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Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller
Closed-loop control is a promising deep brain stimulation (DBS) strategy that could be used to suppress high-amplitude epileptic activity. However, there are currently no analytical approaches to determine the stimulation parameters for effective and safe treatment protocols. Proportional-integral (...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4895166/ https://www.ncbi.nlm.nih.gov/pubmed/27273563 http://dx.doi.org/10.1038/srep27344 |
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author | Wang, Junsong Niebur, Ernst Hu, Jinyu Li, Xiaoli |
author_facet | Wang, Junsong Niebur, Ernst Hu, Jinyu Li, Xiaoli |
author_sort | Wang, Junsong |
collection | PubMed |
description | Closed-loop control is a promising deep brain stimulation (DBS) strategy that could be used to suppress high-amplitude epileptic activity. However, there are currently no analytical approaches to determine the stimulation parameters for effective and safe treatment protocols. Proportional-integral (PI) control is the most extensively used closed-loop control scheme in the field of control engineering because of its simple implementation and perfect performance. In this study, we took Jansen’s neural mass model (NMM) as a test bed to develop a PI-type closed-loop controller for suppressing epileptic activity. A graphical stability analysis method was employed to determine the stabilizing region of the PI controller in the control parameter space, which provided a theoretical guideline for the choice of the PI control parameters. Furthermore, we established the relationship between the parameters of the PI controller and the parameters of the NMM in the form of a stabilizing region, which provided insights into the mechanisms that may suppress epileptic activity in the NMM. The simulation results demonstrated the validity and effectiveness of the proposed closed-loop PI control scheme. |
format | Online Article Text |
id | pubmed-4895166 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48951662016-06-10 Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller Wang, Junsong Niebur, Ernst Hu, Jinyu Li, Xiaoli Sci Rep Article Closed-loop control is a promising deep brain stimulation (DBS) strategy that could be used to suppress high-amplitude epileptic activity. However, there are currently no analytical approaches to determine the stimulation parameters for effective and safe treatment protocols. Proportional-integral (PI) control is the most extensively used closed-loop control scheme in the field of control engineering because of its simple implementation and perfect performance. In this study, we took Jansen’s neural mass model (NMM) as a test bed to develop a PI-type closed-loop controller for suppressing epileptic activity. A graphical stability analysis method was employed to determine the stabilizing region of the PI controller in the control parameter space, which provided a theoretical guideline for the choice of the PI control parameters. Furthermore, we established the relationship between the parameters of the PI controller and the parameters of the NMM in the form of a stabilizing region, which provided insights into the mechanisms that may suppress epileptic activity in the NMM. The simulation results demonstrated the validity and effectiveness of the proposed closed-loop PI control scheme. Nature Publishing Group 2016-06-07 /pmc/articles/PMC4895166/ /pubmed/27273563 http://dx.doi.org/10.1038/srep27344 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Wang, Junsong Niebur, Ernst Hu, Jinyu Li, Xiaoli Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller |
title | Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller |
title_full | Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller |
title_fullStr | Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller |
title_full_unstemmed | Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller |
title_short | Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller |
title_sort | suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4895166/ https://www.ncbi.nlm.nih.gov/pubmed/27273563 http://dx.doi.org/10.1038/srep27344 |
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