title: Granger causality and information flow in multivariate processes.
abstract: The multivariate versus bivariate measures of Granger causality were considered. Granger causality in the application to multivariate physiological time series has the meaning of the information flow between channels. It was shown by means of simulations and by the example of experimental electroencephalogram signals that bivariate estimates of directionality in case of mutually interdependent channels give erroneous results, therefore multivariate measures such as directed transfer function should be used for determination of the information flow.
authors.affiliation: Laboratory of Medical Physics, Institute of Experimental Physics, Warsaw University, Hoza 69, 00-681 Warsaw, Poland.
authors.forename: Katarzyna J
authors.initials: KJ
authors.lastname: Blinowska
authors.forename: Rafał
authors.initials: R
authors.lastname: Kuś
authors.forename: Maciej
authors.initials: M
authors.lastname: Kamiński
mesh_terms: D000465:Algorithms; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping / Q000379:methods*; D015984:Causality; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008959:Models, Neurological; D015233:Models, Statistical; D015999:Multivariate Analysis; D009415:Nerve Net / Q000502:physiology*; D013223:Statistics as Topic; D009435:Synaptic Transmission / Q000502:physiology