The role of ascending arousal network in patients with chronic insomnia disorder

作者：Liang Gong, Kewu He, Cheng Fang, Zhenping Deng, Kang Cheng, Xi'e Zhang, Wenjun Zhou, Ou Jing, Jian Wang, Bei Zhang, Xin Ding, Ronghua Xu, Chunhua Xi · 发表于：Human Brain Mapping · 年份：2022 · DOI：10.1002/hbm.26072 · 被引用次数：23 · 研究领域：Functional Brain Connectivity Studies、Sleep and Wakefulness Research、Advanced Neuroimaging Techniques and Applications

Abstract The ascending arousal system plays a crucial role in individuals' consciousness. Recently, advanced functional magnetic resonance imaging (fMRI) has made it possible to investigate the ascending arousal network (AAN) in vivo. However, the role of AAN in the neuropathology of human insomnia remains unclear. Our study aimed to explore alterations in AAN and its connections with cortical networks in chronic insomnia disorder (CID). Resting‐state fMRI data were acquired from 60 patients with CID and 60 good sleeper controls (GSCs). Changes in the brain's functional connectivity (FC) between the AAN and eight cortical networks were detected in patients with CID and GSCs. Multivariate pattern analysis (MVPA) was employed to differentiate CID patients from GSCs and predict clinical symptoms in patients with CID. Finally, these MVPA findings were further verified using an external data set (32 patients with CID and 33 GSCs). Compared to GSCs, patients with CID exhibited increased FC within the AAN, as well as increased FC between the AAN and default mode, cerebellar, sensorimotor, and dorsal attention networks. These AAN‐related FC patterns and the MVPA classification model could be used to differentiate CID patients from GSCs with 88% accuracy in the first cohort and 77% accuracy in the validation cohort. Moreover, the MVPA prediction models could separately predict insomnia (data set 1, R 2 = .34; data set 2, R 2 = .15) and anxiety symptoms (data set 1, R 2 = .35; data set...