Connectivity measures applied to human brain electrophysiological data

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• 作者：R.E. Greenblatt^a ; ^b ; ^{Richard.Greenblatt@gmail.com} ; M.E. Pflieger^a ; ^b ; A.E. Ossadtchi^c
• 关键词：Brain networks ; EEG ; MEG ; ECoG ; iEEG ; Mutual information ; Coherence ; Connectivity ; Causality
• 刊名：Journal of Neuroscience Methods
• 出版年：2012
• 期刊代码：33_01650270
• 类别：neu
• 出版时间：30 May, 2012
• 卷：207
• 期：1
• 页码：1-16
• 文件大小：715 K

摘要

Connectivity measures are (typically bivariate) statistical measures that may be used to estimate interactions between brain regions from electrophysiological data. We review both formal and informal descriptions of a range of such measures, suitable for the analysis of human brain electrophysiological data, principally electro- and magnetoencephalography. Methods are described in the space-time, space-frequency, and space-time-frequency domains. Signal processing and information theoretic measures are considered, and linear and nonlinear methods are distinguished. A novel set of cross-time-frequency measures is introduced, including a cross-time-frequency phase synchronization measure.