Changchun He1,2, Yanchi Chen3, Taorong Jian1,2, Heng Chen1,2, Xiaonan Guo1,2, Jia Wang4, Lijie Wu4, Huafu Chen1,2, Xujun Duan1,2. 1. The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformaiton, University of Electronic Science and Technology of China, Chengdu, 611731, China. 2. School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China. 3. Chengdu Shishi High School, Chengdu, 610041, China. 4. Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, 150081, China.
Abstract
Accumulating neuroimaging evidence suggests that abnormal functional connectivity of the default mode network (DMN) contributes to the social-cognitive deficits of autism spectrum disorder (ASD). Although most previous studies relied on conventional functional connectivity methods, which assume that connectivity patterns remain constant over time, understanding the temporal dynamics of functional connectivity during rest may provide new insights into the dysfunction of the DMN in ASD. In this work, dynamic functional connectivity analysis based on sliding time window correlation was applied to the resting-state functional magnetic resonance imaging data of 28 young children with ASD (age range: 3-7 years) and 29 matched typically developing controls (TD group). In addition, k-means cluster analysis was performed to identify distinct temporal states based on the spatial similarity of each functional connectivity pattern. Compared with the TD group, young children with ASD showed decreased dynamic functional connectivity variance between the posterior cingulate cortex (PCC) and the right precentral gyrus, which is negatively correlated with social motivation and social relating. Cluster analysis revealed significant differences in functional connectivity patterns between the ASD and TD groups in discrete temporal states. Our findings reveal that atypical dynamic interactions between the PCC and sensorimotor cortex are associated with social deficits in ASD. Results also highlight the critical role of PCC in the social-cognitive deficits of ASD and support the concept that understanding the dynamic neural interactions among brain regions can provide insights into functional abnormalities in ASD. Autism Research 2018, 11: 1479-1493.
Accumulating neuroimaging evidence suggests that abnormal functional connectivity of the default mode network (DMN) contributes to the social-cognitive deficits of autism spectrum disorder (ASD). Although most previous studies relied on conventional functional connectivity methods, which assume that connectivity patterns remain constant over time, understanding the temporal dynamics of functional connectivity during rest may provide new insights into the dysfunction of the DMN in ASD. In this work, dynamic functional connectivity analysis based on sliding time window correlation was applied to the resting-state functional magnetic resonance imaging data of 28 young children with ASD (age range: 3-7 years) and 29 matched typically developing controls (TD group). In addition, k-means cluster analysis was performed to identify distinct temporal states based on the spatial similarity of each functional connectivity pattern. Compared with the TD group, young children with ASD showed decreased dynamic functional connectivity variance between the posterior cingulate cortex (PCC) and the right precentral gyrus, which is negatively correlated with social motivation and social relating. Cluster analysis revealed significant differences in functional connectivity patterns between the ASD and TD groups in discrete temporal states. Our findings reveal that atypical dynamic interactions between the PCC and sensorimotor cortex are associated with social deficits in ASD. Results also highlight the critical role of PCC in the social-cognitive deficits of ASD and support the concept that understanding the dynamic neural interactions among brain regions can provide insights into functional abnormalities in ASD. Autism Research 2018, 11: 1479-1493.