| Literature DB >> 33791779 |
Jinming Xiao1,2, Huafu Chen1,2, Xiaolong Shan1,2, Changchun He1,2, Ya Li1,2, Xiaonan Guo3,4, Heng Chen5, Wei Liao1,2, Lucina Q Uddin6, Xujun Duan1,2.
Abstract
Much recent attention has been directed toward elucidating the structure of social interaction-communication dimensions and whether and how these symptom dimensions coalesce with each other in individuals with autism spectrum disorder (ASD). However, the underlying neurobiological basis of these symptom dimensions is unknown, especially the association of social interaction and communication dimensions with brain networks. Here, we proposed a method of whole-brain network-based regression to identify the functional networks linked to these symptom dimensions in a large sample of children with ASD. Connectome-based predictive modeling (CPM) was established to explore neurobiological evidence that supports the merging of communication and social interaction deficits into one symptom dimension (social/communication deficits). Results showed that the default mode network plays a core role in communication and social interaction dimensions. A primary sensory perceptual network mainly contributed to communication deficits, and high-level cognitive networks mainly contributed to social interaction deficits. CPM revealed that the functional networks associated with these symptom dimensions can predict the merged dimension of social/communication deficits. These findings delineate a link between brain functional networks and symptom dimensions for social interaction and communication and further provide neurobiological evidence supporting the merging of communication and social interaction deficits into one symptom dimension.Entities:
Keywords: autism spectrum disorder; connectome-based predictive modeling; functional brain networks; network-based regression; social–communication dimensions
Mesh:
Year: 2021 PMID: 33791779 PMCID: PMC8258445 DOI: 10.1093/cercor/bhab057
Source DB: PubMed Journal: Cereb Cortex ISSN: 1047-3211 Impact factor: 5.357