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| Global Motif-Synchronization Based Multivariate EEG Synchronization Analysis |
| Cui Dong1*, Pu Weiting1, Li Xiaoli2, Wang Lei3, Yin Shimin3, Bian Zhijie3, |
1( School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China)
2(State Key Laboratory of Cognitive Neuroscience and Learning ＆ IDG/McGovern Institute for Brain Research, Beijing Normal University,Beijing 100875, China)
3(Department of Neurology, The Rocket Force General Hospital of PLA, Beijing 100088, China) |
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Abstract EEG synchronization is considered to be the performance of brain functional area integration. A time series motif based multi-channel synchronization method——global motif-synchronization (GMS) was proposed in this study. The simulation analysis indicated that the new algorithm was more sensitive than S-estimator based normalized weighted permutation mutual information in detection weak coupling. The algorithm was used to analyze the EEG synchronization of 26 amnesic MCI and 20 normal controls of patients with diabetes in eye-closed resting state. The wavelet enhanced independent component analysis was used to eliminate artifacts. The 32-channels EEG was divided to frontal, central, parietal, occipital, left temporal and right temporal region respectively. The independent samples t-test was performed to test differences in demographic characteristics, neuropsychology and regional synchronization values between two groups. The Pearson’s linear correlation was used to study the associations between regional synchronization values and cognitive functions. The results showed that GMS values in each brain region of diabetes patients with MCI were lower than that of control group. Especially, the GMS values decreased significantly in central (P<0.01), parietal (P<0.05) and occipital (P<0.05) regions. The MOCA scores and GMS value had a significant positive correlation in frontal (r=0.298, P=0.045), central (r=0.327, P=0.026) and parietal (r=0.32, P=0.03) regions. The GMS is an important EEG characteristic that is correlated with cognitive function impairment.
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Received: 30 May 2016
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