Abstract

Introduction The experimental science to inform application of Repetitive Transcranial Magnetic Stimulation (rTMS) is inconsistent. Evidence is strongly based on measurements of motor-evoked potentials (MEPs) which are indirect measures of cortical changes. It is still unclear whether rTMS achieves its effects through plasticity, changes in neural excitability, control of gene expression or another route. Objectives We approached this work as computational physicists. Our aim was to analyze rTMS literature to identify underlying trends. Specifically: 1. Which parameters (e.g. number of pulses, repetition rate) are important? 2. How does the MEP relate to changes in the cortex? 3. What science must be included in a numerical model of the MEP and rTMS? Materials & methods We identified 92 rTMS publications reporting data from 164 experiments. Often, data were poorly recorded and key information was absent. With non-bursting protocols, we identified only 39 publications (76 experiments) which unambiguously gave the rTMS frequency, the number of pulses applied, the pulse intensity and the effect on the MEP. We used principal component analysis to identify which parameters most affected the MEP. We tried to repeat this for bursting protocols; but were prevented by lack of variation in the reported protocols. We used an existing neural field model to study the effect on the MEP of changes in cortical excitability and connection strengths. Results Results are in line with existing dogma: >5 Hz rTMS leads to an increase in MEP; Conclusion Overall, we need better data. Many experiments are poorly reported. Key information is missing or ambiguous. The MEP is an inconvenient and indirect measure of the effect of rTMS. It is often poorly defined and recorded. One needs to 1. record it and report it rigorously and quantitatively, and 2. develop better numerical models of MEPs. Bursting experiments have focused on too few possibilities (e.g. 5 Hz theta-burst stimulation or quadripulse) to unlock underlying science.

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