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Numerical simulation of the electric fields induced by Non-Invasive Brain Stimulation (NIBS), using realistic anatomical head models has gained interest in recent years for understanding the NIBS effects in individual subjects. Although automated tools for generating the head models and performing the electric field simulations have become available, individualized modelling is still not standard practice in NIBS studies. This is likely partly explained by the lack of robustness and usability of the previously available software tools, and partly by the still developing understanding of the link between physiological effects and electric field distributions in the brain. To facilitate individualized modelling in NIBS, we have introduced the SimNIBS (Simulation of NIBS) software package, providing easy-to-use automated tools for electric field modelling. In this article, we give an overview of the modelling pipeline in SimNIBS 2.1, with step-by-step examples of how to run a simulation. Furthermore, we demonstrate a set of scripts for extracting average electric fields for a group of subjects, and finally demonstrate the accuracy of automated placement of standard electrode montages on the head model. SimNIBS 2.1 is freely available at www.simnibs.org.

During the past decade, it became clear that the effects of non-invasivebrain stimulation (NIBS) techniques such as transcranial direct currentstimulation (tDCS) and transcranial magnetic stimulation (TMS) are substantiallyinfluenced by variations in individual head and brain anatomy.In addition to structural variations in the healthy, several psychiatric disordersare characterized by anatomical alterations that are likely to furtherconstrain the intracerebral effects of NIBS. Here, we present highresolutionrealistic head models derived from structural magnetic resonanceimaging data of 19 healthy adults and 19 patients diagnosed withmajor depressive disorder (MDD). By using a freely available softwarepackage for modelling the effects of different NIBS protocols, we showthat our head models are well-suited for assessing inter-individual andbetween-group variability in the magnitude and focality of tDCS-inducedelectric fields for two protocols targeting the left dorsolateral prefrontalcortex.