title: Robustly estimating the flow direction of information in complex physical systems.
abstract: We propose a new measure (phase-slope index) to estimate the direction of information flux in multivariate time series. This measure (a) is insensitive to mixtures of independent sources, (b) gives meaningful results even if the phase spectrum is not linear, and (c) properly weights contributions from different frequencies. These properties are shown in extended simulations and contrasted to Granger causality which yields highly significant false detections for mixtures of independent sources. An application to electroencephalography data (eyes-closed condition) reveals a clear front-to-back information flow.
authors.affiliation: Fraunhofer FIRST IDA, Berlin, Germany.
authors.forename: Guido
authors.initials: G
authors.lastname: Nolte
authors.forename: Andreas
authors.initials: A
authors.lastname: Ziehe
authors.forename: Vadim V
authors.initials: VV
authors.lastname: Nikulin
authors.forename: Alois
authors.initials: A
authors.lastname: Schlögl
authors.forename: Nicole
authors.initials: N
authors.lastname: Krämer
authors.forename: Tom
authors.initials: T
authors.lastname: Brismar
authors.forename: Klaus-Robert
authors.initials: KR
authors.lastname: Müller
mesh_terms: D000465:Algorithms; D002540:Cerebral Cortex / Q000502:physiology; D003627:Data Interpretation, Statistical; D004569:Electroencephalography; D005583:Fourier Analysis; D006801:Humans; D008959:Models, Neurological; D008962:Models, Theoretical; D013788:Thalamus / Q000502:physiology