Robustly estimating the flow direction of information in complex physical systems.
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.
Nolte
Guido
G
Fraunhofer FIRST IDA, Berlin, Germany.
Ziehe
Andreas
A
Nikulin
Vadim V
VV
Schlögl
Alois
A
Krämer
Nicole
N
Brismar
Tom
T
Müller
Klaus-Robert
KR
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