Motor unit number estimation: A technology and literature review

• Published in: Muscle & nerve Vol. 50; no. 6; pp. 884 - 893
• Main Authors: Gooch, Clifton L., Doherty, Timothy J., Chan, K. Ming, Bromberg, Mark B., Lewis, Richard A., Stashuk, Dan W., Berger, Michael J., Andary, Michael T., Daube, Jasper R.
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.12.2014; Wiley Subscription Services, Inc
• Subjects: Action Potentials - physiology; aging; Amyotrophic lateral sclerosis; Biomedical Research - methods; Cell Count - methods; compound muscle action potential; Electric Stimulation; Electrophysiology - methods; Humans; Literature reviews; Motor Neurons - cytology; Motor Neurons - physiology; motor unit; motor unit number estimation; Neural Conduction - physiology; Reproducibility of Results; compound muscle action potential; motor unit; motor unit number estimation; aging; amyotrophic lateral sclerosis
• ISSN: 0148-639X; 1097-4598; 1097-4598
• DOI: 10.1002/mus.24442

ABSTRACT Introduction: Numerous methods for motor unit number estimation (MUNE) have been developed. The objective of this article is to summarize and compare the major methods and the available data regarding their reproducibility, validity, application, refinement, and utility. Methods: Using specified search criteria, a systematic review of the literature was performed. Reproducibility, normative data, application to specific diseases and conditions, technical refinements, and practicality were compiled into a comprehensive database and analyzed. Results: The most commonly reported MUNE methods are the incremental, multiple‐point stimulation, spike‐triggered averaging, and statistical methods. All have established normative data sets and high reproducibility. MUNE provides quantitative assessments of motor neuron loss and has been applied successfully to the study of many clinical conditions, including amyotrophic lateral sclerosis and normal aging. Conclusions: MUNE is an important research technique in human subjects, providing important data regarding motor unit populations and motor unit loss over time. Muscle Nerve 50: 884–893, 2014