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Article

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

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Department of Clinical and Experimental Psychology, University of Huelva, 21007 Huelva, Spain
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Leibniz Research Centre for Working Environment and Human Factors, 44139 Dortmund, Germany
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Department of Neurology, University Medical Hospital Bergmannsheil, 44789 Bochum, Germany
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Department of Psychology, University of Córdoba, 14071 Córdoba, Spain
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Histology Department, School of Medicine, Cadiz University and District Jerez Costa-N., Andalusian Health Service, 11003 Cádiz, Spain
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Psychology Center, Faculty of Administrative Sciences, Autonomous University of Baja California, Ensenada 22890, Mexico
*
Author to whom correspondence should be addressed.
Academic Editor: Sandro Krieg
Biology 2021, 10(12), 1230; https://doi.org/10.3390/biology10121230 (registering DOI)
Received: 8 November 2021 / Accepted: 23 November 2021 / Published: 25 November 2021
(This article belongs to the Section Neuroscience)
The magnitude, distribution, and characteristics of the electric field induced in the brain by application of transcranial electric stimulation depend on the electrode configuration used and the specific parameters of stimulation. An approach to calculate the generated electric field is the computational finite element method. This method enables simulation of the current spread and electric field strength according to the electrode configuration and stimulation parameters used. However, current approaches have several limitations, which constrain the application of tDCS in empirical research and clinical practice. In this study, we provide examples of standard model-based electric field simulations corresponding to motor, dorsolateral prefrontal, and posterior parietal cortex stimulation using twenty typical electrode configurations. Two different current flow-modeling tools were used to compare the results and determine possible differences between both procedures regarding the specificity, as well as the reliability of the estimates. The results were rather consistent between both simulations. Some modest differences of the simulated distribution and intensity of the electric fields between the results of the respective modeling approaches were identified, which might have functional significance and reveal the need to empirically validate these models. The non-availability of quantitative data about the precise electric field distribution beyond the cortical target is a common limitation of both methods, which limits the determination of the spatial specificity of the intervention. These findings help to define future directions of research that allow to exploit the full potential of standard simulation approaches in the field of non-invasive brain stimulation.
Transcranial 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 stimulation. View Full-Text
Keywords: current flow; current intensity; electric field; finite element method; tDCS current flow; current intensity; electric field; finite element method; tDCS
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MDPI and ACS Style

Molero-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. 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. Biology 2021, 10, 1230. https://doi.org/10.3390/biology10121230

AMA Style

Molero-Chamizo A, Nitsche MA, Gutiérrez Lérida C, Salas Sánchez Á, Martín Riquel R, Andújar Barroso RT, Alameda Bailén JR, García Palomeque JC, Rivera-Urbina GN. 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. Biology. 2021; 10(12):1230. https://doi.org/10.3390/biology10121230

Chicago/Turabian Style

Molero-Chamizo, Andrés, Michael A. Nitsche, Carolina Gutiérrez Lérida, Ángeles Salas Sánchez, Raquel Martín Riquel, Rafael T. Andújar Barroso, José R. Alameda Bailén, Jesús C. García Palomeque, and Guadalupe N. Rivera-Urbina 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" Biology 10, no. 12: 1230. https://doi.org/10.3390/biology10121230

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