Identifying delayed directional couplings with symbolic transfer entropy
arXiv:1610.02308 · doi:10.1103/PhysRevE.90.062706
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.
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Cited by in corpus (6)
- Assessing directionality and strength of coupling through symbolic analysis: an application to epilepsy patients
- Ordinal methods for a characterization of evolving functional brain networks
- Transfer entropy computation using the Perron-Frobenius operator
- Reconstruction of a scalar voltage-based neural field network from observed time series
- Transcript-based estimators for characterizing interactions
- Unravelling the Flow of Information in a Nonequilibrium Process in the Presence of Hydrodynamic Interactions