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 cross-time–frequency measures is introduced, including a cross-time–frequency phase synchronization measure.

► Bivariate measures estimate interactions between brain regions from EMEG data.
► Space–time, space–frequency, and space–time–frequency measures are described.
► Signal processing and information theoretic measures are considered.
► Linear and nonlinear methods are distinguished.
► Novel cross-time–frequency measures are introduced.