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Abstract

The extension of current models in the field of transcranial brain stimulation beyond the estimation of the electric fields is elementary to improve our understanding of the underlying stimulation processes and adds to the accuracy of targeting and mapping procedures. The key question current endeavors try to answer is how the electric field modulates the behavior of neuronal structures in the brain. To answer this question, the integration of highly detailed descriptions of single neurons into existing electromagnetic field models is necessary, resulting in models covering multiple scales. The construction of such models is very complex and requires large amounts of computational effort. This limits their application in current studies, especially mapping and targeting procedures, significantly.

In this talk, we present the derivation of a highly efficient and easy-to-use model for coupling the electric field into neural structures and its application in TMS mapping. For this purpose, we performed extensive simulations with detailed models of numerous realistic L2/3 and L5 pyramidal cells and, from there, derived a fast and efficient mean-field approximation, exhibiting a relative error of only ∼1%.

We applied the model to TMS mapping of the generation of motor evoked potentials in the hand area of M1, and compared it to the classical model, where the electric field serves as proxy for the neuronal excitation. We show that including the coupling model improves the mapping results in that they become more focal and spurious deflections at unphysiological locations disappear.