A probabilistic transcranial magnetic stimulation localization method

Abstract Objective. Transcranial magnetic stimulation (TMS) can be used to safely and noninvasively activate brain tissue. However, the characteristic parameters of neuronal activation have been largely unclear. In this work, we propose a novel model develop method infer its from measured motor evoked potential signals. Approach. The connection between due an induced electric field threshold is modeled. posterior distribution are inferred measurement data using Bayes’ formula. measurements active thresholds obtained with multiple stimulating coil locations, location, preferred direction activation, value site. sampled Markov chain Monte Carlo method. We quantify plausibility by calculating marginal likelihood thresholds. validated synthetic applied first dorsal interosseus muscle in five healthy participants. Main results. produces probability for which minimal volume where occurs 95% derived. For eight or nine smallest such was approximately 100 mm 3 . intersected pre-central gyral crown anterior wall central sulcus, perpendicular both findings being consistent literature. Furthermore, it not possible rule out if occurred either white grey matter. one participant, two distinct activations sites were found while others exhibited unique Significance. generic robust, lays foundation framework that enables accurate analysis characterization TMS mechanisms.