Abnormal Global Brain Functional Connectivity in Primary Insomnia Patients: A Resting-State Functional MRI Study - Yan, Chao-Qun; Wang, Xu; Huo, Jian-Wei; Zhou, Ping; Li, Jin-Ling; Wang, Zhong-Yan; Zhang, Jie; Fu, Qing-Nan; Wang, Xue-Rui; Liu, Cun-Zhi; Liu, Qing-Quan (Frontiers in Neurology, 2018)
Background: Resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated the disruptions of functional brain networks in primary insomnia (PI) patients. However, the etiology and pathogenesis underlying this disorder remains ambiguous, and the insomnia related symptoms are inﬂuenced by a complex network organization in the brain. The purpose of this study was to explore the abnormal intrinsic functional hubs in PI patients using a voxel-wise degree centrality (DC) analysis and seed-based functional connectivity (FC) approach. Methods: Twenty-six PI patients and 28 healthy controls were enrolled and underwent resting-state fMRI. DC was measured across the whole brain, and group differences in DC were compared. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC of the whole brain. Then, correlation analyses were performed between the changes in brain function and clinical features. Results: PI patients showed lower DC values than healthy controls in the left inferior frontal gyrus (IFG) and middle temporal gyrus (MTG), and higher DC values in the right precuneus. The seed-based analyses demonstrated decreased FC between the left MTG and the left posterior cingulate cortex (PCC), and decreased FC between the right precuneus and the right lateral occipital cortex. Reduced DC in the left LFG and decreased FC in the left PCC were positively correlated with Pittsburgh sleep quality index and Insomnia Severity Index. Conclusions: This study revealed that PI patients exhibited abnormal intrinsic functional hubs in the left IFG, MTG and the right precuneus, as well as abornomal seed-based FC in these hubs. The results contribute to better understand how brain function inﬂuences the symptoms of PI.