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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Online Access: | https://www.mdpi.com/1099-4300/23/3/309 |
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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 |
work_keys_str_mv |
AT juttagkurth testingjumpdiffusioninepilepticbraindynamicsimpactofdailyrhythms AT thorstenrings testingjumpdiffusioninepilepticbraindynamicsimpactofdailyrhythms AT klauslehnertz testingjumpdiffusioninepilepticbraindynamicsimpactofdailyrhythms |
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