Modeling Transcranial Magnetic Stimulation-Driven Stimulus-Response Curves

• Activity Number: 333 - SPEED: Biopharmaceutical Statistics, Medical Devices, and Mental Health
• Type: Contributed
• Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
• Sponsor: Section on Medical Devices and Diagnostics
• Author(s): Caitlin I. Steiner* and Sahana N. Kukke and Nivethida Thirugnanasambandam and Mark Hallett and Daniel M. Keenan
• Companies: Department of Statistics, University of Virginia and Department of Biomedical Engineering, The Catholic University of America and Human Motor Control Section, Medical Neurology Branch, National Institute of Neurological and Human Motor Control Section, Medical Neurology Branch, National Institute of Neurological and Department of Statistics, University of Virginia
• Keywords: Transcranial Magnetic Stimulation (TMS) ; Motor-Evoked Potential (MEP) ; Recruitment curve ; Cortico-Motor Threshold (CMT) value ; Intensity-dependent variability ; Sigmoid function

Abstract

Transcranial Magnetic Stimulation (TMS) is a technology that can quantify the brain-to-muscle interface (corticospinal system) using stimulus-response relationships. The key indicator of excitability of a muscle is the stimulus intensity versus motor-evoked potential (MEP) recruitment curve. Conventional analysis of the recruitment curve assumes a sigmoidal shape with constant additive Gaussian noise. As the MEP responses are very sensitive to intrinsic, visceral, and extrinsic factors, additive noise does not accurately account for the observed intensity dependent variability. To better analyze the relationship and extract key clinically significant parameters, a new mathematical model was developed that allows for intensity dependent variability about the response and calculates the cortico-motor threshold (a fundamental neurological concept) within its parameterization. In a comparison of model fits and parameters, our model performed better than the conventional approach. By accurately capturing the relationship of recruitment curves with this improved estimation technique additional insight into the corticospinal system and subject-specific parameters for TMS could be gained.