A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data

PLoS Comput Biol. 2018 Jan 16;14(1):e1005928. doi: 10.1371/journal.pcbi.1005928. eCollection 2018 Jan.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Bayes Theorem
  • Brain / physiology*
  • Electroencephalography*
  • Female
  • Healthy Volunteers
  • Humans
  • Male
  • Models, Neurological
  • Normal Distribution
  • Oscillometry*
  • Periodicity
  • Reproducibility of Results
  • Signal Processing, Computer-Assisted
  • Systems Analysis
  • Young Adult

Grants and funding

TO was supported by JSPS KAKENHI Grant Number 15J07444. HM was supported by MEXT KAKENHI Grant Numbers 21120008 and 16H01610, and by JSPS KAKENHI Grant Number 25240019. HM and TA were partially supported by JST ImPACT (2015-PM11-09-01). TA was supported by MEXT KAKENHI Grant Numbers 15H05877 and 26120006, and by JSPS KAKENHI Grant Numbers 16KT0019, and 15587273. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.