2018年1月
A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data.
PLoS computational biology
- ,
- ,
- ,
- 巻
- 14
- 号
- 1
- 開始ページ
- e1005928
- 終了ページ
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1371/journal.pcbi.1005928
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.
- リンク情報
- ID情報
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- DOI : 10.1371/journal.pcbi.1005928
- ISSN : 1553-734X
- PubMed ID : 29337999
- PubMed Central 記事ID : PMC5770039