Changing head model extent affects finite element predictions of transcranial direct current stimulation distributions

Aprinda Indahlastari, Munish Chauhan, Benjamin Schwartz, Rosalind Sadleir

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


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.

Original languageEnglish (US)
Article number066006
JournalJournal of neural engineering
Issue number6
StatePublished - Oct 5 2016


  • current density
  • finite element simulation
  • segmentation
  • tDCS

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience


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