Altered dynamic network interactions in children with ASD during face recognition revealed by time-varying EEG networks

Author:

Chen Baodan1234,Jiang Lin1234,Lu Guoqing5,Li Yuqin1234,Zhang Shu34,Huang Xunan12346,Xu Peng123478,Li Fali12347,Yao Dezhong123479

Affiliation:

1. The Clinical Hospital of Chengdu Brain Science Institute , MOE Key Lab for Neuroinformation, , Chengdu 610054 , China

2. University of Electronic Science and Technology of China , MOE Key Lab for Neuroinformation, , Chengdu 610054 , China

3. School of Life Science and Technology , Center for Information in BioMedicine, , Chengdu 611731 , China

4. University of Electronic Science and Technology of China , Center for Information in BioMedicine, , Chengdu 611731 , China

5. School of Computer Science and Technology, Chongqing University of Posts and Telecommunications , Chongqing 600054 , China

6. School of Foreign Languages, University of Electronic Science and Technology of China , Chengdu 611731 , China

7. Research Unit of Neuro Information, Chinese Academy of Medical Sciences , Chengdu 2019RU035 , China

8. Radiation Oncology Key Laboratory of Sichuan Province , Chengdu 610041 , China

9. School of Electrical Engineering, Zhengzhou University , Zhengzhou 450001 , China

Abstract

Abstract Although the electrophysiological event-related potential in face processing (e.g. N170) is widely accepted as a face-sensitivity biomarker that is deficient in children with autism spectrum disorders, the time-varying brain networks during face recognition are still awaiting further investigation. To explore the social deficits in autism spectrum disorder, especially the time-varying brain networks during face recognition, the current study analyzed the N170, cortical activity, and time-varying networks under 3 tasks (face-upright, face-inverted, and house-upright) in autism spectrum disorder and typically developing children. The results revealed a smaller N170 amplitude in autism spectrum disorder compared with typically developing, along with decreased cortical activity mainly in occipitotemporal areas. Concerning the time-varying networks, the atypically stronger information flow and brain network connections across frontal, parietal, and temporal regions in autism spectrum disorder were reported, which reveals greater effort was exerted by autism spectrum disorder to obtain comparable performance to the typically developing children, although the amplitude of N170 was still smaller than that of the typically developing children. Different brain activation states and interaction patterns of brain regions during face processing were discovered between autism spectrum disorder and typically developing. These findings shed light on the face-processing mechanisms in children with autism spectrum disorder and provide new insight for understanding the social dysfunction of autism spectrum disorder.

Funder

STI 2030-Major Projects

National Natural Science Foundation of China

Scientific Research of Brain Science and Brain Computer Interface Technology

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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