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Detecting chronotaxic systems from single-variable time series with separable amplitude and phase

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Detecting chronotaxic systems from single-variable time series with separable amplitude and phase. / Lancaster, Gemma; Clemson, Philip; Suprunenko, Yevhen; Stankovski, Tomislav; Stefanovska, Aneta.

In: Entropy, Vol. 17, No. 6, 23.06.2015, p. 4413-4438.

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@article{45c4038f60c1419abb8d83ac44c4c777,
title = "Detecting chronotaxic systems from single-variable time series with separable amplitude and phase",
abstract = "The recent introduction of chronotaxic systems provides the means to describe nonautonomous systems with stable yet time-varying frequencies which are resistant to continuous external perturbations. This approach facilitates realistic characterization of the oscillations observed in living systems, including the observation of transitions in dynamics which were not considered previously. The novelty of this approach necessitated the development of a new set of methods for the inference of the dynamics and interactions present in chronotaxic systems. These methods, based on Bayesian inference and detrended fluctuation analysis, can identify chronotaxicity in phase dynamics extracted from a single time series. Here, they are applied to numerical examples and real experimental EEG data. We also review the current methods, including their assumptions and limitations, elaborate on their implementation, and discuss future perspectives.",
author = "Gemma Lancaster and Philip Clemson and Yevhen Suprunenko and Tomislav Stankovski and Aneta Stefanovska",
year = "2015",
month = "6",
day = "23",
doi = "10.3390/e17064413",
language = "English",
volume = "17",
pages = "4413--4438",
journal = "Entropy",
issn = "1099-4300",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "6",

}

RIS

TY - JOUR

T1 - Detecting chronotaxic systems from single-variable time series with separable amplitude and phase

AU - Lancaster, Gemma

AU - Clemson, Philip

AU - Suprunenko, Yevhen

AU - Stankovski, Tomislav

AU - Stefanovska, Aneta

PY - 2015/6/23

Y1 - 2015/6/23

N2 - The recent introduction of chronotaxic systems provides the means to describe nonautonomous systems with stable yet time-varying frequencies which are resistant to continuous external perturbations. This approach facilitates realistic characterization of the oscillations observed in living systems, including the observation of transitions in dynamics which were not considered previously. The novelty of this approach necessitated the development of a new set of methods for the inference of the dynamics and interactions present in chronotaxic systems. These methods, based on Bayesian inference and detrended fluctuation analysis, can identify chronotaxicity in phase dynamics extracted from a single time series. Here, they are applied to numerical examples and real experimental EEG data. We also review the current methods, including their assumptions and limitations, elaborate on their implementation, and discuss future perspectives.

AB - The recent introduction of chronotaxic systems provides the means to describe nonautonomous systems with stable yet time-varying frequencies which are resistant to continuous external perturbations. This approach facilitates realistic characterization of the oscillations observed in living systems, including the observation of transitions in dynamics which were not considered previously. The novelty of this approach necessitated the development of a new set of methods for the inference of the dynamics and interactions present in chronotaxic systems. These methods, based on Bayesian inference and detrended fluctuation analysis, can identify chronotaxicity in phase dynamics extracted from a single time series. Here, they are applied to numerical examples and real experimental EEG data. We also review the current methods, including their assumptions and limitations, elaborate on their implementation, and discuss future perspectives.

U2 - 10.3390/e17064413

DO - 10.3390/e17064413

M3 - Journal article

VL - 17

SP - 4413

EP - 4438

JO - Entropy

JF - Entropy

SN - 1099-4300

IS - 6

ER -