title: Revealing direction of coupling between neuronal oscillators from time series: phase dynamics modeling versus partial directed coherence.
abstract: The problem of determining directional coupling between neuronal oscillators from their time series is addressed. We compare performance of the two well-established approaches: partial directed coherence and phase dynamics modeling. They represent linear and nonlinear time series analysis techniques, respectively. In numerical experiments, we found each of them to be applicable and superior under appropriate conditions: The latter technique is superior if the observed behavior is "closer" to limit-cycle dynamics, the former is better in cases that are closer to linear stochastic processes.
authors.affiliation: Saratov Branch of the Institute of RadioEngineering and Electronics, Russian Academy of Sciences, 38 Zelyonaya Street, Saratov, 410019, Russia.
authors.forename: Dmitry
authors.initials: D
authors.lastname: Smirnov
authors.forename: Bjoern
authors.initials: B
authors.lastname: Schelter
authors.forename: Matthias
authors.initials: M
authors.lastname: Winterhalder
authors.forename: Jens
authors.initials: J
authors.lastname: Timmer
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D005246:Feedback / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D009991:Oscillometry / Q000379:methods; D012815:Signal Processing, Computer-Assisted; D009435:Synaptic Transmission / Q000502:physiology*; D013997:Time Factors