Abnormal Topology of the Structural Connectome in the Limbic Cortico-Basal-Ganglia Circuit and Default-Mode Network Among Primary Insomnia Patients - Wu, Yunfan; Liu, Mengchen; Zeng, Shaoqing; Ma, Xiaofen; Yan, Jianhao; Lin, Chulan; Xu, Guang; Li, Guomin; Yin, Yi; Fu, Shishun; Hua, Kelei; Li, Chao; et al. (Frontiers in Neuroscience, 2018)
Abstract: Purpose Insomnia is the second most common mental disorder. However, the topologic alterations in structural brain connectome in patients with primary insomnia (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 nonparametric 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. Conclusions 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.