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Front. Physiol. | doi: 10.3389/fphys.2018.00475

Abnormal functional connectivity of resting state network detection based on linear ICA analysis in autism spectrum disorder

 Xia-An Bi1*, Qian Xu1, Junxia Zhao1, Qi Sun1 and Zhigang Wang1
  • 1Hunan Normal University, China

Some functional magnetic resonance imaging (fMRI) researches in autism spectrum disorder (ASD) patients have shown that ASD patients have significant impairment in brain response. However, few researchers have studied the functional structure changes of the eight resting state networks (RSNs) in ASD patients. Therefore, research on statistical differences of RSNs between 42 healthy controls (HC) and 50 ASD patients has been studied using linear independent component analysis (ICA) in this paper. Our researches showed that there was abnormal functional connectivity (FC) of RSNs in ASD patients. The RSNs with the decreased FC and increased FC in ASD patients included default mode network (DMN), central executive network (CEN), core network (CN), visual network (VN), self-referential network (SRN) compared to HC. The RSNs with the increased FC in ASD patients included auditory network (AN), somato-motor network (SMN). The dorsal attention network (DAN) in ASD patients showed the decreased FC. Our findings indicate that the abnormal FC in RSNs extensively exists in ASD patients. Our results have important contribution for the study of neuro-pathophysiological mechanisms in ASD patients.

Keywords: Linear independent component analysis, functional connectivity, Autism Spectrum Disorder, Neuro-pathophysiological mechanisms, resting state networks

Received: 29 Aug 2017; Accepted: 16 Apr 2018.

Edited by:

Quanxin Zhu, Nanjing Normal University, China

Reviewed by:

Hiroaki Wagatsuma, Kyushu Institute of Technology, Japan
Guanjun Wang, Southeast University, China  

Copyright: © 2018 Bi, Xu, Zhao, Sun and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Xia-An Bi, Hunan Normal University, Changsha, China, bixiaan@hnu.edu.cn