Transcranial electrical neuromodulation based on the reciprocity principle

Autores
Fernandez Corazza, Mariano; Turovets, Sergei; Luu, Phan; Anderson, Erik; Tucker, Don
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints.
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. University of Oregon; Estados Unidos
Fil: Turovets, Sergei. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados Unidos
Fil: Luu, Phan. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados Unidos
Fil: Anderson, Erik. Electrical Geodesics Inc.; Estados Unidos
Fil: Tucker, Don. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados Unidos
Materia
HIGH-DENSITY ELECTRODE ARRAYS
NON-INVASIVE NEUROMODULATION
RECIPROCITY PRINCIPLE
TRANSCRANIAL DIRECT CURRENT STIMULATION
TRANSCRANIAL ELECTRICAL STIMULATION
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:11336/54381

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spelling Transcranial electrical neuromodulation based on the reciprocity principleFernandez Corazza, MarianoTurovets, SergeiLuu, PhanAnderson, ErikTucker, DonHIGH-DENSITY ELECTRODE ARRAYSNON-INVASIVE NEUROMODULATIONRECIPROCITY PRINCIPLETRANSCRANIAL DIRECT CURRENT STIMULATIONTRANSCRANIAL ELECTRICAL STIMULATIONhttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints.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. University of Oregon; Estados UnidosFil: Turovets, Sergei. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados UnidosFil: Luu, Phan. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados UnidosFil: Anderson, Erik. Electrical Geodesics Inc.; Estados UnidosFil: Tucker, Don. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados UnidosFrontiers Research Foundation2016-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/54381Fernandez Corazza, Mariano; Turovets, Sergei; Luu, Phan; Anderson, Erik; Tucker, Don; Transcranial electrical neuromodulation based on the reciprocity principle; Frontiers Research Foundation; Frontiers in Psychiatry; 7; 87; 5-2016; 1-191664-0640CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3389/fpsyt.2016.00087info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fpsyt.2016.00087/fullinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:13:15Zoai:ri.conicet.gov.ar:11336/54381instacron: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 10:13:15.438CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Transcranial electrical neuromodulation based on the reciprocity principle
title Transcranial electrical neuromodulation based on the reciprocity principle
spellingShingle Transcranial electrical neuromodulation based on the reciprocity principle
Fernandez Corazza, Mariano
HIGH-DENSITY ELECTRODE ARRAYS
NON-INVASIVE NEUROMODULATION
RECIPROCITY PRINCIPLE
TRANSCRANIAL DIRECT CURRENT STIMULATION
TRANSCRANIAL ELECTRICAL STIMULATION
title_short Transcranial electrical neuromodulation based on the reciprocity principle
title_full Transcranial electrical neuromodulation based on the reciprocity principle
title_fullStr Transcranial electrical neuromodulation based on the reciprocity principle
title_full_unstemmed Transcranial electrical neuromodulation based on the reciprocity principle
title_sort Transcranial electrical neuromodulation based on the reciprocity principle
dc.creator.none.fl_str_mv Fernandez Corazza, Mariano
Turovets, Sergei
Luu, Phan
Anderson, Erik
Tucker, Don
author Fernandez Corazza, Mariano
author_facet Fernandez Corazza, Mariano
Turovets, Sergei
Luu, Phan
Anderson, Erik
Tucker, Don
author_role author
author2 Turovets, Sergei
Luu, Phan
Anderson, Erik
Tucker, Don
author2_role author
author
author
author
dc.subject.none.fl_str_mv HIGH-DENSITY ELECTRODE ARRAYS
NON-INVASIVE NEUROMODULATION
RECIPROCITY PRINCIPLE
TRANSCRANIAL DIRECT CURRENT STIMULATION
TRANSCRANIAL ELECTRICAL STIMULATION
topic HIGH-DENSITY ELECTRODE ARRAYS
NON-INVASIVE NEUROMODULATION
RECIPROCITY PRINCIPLE
TRANSCRANIAL DIRECT CURRENT STIMULATION
TRANSCRANIAL ELECTRICAL STIMULATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints.
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. University of Oregon; Estados Unidos
Fil: Turovets, Sergei. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados Unidos
Fil: Luu, Phan. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados Unidos
Fil: Anderson, Erik. Electrical Geodesics Inc.; Estados Unidos
Fil: Tucker, Don. University of Oregon; Estados Unidos. Electrical Geodesics Inc.; Estados Unidos
description A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints.
publishDate 2016
dc.date.none.fl_str_mv 2016-05
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/11336/54381
Fernandez Corazza, Mariano; Turovets, Sergei; Luu, Phan; Anderson, Erik; Tucker, Don; Transcranial electrical neuromodulation based on the reciprocity principle; Frontiers Research Foundation; Frontiers in Psychiatry; 7; 87; 5-2016; 1-19
1664-0640
CONICET Digital
CONICET
url http://hdl.handle.net/11336/54381
identifier_str_mv Fernandez Corazza, Mariano; Turovets, Sergei; Luu, Phan; Anderson, Erik; Tucker, Don; Transcranial electrical neuromodulation based on the reciprocity principle; Frontiers Research Foundation; Frontiers in Psychiatry; 7; 87; 5-2016; 1-19
1664-0640
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3389/fpsyt.2016.00087
info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fpsyt.2016.00087/full
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
dc.publisher.none.fl_str_mv Frontiers Research Foundation
publisher.none.fl_str_mv Frontiers Research Foundation
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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