Juan Kou1, Jiao Le1, Meina Fu1, Chunmei Lan1, Zhuo Chen1, Qin Li1, Weihua Zhao1, Lei Xu2, Benjamin Becker1, Keith M Kendrick1. 1. The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China. 2. Chengdu Southwest Children's Hospital, Institute of Child Rehabilitation Medicine, Chengdu, China.
Abstract
Altered patterns of visual social attention preference detected using eye-tracking and a variety of different paradigms are increasingly proposed as sensitive biomarkers for autism spectrum disorder. However, few eye-tracking studies have compared the relative efficacy of different paradigms to discriminate between autistic compared with typically developing children and their sensitivity to specific symptoms. To target this issue, the current study used three common eye-tracking protocols contrasting social versus nonsocial stimuli in young (2-7 years old) Chinese autistic (n = 35) and typically developing (n = 34) children matched for age and gender. Protocols included dancing people versus dynamic geometrical images, biological motion (dynamic light point walking human or cat) versus nonbiological motion (scrambled controls), and child playing with toy versus toy alone. Although all three paradigms differentiated autistic and typically developing children, the dancing people versus dynamic geometry pattern paradigm was the most effective, with autistic children showing marked reductions in visual preference for dancing people and correspondingly increased one for geometric patterns. Furthermore, this altered visual preference in autistic children was correlated with the Autism Diagnostic Observation Schedule social affect score and had the highest discrimination accuracy. Our results therefore indicate that decreased visual preference for dynamic social stimuli may be the most effective visual attention-based paradigm for use as a biomarker for autism in Chinese children. Clinical trial ID: NCT03286621 (clinicaltrials.gov); Clinical trial name: Development of Eye-tracking Based Markers for Autism in Young Children. Autism Res 2019, 12: 1529-1540.
Altered patterns of visual social attention preference detected using eye-tracking and a variety of different paradigms are increasingly proposed as sensitive biomarkers for autism spectrum disorder. However, few eye-tracking studies have compared the relative efficacy of different paradigms to discriminate between autistic compared with typically developing children and their sensitivity to specific symptoms. To target this issue, the current study used three common eye-tracking protocols contrasting social versus nonsocial stimuli in young (2-7 years old) Chinese autistic (n = 35) and typically developing (n = 34) children matched for age and gender. Protocols included dancing people versus dynamic geometrical images, biological motion (dynamic light point walking human or cat) versus nonbiological motion (scrambled controls), and child playing with toy versus toy alone. Although all three paradigms differentiated autistic and typically developing children, the dancing people versus dynamic geometry pattern paradigm was the most effective, with autisticchildren showing marked reductions in visual preference for dancing people and correspondingly increased one for geometric patterns. Furthermore, this altered visual preference in autisticchildren was correlated with the Autism Diagnostic Observation Schedule social affect score and had the highest discrimination accuracy. Our results therefore indicate that decreased visual preference for dynamic social stimuli may be the most effective visual attention-based paradigm for use as a biomarker for autism in Chinese children. Clinical trial ID: NCT03286621 (clinicaltrials.gov); Clinical trial name: Development of Eye-tracking Based Markers for Autism in Young Children. Autism Res 2019, 12: 1529-1540.
Authors: Emily J Knight; Aaron I Krakowski; Edward G Freedman; John S Butler; Sophie Molholm; John J Foxe Journal: Mol Autism Date: 2022-07-18 Impact factor: 6.476