Children view own-age faces qualitatively differently to other-age faces

Hills, Peter J.; Willis, Susan

doi:10.1080/20445911.2016.1164710

Cited by 10 publications

(10 citation statements)

References 40 publications

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“…Furthermore, Goldinger, He, and Papesh (2009) found differences in the way that own-and other-ethnicity faces are viewed, with a less effortful encoding strategy highlighted by fewer and longer fixations with more fixations to the nose for other-ethnicity faces relative to own-ethnicity faces (see also, Brielmann, Bülthoff, & Armann, 2014;Fu, Hu, Wang, Quinn, & Lee, 2012; but see, Blais, Jack, Scheepers, Fiset, & Caldara, 2008). Similarly, Hills and Willis (2016) have shown that participants focus more on the nose in other-age faces relative to own-age faces. These results indicate differential scanning for own-and other-group faces.…”

Section: Eye-tracking the Own-gender Bias In Face Recognitionmentioning

confidence: 89%

“…Inverted faces are typically processed in an inexpert manner (Kanwisher, Tong, & Nakayama, 1998;McKone & Yovel, 2009;Tanaka & Farah, 1993). Reduced expert processing (and a smaller face-inversion effect) has been revealed for faces of other groups relative to own group faces (Hills & Willis, 2016;Hugenberg & Corneille, 2008;Michel, Rossion, Han, Chung, & Caldara, 2006;Rhodes, Brake, Taylor, & Tan, 1989). The perceptual expertise account is typically contrasted with the socio-cognitive motivational accounts.…”

Section: Eye-tracking the Own-gender Bias In Face Recognitionmentioning

confidence: 99%

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Eye-tracking the own-gender bias in face recognition: Other-gender faces are viewed differently to own-gender faces

Man

Hills

2016

Visual Cognition

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Research on the own-gender bias in face recognition has indicated an asymmetrical effect: an effect found only in women (Lovén, Herlitz, & Rehnman, 2011). We investigated the own-gender bias, using an eye-tracker to examine whether the own-gender bias is associated with differential processing strategies. We found an own-gender bias in our female participants, consistent with Herlitz and Lovén (2013). Our eye-tracking analysis indicated different scanning behaviours when processing own-and other-gender faces, with longer and more fixations to the eyes when viewing own-gender faces. Our results favour the socio-cognitive model, whilst acknowledging the role of perceptual expertise in the own-gender bias.

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Section: Eye-tracking the Own-gender Bias In Face Recognitionmentioning

confidence: 89%

Section: Eye-tracking the Own-gender Bias In Face Recognitionmentioning

confidence: 99%

Eye-tracking the own-gender bias in face recognition: Other-gender faces are viewed differently to own-gender faces

Man

Hills

2016

Visual Cognition

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“…The images of faces used in this study was selected from the database held by Stirling University ( PICS, 2014 ): As in the original CFMT, six identities were used as targets for the upright and a different six identities (counterbalanced across participants) were used as targets in the inverted versions. All faces used within the study were of male individuals aged between 18 and 40 years (mean age 25 years) in order to match the age of the participants (note identical age range to participants) in order to prevent any effects of the own-age bias ( Anastasi and Rhodes, 2005 ; Hills and Willis, 2016 ). The images were matched for lighting, expression, and pose.…”

Section: Methodsmentioning

confidence: 99%

Explaining Sad People’s Memory Advantage for Faces

2017

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Sad people recognize faces more accurately than happy people (Hills et al., 2011). We devised four hypotheses for this finding that are tested between in the current study. The four hypotheses are: (1) sad people engage in more expert processing associated with face processing; (2) sad people are motivated to be more accurate than happy people in an attempt to repair their mood; (3) sad people have a defocused attentional strategy that allows more information about a face to be encoded; and (4) sad people scan more of the face than happy people leading to more facial features to be encoded. In Experiment 1, we found that dysphoria (sad mood often associated with depression) was not correlated with the face-inversion effect (a measure of expert processing) nor with response times but was correlated with defocused attention and recognition accuracy. Experiment 2 established that dysphoric participants detected changes made to more facial features than happy participants. In Experiment 3, using eye-tracking we found that sad-induced participants sampled more of the face whilst avoiding the eyes. Experiment 4 showed that sad-induced people demonstrated a smaller own-ethnicity bias. These results indicate that sad people show different attentional allocation to faces than happy and neutral people.

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“…This bias is dependent upon differential experience with face age (31,32), is reduced by visual exposure training of other-aged faces (33), and has been reliably observed in both tasks of face recognition memory (11) and FER (10,34). As is true of many indicators of perceptual expertise, the OAB is also reflected in differential patterns of visual attention to own-age faces (35)(36)(37)(38)(39) and the recruitment of specialized cortical networks when processing own-age faces (36,40).…”

Section: Introductionmentioning

confidence: 97%

Evidence of an Own-Age Bias in Facial Emotion Recognition for Adolescents With and Without Autism Spectrum Disorder

et al. 2020

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A common interpretation of the face-processing deficits associated with autism spectrum disorder (ASD) is that they arise from a failure to develop normative levels of perceptual expertise. One indicator of perceptual expertise for faces is the own-age bias, operationalized as a processing advantage for faces of one's own age, presumably due to more frequent contact and experience. This effect is especially evident in domains of face recognition memory but less commonly investigated in social-emotional expertise (e.g., facial emotion recognition; FER), where individuals with ASD have shown consistent deficits. In the present study, we investigated whether a FER task would elicit an own-age bias for individuals with and without ASD and explored how the magnitude of an own-age bias may differ as a function of ASD status and symptoms. Ninety-two adolescents (63 male) between the ages of 11 and 14 years completed the child-and adult-face subtests of a standardized FER task. Overall FER accuracy was found to differ by ASD severity, reflecting poorer performance for those with increased symptoms. Results also indicated that an own-age bias was evident, reflecting greater FER performance for child compared to adult faces, for all adolescents regardless of ASD status or symptoms. However, the strength of the observed own-age bias did not differ by ASD status or severity. Findings suggest that face processing abilities of adolescents with ASD may be influenced by experience with specific categories of stimuli, similar to their typically developing peers.

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Children view own-age faces qualitatively differently to other-age faces

Cited by 10 publications

References 40 publications

Eye-tracking the own-gender bias in face recognition: Other-gender faces are viewed differently to own-gender faces

Eye-tracking the own-gender bias in face recognition: Other-gender faces are viewed differently to own-gender faces

Explaining Sad People’s Memory Advantage for Faces

Evidence of an Own-Age Bias in Facial Emotion Recognition for Adolescents With and Without Autism Spectrum Disorder

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