Connectivity measures applied to human brain electrophysiological data
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 crosstime–frequency measures is introduced, including a cross-time–frequency phase synchronization measure.