Computer-analyzed facial expression as a surrogate marker for autism spectrum social core symptoms

计算机分析的面部表情作为自闭症谱系社交核心症状的替代指标

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Abstract

To develop novel interventions for autism spectrum disorder (ASD) core symptoms, valid, reliable, and sensitive longitudinal outcome measures are required for detecting symptom change over time. Here, we tested whether a computerized analysis of quantitative facial expression measures could act as a marker for core ASD social symptoms. Facial expression intensity values during a semi-structured socially interactive situation extracted from the Autism Diagnostic Observation Schedule (ADOS) were quantified by dedicated software in 18 high-functioning adult males with ASD. Controls were 17 age-, gender-, parental socioeconomic background-, and intellectual level-matched typically developing (TD) individuals. Statistical analyses determined whether values representing the strength and variability of each facial expression element differed significantly between the ASD and TD groups and whether they correlated with ADOS reciprocal social interaction scores. Compared with the TD controls, facial expressions in the ASD group appeared more "Neutral" (d = 1.02, P = 0.005, PFDR < 0.05) with less variation in Neutral expression (d = 1.08, P = 0.003, PFDR < 0.05). Their expressions were also less "Happy" (d = -0.78, P = 0.038, PFDR > 0.05) with lower variability in Happy expression (d = 1.10, P = 0.003, PFDR < 0.05). Moreover, the stronger Neutral facial expressions in the ASD participants were positively correlated with poorer ADOS reciprocal social interaction scores (ρ = 0.48, P = 0.042). These findings indicate that our method for quantitatively measuring reduced facial expressivity during social interactions can be a promising marker for core ASD social symptoms.

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