PT  - JOURNAL ARTICLE
AU  - Stefan M. Goetz
AU  - S. M. Madhi Alavi
AU  - Zhi-De Deng
AU  - Angel V. Peterchev
TI  - Statistical Model of Motor Evoked Potentials for Simulation of Transcranial Magnetic and Electric Stimulation
AID  - 10.1101/406777
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 406777
4099  - http://biorxiv.org/content/early/2018/09/03/406777.short
4100  - http://biorxiv.org/content/early/2018/09/03/406777.full
AB  - Motor evoked potentials (MEPs) are used for biomarkers or dose individualization in transcranial stimulation. We aimed to develop a statistical model that can generate long sequences of individualized MEP amplitude data with the experimentally observed properties. The MEP model includes three sources of trial-to-trial variability to mimic excitability fluctuations, variability in the neural and muscular pathways, and physiological and measurement noise. It also generates virtual human subject data from statistics of population variability. All parameters are extracted as statistical distributions from experimental data from the literature. The model exhibits previously described features, such as stimulus-intensity-dependent MEP amplitude distributions, including bimodal ones. The model can generate long sequences of test data for individual subjects with specified parameters or for subjects from a virtual population. The presented MEP model is the most detailed to date and can be used for the development and implementation of dosing and biomarker estimation algorithms for transcranial stimulation.