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Locally optimal extracellular stimulation for chaotic desynchronization of neural populations
We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this m...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159599/ https://www.ncbi.nlm.nih.gov/pubmed/24899243 http://dx.doi.org/10.1007/s10827-014-0499-3 |
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author | Wilson, Dan Moehlis, Jeff |
author_facet | Wilson, Dan Moehlis, Jeff |
author_sort | Wilson, Dan |
collection | PubMed |
description | We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this methodology in the presence of interneuron coupling to make predictions about the strength of stimulation required to overcome synchronizing effects of coupling. This methodology suggests a powerful alternative to pulsatile stimuli for deep brain stimulation as it uses less energy than pulsatile stimuli, and could eliminate the time consuming tuning process. |
format | Online Article Text |
id | pubmed-4159599 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-41595992014-09-11 Locally optimal extracellular stimulation for chaotic desynchronization of neural populations Wilson, Dan Moehlis, Jeff J Comput Neurosci Article We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this methodology in the presence of interneuron coupling to make predictions about the strength of stimulation required to overcome synchronizing effects of coupling. This methodology suggests a powerful alternative to pulsatile stimuli for deep brain stimulation as it uses less energy than pulsatile stimuli, and could eliminate the time consuming tuning process. Springer US 2014-06-05 2014 /pmc/articles/PMC4159599/ /pubmed/24899243 http://dx.doi.org/10.1007/s10827-014-0499-3 Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Article Wilson, Dan Moehlis, Jeff Locally optimal extracellular stimulation for chaotic desynchronization of neural populations |
title | Locally optimal extracellular stimulation for chaotic desynchronization of neural populations |
title_full | Locally optimal extracellular stimulation for chaotic desynchronization of neural populations |
title_fullStr | Locally optimal extracellular stimulation for chaotic desynchronization of neural populations |
title_full_unstemmed | Locally optimal extracellular stimulation for chaotic desynchronization of neural populations |
title_short | Locally optimal extracellular stimulation for chaotic desynchronization of neural populations |
title_sort | locally optimal extracellular stimulation for chaotic desynchronization of neural populations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159599/ https://www.ncbi.nlm.nih.gov/pubmed/24899243 http://dx.doi.org/10.1007/s10827-014-0499-3 |
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