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Abstract #3081

Study of brain network alternations in sleep-related hypermotor epilepsy by resting-state functional magnetic resonance imaging

Huaxia Pu1, Huaxia Pu2, Xintong Wu3, Liping Wang2, Qiaoyue Tan2, Weina Wang4, Xinyue Wan5, Xiaorui Su2, Simin Zhang2, Qiang Yue1, and Qiyong Gong6,7
1Radiology, West China Hospital of Sichuan University, Chengdu, China, 2Department of Radiology and Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China, 3Department of Neurology, West China Hospital of Sichuan University, Chengdu, China, 4Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China, 5Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China, 6Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 7Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, China

Synopsis

Keywords: Epilepsy, fMRI (resting state), Sleep-related hypermotor epilepsy, graph theory analysis, functional brain network.

Motivation: To investigate the topological properties of brain functional connectomes in patients with sleep-related hypermotor epilepsy (SHE).

Goal(s): Little is known about the topological organization changes of brain functional networks in SHE patients.

Approach: 57 SHE patients and 54 healthy controls underwent resting-state functional MRI examination. Topological properties of brain networks were identified using graph-based theoretical analysis.

Results: Compared to controls, SHE patients showed longer characteristic path length (Lp) and lower global efficiency (Eglob), decreased nodal centralities in several regions, and connectivity aberrations. Lp and normalized Lp had positive correlations while Eglob and nodal centralities of thalamus had negative correlations with epilepsy duration.

Impact: The aberrant topological properties in brain functional networks of SHE may provide insights into the pathophysiology of epileptogenesis. The identification and characterization of network changes may contribute to clinical treatment through the disruption or inhibition of these epileptogenic networks.

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Keywords