自闭症
心理学
认知心理学
感知
社会认知
固定(群体遗传学)
自闭症谱系障碍
集合(抽象数据类型)
认知
发展心理学
神经科学
计算机科学
社会学
人口学
程序设计语言
人口
作者
Amanda J. Haskins,Jeff Mentch,Thomas L. Botch,Brenda D. Garcia,Alexandra L. Burrows,Caroline E. Robertson
摘要
Abstract Individuals with autism spectrum conditions (ASC) describe differences in both social cognition and sensory processing, but little is known about the causal relationship between these disparate functional domains. In the present study, we sought to understand how a core characteristic of autism—reduced social attention—is impacted by the complex multisensory signals present in real‐world environments. We tested the hypothesis that reductions in social attention associated with autism would be magnified by increasing perceptual load (e.g., motion, multisensory cues). Adult participants ( N = 40; 19 ASC) explored a diverse set of 360° real‐world scenes in a naturalistic, active viewing paradigm (immersive virtual reality + eyetracking). Across three conditions, we systematically varied perceptual load while holding the social and semantic information present in each scene constant. We demonstrate that reduced social attention is not a static signature of the autistic phenotype. Rather, group differences in social attention emerged with increasing perceptual load in naturalistic environments, and the susceptibility of social attention to perceptual load predicted continuous measures of autistic traits across groups. Crucially, this pattern was specific to the social domain: we did not observe differential impacts of perceptual load on attention directed toward nonsocial semantic (i.e., object, place) information or low‐level fixation behavior (i.e., overall fixation frequency or duration). This study provides a direct link between social and sensory processing in autism. Moreover, reduced social attention may be an inaccurate characterization of autism. Instead, our results suggest that social attention in autism is better explained by “social vulnerability,” particularly to the perceptual load of real‐world environments.
科研通智能强力驱动
Strongly Powered by AbleSci AI