Combining EEG and MRI data to personalize neurostimulation for focal epilepsy: an open-source software implementation

Personalizing the stimulation location of transcranial neurostimulation based on the subject's individual anatomy is becoming more important in clinical research. In the case of focal epilepsy, there often is a clear target to stimulate that can be found by analysis of multi-modal clinical data, including EEG source localization. Hypothesizing its clinical importance, we developed a procedure to exploit the spatial target information and optimize the tDCS montage such that the induced electric field has maximum overlap with the target. This could be beneficial to tailor the treatment on a per-patient basis, so every patient will be stimulated with the intended field at the intended location. While commercial workflows for personalized tDCS exist, a flexible, easy-to-use and open-source software that integrates EEG source localization and tDCS optimization techniques in one application was not yet available. To support open research, we therefore combined open-source solutions into an intuitive MATLAB software tool for (clinical) research purposes. This tool interfaces intuitively with other open-source tools: the Brain-storm package (EEG processing and source localization) and SimNibs (neurostimulation optimization). The most relevant parameters such as tissue conductivity and optimization constraints can be changed via the user interface. Based on MRI data, a head segmentation can be made and converted into a FEM model for both software's. Clinical targets can be defined in subjects pace or calculated via source localization. A tDCS montage can be optimized for this target using either patch electrodes or high-definition electrodes. The field maps for the optimized montage and the field distribution histograms are presented in the user interface. Based on these analyses, the tool produces a report in which the flow from input to output can be analyzed. In this way, clinical researchers worldwide are offered a research tool for streamlining the research into dose-effect relations, as well as personalization possibilities.