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. 2018 Jan 28:18:178-185.
doi: 10.1016/j.nicl.2018.01.012. eCollection 2018.

Disrupted brain network topology in chronic insomnia disorder: A resting-state fMRI study

Zhonglin Li  1 , Rui Chen  1 , Min Guan  1 , Enfeng Wang  1 , Tianyi Qian  2 , Cuihua Zhao  1 , Zhi Zou  1 , Thomas Beck  3 , Dapeng Shi  1 , Meiyun Wang  1 , Hongju Zhang  4 , Yongli Li  5
Affiliations

Disrupted brain network topology in chronic insomnia disorder: A resting-state fMRI study

Zhonglin Li et al. Neuroimage Clin. .

Abstract

This study investigated the topological characteristics of brain functional networks in chronic insomnia disorder (CID) patients. The resting-state functional magnetic resonance imaging and graph theory analysis method were applied to investigate the brain functional connectome patterns among 45 CID patients and 32 healthy controls. The brain functional connectome was constructed by thresholding partial correlation matrices of 90 brain regions from an automated anatomical labeling atlas. The topologic properties of brain functional connectomes at both global and nodal levels were tested. The CID patients had decreased number of module (p = .014) and hierarchy (p = .038), and increased assortativity (p = .035). Furthermore, some brain regions located in the default mode network, dorsal attention network, and sensory-motor network in these patients showed altered nodal centralities. Within these areas, the node betweenness of right central paracentral lobule had positive correlation with the Pittsburgh Sleep Quality Index score (R = 0.319, p = .039). The results imply that functional disruptions of CID patients may be related to disruptions in global and regional topological organization of the brain functional connectome, and provide new and important insights to understand the pathophysiological mechanisms of CID.

Keywords: Functional connectome; Graph theory; Insomnia; Network topology; Resting-state functional magnetic resonance imaging; Small-world.

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Figures

Fig. 1
Fig. 1
Altered global topological parameters of the functional connectome across different sparsity thresholds (0.01–0.4). (A) Network number of modularity of the functional connectome. (B) Network assortativity of the functional connectome. (C) Network hierarchy of the functional connectome. Black stars indicate where the difference between CID patients and HCs was significant (p < .05). Abbreviation: CID, chronic insomnia disorder; HC, healthy control.
Fig. 2
Fig. 2
Significantly altered nodal centralities of the brain functional connectome in CID patients, compared with HCs (p < .01, uncorrected). These connections formed a single connected network with ten nodes and five connections (p < .05, uncorrected). Red lines represent increased functional connectivity strength in CID patients. Blue lines represent decreased functional connectivity strength in CID patients. Details are listed in Table 3. Abbreviations: MFGorb, middle frontal orbital; oIFG, opercular inferior frontal gyrus; tIFG, triangular inferior frontal gyrus; ANG, angular; MCG, middle cingulum gyrus; HIP, hippocampus; CUN, cuneus; PCL, central paracentral lobule; ITG, inferior temporal gyrus; CID, chronic insomnia disorder; HC, healthy control.
Fig. 3
Fig. 3
(A) Scatterplot showing a significant positive correlation between CID patients PSQI scores and node betweenness of right PCL (R = 0.319, P = .039). (B) Scatterplot showing a significant negative correlation between CID patients HAMD scores and network modularity (R = −0.318, P = .040). Abbreviations: PSQI, Pittsburgh Sleep Quality Index; HAMA, Hamilton Anxiety Rating Scale; PCL, central paracentral Lobule; CID, chronic insomnia disorder.
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