Research on interaction between default mode network and task-positive network in autism spectrum disorder based on coactivation patterns
10.3760/cma.j.cn113661-20221009-00278
- VernacularTitle:孤独症谱系障碍默认网络与任务正激活网络交互的共激活模式研究
- Author:
Qingyu ZHENG
1
;
Lei LI
1
;
Jinming XIAO
1
;
Huafu CHEN
1
;
Xujun DUAN
1
Author Information
1. 电子科技大学神经信息教育部重点实验室 电子科技大学生命科学与技术学院，成都 611731
- Publication Type:Journal Article
- Keywords:
Autistic disorder;
Coactivation pattern;
Functional integration and segregation;
Default mode network;
Task-positive network
- From:
Chinese Journal of Psychiatry
2023;56(4):284-291
- CountryChina
- Language:Chinese
-
Abstract:
Objective:This study aims to explore the abnormal instantaneous coactivation pattern of the key nodes of default mode network (DMN) and its relationship with social deficits in participants with autism spectrum disorder (ASD).Methods:This study included participants (ASD: n=354, healthy control (HC): n=446) from the Autism Brain Imaging Data Exchange (ABIDE), which is a multi-center and large-sample resting-state functional magnetic resonance imaging (rs-fMRI) database. Coactivation pattern (CAP) analysis was used to explore the coactivation pattern characteristics of medial prefrontal cortex (mPFC), the key node of DMN, and its abnormal interaction with other key nodes of DMN as well as task-positive network. Network dissociation index (NDI) was used to capture the extent of functional dissociation within and between networks and predict the clinical symptoms of ASD based on multi-variable support vector regression. Results:When mPFC was activated, precuneus, another key node of DMN, showed lower activation in participants with ASD than those in the HC group ( t=-4.21, P<0.01). Instead, dorsal anterior cingulate cortex (dACC) and orbital fronto-insula junction, key nodes of the salience network (SN), showed higher activation in participants with ASD than those in the HC group ( t=2.93, 2.61, all P<0.05). Additionally, compared with HC, ASD showed significantly higher NDI within DMN ( t=3.63, P<0.01) and significantly lower NDI between DMN and SN (dACC and orbital fronto-insula junction) ( t=-2.97, -3.31, all P<0.01). Additionally, using multi-variable support vector regression model, altered NDI could well predict social, speech communication deficits and disease severity of ASD ( r=0.191,0.216,0.186, all P<0.01). Conclusion:The CAP of mPFC in ASD in resting state was abnormal, which reflected the decreased functional integration within DMN and the decreased functional segregation between DMN and task-positive network. Besides, this abnormal network function pattern was closely related to clinical symptoms of ASD.
