title: Identifying delayed directional couplings with symbolic transfer entropy.
abstract: We propose a straightforward extension of symbolic transfer entropy to enable the investigation of delayed directional relationships between coupled dynamical systems from time series. Analyzing time series from chaotic model systems, we demonstrate the applicability and limitations of our approach. Our findings obtained from applying our method to infer delayed directed interactions in the human epileptic brain underline the importance of our approach for improving the construction of functional network structures from data.
authors.affiliation: Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn, Germany and Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn, Germany and Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53175 Bonn, Germany.
authors.forename: Henning
authors.initials: H
authors.lastname: Dickten
authors.affiliation: Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn, Germany and Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn, Germany and Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53175 Bonn, Germany.
authors.forename: Klaus
authors.initials: K
authors.lastname: Lehnertz
mesh_terms: D001921:Brain / Q000503:physiopathology; D004569:Electroencephalography; D019277:Entropy; D004827:Epilepsy / Q000503:physiopathology; D006801:Humans; D008959:Models, Neurological; D008962:Models, Theoretical