Testing Jump-Diffusion in Epileptic Brain Dynamics: Impact of Daily Rhythms

Stochastic approaches to complex dynamical systems have recently provided broader insights into spatial-temporal aspects of epileptic brain dynamics. Stochastic qualifiers based on higher-order Kramers-Moyal coefficients derived directly from time series data indicate improved differentiability betw...

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Main Authors: Jutta G. Kurth, Thorsten Rings, Klaus Lehnertz
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/23/3/309
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spelling doaj-1e099d72804546c2b9bc50a9c94922b32021-03-06T00:08:16ZengMDPI AGEntropy1099-43002021-03-012330930910.3390/e23030309Testing Jump-Diffusion in Epileptic Brain Dynamics: Impact of Daily RhythmsJutta G. Kurth0Thorsten Rings1Klaus Lehnertz2Department of Epileptology, University Hospital Bonn, Venusberg Campus 1, 53127 Bonn, GermanyDepartment of Epileptology, University Hospital Bonn, Venusberg Campus 1, 53127 Bonn, GermanyDepartment of Epileptology, University Hospital Bonn, Venusberg Campus 1, 53127 Bonn, GermanyStochastic approaches to complex dynamical systems have recently provided broader insights into spatial-temporal aspects of epileptic brain dynamics. Stochastic qualifiers based on higher-order Kramers-Moyal coefficients derived directly from time series data indicate improved differentiability between physiological and pathophysiological brain dynamics. It remains unclear, however, to what extent stochastic qualifiers of brain dynamics are affected by other endogenous and/or exogenous influencing factors. Addressing this issue, we investigate multi-day, multi-channel electroencephalographic recordings from a subject with epilepsy. We apply a recently proposed criterion to differentiate between Langevin-type and jump-diffusion processes and observe the type of process most qualified to describe brain dynamics to change with time. Stochastic qualifiers of brain dynamics are strongly affected by endogenous and exogenous rhythms acting on various time scales—ranging from hours to days. Such influences would need to be taken into account when constructing evolution equations for the epileptic brain or other complex dynamical systems subject to external forcings.https://www.mdpi.com/1099-4300/23/3/309diffusion processjump-diffusion processtime series analysisbrainepilepsybiological rhythms
collection DOAJ
language English
format Article
sources DOAJ
author Jutta G. Kurth
Thorsten Rings
Klaus Lehnertz
spellingShingle Jutta G. Kurth
Thorsten Rings
Klaus Lehnertz
Testing Jump-Diffusion in Epileptic Brain Dynamics: Impact of Daily Rhythms
Entropy
diffusion process
jump-diffusion process
time series analysis
brain
epilepsy
biological rhythms
author_facet Jutta G. Kurth
Thorsten Rings
Klaus Lehnertz
author_sort Jutta G. Kurth
title Testing Jump-Diffusion in Epileptic Brain Dynamics: Impact of Daily Rhythms
title_short Testing Jump-Diffusion in Epileptic Brain Dynamics: Impact of Daily Rhythms
title_full Testing Jump-Diffusion in Epileptic Brain Dynamics: Impact of Daily Rhythms
title_fullStr Testing Jump-Diffusion in Epileptic Brain Dynamics: Impact of Daily Rhythms
title_full_unstemmed Testing Jump-Diffusion in Epileptic Brain Dynamics: Impact of Daily Rhythms
title_sort testing jump-diffusion in epileptic brain dynamics: impact of daily rhythms
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2021-03-01
description Stochastic approaches to complex dynamical systems have recently provided broader insights into spatial-temporal aspects of epileptic brain dynamics. Stochastic qualifiers based on higher-order Kramers-Moyal coefficients derived directly from time series data indicate improved differentiability between physiological and pathophysiological brain dynamics. It remains unclear, however, to what extent stochastic qualifiers of brain dynamics are affected by other endogenous and/or exogenous influencing factors. Addressing this issue, we investigate multi-day, multi-channel electroencephalographic recordings from a subject with epilepsy. We apply a recently proposed criterion to differentiate between Langevin-type and jump-diffusion processes and observe the type of process most qualified to describe brain dynamics to change with time. Stochastic qualifiers of brain dynamics are strongly affected by endogenous and exogenous rhythms acting on various time scales—ranging from hours to days. Such influences would need to be taken into account when constructing evolution equations for the epileptic brain or other complex dynamical systems subject to external forcings.
topic diffusion process
jump-diffusion process
time series analysis
brain
epilepsy
biological rhythms
url https://www.mdpi.com/1099-4300/23/3/309
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