Investigating the Face Inversion Effect in Autism Across Behavioral and Neural Measures of Face Processing

神经质的 自闭症谱系障碍 自闭症 荟萃分析 心理学 人工智能 计算机科学 认知 认知心理学 机器学习 发展心理学 医学 精神科 内科学
作者
Jason W. Griffin,Margaret A. Azu,Sophie Cramer-Benjamin,Cassandra J. Franke,Nicole Herman,Reeda Iqbal,Cara M. Keifer,Lindsey H. Rosenthal,James C. McPartland
出处
期刊:JAMA Psychiatry [American Medical Association]
卷期号:80 (10): 1026-1026 被引量:18
标识
DOI:10.1001/jamapsychiatry.2023.2105
摘要

Importance: Face processing is foundational to human social cognition, is central to the hallmark features of autism spectrum disorder (ASD), and shapes neural systems and social behavior. Highly efficient and specialized, the face processing system is sensitive to inversion, demonstrated by reduced accuracy in recognition and altered neural response to inverted faces. Understanding at which mechanistic level the autistic face processing system may be particularly different, as measured by the face inversion effect, will improve overall understanding of brain functioning in autism. Objective: To synthesize data from the extant literature to determine differences of the face processing system in ASD, as measured by the face inversion effect, across multiple mechanistic levels. Data Sources: Systematic searches were conducted in the MEDLINE, Embase, Web of Science, and PubMed databases from inception to August 11, 2022. Study Selection: Original research that reported performance-based measures of face recognition to upright and inverted faces in ASD and neurotypical samples were included for quantitative synthesis. All studies were screened by at least 2 reviewers. Data Extraction and Synthesis: This systematic review and meta-analysis was conducted according to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Multiple effect sizes were extracted from studies to maximize information gain and statistical precision and used a random-effects, multilevel modeling framework to account for statistical dependencies within study samples. Main Outcomes and Measures: Effect sizes were calculated as a standardized mean change score between ASD and neurotypical samples (ie, Hedges g). The primary outcome measure was performance difference between upright and inverted faces during face recognition tasks. Measurement modality, psychological construct, recognition demand, sample age, sample sex distribution, and study quality assessment scores were assessed as moderators. Results: Of 1768 screened articles, 122 effect sizes from 38 empirical articles representing data from 1764 individual participants (899 ASD individuals and 865 neurotypical individuals) were included in the meta-analysis. Overall, face recognition performance differences between upright and inverted faces were reduced in autistic individuals compared with neurotypical individuals (g = -0.41; SE = 0.11; 95% credible interval [CrI], -0.63 to -0.18). However, there was considerable heterogeneity among effect sizes, which were explored with moderator analysis. The attenuated face inversion effect in autistic individuals was more prominent in emotion compared with identity recognition (b = 0.46; SE = 0.26; 95% CrI, -0.08 to 0.95) and in behavioral compared with electrophysiological measures (b = 0.23; SE = 0.24; 95% CrI, -0.25 to 0.70). Conclusions and Relevance: This study found that on average, face recognition in autism is less impacted by inversion. These findings suggest less specialization or expertise of the face processing system in autism, particularly in recognizing emotion from faces as measured in behavioral paradigms.
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