Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4335194 | Journal of Neuroscience Methods | 2012 | 16 Pages |
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.