title: A simulation-based analysis of motor unit number index (MUNIX) technique using motoneuron pool and surface electromyogram models.
abstract: Motor unit number index (MUNIX) measurement has recently achieved increasing attention as a tool to evaluate the progression of motoneuron diseases. In our current study, the sensitivity of the MUNIX technique to changes in motoneuron and muscle properties was explored by a simulation approach utilizing variations on published motoneuron pool and surface electromyogram (EMG) models. Our simulation results indicate that, when keeping motoneuron pool and muscle parameters unchanged and varying the input motor unit numbers to the model, then MUNIX estimates can appropriately characterize changes in motor unit numbers. Such MUNIX estimates are not sensitive to different motor unit recruitment and rate coding strategies used in the model. Furthermore, alterations in motor unit control properties do not have a significant effect on the MUNIX estimates. Neither adjustment of the motor unit recruitment range nor reduction of the motor unit firing rates jeopardizes the MUNIX estimates. The MUNIX estimates closely correlate with the maximum M-wave amplitude. However, if we reduce the amplitude of each motor unit action potential rather than simply reduce motor unit number, then MUNIX estimates substantially underestimate the motor unit numbers in the muscle. These findings suggest that the current MUNIX definition is most suitable for motoneuron diseases that demonstrate secondary evidence of muscle fiber reinnervation. In this regard, when MUNIX is applied, it is of much importance to examine a parallel measurement of motor unit size index (MUSIX), defined as the ratio of the maximum M-wave amplitude to the MUNIX. However, there are potential limitations in the application of the MUNIX methods in atrophied muscle, where it is unclear whether the atrophy is accompanied by loss of motor units or loss of muscle fiber size.
authors.affiliation: Sensory Motor Performance Program (SMPP), Rehabilitation Institute of Chicago, Chicago, IL 60611, USA.
authors.forename: Xiaoyan
authors.initials: X
authors.lastname: Li
authors.forename: William Zev
authors.initials: WZ
authors.lastname: Rymer
authors.forename: Ping
authors.initials: P
authors.lastname: Zhou
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000465:Algorithms; D002452:Cell Count; D003198:Computer Simulation; D004576:Electromyography / Q000379:methods*; D055724:Electrophysiological Phenomena; D006801:Humans; D009046:Motor Neurons / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology; D018485:Muscle Fibers, Skeletal / Q000502:physiology* / Q000648:ultrastructure; D018482:Muscle, Skeletal / Q000294:innervation / Q000502:physiology; D009133:Muscular Atrophy / Q000503:physiopathology; D011999:Recruitment, Neurophysiological / Q000502:physiology