Unification of optimal targeting methods in transcranial electrical stimulation

Autores
Fernandez Corazza, Mariano; Turovets, Sergei; Muravchik, Carlos Horacio
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
One of the major questions in high-density transcranial electrical stimulation (TES) is: given a region of interest (ROI) and electric current limits for safety, how much current should be delivered by each electrode for optimal targeting of the ROI? Several solutions, apparently unrelated, have been independently proposed depending on how ?optimality? is defined and on how this optimization problem is stated mathematically. The least squares (LS), weighted LS (WLS), or reciprocity-based approaches are the simplest ones and have closed-form solutions. An extended optimization problem can be stated as follows: maximize the directional intensity at the ROI, limit the electric fields at the non-ROI, and constrain total injected current and current per electrode for safety. This problem requires iterative convex or linear optimization solvers. We theoretically prove in this work that the LS, WLS and reciprocity-based closed-form solutions are specific solutions to the extended directional maximization optimization problem. Moreover, the LS/WLS and reciprocity-based solutions are the two extreme cases of the intensity-focality trade-off, emerging under variation of a unique parameter of the extended directional maximization problem, the imposed constraint to the electric fields at the non-ROI. We validate and illustrate these findings with simulations on an atlas head model. The unified approach we present here allows a better understanding of the nature of the TES optimization problem and helps in the development of advanced and more effective targeting strategies.
Fil: Fernandez Corazza, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales. Universidad Nacional de La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales; Argentina
Fil: Turovets, Sergei. University of Oregon; Estados Unidos
Fil: Muravchik, Carlos Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales. Universidad Nacional de La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina
Materia
LEAST SQUARES
OPTIMAL ELECTRICAL STIMULATION
RECIPROCITY THEOREM
TRANSCRANIAL DIRECT CURRENT STIMULATION (TDCS)
TRANSCRANIAL ELECTRICAL STIMULATION (TES)
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:11336/121235

id CONICETDig_3c88f259c581be6439dbdf1e60701cc1
oai_identifier_str oai:ri.conicet.gov.ar:11336/121235
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Unification of optimal targeting methods in transcranial electrical stimulationFernandez Corazza, MarianoTurovets, SergeiMuravchik, Carlos HoracioLEAST SQUARESOPTIMAL ELECTRICAL STIMULATIONRECIPROCITY THEOREMTRANSCRANIAL DIRECT CURRENT STIMULATION (TDCS)TRANSCRANIAL ELECTRICAL STIMULATION (TES)https://purl.org/becyt/ford/2.6https://purl.org/becyt/ford/2One of the major questions in high-density transcranial electrical stimulation (TES) is: given a region of interest (ROI) and electric current limits for safety, how much current should be delivered by each electrode for optimal targeting of the ROI? Several solutions, apparently unrelated, have been independently proposed depending on how ?optimality? is defined and on how this optimization problem is stated mathematically. The least squares (LS), weighted LS (WLS), or reciprocity-based approaches are the simplest ones and have closed-form solutions. An extended optimization problem can be stated as follows: maximize the directional intensity at the ROI, limit the electric fields at the non-ROI, and constrain total injected current and current per electrode for safety. This problem requires iterative convex or linear optimization solvers. We theoretically prove in this work that the LS, WLS and reciprocity-based closed-form solutions are specific solutions to the extended directional maximization optimization problem. Moreover, the LS/WLS and reciprocity-based solutions are the two extreme cases of the intensity-focality trade-off, emerging under variation of a unique parameter of the extended directional maximization problem, the imposed constraint to the electric fields at the non-ROI. We validate and illustrate these findings with simulations on an atlas head model. The unified approach we present here allows a better understanding of the nature of the TES optimization problem and helps in the development of advanced and more effective targeting strategies.Fil: Fernandez Corazza, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales. Universidad Nacional de La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales; ArgentinaFil: Turovets, Sergei. University of Oregon; Estados UnidosFil: Muravchik, Carlos Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales. Universidad Nacional de La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaAcademic Press Inc.2019-12info: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/11336/121235Fernandez Corazza, Mariano; Turovets, Sergei; Muravchik, Carlos Horacio; Unification of optimal targeting methods in transcranial electrical stimulation; Academic Press Inc.; Journal Neuroimag; 209; 116403; 12-2019; 1-661053-8119CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.neuroimage.2019.116403info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1053811919309942info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:40:37Zoai:ri.conicet.gov.ar:11336/121235instacron: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:34982025-10-15 15:40:37.758CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Unification of optimal targeting methods in transcranial electrical stimulation
title Unification of optimal targeting methods in transcranial electrical stimulation
spellingShingle Unification of optimal targeting methods in transcranial electrical stimulation
Fernandez Corazza, Mariano
LEAST SQUARES
OPTIMAL ELECTRICAL STIMULATION
RECIPROCITY THEOREM
TRANSCRANIAL DIRECT CURRENT STIMULATION (TDCS)
TRANSCRANIAL ELECTRICAL STIMULATION (TES)
title_short Unification of optimal targeting methods in transcranial electrical stimulation
title_full Unification of optimal targeting methods in transcranial electrical stimulation
title_fullStr Unification of optimal targeting methods in transcranial electrical stimulation
title_full_unstemmed Unification of optimal targeting methods in transcranial electrical stimulation
title_sort Unification of optimal targeting methods in transcranial electrical stimulation
dc.creator.none.fl_str_mv Fernandez Corazza, Mariano
Turovets, Sergei
Muravchik, Carlos Horacio
author Fernandez Corazza, Mariano
author_facet Fernandez Corazza, Mariano
Turovets, Sergei
Muravchik, Carlos Horacio
author_role author
author2 Turovets, Sergei
Muravchik, Carlos Horacio
author2_role author
author
dc.subject.none.fl_str_mv LEAST SQUARES
OPTIMAL ELECTRICAL STIMULATION
RECIPROCITY THEOREM
TRANSCRANIAL DIRECT CURRENT STIMULATION (TDCS)
TRANSCRANIAL ELECTRICAL STIMULATION (TES)
topic LEAST SQUARES
OPTIMAL ELECTRICAL STIMULATION
RECIPROCITY THEOREM
TRANSCRANIAL DIRECT CURRENT STIMULATION (TDCS)
TRANSCRANIAL ELECTRICAL STIMULATION (TES)
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.6
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv One of the major questions in high-density transcranial electrical stimulation (TES) is: given a region of interest (ROI) and electric current limits for safety, how much current should be delivered by each electrode for optimal targeting of the ROI? Several solutions, apparently unrelated, have been independently proposed depending on how ?optimality? is defined and on how this optimization problem is stated mathematically. The least squares (LS), weighted LS (WLS), or reciprocity-based approaches are the simplest ones and have closed-form solutions. An extended optimization problem can be stated as follows: maximize the directional intensity at the ROI, limit the electric fields at the non-ROI, and constrain total injected current and current per electrode for safety. This problem requires iterative convex or linear optimization solvers. We theoretically prove in this work that the LS, WLS and reciprocity-based closed-form solutions are specific solutions to the extended directional maximization optimization problem. Moreover, the LS/WLS and reciprocity-based solutions are the two extreme cases of the intensity-focality trade-off, emerging under variation of a unique parameter of the extended directional maximization problem, the imposed constraint to the electric fields at the non-ROI. We validate and illustrate these findings with simulations on an atlas head model. The unified approach we present here allows a better understanding of the nature of the TES optimization problem and helps in the development of advanced and more effective targeting strategies.
Fil: Fernandez Corazza, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales. Universidad Nacional de La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales; Argentina
Fil: Turovets, Sergei. University of Oregon; Estados Unidos
Fil: Muravchik, Carlos Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales. Universidad Nacional de La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina
description One of the major questions in high-density transcranial electrical stimulation (TES) is: given a region of interest (ROI) and electric current limits for safety, how much current should be delivered by each electrode for optimal targeting of the ROI? Several solutions, apparently unrelated, have been independently proposed depending on how ?optimality? is defined and on how this optimization problem is stated mathematically. The least squares (LS), weighted LS (WLS), or reciprocity-based approaches are the simplest ones and have closed-form solutions. An extended optimization problem can be stated as follows: maximize the directional intensity at the ROI, limit the electric fields at the non-ROI, and constrain total injected current and current per electrode for safety. This problem requires iterative convex or linear optimization solvers. We theoretically prove in this work that the LS, WLS and reciprocity-based closed-form solutions are specific solutions to the extended directional maximization optimization problem. Moreover, the LS/WLS and reciprocity-based solutions are the two extreme cases of the intensity-focality trade-off, emerging under variation of a unique parameter of the extended directional maximization problem, the imposed constraint to the electric fields at the non-ROI. We validate and illustrate these findings with simulations on an atlas head model. The unified approach we present here allows a better understanding of the nature of the TES optimization problem and helps in the development of advanced and more effective targeting strategies.
publishDate 2019
dc.date.none.fl_str_mv 2019-12
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/11336/121235
Fernandez Corazza, Mariano; Turovets, Sergei; Muravchik, Carlos Horacio; Unification of optimal targeting methods in transcranial electrical stimulation; Academic Press Inc.; Journal Neuroimag; 209; 116403; 12-2019; 1-66
1053-8119
CONICET Digital
CONICET
url http://hdl.handle.net/11336/121235
identifier_str_mv Fernandez Corazza, Mariano; Turovets, Sergei; Muravchik, Carlos Horacio; Unification of optimal targeting methods in transcranial electrical stimulation; Academic Press Inc.; Journal Neuroimag; 209; 116403; 12-2019; 1-66
1053-8119
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.neuroimage.2019.116403
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1053811919309942
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 Academic Press Inc.
publisher.none.fl_str_mv Academic Press Inc.
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
_version_ 1846083519613239296
score 13.22299