<p>The paper explores the application of two nonlinear dynamics methods of phase dynamics modeling and the partial mean conditional probabilities of recurrence. The aim of the study is to identify triplewise couplings in three time series extracted from physiological rhythms of the respiratory, cardiovascular, and nervous systems. The determination reliability of three-oscillator network coupling structure was verified using the Rössler model of three interacting oscillators with known unidirectional connections. Differences in coupling configurations between the respiratory rhythm oscillations, blood pressure variability, and variability of neuronal activity in medulla oblongata neurons were identified in datasets of two groups. The use of the nonlinear dynamics methods made it possible to determine the influence of a pathological condition on the triplewise interactions of multivariate time series extracted from physiological rhythms.</p>

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Revealing the configuration of triplewise couplings of time series extracted from physiological rhythms

  • O. E. Dick,
  • A. L. Glazov

摘要

The paper explores the application of two nonlinear dynamics methods of phase dynamics modeling and the partial mean conditional probabilities of recurrence. The aim of the study is to identify triplewise couplings in three time series extracted from physiological rhythms of the respiratory, cardiovascular, and nervous systems. The determination reliability of three-oscillator network coupling structure was verified using the Rössler model of three interacting oscillators with known unidirectional connections. Differences in coupling configurations between the respiratory rhythm oscillations, blood pressure variability, and variability of neuronal activity in medulla oblongata neurons were identified in datasets of two groups. The use of the nonlinear dynamics methods made it possible to determine the influence of a pathological condition on the triplewise interactions of multivariate time series extracted from physiological rhythms.