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Abnormal Topology of the Structural Connectome in the Limbic Cortico-Basal-Ganglia Circuit and Default-Mode Network Among Primary Insomnia Patients

Authors :
Yunfan Wu
Mengchen Liu
Shaoqing Zeng
Xiaofen Ma
Jianhao Yan
Chulan Lin
Guang Xu
Guomin Li
Yi Yin
Shishun Fu
Kelei Hua
Chao Li
Tianyue Wang
Cheng Li
Guihua Jiang
Source :
Frontiers in Neuroscience, Vol 12 (2018)
Publication Year :
2018
Publisher :
Frontiers Media S.A., 2018.

Abstract

Purpose: Primary insomnia (PI) is the second most common mental disorder. However, the topologic alterations in structural brain connectome in patients with PI remain largely unknown.Methods: A total of 44 PI patients and 46 age-, gender-, and education level matched healthy control (HC) participants were recruited in this study. Diffusion tensor imaging (DTI) and resting state MRI were used to construct structural connectome for each participant, and the network parameters were employed by non-parametric permutations to evaluate the significant differences between the two groups. Relationships between abnormal network metrics and clinical characteristics, including the disease duration, the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), the Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS), were investigated with Spearman’s correlation analysis in PI patients.Results: PI patients demonstrated small-world architecture with lower global (P = 0.005) and local (P = 0.035) efficiencies compared with the HC group. The unique hub nodal properties in PI patients were mainly in the right limbic cortico-basal-ganglia circuit. Five disrupted subnetworks in PI patients were observed in the limbic cortico-basal-ganglia circuit and left default-mode networks (DMN) (P < 0.05, NBS corrected). Moreover, most unique hub nodal properties in the right limbic cortico-basal-ganglia circuit were significantly correlated with disease duration, and clinical characteristics (SAS, SDS, ISI scores) in PI processing.Conclusion: These findings suggested the abnormal anatomical network architecture may be closely linked to clinical characteristics in PI. The study provided novel insights into the neural substrates underlying symptoms and neurophysiologic mechanisms of PI.

Details

Language :
English
ISSN :
1662453X
Volume :
12
Database :
Directory of Open Access Journals
Journal :
Frontiers in Neuroscience
Publication Type :
Academic Journal
Accession number :
edsdoj.25fda2a31bcc434da06fdc30f95d22c6
Document Type :
article
Full Text :
https://doi.org/10.3389/fnins.2018.00860