Connectivity measures applied to human brain electrophysiological data

J Neurosci Methods. 2012 May 30;207(1):1-16. doi: 10.1016/j.jneumeth.2012.02.025. Epub 2012 Mar 16.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Brain / physiology*
  • Electrophysiological Phenomena*
  • Humans
  • Models, Neurological*
  • Models, Statistical*
  • Nerve Net / physiology*
  • Neural Pathways / physiology
  • Signal Processing, Computer-Assisted*