title: Statistical model applied to motor evoked potentials analysis.
abstract: Motor evoked potentials (MEPs) convey information regarding the functional integrity of the descending motor pathways. Absence of the MEP has been used as a neurophysiological marker to suggest cortico-spinal abnormalities in the operating room. Due to their high variability and sensitivity, detailed quantitative studies of MEPs are lacking. This paper applies a statistical method to characterize MEPs by estimating the number of motor units and single motor unit potential amplitudes. A clearly increasing trend of single motor unit potential amplitudes in the MEPs after each pulse of the stimulation pulse train is revealed by this method. This statistical method eliminates the effects of anesthesia, and provides an objective assessment of MEPs. Consequently this statistical method has high potential to be useful in future quantitative MEPs analysis.
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA. yma10@jhu.edu
authors.forename: Ying
authors.initials: Y
authors.lastname: Ma
authors.forename: Nitish V
authors.initials: NV
authors.lastname: Thakor
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Jia
mesh_terms: D000818:Animals; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology*; D008959:Models, Neurological; D015233:Models, Statistical; D009044:Motor Cortex / Q000502:physiology*; D009046:Motor Neurons / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D051381:Rats; D017208:Rats, Wistar