Robust Nonlinear Control for Synchronising and Regulating Neural Activity

Autores
Martinez, Sebastian; Sanchez Peña, Ricardo Salvador; García Violini, Diego Demián
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Modulating neural activity in a systematic manner holds significant potential for advancing the understanding of brain functions and improving therapeutic strategies. To forecast the dynamics behind several brain activities, numerous neurobiological models have been developed, targeting both individual neurons and entire neural populations. In this context, control systems emerge as powerful tools for effectively linking inputs, such as neural stimuli, to measurable outputs. This study introduces a control framework aimed at regulating neural-mass activity, which has promising applications in pattern tracking, including rhythm generation and phase synchronisation. Given the strong connection of these mechanisms to real brain computations, the presented approach offers biologically relevant insights. To demonstrate this, the Wilson-Cowan model is used, in which stimuli are delivered via light signals to genetically engineered neurons expressing light-sensitive actuators. This proof of concept provides a foundation for future experimental applications in neurobiological systems control. Furthermore, building on previous results, this work integrates opsin dynamics, of the channelrhodopsin and halorhodopsin-type, to accurately model the optogenetic activation channels, enhancing the description of the actuation process.
Fil: Martinez, Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Tecnológico de Buenos Aires; Argentina
Fil: Sanchez Peña, Ricardo Salvador. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: García Violini, Diego Demián. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
WILSON-COWAN
ROBUST CONTROL
CLOSED LOOP
OPTOGENETICS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/262766
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Robust Nonlinear Control for Synchronising and Regulating Neural ActivityMartinez, SebastianSanchez Peña, Ricardo SalvadorGarcía Violini, Diego DemiánWILSON-COWANROBUST CONTROLCLOSED LOOPOPTOGENETICShttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Modulating neural activity in a systematic manner holds significant potential for advancing the understanding of brain functions and improving therapeutic strategies. To forecast the dynamics behind several brain activities, numerous neurobiological models have been developed, targeting both individual neurons and entire neural populations. In this context, control systems emerge as powerful tools for effectively linking inputs, such as neural stimuli, to measurable outputs. This study introduces a control framework aimed at regulating neural-mass activity, which has promising applications in pattern tracking, including rhythm generation and phase synchronisation. Given the strong connection of these mechanisms to real brain computations, the presented approach offers biologically relevant insights. To demonstrate this, the Wilson-Cowan model is used, in which stimuli are delivered via light signals to genetically engineered neurons expressing light-sensitive actuators. This proof of concept provides a foundation for future experimental applications in neurobiological systems control. Furthermore, building on previous results, this work integrates opsin dynamics, of the channelrhodopsin and halorhodopsin-type, to accurately model the optogenetic activation channels, enhancing the description of the actuation process.Fil: Martinez, Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Tecnológico de Buenos Aires; ArgentinaFil: Sanchez Peña, Ricardo Salvador. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: García Violini, Diego Demián. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaUniversal Wiser Publisher2025-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/262766Martinez, Sebastian; Sanchez Peña, Ricardo Salvador; García Violini, Diego Demián; Robust Nonlinear Control for Synchronising and Regulating Neural Activity; Universal Wiser Publisher; Journal of Electronics and Electrical Engineering; 4; 1-2025; 60-792972-3280CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://ojs.wiserpub.com/index.php/JEEE/article/view/5834info:eu-repo/semantics/altIdentifier/doi/10.37256/jeee.4120255834info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:32:58Zoai:ri.conicet.gov.ar:11336/262766instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:32:59.142CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Robust Nonlinear Control for Synchronising and Regulating Neural Activity
title Robust Nonlinear Control for Synchronising and Regulating Neural Activity
spellingShingle Robust Nonlinear Control for Synchronising and Regulating Neural Activity
Martinez, Sebastian
WILSON-COWAN
ROBUST CONTROL
CLOSED LOOP
OPTOGENETICS
title_short Robust Nonlinear Control for Synchronising and Regulating Neural Activity
title_full Robust Nonlinear Control for Synchronising and Regulating Neural Activity
title_fullStr Robust Nonlinear Control for Synchronising and Regulating Neural Activity
title_full_unstemmed Robust Nonlinear Control for Synchronising and Regulating Neural Activity
title_sort Robust Nonlinear Control for Synchronising and Regulating Neural Activity
dc.creator.none.fl_str_mv Martinez, Sebastian
Sanchez Peña, Ricardo Salvador
García Violini, Diego Demián
author Martinez, Sebastian
author_facet Martinez, Sebastian
Sanchez Peña, Ricardo Salvador
García Violini, Diego Demián
author_role author
author2 Sanchez Peña, Ricardo Salvador
García Violini, Diego Demián
author2_role author
author
dc.subject.none.fl_str_mv WILSON-COWAN
ROBUST CONTROL
CLOSED LOOP
OPTOGENETICS
topic WILSON-COWAN
ROBUST CONTROL
CLOSED LOOP
OPTOGENETICS
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Modulating neural activity in a systematic manner holds significant potential for advancing the understanding of brain functions and improving therapeutic strategies. To forecast the dynamics behind several brain activities, numerous neurobiological models have been developed, targeting both individual neurons and entire neural populations. In this context, control systems emerge as powerful tools for effectively linking inputs, such as neural stimuli, to measurable outputs. This study introduces a control framework aimed at regulating neural-mass activity, which has promising applications in pattern tracking, including rhythm generation and phase synchronisation. Given the strong connection of these mechanisms to real brain computations, the presented approach offers biologically relevant insights. To demonstrate this, the Wilson-Cowan model is used, in which stimuli are delivered via light signals to genetically engineered neurons expressing light-sensitive actuators. This proof of concept provides a foundation for future experimental applications in neurobiological systems control. Furthermore, building on previous results, this work integrates opsin dynamics, of the channelrhodopsin and halorhodopsin-type, to accurately model the optogenetic activation channels, enhancing the description of the actuation process.
Fil: Martinez, Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Tecnológico de Buenos Aires; Argentina
Fil: Sanchez Peña, Ricardo Salvador. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: García Violini, Diego Demián. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Modulating neural activity in a systematic manner holds significant potential for advancing the understanding of brain functions and improving therapeutic strategies. To forecast the dynamics behind several brain activities, numerous neurobiological models have been developed, targeting both individual neurons and entire neural populations. In this context, control systems emerge as powerful tools for effectively linking inputs, such as neural stimuli, to measurable outputs. This study introduces a control framework aimed at regulating neural-mass activity, which has promising applications in pattern tracking, including rhythm generation and phase synchronisation. Given the strong connection of these mechanisms to real brain computations, the presented approach offers biologically relevant insights. To demonstrate this, the Wilson-Cowan model is used, in which stimuli are delivered via light signals to genetically engineered neurons expressing light-sensitive actuators. This proof of concept provides a foundation for future experimental applications in neurobiological systems control. Furthermore, building on previous results, this work integrates opsin dynamics, of the channelrhodopsin and halorhodopsin-type, to accurately model the optogenetic activation channels, enhancing the description of the actuation process.
publishDate 2025
dc.date.none.fl_str_mv 2025-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/262766
Martinez, Sebastian; Sanchez Peña, Ricardo Salvador; García Violini, Diego Demián; Robust Nonlinear Control for Synchronising and Regulating Neural Activity; Universal Wiser Publisher; Journal of Electronics and Electrical Engineering; 4; 1-2025; 60-79
2972-3280
CONICET Digital
CONICET
url http://hdl.handle.net/11336/262766
identifier_str_mv Martinez, Sebastian; Sanchez Peña, Ricardo Salvador; García Violini, Diego Demián; Robust Nonlinear Control for Synchronising and Regulating Neural Activity; Universal Wiser Publisher; Journal of Electronics and Electrical Engineering; 4; 1-2025; 60-79
2972-3280
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://ojs.wiserpub.com/index.php/JEEE/article/view/5834
info:eu-repo/semantics/altIdentifier/doi/10.37256/jeee.4120255834
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universal Wiser Publisher
publisher.none.fl_str_mv Universal Wiser Publisher
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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