Functional network characteristics based on EEG of patients in acute ischemic stroke: A pilot study

Article type: Research Article

Authors: Xin, Xiyan^{a; 1} | Duan, Fang^{b; 1} | Kranz, Georg S.^{c; d; e} | Shu, Dong^b | Fan, Ruiwen^a | Gao, Ying^f | Yan, Zheng^{b; *} | Chang, Jingling^{f; *}

Affiliations: [a] TCM Department, Peking University Third Hospital, Beijing, China | [b] Department of Information Science & Engineering, Huaqiao University, Xiamen, China | [c] Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China | [d] Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria | [e] TheState Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China | [f] Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China

Correspondence: [*] Address for correspondence: Jingling Chang, Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China. E-mail: [email protected]. and Yan Zheng, Department of Information Science & Engineering, Huaqiao University, Xiamen, 361021, China. E-mail: [email protected].

Note: [1] These authors contributed equally.

Abstract: BACKGROUND:Ischemic stroke is a common type of stroke associated with reorganization of functional network of the brain. OBJECTIVE:This pilot study aimed to investigate the characteristics of functional brain networks based on EEG in patients with acute ischemic stroke. METHODS:Seven patients with ischemic stroke within 72 hours of onset and seven healthy controls were enrolled in the study. Dynamic EEG monitoring and clinical information were repeatedly collected within 72 hours (T1), on the 5th day (T2), and on the 7th day (T3) of stroke onset. A directed transfer function was employed to construct functional brain connection patterns. Graph theoretical analysis was performed to evaluate the characteristics of functional brain networks. RESULTS:First, we found that the brain networks of ischemic stroke patients were quite different from the healthy controls. The clustering coefficient (0.001 < Threshold < 0.2) in Delta, Theta, and Alpha bands for the patients were significantly lower (P < 0.01) and the shortest path length in all bands (0.001 < Threshold < 0.2) for the patients were significantly longer (P < 0.01). Moreover, the peaks of the shortest path length for the patients seemed to be higher in all bands with larger thresholds. Secondly, the brain networks for the patients showed a characterized time-variation pattern. The clustering coefficient (0.001 < Threshold < 0.2) of T1 was higher than that of T2 in alpha band (P < 0.01). The shortest path length (0.001 < Threshold < 0.2) of T3 was shorter than that of T2 (P < 0.01) in all bands, and the peak of T3 was numerically higher than that of T2 in all bands with narrower thresholds. CONCLUSION:Functional brain networks in patients with acute ischemic stroke showed impaired global functional integration and decreased efficiency of information transmission compared with healthy subjects. The shortening of the shortest path length during the recovery indicates neural plasticity and reorganization.

Keywords: Acute ischemic stroke, functional connectivity, EEG, The clustering coefficient, The shortest path length

DOI: 10.3233/NRE-220107

Journal: NeuroRehabilitation, vol. 51, no. 3, pp. 455-465, 2022