.22. Reaction Time. Results of the target presence x face type x set size ANOVA indicated a main effect of face type on reaction time, F (2, 130) = 5.05, p = .008, h p 2 = .07. Participants were overall slower to respond during trials in which the familiar face ( M = 741.79, SD = 154.79) or self-face ( M = 745.28, SD = 157.62) appeared as a distractor compared to trials in which the stranger face was a distractor, M = 726.56, SD = 150.95; t Familiar (65) = 2.30, p = .025, d = .28; t Self (65) = 3.03, p = .003, d = .37. However there was no difference in target reaction times when the familiar face and self-face appeared as distractors ( p = .562). In addition to this main effect there was also a significant target presence x face type x set size interaction, F (3.53, 229.28) = 4.51, p = .003, h p 2 = .07 (Figure 5). Follow-up analyses revealed a face type x set size interaction in only the target present condition, F (2.92, 189.67) = 12.80, p < .001, h p 2 = .17, but not the target absent condition ( p = .183). Within the target present condition, there was no effect of face type during set size 3 trials ( p = .394), but there was a significant effect of face type during both the set size 6 trials, F (2, 130) = 24.67, p < .001, h p 2 = .28, and set size 9 trials, F (1.67, 108.79) = 7.33, p < .001, h p 2 = .10. However, the direction of these effects varied across set size 6 and 9. During set size 6 trials, participants responded to the target more slowly when the self-face distractor was present ( M = 675.16, SD = 142.35) compared to trials with either the familiar face distractor, M = 611.52, SD = 129.30; t (65) = 5.27, p < .001, d = .65, or the stranger face distractor, M = 598.17, SD = 103.42; t (65) = 7.12, p < .001, d = .88. In contrast, during set size 9 trials, participants responded to the target faster when the self-face distractor was present ( M = 700.07, SD = 139.23) compared to trials with the familiar face distractor, M = 776.25, SD = 185.51; t (65) = 5.04, p < .001, d = 0.62. However, there was no difference in response times in the presence of the self-face distractor compared to the stranger face distractor during set size 9 trials, M = 738.25, SD = 223.56; t (65) = 1.82, p = .074, d = 0.22. Participants also showed no difference in response times during either set size 6 or set size 9 trials in which the familiar face distractor appeared compared to those with the stranger face distractor ( p ’s > .074). Summary. Participants showed overall poorer target detection, indicated by poorer accuracy and slower reaction time, when the distractor was a familiar face or the self-face compared to a stranger face. However, these effects were moderated by target presence and set size. When the target was present, there was no effect of face type during set size 3 trials and the direction of the face type effects varied across set sizes 6 and 9. During set size 6 trials, participants showed the slowest and least accurate target detection when the self-face distractor was present and showed the best target detection performance when the stranger face distractor appeared. In contrast, during set size 9 trials, target detection was least affected by the presence of the self-face distractor and participants instead showed the poorest performance when the familiar face distractor appeared. These findings indicate that the familiar and self-face distractors had different effects on target detection performance and suggest that the presence of the self-face distractor may hinder performance to the greatest extent during set size 6 trials. Effects of Self-Esteem We conducted a final exploratory analysis to examine whether self-esteem moderates the effects of face type on target detection performance described above. We examined target detection performance using a repeated-measures ANCOVA with within-subject factors of target presence (present, absent), face type (self, familiar, stranger), and set size (three, six, nine), with the self-esteem composite score centered as a covariate. Results indicated no significant effects of face type, target type, set size, or self-esteem for the model examining target detection accuracy ( p’s < .100). There was a marginally significant face type x set size x self-esteem interaction on reaction time, F (3.12, 199.73) = 2.60, p = .051, h p 2 = .04. However, follow-up analyses indicated that self-esteem was not related to reaction times during any trials with the self, familiar or stranger faces ( p ’s > .202). For more details see the Supplementary Materials. Discussion Prior investigations of the role of reward and familiarity in the self-face bias yielded mixed results, which may reflect the use of task designs in which faces were task-relevant or predictive. The present study addressed this limitation by using an attention capture paradigm that isolates automatic, stimulus-driven orienting, allowing a more precise assessment of the role of reward and familiarity in the self-face attention bias. Although the presence of any face distractor impaired target detection, this interference was specific to trials in which the target was present and depended on set size. Specifically, face distractors facilitated target detection performance during target present, set size 6 trials but instead resulted in increased distraction during target present, set size 9 trials. Distraction by faces also depended on face identity, as attention capture was strongest to the self-face during set size 6 trials but to the familiar face during set size 9 trials. Overall, these findings demonstrate differential attention capture across self- and familiar faces and suggest that these effects are sensitive to task context. Target detection performance was consistent with past research using visual search and attention capture tasks. Participants were more accurate but slower when the target was absent, likely reflecting increased time to confirm its absence (Godwin et al., 2015 ; Langton et al., 2008 ; Peltier & Becker, 2016 ; Riby et al., 2012 ). Perfomance also declined as the number of distractors increased, reflecting greater difficulty suppressing task-irrelevant items (Botch et al., 2023 ; Carrasco et al., 2004 ; Jerde et al., 2011 ; Mazyar et al., 2013 ; Palmer, 1994 ). Similar effects have been observed consistently in studies using the same task design, underscoring the validity of the current task (Hunter & Markant, 2023a , 2023b ; Langton et al., 2008 ; Riby et al., 2012 ). Participants showed slower target detection when any face appeared as a distractor, indicating that faces captured attention and disrupted performance. These results replicate previous findings that faces capture adults’ attention, even when task-irrelevant (Devue et al., 2009 ; Hodsoll et al., 2011 ; Langton et al., 2008 ; Riby et al., 2012 ). In particular, our results converged with prior attention capture findings that the presence of a face slowed task performance only when the target was present (Langton et al., 2008 ; Riby et al., 2012 ). The current results also extended these past findings by demonstrating that face presence effects varied across set size. Specifically, in target present trials, face distractors disrupted target detection at set sizes 3 and 9, but instead facilitated performance at set size 6. Face distractors may affect performance differently depending on participants’ search strategy. Specifically, these effects may reflect a shift from a global search strategy at moderate set sizes to a serial search strategy in denser arrays (Findlay, 1982 ; Pomplun et al., 2013 ). However, it was beyond the scope of the current research to determine the search strategies that participants engaged during each set size. Future work can test this possibility by examining eye movements patterns during this task or manipulating array layout and density to determine how these factors interact with set size to affect attention capture by faces. Beyond general distraction by faces, participants showed increased attention capture by the self- and familiar faces compared to the stranger face, but these effects depended on task context. Self- and familiar-face biases only emerged at certain set sizes, suggesting that face identity interacted with search demands rather than operating uniformly. This aligns with prior research demonstrating self-face advantages only under specific task conditions or measures (Bola et al., 2021 ; Devue & Brédart, 2008 ; Hunter & Markant, 2023b ; Żochowska et al., 2023 ). Together, these findings suggest that identity-based distraction is embedded within broader dynamics of search strategy and cognitive or task demands. Future work should test how self- and familiar face attention biases generalize to other task designs, including naturalistic settings where individuals frequently view their own face (e.g., online meetings/classes). While context-dependent, this study clearly demonstrated differential attention capture by the self- and familiar faces, aligning with theories that self-related stimuli are intrinsically rewarding and prioritized for attentional selection (Northoff & Hayes, 2011 ; Sui & Humphreys, 2015 ; Zhan et al., 2016 ). Comparable patterns have been observed in children, in which caregiver faces captured attention during target present set size 6 trials, but stranger faces caused increased distraction during target present set size 9 trials. Critically, the caregiver face, like the self-face, is a rewarding stimulus for young children (Minagawa-Kawai et al., 2008 ). The current study thus showed a similar pattern of results in that participants showed increased attention capture by the more rewarding face identity during trials in which the task difficulty was moderate. Importantly, these results are unlikely to reflect goal-driven or low-level visual salience. The faces were presented as task-irrelevant distractors and participants were unaware that they would appear in the search arrays, suggesting that orienting to the faces was not based primarily on endogenous mechanisms. We also reduced differences in low-level salience by using stringent photo requirements and cropped extraneous features from the images to reduce major perceptual differences across the faces. However, while we yoked the self- and stranger face images as much as possible, not all self- and stranger images were fully yoked and the familiar face images were not yoked at all, which may have created inconsistencies in the stimuli. Future studies could further minimize stimulus variability by fully yoking familiar and self-face conditions (e.g., recruiting participants in pairs). Overall, these findings converge to suggest that these attention biases may be driven by reward-based selection mechanisms. However, we cannot rule out familiarity. Participants reported similar familiarity ratings for the self- and familiar faces, suggesting that differential attention capture was not driven by familiarity alone (e.g. Diliberto et al., 2000 ; Nelson & Palmer, 2007 ). However, ceiling effects in familiarity ratings could have masked variability in familiarity that may have contributed to differential attention capture. Neuroimaging research is needed to corroborate these behavioral findings and confirm whether reward-based selection underlies the self-face attention bias. Finally, although we demonstrated group-level differences in attention capture by the self- and familiar faces, these effects may vary across individuals. Our exploratory analyses found no association between self-esteem and the self-face bias. However, our predominantly female (66%) sample limited to a mid-size southern U.S. city may have introduced bias. Prior work indicates that women tend to report lower self-esteem than men (Bleidorn et al., 2016 ), and that both self-esteem (Bleidorn et al., 2016 ) and the magnitude of the self-face attention bias vary across cultures (Румянцева et al., 2023 ). Future work should include more diverse samples to investigate how individual differences moderate attention capture to the self-face. Conclusion In conclusion, this work investigated whether the self-face bias was driven by its rewarding value by comparing automatic attention capture to the self, familiar and stranger faces using an attention capture task designed to minimize endogenous influences. Face distractors disrupted target detection, and this distraction varied by face identity and search array size. Although context-dependent, the results demonstrated differential attention capture by self- and familiar faces. Moreover, by employing an attention capture task in which the faces were distractors from the task, and minimizing perceptual differences across face types by cropping extraneous features and yoking the self and stranger images when available, our results suggest that this distraction by the self-face was not driven merely by perceptual salience or goal relevance. Overall, these findings provide support the role of motivational salience in the self-face attention bias by demonstrating that it is distinguishable from familiarity, exogenous, and endogenous factors. These findings therefore suggest a role for reward-based mechanisms in the self-face attention bias. Statements and Declarations Competing Interests The authors declare no competing interests. Ethics Approval All study protocols were approved by the local Institutional Review Board and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Consent to Participate All participants provided written informed consent prior to participation. Consent for Publiation The authors confirm that the face stimuli provided in Figure 1 are used with permission from study staff. Availability of Data and Materials The datasets generated during the current study are available from the corresponding author on reasonable request. Code Availability Not applicable. Author contributions T.M.: Conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing-original draft, writing—review & editing, visualization. A.W.: Methodology, formal analysis, investigation, data curation, writing-original draft, writing—review & editing. B.H.: Conceptualization, methodology, software, writing—review & editing. J.M.: Conceptualization, methodology, formal analysis, resources, data curation, writing—original draft, writing—review & editing, visualization, supervision, funding acquisition. Acknowledgements We thank the members of the Learning and Brain Development Lab for assistance with participant recruitment and data processing. Author Note We have no conflicts of interest to disclose. Correspondence concerning this article should be addressed to Taylor Marcus. 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Психология человека в образовании, 5 (2), 161–168. https://doi.org/10.33910/2686-9527-2023-5-2-161-168 Additional Declarations No competing interests reported. Supplementary Files SupplementalMaterialsMarcusetalFinal.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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15:39:27","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":173290,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8311098/v1/1ca94db9de3405fdc875e86a.html"},{"id":97849032,"identity":"5697156e-4f03-48bd-a1d8-f77fc1641d03","added_by":"auto","created_at":"2025-12-10 06:25:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75647,"visible":true,"origin":"","legend":"\u003cp\u003eExample stimuli for target present trials. The search array contained the butterfly target and multiple distractors. During face absent trials, all distractors were non-face objects. During face present trials, one of the distractors was either the self-face, a familiar face, or a stranger face. Face stimuli are used with permission from study staff. Nonface stimuli were obtained from royalty-free stock photo websites (e.g. pixabay.com).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8311098/v1/99230c77b024df648b94e734.png"},{"id":97849033,"identity":"bd58e409-2432-414b-861c-c34a5ef76ee6","added_by":"auto","created_at":"2025-12-10 06:25:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":14124,"visible":true,"origin":"","legend":"\u003cp\u003eTarget detection accuracy during face present and face absent trials across set sizes, plotted separately for target absent and target present trials. Error bars represent SEM. *p \u0026lt; .05\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8311098/v1/f95b69804e8e26decb598e45.png"},{"id":97899960,"identity":"c24eba0f-94d1-41a9-a280-3603d56db6e8","added_by":"auto","created_at":"2025-12-10 15:45:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17428,"visible":true,"origin":"","legend":"\u003cp\u003eReaction time of correct responses during face present and face absent trials across set sizes, plotted separately for target absent and target present trials. Error bars represent SEM. *p \u0026lt; .05\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8311098/v1/3891d40c2f74e9cd83b7b154.png"},{"id":97899701,"identity":"9f3c6efc-91ff-48ed-97f9-786d0086e0b2","added_by":"auto","created_at":"2025-12-10 15:44:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":17142,"visible":true,"origin":"","legend":"\u003cp\u003eTarget detection accuracy during face present and face absent trials across set sizes, plotted separately for the target absent and target present conditions. Error bars represent SEM. *p \u0026lt; .05\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8311098/v1/e76d303df4b587b7580fba24.png"},{"id":97849043,"identity":"7aae5f77-9251-48c7-b493-5d38e5d6c982","added_by":"auto","created_at":"2025-12-10 06:25:37","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":19918,"visible":true,"origin":"","legend":"\u003cp\u003eTarget detection reaction time during trials in which the self-face, familiar face and stranger face appeared as distractors, plotted separately across set sizes and target absent and target present conditions. Error bars represent SEM. *p \u0026lt; .05\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8311098/v1/3d4bfdfd3a0d41f60346bc72.png"},{"id":103488922,"identity":"0dd7adf9-0b3e-462d-b782-fd5388bbce0a","added_by":"auto","created_at":"2026-02-26 09:28:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":945292,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8311098/v1/c66626ec-a501-40d0-9e5e-06ecee36d3fc.pdf"},{"id":97849040,"identity":"579befd2-5ba3-4da5-b541-2acbae7d6785","added_by":"auto","created_at":"2025-12-10 06:25:37","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":689363,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalMaterialsMarcusetalFinal.docx","url":"https://assets-eu.researchsquare.com/files/rs-8311098/v1/32c84f2309ec33545f54009c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Distinct Attention Capture for Self- and Familiar Faces in Visual Search","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFaces are common stimuli in our environments that provide critical information for communication and social interactions (e.g., Stolzenberg et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Willis \u0026amp; Todorov, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Individuals are strongly biased to attend to faces, even when they are not relevant to current task goals (e.g. Bindemann et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Riby et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In particular, individuals are biased to attend to their own face compared to an unfamiliar face (i.e., the \u003cem\u003eself-face attention bias\u003c/em\u003e), indicated by longer looking to the self-face and increased distraction by the self-face when it appears as a distractor in a visual search task (Devue \u0026amp; Bredart, 2008; Devue et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Some have argued that the self-face bias reflects underlying reward processing, given that the self-face activates neural reward regions (e.g. Ota \u0026amp; Nakano, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, familiarity may also play a critical role, given evidence that close others may also automatically capture attention (Bortolon et al., Zochowska et al, 2023). As a result, the mechanisms contributing to the self-face attention bias remain unclear. The current study addressed this gap by examining whether adults showed differential attention capture by the self-face compared to familiar or unfamiliar faces. We also conducted exploratory analyses examining whether the self-face attention bias is moderated by individual differences in self-esteem, based on past findings linking self-esteem to both reward processing and automatic orienting to the self-face (Izuma et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough faces are ubiquitous, they compete with many other stimuli for cognitive processing resources. We cannot simultaneously process all the information available in our cluttered visual environments, and therefore must select inputs that are most relevant to our current goals while filtering irrelevant stimuli (Chun et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This selection of relevant inputs is mediated by multiple mechanisms including exogenous selection, which is based on the perceptual features of a stimulus, and endogenous selection, which is based on current task goals (Zelinsky \u0026amp; Bisley, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Many factors beyond perceptual salience and goal relevance can also drive selective attention (Anderson et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Awh et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Carrigan et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Failing \u0026amp; Theeuwes, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For example, stimuli that have been previously associated with a reward robustly capture attention, even when they are not perceptually salient or goal-relevant (Engelmann \u0026amp; Pessoa, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Libera \u0026amp; Chelazzi, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Munneke et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Theeuwes \u0026amp; Belopolsky, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Theeuwes \u0026amp; Belopolsky (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) examined automatic attention capture of stimuli that were associated with either a high or low monetary reward. Participants completed an initial training phase in which they learned to associate certain shapes with either a high or low monetary reward. They next completed an attention capture task in which they searched for a target shape in the presence of task-irrelevant distractors. On some of the trials, one of the task-irrelevant distractors was either the high or low reward stimulus from the training phase. Participants demonstrated stronger attention capture to the high reward distractor than the low reward distractor, even though all distractors were similar in perceptual salience (i.e. red shapes) and irrelevant to the task. Overall, this suggests that reward-associated stimuli capture attention via \u003cem\u003emotivational or value/reward-driven attention\u003c/em\u003e, which is independent of exogenous and endogenous selection.\u003c/p\u003e\u003cp\u003eIndividuals are strongly biased to orient to and sustain attention on faces, even when this disrupts performance on another task (Bindemann et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Langton et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Riby et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Beyond faces in general, attention is also biased toward specific face identities (e.g. Devue \u0026amp; Br\u0026eacute;dart, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hunter \u0026amp; Markant, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e; Nakamura et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In particular, individuals show a \u003cem\u003eself-face attention bias\u003c/em\u003e, indicated by longer looking times or greater distraction by their own face compared to a stranger\u0026rsquo;s face (Devue \u0026amp; Bredart, 2008; Devue, Van der Stigchel, et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Some have argued that this self-face bias reflects reward-based attention mechanisms, as the self-face activates neural reward regions (Alzueta et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jublie \u0026amp; Kumar, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ota \u0026amp; Nakano, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhan et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, familiarity may also play a critical role, as attention can also be biased to familiar objects (e.g. Diliberto et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Nelson \u0026amp; Palmer, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and regular exposure to the self-face begins in infancy (Sugden \u0026amp; Moulson, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As a result, the mechanisms contributing to the self-face attention bias remain unclear.\u003c/p\u003e\u003cp\u003ePrior work has addressed this question by using a range of paradigms to investigate differences in attention biases towards the self-and other familiar faces, such as friends and classmates (e.g., Bola et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bortolon et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Bredart et al., 2006; Devue, et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). For example, in a modified Flanker task, participants identified their own name or a classmate\u0026rsquo;s name in the center of a display while a face appeared on the side. The self-face slowed performance more than familiar faces, suggesting stronger interference (Bredart et al., 2006). Other paradigms have shown similar effects, including a visual search in which participants searched arrays of faces to find the face making an \u0026ldquo;m\" or \u0026ldquo;o\u0026rdquo; sound with its mouth (Devue et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and a head orientation task, in which participants judged the direction of the face (Sui et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Both of these studies showed stronger biases to the self-face than familiar faces. However, other studies have yielded mixed results. In a dot-probe task, participants see the self- and familiar faces briefly appear on opposite sides of the screen, followed by a target in one of those locations. Faster responses to targets following one face type indicate biased orienting toward that face. Although some work found biased attention to the self-face (Jublie \u0026amp; Kumar, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), others found no difference in reaction time across the self- and familiar faces (Bola et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Żochowska et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Participants similarly showed no difference during a delayed matching task, in which they judged whether two sequentially presented faces matched in identity (Bortolon et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese inconsistent findings may be a result of task designs in which the self- or familiar faces could serve as endogenous targets. In the dot-probe, faces served as cues that could predict target locations. In the Flanker, the self-face sometimes corresponded to the target name, and in the matching, visual search, and head-orientation tasks, the faces were direct response targets. This overlap between task goals and face relevance may have engaged endogenous, goal-driven attention, obscuring the contribution of motivational salience to the self-face bias. In contrast, the attention capture task isolates automatic, stimulus-driven attention by presenting task-irrelevant distractors unpredictably alongside targets (e.g., Hunter \u0026amp; Markant, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e; Langton et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Because distractor identity and location are unrelated to the target, the task minimizes endogenous influences. Prior work comparing attention tasks showed that attention capture paradigms are more sensitive than dot-probe or cueing tasks in detecting face-related attention biases (Sigurj\u0026oacute;nsd\u0026oacute;ttir et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, to our knowledge, no study has compared automatic orienting to self- versus familiar faces using this task.\u003c/p\u003e\u003cp\u003eTo address this gap, we used an attention capture task to determine whether the self-face interfered with task performance more than a familiar or unfamiliar face when presented as a task-irrelevant distractor. Participants searched for a target among multiple distractors and during some trials the self-face, a familiar face, or a stranger face appeared as one of these distractors. Slower or less accurate target detection indicated increased distraction, reflecting automatic orienting to the face. We predicted that the self-face would capture attention to a greater degree than familiar and stranger faces. Finally, we also conducted exploratory analyses to examine whether self-face attention-capture was moderated by individual differences in self-esteem, or the value one assigns to themselves. Prior work demonstrated links between higher self-esteem and increased neural reward activity in response to the self-face (Izuma et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), as well as stronger attention biases toward the self-face (Salehinejad et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) suggesting that individuals with higher self-esteem may show increased attention capture by the self-face.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe tested 66 adults between the ages of 18 to 35 years old (21 M; 42 F; 3 Other; \u003cem\u003eM\u003csub\u003eage\u003c/sub\u003e \u003c/em\u003e= 20.82, \u003cem\u003eSD\u003c/em\u003e = 3.63). An \u003cem\u003ea priori\u003c/em\u003e power analysis (\u003cem\u003ea\u003c/em\u003e = .05, \u003cem\u003epower \u003c/em\u003e= .8) indicated that a minimum sample size of 52 would be needed to observe main effects similar to those previously observed with this task (i.e., \u003cem\u003eh\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e = .18; Riby et al., 2012). All participants had normal or corrected-to-normal vision and hearing and reported no neurological or developmental diagnoses (e.g., autism spectrum disorder, attention defecit hyperactivity disorder). According to self-report, 72.7% of participants were White/Caucasian, 6.1% were Hispanic, 3.0% were Black/African American, 7.6% were Asian, and 10.6% were more than one race. We tested an additional 37 participants who were excluded from analyses because they did not provide usable images for the self-face or familiar face stimuli (see Materials and Procedure; \u003cem\u003eN\u003c/em\u003e = 32); their accuracy on the task was \u0026lt; 3 \u003cem\u003eSD \u003c/em\u003ebelow the group mean (\u003cem\u003eN\u003c/em\u003e = 2), the participant knew the identity of the stranger face used in the task (\u003cem\u003eN\u003c/em\u003e = 1), or due to technical errors (\u003cem\u003eN\u003c/em\u003e = 2). All participants provided written informed consent prior to participation and received a $5 gift card or academic credit as compensation for completing the study. All study protocols were approved by the local Institutional Review Board.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAttention capture task.\u003c/em\u003e\u003c/strong\u003eWe measured attention capture by the self-face using a task based on Hunter and Markant (2023). Figure 1 presents a schematic of the task (see Supplemental Figure 1 for all trial types). In this task, participants responded with key presses to indicate whether a target was present or absent in a search array. The target appeared within an array of distractors containing 3, 6, or 9 images (150 x 150 pixels per image) appearing in a 3 x 3 grid (200 x 200 pixels per square). The target images were three unique butterfly images and non-face distractors included flowers, fruits, houses, plants, shells, and shoes. During a subset of trials (\u003cem\u003eface-present\u003c/em\u003e \u003cem\u003etrials\u003c/em\u003e), a face appeared as one of the distractors in the array. The identity of the face varied across the face-present trials, including either the participant\u0026rsquo;s own face (i.e., \u0026ldquo;self-face\u0026rdquo;), a non-romantic friend or acquaintance (i.e. \u0026ldquo;familiar face\u0026rdquo;), or a stranger\u0026apos;s face that was unfamiliar to the participant (i.e., \u0026ldquo;stranger face\u0026rdquo;). Based on participant ratings, the self- and familiar face stimuli were more familiar and preferred compared to the stranger faces, but there were no differences in these ratings across the self- and familiar faces (see Supplementary Materials for details). These ratings thus confirm that the stranger face stimuli used were not known to the participants.\u003c/p\u003e\n\u003cp\u003eParticipants provided the self-face and familiar face images prior to the study visit based on the same guidelines for both face types. We instructed participants to provide images that included the face completely in the frame, directly facing the camera with no part of the face cut off, and did not contain glasses, hats, or any accessories that obscured the face. We also asked participants to submit face images that exhibited a neutral expression with a closed mouth and direct eye gaze. Finally, we asked participants to submit photos that were taken within the past 6 months in good lighting and with no filters added. We cropped all face images to an oval shape to remove external features (e.g., hair) and the image background. We used each self-face image as a stranger face for another participant to control for differences in perceptual salience across images. We gender and race-matched the self and stranger faces whenever possible[1]. We did not specify that the familiar images should be race or gender-matched to avoid biasing who the participants selected as their familiar other; however most familiar face images matched the participants\u0026rsquo; gender and race[2]. \u003c/p\u003e\n\u003cp\u003eWe administered the attention capture task via PsychoPy (Peirce et al., 2019) at our lab using either a desktop computer (1920 x 1080; N = 26) or a laptop (2560 x 1600; N = 40). The experiment began with six practice trials with audiovisual feedback, followed by the primary task. Participants responded using the Z and M keys to indicate the presence or absence of the butterfly target. The corresponding letter and response type (present vs. absent) were counterbalanced across participants to control for differences in handedness. At the start of each trial, an empty grid appeared for 500 ms. Then, the search array appeared and remained visible for up to 3,500 ms or until the participant responded. After each trial, a blank screen appeared for 1000 ms. \u003c/p\u003e\n\u003cp\u003eThere were a total of 108 trials, with an equal number of target present and target absent trials (54 target present, 54 target absent), as well as an equal number of face present and face absent trials (54 face present, 54 face absent). Within the face present trials, there were an equal number of trials in which the self-, familiar-, and stranger-face appeared as a distractor (18 self-face present, 18 familiar-face present, 18 stranger-face present), split evenly across the set size 3, 6, and 9 trials (9 self-, familiar- and stranger-faces each). Across the task, the target and face images were counterbalanced so that each face, butterfly, and distractor appeared in all locations an equal number of times. Once target and face locations were determined, non-face distractor images were randomly positioned in the remaining locations and occurred with equal frequency throughout the task. All trial types were preselected, ensuring that each participant observed the identical set of 108 search arrays, presented in a randomized sequence.\u003c/p\u003e\n\u003cp\u003eWe assessed participants\u0026rsquo; accuracy and response times to detect the butterfly target within each search array. We computed accuracy based on the proportion of trials in which participants correctly indicated the presence or absence of the butterfly target. We computed reaction time by averaging the time it took participants to respond correctly. We calculated reaction time only for accurate trials and excluded any responses that were less than 200ms or more than two standard deviations slower than the participants\u0026rsquo; average reaction time. Attention capture by the face distractors is indicated by poorer accuracy and/or slower reaction times to detect the target.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eQuestionnaires.\u003c/em\u003e\u003c/strong\u003e Participants completed two questionnaires to assess individual differences in self-esteem and self-consciousness. However, because these measures were highly correlated, analyses focused on the measure of self-esteem assessed via the Rosenberg Self-Esteem Scale (Rosenberg, 1965). See Supplementary Materials for additional details. \u003c/p\u003e\n\u003cp\u003e[1] We were unable to fully gender- and race-match the self and stranger faces for N = 8 participants. However, the overall pattern of results did not change when we limited analyses to participants (N = 58) with fully gender and race-matched faces.\u003c/p\u003e\n\u003cp\u003e[2] Since participants selected their own familiar images, some of familiar faces were not gender- and race-matched to the participants (N = 7). The overall pattern of results did not change when we limited analyses to participants (N = 59) with fully gender- and race-matched faces. \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePreliminary Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInitial analyses indicated that there were no significant effects of gender on any variables of interest (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s \u0026gt; .055). Older participants showed slower overall target response times (\u003cem\u003er\u003c/em\u003e(66) = .25, \u003cem\u003ep\u003c/em\u003e = .041), but this effect of age did not interact with face presence or face type (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s \u0026gt; .233)\u003cem\u003e.\u003c/em\u003e As a result, we did not include age or gender in any subsequent analyses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor our primary analyses, we first examined the effects of overall face presence on target detection performance using a repeated-measures ANOVA with within-subject factors of target presence (present, absent), face presence (present, absent), and set size (three, six, nine). Next, we focused on trials in which a face was present and examined effects of face type on target detection performance using a repeated-measures ANOVA with within-subject factors of target presence (present, absent), face type (self, familiar, stranger), and set size (three, six, nine). For all analyses we conducted separate analyses to examine accuracy and response time measures and used Greenhouse-Geisser corrections when necessary to correct for violations of sphericity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects of Face Presence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003cem\u003eAccuracy.\u003c/em\u003e\u0026nbsp;\u003c/strong\u003eParticipants were overall less accurate during target present vs. target absent trials, \u003cem\u003eF\u003c/em\u003e(1,65) = 92.98, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001,\u0026nbsp;\u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .59 (\u003cem\u003eM\u003csub\u003ePresent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .96, \u003cem\u003eSD\u003c/em\u003e = .03; \u003cem\u003eM\u003csub\u003eAbsent\u003c/sub\u003e\u003c/em\u003e = .99, \u003cem\u003eSD\u003c/em\u003e = .01). There was no overall effect of face presence on accuracy, \u003cem\u003eF\u003c/em\u003e(1,65) = 1.353, \u003cem\u003ep\u003c/em\u003e = .249,\u0026nbsp;\u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .02 (\u003cem\u003eM\u003csub\u003ePresent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .98, \u003cem\u003eSD\u003c/em\u003e = .02; \u003cem\u003eM\u003csub\u003eAbsent\u003c/sub\u003e\u003c/em\u003e = .98, \u003cem\u003eSD\u003c/em\u003e = .02). There was a main effect of set size on accuracy, \u003cem\u003eF\u003c/em\u003e(1.71, 111.39) = 4.81, \u003cem\u003ep\u003c/em\u003e = .014,\u0026nbsp;\u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .07, such that participants were more accurate during set size 3 trials (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .98, \u003cem\u003eSD\u003c/em\u003e = .018) compared to set size 6 (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .97, \u003cem\u003eSD\u003c/em\u003e = .03), \u003cem\u003et\u003c/em\u003e(65) = 2.75, \u003cem\u003ep\u003c/em\u003e = .008, \u003cem\u003ed\u003c/em\u003e = .34), and set size 9 trials (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .97, \u003cem\u003eSD\u003c/em\u003e = .03), \u003cem\u003et\u003c/em\u003e(65) = 3.28, \u003cem\u003ep\u003c/em\u003e = \u0026lt;.001, \u003cem\u003ed\u003c/em\u003e = .40. There was no difference between set size 6 and set size 9 trials (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= .944).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults also indicated a target presence x set size interaction, \u003cem\u003eF\u003c/em\u003e(1.81, 117.40) = 4.39, \u003cem\u003ep\u003c/em\u003e = .017, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .06, and a face presence x set size interaction, \u003cem\u003eF\u003c/em\u003e(2, 130) = 5.630, \u003cem\u003ep\u003c/em\u003e = .005, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .08, which were further moderated by a target presence x face presence x set size interaction, \u003cem\u003eF\u003c/em\u003e(1.79, 116.45) = 10.88, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .14 (Figure 2). Follow-up analyses revealed a significant face presence x set size interaction only during the target present condition, \u003cem\u003eF\u003c/em\u003e(1.81, 117.38) = 9.80, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .13, but not during the target absent condition (\u003cem\u003ep\u003c/em\u003e = .218). When the target was present, the presence vs. absence of a face distractor had no effect on accuracy during set size 3 trials (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= .370). However, during set size 6 trials participants responded more accurately when a face distractor appeared (\u003cem\u003eM\u003c/em\u003e = .97, \u003cem\u003eSD\u003c/em\u003e = .04) compared to trials without a face distractor, \u003cem\u003eM\u003c/em\u003e = .94, \u003cem\u003eSD\u003c/em\u003e = .07; \u003cem\u003eF\u003c/em\u003e(1, 65) = 6.74, \u003cem\u003ep\u003c/em\u003e = .012, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .09. During set size 9 trials participants instead responded less accurately when a face distractor appeared (\u003cem\u003eM\u003c/em\u003e = .94, \u003cem\u003eSD\u003c/em\u003e = .05) compared to trials without a face distractor, \u003cem\u003eM\u003csub\u003eAbsent\u003c/sub\u003e\u003c/em\u003e = .97, \u003cem\u003eSD\u003c/em\u003e = .05; \u003cem\u003eF\u003c/em\u003e(1, 65) = 8.80, \u003cem\u003ep\u003c/em\u003e = .004, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .12.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReaction Time.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eParticipants were overall faster to respond during the target present vs. target absent trials, \u003cem\u003eF\u003c/em\u003e(1,65) = 159.32, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .71; \u003cem\u003eM\u003csub\u003ePresent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 651.36, \u003cem\u003eSD\u003c/em\u003e = 111.42; \u003cem\u003eM\u003csub\u003eAbsen\u003c/sub\u003e\u003c/em\u003e\u003csub\u003et\u0026nbsp;\u003c/sub\u003e= 795.85, \u003cem\u003eSD\u003c/em\u003e = 176.86, and overall slower to respond during the face present vs. face absent trials, \u003cem\u003eF\u003c/em\u003e(1,65) = 28.20, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .30; \u003cem\u003eM\u003csub\u003ePresent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 737.88, \u003cem\u003eSD\u003c/em\u003e = 151.65; \u003cem\u003eM\u003csub\u003eAbsent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 709.33, \u003cem\u003eSD\u003c/em\u003e = 131.62. There was also a main effect of set size on reaction time, \u003cem\u003eF\u003c/em\u003e(1.25, 81.51) = 182.09, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .74, such that participants were slower to respond as the number of distractors in the set size increased (\u003cem\u003eM\u003csub\u003eSetSize3\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 642.91, \u003cem\u003eSD\u003c/em\u003e = 110.49; \u003cem\u003eM\u003csub\u003eSetSize6\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e= 722.95, \u003cem\u003eSD\u003c/em\u003e = 138.61; \u003cem\u003eM\u003csub\u003eSetSize9\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 804.95, \u003cem\u003eSD\u003c/em\u003e = 179.97; \u003cem\u003ep\u003c/em\u003e\u0026rsquo;s \u0026lt; .001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults also indicated a target presence x face presence interaction, \u003cem\u003eF\u003c/em\u003e(1,65) = 7.95, \u003cem\u003ep\u003c/em\u003e = .006, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .11, a target presence x set size interaction \u003cem\u003eF\u003c/em\u003e(1.42, 92.17) = 74.62, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .53, and a face presence x set size interaction \u003cem\u003eF\u003c/em\u003e(1.77, 115.33) = 36.83, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .36. These effects were further moderated by a significant target presence x face presence x set size interaction, \u003cem\u003eF\u003c/em\u003e(1.62, 105.05) = 40.77, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .39 (Figure 3). Follow-up analyses revealed a significant face presence x set size interaction for only the target present condition, \u003cem\u003eF\u003c/em\u003e(1.67, 108.31) = 83.03, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .56, but not the target absent condition (\u003cem\u003ep\u003c/em\u003e = .478). When the target was present, participants were slower to respond during set size 3 trials when a face appeared as a distractor (\u003cem\u003eM\u003csub\u003epresent\u003c/sub\u003e\u003c/em\u003e = 615.95 \u003cem\u003eSD\u003c/em\u003e = 109.75) compared to trials without a face distractor, \u003cem\u003eM\u003csub\u003eabsent\u003c/sub\u003e\u003c/em\u003e = 689.85 \u003cem\u003eSD\u003c/em\u003e = 120.85; \u003cem\u003eF\u003c/em\u003e(1, 65) = 9.79, \u003cem\u003ep\u003c/em\u003e = .003, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .13. Participants showed a similar pattern during set size 9 trials, with slower responses when a face appeared as a distractor (\u003cem\u003eM\u003csub\u003ePresent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 738.19 \u003cem\u003eSD\u003c/em\u003e = 160.87) compared to trials without a face distractor, \u003cem\u003eM\u003csub\u003eAbsent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 642.41 \u003cem\u003eSD\u003c/em\u003e = 115.29; \u003cem\u003eF\u003c/em\u003e(1, 65) = 76.51, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .54. However, during set size 6 trials participants were instead faster to respond when a face appeared as a distractor (\u003cem\u003eM\u003csub\u003ePresen\u003c/sub\u003e\u003c/em\u003e\u003csub\u003et\u0026nbsp;\u003c/sub\u003e= 628.28 \u003cem\u003eSD\u003c/em\u003e = 113.46) compared to trials without a face distractor, \u003cem\u003eM\u003csub\u003eAbsent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 689.85 \u003cem\u003eSD\u003c/em\u003e = 120.85; \u003cem\u003eF\u003c/em\u003e(1, 65) = 59.98, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .47.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSummary.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eOverall, participants demonstrated poorer target detection performance, indicated by poorer accuracy and slower reaction times, during trials with larger set sizes and during target present trials compared to target absent trials. The presence of the face distractors also resulted in poorer target detection performance, as participants showed overall slower reaction times to respond to the target when a face was present in the array. However, the effects of face presence also depended on target presence and set size, such that the presence of face distractors facilitated performance (i.e., improved accuracy and faster reaction times) during target present, set size 6 trials but instead resulted in poorer accuracy and slower reaction times during target present, set size 9 trials.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects of Face Type\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAccuracy.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eResults of the target presence x face type x set size ANOVA indicated that participants were overall less accurate during target present vs. target absent trials, \u003cem\u003eF\u003c/em\u003e(1,65) = 55.758, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e = .46; \u003cem\u003eM\u003csub\u003ePresent\u003c/sub\u003e\u003c/em\u003e = .96, \u003cem\u003eSD\u003c/em\u003e = .03; \u003cem\u003eM\u003csub\u003eAbsent\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .99, \u003cem\u003eSD\u003c/em\u003e = .01. There was a main effect of set size on accuracy, \u003cem\u003eF\u003c/em\u003e(1.76, 114.42) = 5.07, \u003cem\u003ep\u003c/em\u003e = .010, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e = .07, such that participants were more accurate during set size 3 trials (\u003cem\u003eM\u003c/em\u003e = .98, \u003cem\u003eSD\u003c/em\u003e = .018) compared to set size 6, \u003cem\u003eM\u003c/em\u003e = .97, \u003cem\u003eSD\u003c/em\u003e = .03; \u003cem\u003et\u003c/em\u003e(65) = 2.75, \u003cem\u003ep\u003c/em\u003e = .008, \u003cem\u003ed\u003c/em\u003e = .34, and set size 9 trials, \u003cem\u003eM\u003c/em\u003e = .97, \u003cem\u003eSD\u003c/em\u003e = .03; \u003cem\u003et\u003c/em\u003e(65) = 3.28, \u003cem\u003ep\u003c/em\u003e = \u0026lt;.001, \u003cem\u003ed\u003c/em\u003e = .40. There was no difference between set size 6 and set size 9 trials (\u003cem\u003ep\u003c/em\u003e = .944). There was also a marginally significant main effect of face type on accuracy, \u003cem\u003eF\u003c/em\u003e(1.75, 113.91) = 3.11, \u003cem\u003ep\u003c/em\u003e = .055, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .05. Participants were overall less accurate during trials in which the familiar face (\u003cem\u003eM\u003c/em\u003e = .97, \u003cem\u003eSD\u003c/em\u003e = .03) or self-face (\u003cem\u003eM\u003c/em\u003e = .97, \u003cem\u003eSD\u003c/em\u003e = .04) appeared as a distractor compared to trials in which the stranger face was a distractor, \u003cem\u003eM\u003c/em\u003e = .98, \u003cem\u003eSD\u003c/em\u003e = .03; \u003cem\u003et\u003c/em\u003e\u003cem\u003e\u003csub\u003eFamiliar\u003c/sub\u003e\u003c/em\u003e (65) = -2.61, \u003cem\u003ep\u003c/em\u003e = .011, \u003cem\u003ed\u0026nbsp;\u003c/em\u003e= -.32; \u003cem\u003et\u003c/em\u003e\u003cem\u003e\u003csub\u003eSelf\u003c/sub\u003e\u003c/em\u003e (65) = -2.18, \u003cem\u003ep\u003c/em\u003e = .033, \u003cem\u003ed\u003c/em\u003e = -0.27. However, there was no difference across the familiar and self-face trials (\u003cem\u003ep\u003c/em\u003e = .842).\u003c/p\u003e\n\u003cp\u003eResults also indicated a face type x set size interaction, \u003cem\u003eF\u003c/em\u003e(3.13, 203.61) = 9.44, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .13, which was further moderated by a target presence x face type x set size interaction, \u003cem\u003eF\u003c/em\u003e(3.45, 223.45) = 8.55, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .12 (Figure 4). Follow-up analyses revealed a significant face type x set size interaction in only the target present condition only, \u003cem\u003eF\u003c/em\u003e(3.15, 119.03) = 10.76, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .14, but not the target absent condition (\u003cem\u003ep\u003c/em\u003e = .476). Within the target present condition, there was no effect of face type during set size 3 trials (\u003cem\u003ep\u003c/em\u003e = .906), but there was a significant effect of face type during both set size 6 trials, \u003cem\u003eF\u003c/em\u003e(1.26, 81.98) = 15.30, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .19, and set size 9 trials, \u003cem\u003eF\u003c/em\u003e(2, 130) = 7.03, \u003cem\u003ep\u003c/em\u003e = .001, \u003cem\u003eh\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .10. However, the direction of these effects varied across set sizes 6 and 9. During set size 6 trials, participants showed poorer target detection accuracy in the presence of the self-face distractor (\u003cem\u003eM\u003c/em\u003e = .93, \u003cem\u003eSD\u003c/em\u003e = .12) compared to trials with either the familiar face distractor, \u003cem\u003eM\u003c/em\u003e = .98, \u003cem\u003eSD\u003c/em\u003e = .05; \u003cem\u003et\u003c/em\u003e(65) = 3.41, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = 0.42, or the stranger face distractor, \u003cem\u003eM\u003c/em\u003e = .99, \u003cem\u003eSD\u003c/em\u003e = .02; \u003cem\u003et\u003c/em\u003e(65) = 4.67, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = 0.58. Participants also showed poorer accuracy in the presence of the familiar face distractor compared to the stranger face distractor, \u003cem\u003et\u003c/em\u003e(65) = 2.14, \u003cem\u003ep\u003c/em\u003e = .036, \u003cem\u003ed\u003c/em\u003e = 0.26. In contrast, during set size 9 trials, participants showed better target detection accuracy in the presence of the self-face distractor (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .98, \u003cem\u003eSD\u003c/em\u003e = .08) compared to both the familiar face distractor, \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .91, \u003cem\u003eSD\u003c/em\u003e = .12; \u003cem\u003et\u003c/em\u003e(65) = 3.68, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = 0.45, and the stranger face distractor, \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= .94, \u003cem\u003eSD\u003c/em\u003e = .10;\u003cem\u003e\u0026nbsp;t\u003c/em\u003e(65) = 2.01, \u003cem\u003ep\u003c/em\u003e = .049, \u003cem\u003ed\u003c/em\u003e = 0.25. There was no difference in accuracy when the familiar and stranger faces appeared as distractors, \u003cem\u003et\u003c/em\u003e(65) = 1.80, \u003cem\u003ep\u003c/em\u003e = .076, \u003cem\u003ed\u003c/em\u003e = 0.22.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReaction Time.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eResults of the target presence x face type x set size ANOVA indicated a main effect of face type on reaction time, \u003cem\u003eF\u003c/em\u003e(2, 130) = 5.05, \u003cem\u003ep\u003c/em\u003e = .008, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .07. Participants were overall slower to respond during trials in which the familiar face (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 741.79, \u003cem\u003eSD\u003c/em\u003e = 154.79) or self-face (\u003cem\u003eM\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e= 745.28, \u003cem\u003eSD\u003c/em\u003e = 157.62) appeared as a distractor compared to trials in which the stranger face was a distractor, \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= 726.56, \u003cem\u003eSD\u003c/em\u003e = 150.95; \u003cem\u003et\u003csub\u003eFamiliar\u003c/sub\u003e\u003c/em\u003e(65) = 2.30, \u003cem\u003ep\u003c/em\u003e = .025, \u003cem\u003ed\u003c/em\u003e = .28; \u003cem\u003et\u003csub\u003eSelf\u003c/sub\u003e\u003c/em\u003e(65) = 3.03, \u003cem\u003ep\u003c/em\u003e = .003, \u003cem\u003ed\u003c/em\u003e = .37. However there was no difference in target reaction times when the familiar face and self-face appeared as distractors (\u003cem\u003ep\u003c/em\u003e = .562). In addition to this main effect there was also a significant target presence x face type x set size interaction, \u003cem\u003eF\u003c/em\u003e(3.53, 229.28) = 4.51, \u003cem\u003ep\u003c/em\u003e = .003, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .07 (Figure 5). Follow-up analyses revealed a face type x set size interaction in only the target present condition, \u003cem\u003eF\u003c/em\u003e(2.92, 189.67) = 12.80, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .17, but not the target absent condition (\u003cem\u003ep\u003c/em\u003e = .183). Within the target present condition, there was no effect of face type during set size 3 trials (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= .394), but there was a significant effect of face type during both the set size 6 trials, \u003cem\u003eF\u003c/em\u003e(2, 130) = 24.67, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .28, and set size 9 trials, \u003cem\u003eF\u003c/em\u003e(1.67, 108.79) = 7.33, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .10. However, the direction of these effects varied across set size 6 and 9. During set size 6 trials, participants responded to the target more slowly when the self-face distractor was present (\u003cem\u003eM\u003c/em\u003e = 675.16, \u003cem\u003eSD\u003c/em\u003e = 142.35) compared to trials with either the familiar face distractor, \u003cem\u003eM\u003c/em\u003e = 611.52, \u003cem\u003eSD\u003c/em\u003e = 129.30; \u003cem\u003et\u003c/em\u003e(65) = 5.27, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = .65, or the stranger face distractor, \u003cem\u003eM\u003c/em\u003e = 598.17, \u003cem\u003eSD\u003c/em\u003e = 103.42; \u003cem\u003et\u003c/em\u003e(65) = 7.12, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = .88. In contrast, during set size 9 trials, participants responded to the target faster when the self-face distractor was present (\u003cem\u003eM\u003c/em\u003e = 700.07, \u003cem\u003eSD\u003c/em\u003e = 139.23) compared to trials with the familiar face distractor, \u003cem\u003eM\u003c/em\u003e = 776.25, \u003cem\u003eSD\u003c/em\u003e = 185.51; \u003cem\u003et\u003c/em\u003e(65) = 5.04, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = 0.62. However, there was no difference in response times in the presence of the self-face distractor compared to the stranger face distractor during set size 9 trials, \u003cem\u003eM\u003c/em\u003e= 738.25, \u003cem\u003eSD\u003c/em\u003e = 223.56; \u003cem\u003et\u003c/em\u003e(65) = 1.82, \u003cem\u003ep\u003c/em\u003e = .074, \u003cem\u003ed\u003c/em\u003e = 0.22. Participants also showed no difference in response times during either set size 6 or set size 9 trials in which the familiar face distractor appeared compared to those with the stranger face distractor (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s \u0026gt; .074).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSummary.\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eParticipants showed overall poorer target detection, indicated by poorer accuracy and slower reaction time, when the distractor was a familiar face or the self-face compared to a stranger face. However, these effects were moderated by target presence and set size. When the target was present, there was no effect of face type during set size 3 trials and the direction of the face type effects varied across set sizes 6 and 9. During set size 6 trials, participants showed the slowest and least accurate target detection when the self-face distractor was present and showed the best target detection performance when the stranger face distractor appeared. In contrast, during set size 9 trials, target detection was least affected by the presence of the self-face distractor and participants instead showed the poorest performance when the familiar face distractor appeared. These findings indicate that the familiar and self-face distractors had different effects on target detection performance and suggest that the presence of the self-face distractor may hinder performance to the greatest extent during set size 6 trials.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects of Self-Esteem\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a final exploratory analysis to examine whether self-esteem moderates the effects of face type on target detection performance described above. We examined target detection performance using a repeated-measures ANCOVA with within-subject factors of target presence (present, absent), face type (self, familiar, stranger), and set size (three, six, nine), with the self-esteem composite score centered as a covariate. Results indicated no significant effects of face type, target type, set size, or self-esteem for the model examining target detection accuracy (\u003cem\u003ep\u0026rsquo;s\u0026nbsp;\u003c/em\u003e\u0026lt; .100). There was a marginally significant face type x set size x self-esteem interaction on reaction time, \u003cem\u003eF\u003c/em\u003e(3.12, 199.73) = 2.60, \u003cem\u003ep\u003c/em\u003e = .051, \u003cem\u003eh\u003c/em\u003e\u003cem\u003e\u003csub\u003ep\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e= .04. However, follow-up analyses indicated that self-esteem was not related to reaction times during any trials with the self, familiar or stranger faces (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s \u0026gt; .202). For more details see the Supplementary Materials.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePrior investigations of the role of reward and familiarity in the self-face bias yielded mixed results, which may reflect the use of task designs in which faces were task-relevant or predictive. The present study addressed this limitation by using an attention capture paradigm that isolates automatic, stimulus-driven orienting, allowing a more precise assessment of the role of reward and familiarity in the self-face attention bias. Although the presence of any face distractor impaired target detection, this interference was specific to trials in which the target was present and depended on set size. Specifically, face distractors facilitated target detection performance during target present, set size 6 trials but instead resulted in increased distraction during target present, set size 9 trials. Distraction by faces also depended on face identity, as attention capture was strongest to the self-face during set size 6 trials but to the familiar face during set size 9 trials. Overall, these findings demonstrate differential attention capture across self- and familiar faces and suggest that these effects are sensitive to task context.\u003c/p\u003e\u003cp\u003eTarget detection performance was consistent with past research using visual search and attention capture tasks. Participants were more accurate but slower when the target was absent, likely reflecting increased time to confirm its absence (Godwin et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Langton et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Peltier \u0026amp; Becker, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Riby et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Perfomance also declined as the number of distractors increased, reflecting greater difficulty suppressing task-irrelevant items (Botch et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Carrasco et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Jerde et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Mazyar et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Palmer, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Similar effects have been observed consistently in studies using the same task design, underscoring the validity of the current task (Hunter \u0026amp; Markant, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e; Langton et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Riby et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eParticipants showed slower target detection when any face appeared as a distractor, indicating that faces captured attention and disrupted performance. These results replicate previous findings that faces capture adults\u0026rsquo; attention, even when task-irrelevant (Devue et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Hodsoll et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Langton et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Riby et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In particular, our results converged with prior attention capture findings that the presence of a face slowed task performance only when the target was present (Langton et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Riby et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The current results also extended these past findings by demonstrating that face presence effects varied across set size. Specifically, in target present trials, face distractors disrupted target detection at set sizes 3 and 9, but instead facilitated performance at set size 6. Face distractors may affect performance differently depending on participants\u0026rsquo; search strategy. Specifically, these effects may reflect a shift from a global search strategy at moderate set sizes to a serial search strategy in denser arrays (Findlay, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Pomplun et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, it was beyond the scope of the current research to determine the search strategies that participants engaged during each set size. Future work can test this possibility by examining eye movements patterns during this task or manipulating array layout and density to determine how these factors interact with set size to affect attention capture by faces.\u003c/p\u003e\u003cp\u003eBeyond general distraction by faces, participants showed increased attention capture by the self- and familiar faces compared to the stranger face, but these effects depended on task context. Self- and familiar-face biases only emerged at certain set sizes, suggesting that face identity interacted with search demands rather than operating uniformly. This aligns with prior research demonstrating self-face advantages only under specific task conditions or measures (Bola et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Devue \u0026amp; Br\u0026eacute;dart, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hunter \u0026amp; Markant, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e; Żochowska et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Together, these findings suggest that identity-based distraction is embedded within broader dynamics of search strategy and cognitive or task demands. Future work should test how self- and familiar face attention biases generalize to other task designs, including naturalistic settings where individuals frequently view their own face (e.g., online meetings/classes).\u003c/p\u003e\u003cp\u003eWhile context-dependent, this study clearly demonstrated differential attention capture by the self- and familiar faces, aligning with theories that self-related stimuli are intrinsically rewarding and prioritized for attentional selection (Northoff \u0026amp; Hayes, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Sui \u0026amp; Humphreys, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zhan et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Comparable patterns have been observed in children, in which caregiver faces captured attention during target present set size 6 trials, but stranger faces caused increased distraction during target present set size 9 trials. Critically, the caregiver face, like the self-face, is a rewarding stimulus for young children (Minagawa-Kawai et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The current study thus showed a similar pattern of results in that participants showed increased attention capture by the more rewarding face identity during trials in which the task difficulty was moderate. Importantly, these results are unlikely to reflect goal-driven or low-level visual salience. The faces were presented as task-irrelevant distractors and participants were unaware that they would appear in the search arrays, suggesting that orienting to the faces was not based primarily on endogenous mechanisms. We also reduced differences in low-level salience by using stringent photo requirements and cropped extraneous features from the images to reduce major perceptual differences across the faces. However, while we yoked the self- and stranger face images as much as possible, not all self- and stranger images were fully yoked and the familiar face images were not yoked at all, which may have created inconsistencies in the stimuli. Future studies could further minimize stimulus variability by fully yoking familiar and self-face conditions (e.g., recruiting participants in pairs).\u003c/p\u003e\u003cp\u003eOverall, these findings converge to suggest that these attention biases may be driven by reward-based selection mechanisms. However, we cannot rule out familiarity. Participants reported similar familiarity ratings for the self- and familiar faces, suggesting that differential attention capture was not driven by familiarity alone (e.g. Diliberto et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Nelson \u0026amp; Palmer, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). However, ceiling effects in familiarity ratings could have masked variability in familiarity that may have contributed to differential attention capture. Neuroimaging research is needed to corroborate these behavioral findings and confirm whether reward-based selection underlies the self-face attention bias.\u003c/p\u003e\u003cp\u003eFinally, although we demonstrated group-level differences in attention capture by the self- and familiar faces, these effects may vary across individuals. Our exploratory analyses found no association between self-esteem and the self-face bias. However, our predominantly female (66%) sample limited to a mid-size southern U.S. city may have introduced bias. Prior work indicates that women tend to report lower self-esteem than men (Bleidorn et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and that both self-esteem (Bleidorn et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and the magnitude of the self-face attention bias vary across cultures (Румянцева et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Future work should include more diverse samples to investigate how individual differences moderate attention capture to the self-face.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this work investigated whether the self-face bias was driven by its rewarding value by comparing automatic attention capture to the self, familiar and stranger faces using an attention capture task designed to minimize endogenous influences. Face distractors disrupted target detection, and this distraction varied by face identity and search array size. Although context-dependent, the results demonstrated differential attention capture by self- and familiar faces. Moreover, by employing an attention capture task in which the faces were distractors from the task, and minimizing perceptual differences across face types by cropping extraneous features and yoking the self and stranger images when available, our results suggest that this distraction by the self-face was not driven merely by perceptual salience or goal relevance. Overall, these findings provide support the role of motivational salience in the self-face attention bias by demonstrating that it is distinguishable from familiarity, exogenous, and endogenous factors. These findings therefore suggest a role for reward-based mechanisms in the self-face attention bias.\u003c/p\u003e"},{"header":"Statements and Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study protocols were approved by the local Institutional Review Board and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided written informed consent prior to participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publiation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that the face stimuli provided in Figure 1 are used with permission from study staff.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eT.M.: Conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing-original draft, writing—review \u0026amp; editing, visualization. A.W.: Methodology, formal analysis, investigation, data curation, writing-original draft, writing—review \u0026amp; editing. B.H.: Conceptualization, methodology, software, writing—review \u0026amp; editing. J.M.: Conceptualization, methodology, formal analysis, resources, data curation, writing—original draft, writing—review \u0026amp; editing, visualization, supervision, funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the members of the Learning and Brain Development Lab for assistance with participant recruitment and data processing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Note\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have no conflicts of interest to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCorrespondence concerning this article should be addressed to Taylor Marcus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOrcid IDs : Taylor Marcus 0000-0002-4720-9819\u003c/p\u003e\n\u003cp\u003eBrianna Hunter 0000-0002-2197-2533\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Julie Markant 0000-0001-9963-1766\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlzueta, E., Melc\u0026oacute;n, M., Poch, C., \u0026amp; Capilla, A. 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The what, where, and why of priority maps and their interactions with visual working memory. \u003cem\u003eAnnals of the New York Academy of Sciences, 1339\u003c/em\u003e(1), 154\u0026ndash;164. https://doi.org/10.1111/nyas.12606\u003c/li\u003e\n \u003cli\u003eZhan, Y., Chen, J., Xiao, X., Li, J., Yang, Z., Fan, W., \u0026amp; Zhong, Y. (2016). Reward promotes self-face processing: An event-related potential study. \u003cem\u003eFrontiers in Psychology, 7\u003c/em\u003e, 735. https://doi.org/10.3389/fpsyg.2016.00735\u003c/li\u003e\n \u003cli\u003eŻochowska, A., W\u0026oacute;jcik, M. J., \u0026amp; Nowicka, A. (2023). How far can the self be extended? Automatic attention capture is triggered not only by the self-face. \u003cem\u003eFrontiers in Psychology, 14\u003c/em\u003e, 1279653. https://doi.org/10.3389/fpsyg.2023.1279653\u003c/li\u003e\n \u003cli\u003eРумянцева, П. В., Горбачев, Д. А., Иванов, А. С., \u0026amp; Кунах, К. В. (2023). Self-face advantage and social threat: Cross-cultural aspects. \u003cem\u003eПсихология человека в образовании, 5\u003c/em\u003e(2), 161\u0026ndash;168. https://doi.org/10.33910/2686-9527-2023-5-2-161-168\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8311098/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8311098/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFaces are salient social stimuli that convey critical information for communication but compete with other inputs for limited attentional resources. Selection among these inputs can be guided by multiple factors, including the perceptual salience of a stimulus, its relevance to task goals, its reward value, or prior learning about it. One\u0026rsquo;s own face captures attention even when it is neither perceptually salient nor task-relevant. This self-face bias has been proposed to reflect reward value, though others suggest it reflects mere familiarity. Prior studies have compared attention to the self- versus other familiar, but less rewarding, faces, yet findings have been mixed and these inconsistencies may reflect varying task demands (e.g., the goal-relevance of faces across paradigms). The present study used an attention capture paradigm to compare automatic attention orienting to the self-, familiar, and stranger faces that appeared as a task-irrelevant distractor within multi-object search arrays of varying set size. The presence of any face distractor impaired target detection performance, confirming that faces capture attention even when irrelevant to an ongoing task. However, distraction also varied across both face identity and the context of the search array. Faces facilitated target detection at moderate set sizes but interfered at larger set sizes. Moreover, when the target was present, the self-face captured attention most within moderate set sizes, whereas familiar faces did so at the largest set size. These findings demonstrate context-dependent, identity-specific attention capture and suggest that the attention biases to the self- and familiar faces may reflect different mechanisms.\u003c/p\u003e","manuscriptTitle":"Distinct Attention Capture for Self- and Familiar Faces in Visual Search","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-10 06:25:28","doi":"10.21203/rs.3.rs-8311098/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c26f39af-b33f-4597-9c0d-3833903a9f0d","owner":[],"postedDate":"December 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-26T09:27:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-10 06:25:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8311098","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8311098","identity":"rs-8311098","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}