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Updated: Jul 16, 2026

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
More than just statics: altered complexity of dynamic amplitude of low-frequency fluctuations in the resting brain
Na Tian1,2, Liu-Ke Liang1,3, Xue-Mao Luo4
1Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510006, Guangdong, People's Republic of China.
Abstract:
Objective.Previous neuroimaging studies mainly focused on static characteristics of brain activity, and little is known about its characteristics over time, especially in post-stroke (PS) patients. In this study, we aimed to investigate the static and dynamic characteristics of brain activity after stroke using functional magnetic resonance imaging (fMRI).Approach.Twenty ischemic PS patients and nineteen healthy controls (HCs) were recruited to receive a resting-state fMRI scanning. The static amplitude of low-frequency fluctuations (sALFFs) and fuzzy entropy of dynamic ALFF (FE-dALFF) were applied to identify the stroke-induced alterations.Main results.Compared with the HCs, PS patients showed significantly increased FE-dALFF values in the right angular gyrus (ANG), bilateral precuneus (PCUN), and right inferior parietal lobule (IPL) as well as significantly decreased FE-dALFF values in the right postcentral gyrus (PoCG), right dorsolateral superior frontal gyrus (SFGdor), and right precentral gyrus (PreCG). The receiver operating characteristic analyses demonstrated that FE-dALFF and sALFF possess comparable sensitivity in distinguishing PS patients from the HCs. Moreover, a significantly positive correlation was observed between the FE-dALFF values and the Fugl-Meyer Assessment (FMA) scores in the right SFGdor (r= 0.547), right IPL (r= 0.522), and right PCUN (r= 0.486).Significance.This study provided insight into the stroke-induced alterations in static and dynamic characteristics of local brain activity, highlighting the potential of FE-dALFF in understanding neurophysiological mechanisms and evaluating pathological changes.
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