Brainkit: A Platform for Small-Scale Rational Design of tDCS Montages

Abstract

A major obstacle to using tDCS for therapy and cognitive enhancement is the problem of selecting parameters like electrode position which are likely to achieve particular goals for an individual person. tDCS parameters which create significant effects at a group level are often unreliable at an individual level, and in many cases there is little a priori evidence for which regions should be targeted to achieve an effect (especially in the case of complex cognitive functions). A potential way to address these issues is combining tDCS with individual-level neurophysiological data. BrainKit is an open-source tDCS stimulator integrated with tools for automatically predicting effective tDCS parameters based on brain dynamics measurement. Covariance of physiological and behavioral variables is exploited to identify brain variables which predict behavioral variables of interest, and a tDCS model is applied to generate predicted parameters for driving these variables in a desired direction. BrainKit uses a novel current regulator, which allows scalp capacitance measurement (recently developed as a low-resolution neuroimaging technique) to be integrated and used as a source of neurophysiological data. Preliminary data suggest that capacitive measurements reflect natural and tDCS-induced brain activity changes, and are valuable for generating tDCS “targets”. BrainKit therefore offers a simple, integrated platform for rational design and optimization of tDCS montages and delivery of stimulation which may improve the effectiveness and applicability of tDCS in clinical and cognitive-enhancement settings.