Cargando…

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 (...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Junsong, Niebur, Ernst, Hu, Jinyu, Li, Xiaoli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
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
_version_ 1782435797220196352
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
work_keys_str_mv AT wangjunsong suppressingepilepticactivityinaneuralmassmodelusingaclosedloopproportionalintegralcontroller
AT nieburernst suppressingepilepticactivityinaneuralmassmodelusingaclosedloopproportionalintegralcontroller
AT hujinyu suppressingepilepticactivityinaneuralmassmodelusingaclosedloopproportionalintegralcontroller
AT lixiaoli suppressingepilepticactivityinaneuralmassmodelusingaclosedloopproportionalintegralcontroller