NeuroMechanics: Electrophysiological and computational methods to accurately estimate the neural drive to muscles in humans in vivo.

Autor: Caillet AH; Department of Bioengineering, Imperial College London, UK., Phillips ATM; Department of Civil and Environmental Engineering, Imperial College London, UK., Modenese L; Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Australia. Electronic address: l.modenese@unsw.edu.au., Farina D; Department of Bioengineering, Imperial College London, UK. Electronic address: d.farina@imperial.ac.uk.
Jazyk: angličtina
Zdroj: Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology [J Electromyogr Kinesiol] 2024 Jun; Vol. 76, pp. 102873. Date of Electronic Publication: 2024 Mar 07.
DOI: 10.1016/j.jelekin.2024.102873
Abstrakt: The ultimate neural signal for muscle control is the neural drive sent from the spinal cord to muscles. This neural signal comprises the ensemble of action potentials discharged by the active spinal motoneurons, which is transmitted to the innervated muscle fibres to generate forces. Accurately estimating the neural drive to muscles in humans in vivo is challenging since it requires the identification of the activity of a sample of motor units (MUs) that is representative of the active MU population. Current electrophysiological recordings usually fail in this task by identifying small MU samples with over-representation of higher-threshold with respect to lower-threshold MUs. Here, we describe recent advances in electrophysiological methods that allow the identification of more representative samples of greater numbers of MUs than previously possible. This is obtained with large and very dense arrays of electromyographic electrodes. Moreover, recently developed computational methods of data augmentation further extend experimental MU samples to infer the activity of the full MU pool. In conclusion, the combination of new electrode technologies and computational modelling allows for an accurate estimate of the neural drive to muscles and opens new perspectives in the study of the neural control of movement and in neural interfacing.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024. Published by Elsevier Ltd.)
Databáze: MEDLINE
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