匹兹堡睡眠质量指数
原发性失眠
失眠症
心理学
人口
默认模式网络
医学
评定量表
磁共振弥散成像
连接体
精神科
神经科学
睡眠障碍
功能连接
发展心理学
睡眠质量
磁共振成像
放射科
环境卫生
作者
Yunfan Wu,Zhihua Zhou,Shishun Fu,Shaoqing Zeng,Xiaofen Ma,Fang Jin,Ning Yang,Chao Li,Yi Yin,Kelei Hua,Mengchen Liu,Guo‐Min Li,Kanghui Yu,Guihua Jiang
标识
DOI:10.3389/fpsyt.2020.00308
摘要
Purpose: Insomnia is the most prevalent sleep complaint in the general population but is often intractable due to uncertainty regarding the underlying pathomechanisms. Sleep is regulated by a network of neural structures interconnected with the core nodes of the brain connectome referred to as the ‘rich club’. We examined alterations in brain rich-club organization as revealed by diffusion tensor imaging (DTI) and the statistical relationships between abnormalities in rich-club metrics and the clinical features of primary insomnia (PI). Methods This study recruited 43 PI patients and 42 age-, sex- and education level-matched healthy controls. Differences in global and regional network parameters between PI and HC groups were compared by nonparametric tests, and Spearman’s correlations were calculated to assess associations of these network metrics with PI-related clinical features, including disease duration and scores on the Pittsburgh Sleep Quality Index, Insomnia Severity Index, Self-Rating Anxiety Scale and Self-Rating Depression Scale. Results Weighted white matter networks exhibited weaker rich-club organization in PI patients than healthy controls across different thresholds (50%, 75% and 90%) and parcellation schemes (AAL-90 and AAL-1024). Aberrant rich-club organization was found mainly in limbic-cortical-basal ganglia circuits and the default-mode network. Conclusions Abnormal rich-club metrics are a characteristic feature of PI-related to disease severity. These metrics provide potential clues to PI pathogenesis and may be useful as diagnostic markers and for assessment of treatment response.
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