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静息态脑电信号动态功能连接分析?
Dynamic functional connectivity of electro encephalogram in the resting state
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摘要: 静息态脑功能连接分析是近年来脑研究的一个热点问题，对于某些脑疾病的诊断及成因理解具有重要意义。已有的脑功能连接研究基本上都假设功能连接网络在一段时间内是稳定不变的，但越来越多的证据表明它应该是随时间动态变化的。对25名被试睁眼和闭眼状态的64电极脑电生理信号，采用独立成分分析、滑动时间窗、低分辨率脑电断层溯源、图论等方法和技术进行动态功能连接分析，展现了睁眼和闭眼两种基线状态下视觉网络、默认网络等功能连接网络随时间的动态变化，并对动态连接矩阵进行主成分分析得到了在整个时间段内具有代表意义的功能连接模式。该结论支持和补充了传统稳态脑功能连接的研究，也将为相关实验设计以及脑电信号临床研究提供基线选择依据。Abstract: Assessment of resting-state functional connectivity (FC) has become an important tool in studying brain disease mechanisms. Conclusions from previous resting-state investigations were based upon the hypothesis which assumed that the FC was constant throughout a period of task-free time. However, emerging evidence suggests that it may change over time. Here we investigate the dynamic FC based on the 64 electrodes EEG (electroencephalogram) of 25 healthy subjects in eyes closed (EC) and eyes open (EO) resting-state. A data-driven approach based on independent component analysis, standardized low-resolution tomography analysis, sliding time window, and graph theory are employed. Dynamic changes of FC over time with EC and EO in the visual network, the default mode network etc. are discovered. And the principal component analysis is used to the concatenated dynamic FC matrixes for finding meaningful FC patterns. Our results have complemental the traditional stationary analyses, and revealed novel insights in choosing the type of resting condition in experimental design and EEG clinical research.
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