Altered dynamic network interactions in children with ASD during face recognition revealed by time-varying EEG networks.
Cereb Cortex
; 33(22): 11170-11180, 2023 11 04.
Article
em En
| MEDLINE
| ID: mdl-37750334
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.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Reconhecimento Facial
/
Transtorno do Espectro Autista
Limite:
Child
/
Humans
Idioma:
En
Revista:
Cereb Cortex
Assunto da revista:
CEREBRO
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
China