Standard Non-Personalized Electric Field Modeling of Twenty Typical tDCS Electrode Configurations via the Computational Finite Element Method: Contributions and Limitations of Two Different Approaches

dc.contributor.authorMolero Chamizo, Andrés
dc.contributor.authorNitsche, Michael A.
dc.contributor.authorGutiérrez Lérida, Carolina
dc.contributor.authorSalas Sánchez, Ángeles
dc.contributor.authorMartín Riquel, Raquel
dc.contributor.authorAndújar Barroso, Rafael Tomás
dc.contributor.authorAlameda Bailén, José Ramón
dc.contributor.authorGarcía Palomeque, Jesús Carlos
dc.contributor.authorNathzidy Rivera-Urbina, Guadalupe
dc.date.accessioned2021-12-02T12:36:34Z
dc.date.available2021-12-02T12:36:34Z
dc.date.issued2021
dc.description.abstractTranscranial direct current stimulation (tDCS) is a non-invasive brain stimulation procedure to modulate cortical excitability and related brain functions. tDCS can effectively alter multiple brain functions in healthy humans and is suggested as a therapeutic tool in several neurological and psychiatric diseases. However, variability of results is an important limitation of this method. This variability may be due to multiple factors, including age, head and brain anatomy (including skull, skin, CSF and meninges), cognitive reserve and baseline performance level, specific task demands, as well as comorbidities in clinical settings. Different electrode montages are a further source of variability between tDCS studies. A procedure to estimate the electric field generated by specific tDCS electrode configurations, which can be helpful to adapt stimulation protocols, is the computational finite element method. This approach is useful to provide a priori modeling of the current spread and electric field intensity that will be generated according to the implemented electrode montage. Here, we present standard, non-personalized model-based electric field simulations for motor, dorsolateral prefrontal, and posterior parietal cortex stimulation according to twenty typical tDCS electrode configurations using two different current flow modeling software packages. The resulting simulated maximum intensity of the electric field, focality, and current spread were similar, but not identical, between models. The advantages and limitations of both mathematical simulations of the electric field are presented and discussed systematically, including aspects that, at present, prevent more widespread application of respective simulation approaches in the field of non-invasive brain stimulationes_ES
dc.description.departmentPsicología Clínica y Experimental
dc.identifier.citationMolero-Chamizo, A., Nitsche, M. A., Gutiérrez Lérida, C., Salas Sánchez, Á., Martín Riquel, R., Andújar Barroso, R. T., Alameda Bailén, J. R., García Palomeque, J. C., & Rivera-Urbina, G. N. (2021). Standard Non-Personalized Electric Field Modeling of Twenty Typical tDCS Electrode Configurations via the Computational Finite Element Method: Contributions and Limitations of Two Different Approaches. In Biology (Vol. 10, Issue 12, p. 1230). MDPI AG. https://doi.org/10.3390/biology10121230es_ES
dc.identifier.doi10.3390/biology10121230
dc.identifier.issn2079-7737 (electrónico)
dc.identifier.urihttp://hdl.handle.net/10272/20295
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.otherCurrent flowes_ES
dc.subject.otherCurrent intensityes_ES
dc.subject.otherElectric fieldes_ES
dc.subject.otherFinite element methodes_ES
dc.subject.othertDCSes_ES
dc.subject.unesco61 Psicologíaes_ES
dc.titleStandard Non-Personalized Electric Field Modeling of Twenty Typical tDCS Electrode Configurations via the Computational Finite Element Method: Contributions and Limitations of Two Different Approacheses_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublicationf1d55184-6162-411d-a94d-79916a127841
relation.isAuthorOfPublication7d09999e-fb87-46c8-b1a8-dd2f12aec0e6
relation.isAuthorOfPublication97b74b0c-df14-4a1b-968a-9b550a1373f9
relation.isAuthorOfPublication.latestForDiscoveryf1d55184-6162-411d-a94d-79916a127841

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