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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/121235
Ver los metadatos del registro completo
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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 |
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1846083519613239296 |
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13.22299 |