Literature DB >> 33651331

Disrupted frontostriatal connectivity in primary insomnia: a DTI study.

Longmao Chen1,2, Ziqiang Shao1,2, Yan Xu1,2, Shicong Wang1,2, Min Zhang1,2, Shuang Liu1,2, Xinwen Wen1,2, Bo Liu3, Xue Xia4, Kai Yuan5,6,7,8, Dahua Yu9.   

Abstract

Dysfunction of the sleep-wake transition is considered to be associated with the pathology of patients with primary insomnia (PI). Previous animal study had reported that brain circuits between the striatum and cortex can regulate sleep-wake transitions. So far, few studies have systematically explored the structural connectivity of the striatum-centered circuits and their potential roles in patients with PI. In this study, we chosen the striatum as the seed and 10 priori target regions as masks to assess the structural connectivity by using seed-based classification with a diffusion tensor imaging (DTI) probabilistic tractography method. Track strengths of the striatum-centered circuits were compared between 22 patients with PI (41.27 ± 9.21 years) and 30 healthy controls (HC) (35.2 ± 8.14 years). Pittsburgh Sleep Quality Index (PSQI) was used to measure the sleep quality in all participants. Lower track strengths (left striatum- anterior cingulate cortex (ACC), left striatum- dorsal anterior cingulate cortex (dACC), left striatum-Hippocampus, and right striatum-Hippocampus) were observed in patients with PI compared to HC. Additionally, the lower track strengths of brain circuits mentioned above were negatively correlated with PSQI. Taken together, our findings revealed the lower tract strength of frontostriatal circuits in patients with PI and HC, which provided the implications of the system-level structural connections of frontostriatal circuits in the pathology of PI. We suggested that the track strengths of the frontostriatal circuits calculated from DTI can be the potential neuroimaging biomarkers of the sleep quality in patients with PI.

Entities:  

Keywords:  DTI probabilistic tractography; Primary insomnia; Striatum‐centered circuits; Structural connectivity

Year:  2021        PMID: 33651331     DOI: 10.1007/s11682-021-00454-3

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


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