Symbolic transfer entropy: inferring directionality in biosignals

Biomedizinische Technik. Biomedical Engineering
Matthäus Staniek, Klaus Lehnertz

Abstract

Inferring directional interactions from biosignals is of crucial importance to improve understanding of dynamical interdependences underlying various physiological and pathophysiological conditions. We here present symbolic transfer entropy as a robust measure to infer the direction of interactions between multidimensional dynamical systems. We demonstrate its performance in quantifying driver-responder relationships in a network of coupled nonlinear oscillators and in the human epileptic brain.

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Citations

Mar 8, 2013·PloS One·Michael WibralRaul Vicente
Jul 30, 2014·PloS One·Patricia WollstadtMichael Wibral
Aug 5, 2010·IEEE Transactions on Bio-medical Engineering·Matthias Wacker, Herbert Witte
Apr 10, 2013·Neuroscience Letters·Stefanie Blain-MoraesUncheol Lee
May 23, 2014·Brain Topography·Frederic ZublerKaspar Schindler
Aug 18, 2017·IEEE Transactions on Bio-medical Engineering·Gaetano ValenzaRiccardo Barbieri
Oct 27, 2011·Physiological Measurement·Klaus Lehnertz
Dec 31, 2014·Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences·Klaus Lehnertz, Henning Dickten
Dec 31, 2014·Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences·Alberto PortaNiels Wessel
Apr 22, 2016·Physiological Measurement·Andreas MüllerNiels Wessel
May 23, 2013·Anesthesiology·UnCheol LeeGeorge A Mashour
Jul 13, 2018·Frontiers in Neuroscience·Xerxes D Arsiwalla, Paul Verschure
Aug 23, 2018·Nature Reviews. Neurology·Levin KuhlmannHitten P Zaveri
Sep 17, 2017·Journal of Theoretical Biology·Maurizio Porfiri, Manuel Ruiz Marín

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