Transcranial magnetic stimulation (TMS) is a valuable tool in brain research as well as in clinical diagnosis and therapy. Its usability and effectiveness in these domains greatly depends on our ability to accurately describe the underlying mechanisms and predict the outcome. In this presentation, I will discuss a complete modeling chain for stimulation of the hand motor areas, resulting in motor evoked potentials (MEP) recorded at the hand muscles.

First, I will describe the estimation of the induced electric field, based on geometric information on the stimulation coil and the head. Second, I will introduce a novel approach to use such field estimation in a statistical framework to map brain function, and demonstrate its effectiveness in localizing the representation of different hand muscles in the cortex. I will also discuss the generalization of that approach to different brain areas and experimental paradigms, as well as its extension to multivariate problems. Third, I will report on our efforts to create precise, yet computationally efficient, models of the coupling between electric fields and neuronal states. In this context, I will especially highlight the directional sensitivity of neural tissue and discuss the problem of the discrepancy between macroscopic and microscopic electric fields. Finally, I will present models of the motor cortex, the spinal cord circuitry, long-range fiber pathways, and the hand muscles, which allow for linking TMS induced neural excitation to measurements from the spinal cord (DI waves) as well as from the hand muscles (motor evoked potentials – MEP).

As a result of this ongoing endeavor, we expect to obtain a complete mechanistic account for a particular TMS induced effect (MEP elicitation), which may serve as a starting point for quantitative descriptions of other non-invasive brain stimulation scenarios.”