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Neuroscience. 2020 Mar 17. pii: S0306-4522(20)30170-6. doi: 10.1016/j.neuroscience.2020.03.020. [Epub ahead of print]

Reduced Complexity in Stroke with Motor Deficits: A Resting-State fMRI Study.

Author information

1
Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510006, China.
2
Department of Rehabilitation Medicine, Jiangmen Central Hospital, Jiangmen, Guangdong, China.
3
Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China.
4
Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510006, China. Electronic address: songrong@mail.sysu.edu.cn.

Abstract

Recently, alterations of complexity due to brain disorders have been demonstrated using brain entropy (BEN), while the changes of brain complexity in stroke, a common cerebrovascular disease, remain unclear. In this research, resting-state functional magnetic resonance imaging (fMRI) was performed to explore the alterations of brain complexity using BEN in twenty stroke patients with motor deficits and nineteen matched healthy controls. The sample entropy (SampEn) was applied to build the BEN mapping for each participant. Compared with healthy controls, stroke patients exhibited lower BEN values in the contralesional precentral gyrus (preCG), bilateral dorsolateral frontal gyrus (SFGdor) and bilateral supplementary motor area (SMA). Moreover, significantly positive correlations between BEN values and Fugl-Meyer Assessment scores were detected in the ipsilesional SFGdor and ipsilesional SMA. Mutual information independence was observed between BEN and regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), respectively, in the stroke patients. Our findings implied that brain complexity had been impacted after stroke, and also suggested that BEN could be a complementary tool for evaluating the motor impairment after stroke.

KEYWORDS:

Complexity; brain entropy; motor deficits; resting-state fMRI; sample entropy; stroke

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