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Title: A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data.
Authors: T, Onojima
T, Goto
H, Mizuhara
T, Aoyagi
Author's alias: 水原, 啓暁
青柳, 富誌生
Issue Date: 16-Jan-2018
Publisher: Public Library of Science (PLoS)
Journal title: PLoS computational biology
Volume: 14
Issue: 1
Thesis number: e1005928
Abstract: Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results.
Rights: © 2018 Onojima et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
DOI(Published Version): 10.1371/journal.pcbi.1005928
PubMed ID: 29337999
Appears in Collections:Journal Articles

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