TY - JOUR
T1 - Changing head model extent affects finite element predictions of transcranial direct current stimulation distributions
AU - Indahlastari, Aprinda
AU - Chauhan, Munish
AU - Schwartz, Benjamin
AU - Sadleir, Rosalind
N1 - Funding Information:
Research reported in this publication was supported by the National Institute Of Neurological Disorders And Stroke of the National Institutes of Health under Award Number R21NS081646 to RJS.
Publisher Copyright:
© 2016 IOP Publishing Ltd.
PY - 2016/10/5
Y1 - 2016/10/5
N2 - Objective. In this study, we determined efficient head model sizes relative to predicted current densities in transcranial direct current stimulation (tDCS). Approach. Efficiency measures were defined based on a finite element (FE) simulations performed using nine human head models derived from a single MRI data set, having extents varying from 60%-100% of the original axial range. Eleven tissue types, including anisotropic white matter, and three electrode montages (T7-T8, F3-right supraorbital, Cz-Oz) were used in the models. Main results. Reducing head volume extent from 100% to 60%, that is, varying the model's axial range from between the apex and C3 vertebra to one encompassing only apex to the superior cerebellum, was found to decrease the total modeling time by up to half. Differences between current density predictions in each model were quantified by using a relative difference measure (RDM). Our simulation results showed that was the least affected (a maximum of 10% error) for head volumes modeled from the apex to the base of the skull (60%-75% volume). Significance. This finding suggested that the bone could act as a bioelectricity boundary and thus performing FE simulations of tDCS on the human head with models extending beyond the inferior skull may not be necessary in most cases to obtain reasonable precision in current density results.
AB - Objective. In this study, we determined efficient head model sizes relative to predicted current densities in transcranial direct current stimulation (tDCS). Approach. Efficiency measures were defined based on a finite element (FE) simulations performed using nine human head models derived from a single MRI data set, having extents varying from 60%-100% of the original axial range. Eleven tissue types, including anisotropic white matter, and three electrode montages (T7-T8, F3-right supraorbital, Cz-Oz) were used in the models. Main results. Reducing head volume extent from 100% to 60%, that is, varying the model's axial range from between the apex and C3 vertebra to one encompassing only apex to the superior cerebellum, was found to decrease the total modeling time by up to half. Differences between current density predictions in each model were quantified by using a relative difference measure (RDM). Our simulation results showed that was the least affected (a maximum of 10% error) for head volumes modeled from the apex to the base of the skull (60%-75% volume). Significance. This finding suggested that the bone could act as a bioelectricity boundary and thus performing FE simulations of tDCS on the human head with models extending beyond the inferior skull may not be necessary in most cases to obtain reasonable precision in current density results.
KW - current density
KW - finite element simulation
KW - segmentation
KW - tDCS
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U2 - 10.1088/1741-2560/13/6/066006
DO - 10.1088/1741-2560/13/6/066006
M3 - Article
C2 - 27705955
AN - SCOPUS:85002251398
SN - 1741-2560
VL - 13
JO - Journal of neural engineering
JF - Journal of neural engineering
IS - 6
M1 - 066006
ER -