title: Connectivity measures applied to human brain electrophysiological data.
abstract: 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.
authors.affiliation: Source Signal Imaging, Inc., San Diego, CA, USA. Richard.Greenblatt@gmail.com
authors.forename: R E
authors.initials: RE
authors.lastname: Greenblatt
authors.forename: M E
authors.initials: ME
authors.lastname: Pflieger
authors.forename: A E
authors.initials: AE
authors.lastname: Ossadtchi
mesh_terms: D001921:Brain / Q000502:physiology*; D055724:Electrophysiological Phenomena; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net / Q000502:physiology*; D009434:Neural Pathways / Q000502:physiology; D012815:Signal Processing, Computer-Assisted