Variability in the response of individuals to various non-invasive brain stimulation protocols is a major problem that limits their potential for clinical applications. Baseline motor-evoked potential (MEP) amplitude is the key predictor of an individual's response to transcranial magnetic stimulation protocols. However, the factors that predict MEP amplitude and its variability remain unclear. In this study, we aimed to identify the input-output curve (IOC) parameters that best predict MEP amplitude and its variability. We analysed IOC data from 75 subjects and built a general linear model (GLM) using the IOC parameters as regressors and MEP amplitude at 120% resting motor threshold (RMT) as the response variable. We bootstrapped the data to estimate variability of IOC parameters and included them in a GLM to identify the significant predictors of MEP amplitude variability. Peak slope, motor threshold, and maximum MEP amplitude of the IOC were significant predictors of MEP amplitude at 120% RMT and its variability was primarily driven by the variability of peak slope and maximum MEP amplitude. Recruitment gain and maximum corticospinal excitability are the key predictors of MEP amplitude and its variability. Inter-individual variability in motor output may be reduced by achieving a uniform IOC slope.

Inter-Individual Variability in Motor Output Is Driven by Recruitment Gain in the Corticospinal Tract Rather Than Motor Threshold

Leodori, Giorgio;
2022

Abstract

Variability in the response of individuals to various non-invasive brain stimulation protocols is a major problem that limits their potential for clinical applications. Baseline motor-evoked potential (MEP) amplitude is the key predictor of an individual's response to transcranial magnetic stimulation protocols. However, the factors that predict MEP amplitude and its variability remain unclear. In this study, we aimed to identify the input-output curve (IOC) parameters that best predict MEP amplitude and its variability. We analysed IOC data from 75 subjects and built a general linear model (GLM) using the IOC parameters as regressors and MEP amplitude at 120% resting motor threshold (RMT) as the response variable. We bootstrapped the data to estimate variability of IOC parameters and included them in a GLM to identify the significant predictors of MEP amplitude variability. Peak slope, motor threshold, and maximum MEP amplitude of the IOC were significant predictors of MEP amplitude at 120% RMT and its variability was primarily driven by the variability of peak slope and maximum MEP amplitude. Recruitment gain and maximum corticospinal excitability are the key predictors of MEP amplitude and its variability. Inter-individual variability in motor output may be reduced by achieving a uniform IOC slope.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1660551
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