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人脸识别与自闭症特征的相互模型:来自个体差异视角的证据。

A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

作者信息

Halliday Drew W R, MacDonald Stuart W S, Scherf K Suzanne, Tanaka James W

机构信息

University of Victoria, Victoria, British Columbia, Canada; The Centre for Autism Research, Technology and Education, Victoria, British Columbia, Canada.

University of Victoria, Victoria, British Columbia, Canada.

出版信息

PLoS One. 2014 May 22;9(5):e94013. doi: 10.1371/journal.pone.0094013. eCollection 2014.

Abstract

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

摘要

尽管这并非该疾病的核心症状,但自闭症患者通常在面部处理能力方面表现出选择性损伤。重要的是,自闭症特征与面部感知之间的相互联系在正常发育人群中很少被研究。在本研究中,来自社会科学、物理科学和人文专业的大学生参与者完成了一系列评估面部、物体和情绪识别能力、一般感知认知风格以及亚临床自闭症特征(自闭症商数(AQ))的测量。我们采用了单独的分层多元回归分析来评估哪些因素可以预测面部识别分数和AQ分数。性别、物体识别表现和AQ分数可预测面部识别行为。具体而言,男性、具有更多自闭症特征的个体以及物体识别分数较低的个体在面部识别测试中的表现更差。相反,大学专业、性别和面部识别表现能够可靠地预测AQ分数。理科专业学生、男性以及面部识别技能较差的个体表现出更多类似自闭症的特征。这些结果表明,即使在正常发育的个体中,更广泛的自闭症表型也与较低的面部识别能力相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d58/4031083/0aeef80f8dfd/pone.0094013.g001.jpg

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