DEVELOPMENT OF AN ALGORITHM FOR PREDICITING NEOCORTICAL ACTIVATION IN RESPONSE TO TRANSCRANIAL MAGNETIC STIMULATION
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Transcranial magnetic stimulation (TMS) is a powerful technique to noninvasively activate neurons in the brain and is being increasingly used in both clinical and research applications. Despite this growing interest, the relationship between TMS-generated electric fields (E-field) and specific cortical electrophysiological responses is not well understood. Our goal in this study was to investigate the relationship between induced E-fields and cortical activation measured by metabolic responses. For this purpose, we combined human subjectspecific detailed finite element modeling (FEM) of the head to calculate induced cortical E-field profiles and employed concurrent TMS application during positron emission tomography (PET) recordings as a measure of cortical activation. Using the precise coil position relative to each subject, the E-field vectors induced in each subject were calculated throughout the cortex. A functional map of local circuit connections in and between neocortical columns was developed which was used to study the relationship between applied magnetic fields, hence induced E-fields, and activation in the neocortex. We then fitted the theoretical model to experimental data in order to develop a predictive algorithm for TMS induced activation in the neocortex of humans. Previous research in our lab demonstrated that decomposing the E-field into orthogonal vectors based on cortical neuronal orientation differentiates the relative contribution of the E-fields that lead to activation. The sensitivities of activation of pyramidal neurons vs. interneurons to induced E-field vectors either normal (Enorm) or tangential (Etan) to the cortical surface, respectively, were determined. Interneuronal sensitivity to induced Etan was over twice as strong as pyramidal neurons to the induced Enorm vector that may help to explain why cortical electrophysiological responses to TMS at a given power level has specific strong sensitivities to coil orientation. Furthermore, this study produced an algorithm for predicting the electrophysiological responses of neurons in human neocortex with high accuracy (>95%) that could provide an invaluable tool for planning of specific regional cortical activation critical in both research and clinical applications and could help guide new TMS coil designs.