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Fractional-Order Traveling Wave Approximations for a Fractional-Order Neural Field Model

In this work, we establish a fractional-order neural field mathematical model with Caputo's fractional derivative temporal order α considering 0 < α < 2, to analyze the effect of fractional-order on cortical wave features observed preceding seizure termination. The importance of this inco...

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Autor principal: González-Ramírez, Laura R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987931/
https://www.ncbi.nlm.nih.gov/pubmed/35399918
http://dx.doi.org/10.3389/fncom.2022.788924
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author González-Ramírez, Laura R.
author_facet González-Ramírez, Laura R.
author_sort González-Ramírez, Laura R.
collection PubMed
description In this work, we establish a fractional-order neural field mathematical model with Caputo's fractional derivative temporal order α considering 0 < α < 2, to analyze the effect of fractional-order on cortical wave features observed preceding seizure termination. The importance of this incorporation relies on the theoretical framework established by fractional-order derivatives in which memory and hereditary properties of a system are considered. Employing Mittag-Leffler functions, we first obtain approximate fractional-order solutions that provide information about the initial wave dynamics in a fractional-order frame. We then consider the Adomian decomposition method to approximate pulse solutions in a wider range of orders and longer times. The former approach establishes a direct way to investigate the initial relationships between fractional-order and wave features, such as wave speed and wave width. In contrast, the latter approach displays wave propagation dynamics in different fractional orders for longer times. Using the previous two approaches, we establish approximate wave solutions with characteristics consistent with in vivo cortical waves preceding seizure termination. In our analysis, we find consistent differences in the initial effect of the fractional-order on the features of wave speed and wave width, depending on whether α <1 or α>1. Both cases can model the shape of cortical wave propagation for different fractional-orders at the cost of modifying the wave speed. Our results also show that the effect of fractional-order on wave width depends on the synaptic threshold and the synaptic connectivity extent. Fractional-order derivatives have been interpreted as the memory trace of the system. This property and the results of our analysis suggest that fractional-order derivatives and neuronal collective memory modify cortical wave features.
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spelling pubmed-89879312022-04-08 Fractional-Order Traveling Wave Approximations for a Fractional-Order Neural Field Model González-Ramírez, Laura R. Front Comput Neurosci Neuroscience In this work, we establish a fractional-order neural field mathematical model with Caputo's fractional derivative temporal order α considering 0 < α < 2, to analyze the effect of fractional-order on cortical wave features observed preceding seizure termination. The importance of this incorporation relies on the theoretical framework established by fractional-order derivatives in which memory and hereditary properties of a system are considered. Employing Mittag-Leffler functions, we first obtain approximate fractional-order solutions that provide information about the initial wave dynamics in a fractional-order frame. We then consider the Adomian decomposition method to approximate pulse solutions in a wider range of orders and longer times. The former approach establishes a direct way to investigate the initial relationships between fractional-order and wave features, such as wave speed and wave width. In contrast, the latter approach displays wave propagation dynamics in different fractional orders for longer times. Using the previous two approaches, we establish approximate wave solutions with characteristics consistent with in vivo cortical waves preceding seizure termination. In our analysis, we find consistent differences in the initial effect of the fractional-order on the features of wave speed and wave width, depending on whether α <1 or α>1. Both cases can model the shape of cortical wave propagation for different fractional-orders at the cost of modifying the wave speed. Our results also show that the effect of fractional-order on wave width depends on the synaptic threshold and the synaptic connectivity extent. Fractional-order derivatives have been interpreted as the memory trace of the system. This property and the results of our analysis suggest that fractional-order derivatives and neuronal collective memory modify cortical wave features. Frontiers Media S.A. 2022-03-24 /pmc/articles/PMC8987931/ /pubmed/35399918 http://dx.doi.org/10.3389/fncom.2022.788924 Text en Copyright © 2022 González-Ramírez. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
González-Ramírez, Laura R.
Fractional-Order Traveling Wave Approximations for a Fractional-Order Neural Field Model
title Fractional-Order Traveling Wave Approximations for a Fractional-Order Neural Field Model
title_full Fractional-Order Traveling Wave Approximations for a Fractional-Order Neural Field Model
title_fullStr Fractional-Order Traveling Wave Approximations for a Fractional-Order Neural Field Model
title_full_unstemmed Fractional-Order Traveling Wave Approximations for a Fractional-Order Neural Field Model
title_short Fractional-Order Traveling Wave Approximations for a Fractional-Order Neural Field Model
title_sort fractional-order traveling wave approximations for a fractional-order neural field model
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987931/
https://www.ncbi.nlm.nih.gov/pubmed/35399918
http://dx.doi.org/10.3389/fncom.2022.788924
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