Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity

被引:24
作者
Racz, Frigyes Samuel [1 ]
Stylianou, Orestis [1 ]
Mukli, Peter [1 ]
Eke, Andras [1 ]
机构
[1] Semmelweis Univ, Dept Physiol, 37-47 Tuzolto St, H-1094 Budapest, Hungary
关键词
PHYSIOLOGICAL TIME-SERIES; GENERALIZED SYNCHRONIZATION; VARYING CONNECTIVITY; NETWORKS; EEG; POWER; LIKELIHOOD; SIGNAL; MODEL;
D O I
10.1038/s41598-019-49726-5
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Functional connectivity of the brain fluctuates even in resting-state condition. It has been reported recently that fluctuations of global functional network topology and those of individual connections between brain regions expressed multifractal scaling. To expand on these findings, in this study we investigated if multifractality was indeed an inherent property of dynamic functional connectivity (DFC) on the regional level as well. Furthermore, we explored if local DFC showed region-specific differences in its multifractal and entropy-related features. DFC analyses were performed on 62-channel, resting-state electroencephalography recordings of twelve young, healthy subjects. Surrogate data testing verified the true multifractal nature of regional DFC that could be attributed to the presumed nonlinear nature of the underlying processes. Moreover, we found a characteristic spatial distribution of local connectivity dynamics, in that frontal and occipital regions showed stronger long-range correlation and higher degree of multifractality, whereas the highest values of entropy were found over the central and temporal regions. The revealed topology reflected well the underlying resting-state network organization of the brain. The presented results and the proposed analysis framework could improve our understanding on how resting-state brain activity is spatio-temporally organized and may provide potential biomarkers for future clinical research.
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页数:15
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