A Del Vecchio1,2, F Negro3, F Felici1, D Farina2. 1. Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Rome, Italy. 2. Department of Bioengineering, Imperial College London, London, UK. 3. Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
Abstract
AIM: Motor units are recruited in an orderly manner according to the size of motor neurones. Moreover, because larger motor neurones innervate fibres with larger diameters than smaller motor neurones, motor units should be recruited orderly according to their conduction velocity (MUCV). Because of technical limitations, these relations have been previously tested either indirectly or in small motor unit samples that revealed weak associations between motor unit recruitment threshold (RT) and MUCV. Here, we analyse the relation between MUCV and RT for large samples of motor units. METHODS: Ten healthy volunteers completed a series of isometric ankle dorsiflexions at forces up to 70% of the maximum. Multi-channel surface electromyographic signals recorded from the tibialis anterior muscle were decomposed into single motor unit action potentials, from which the corresponding motor unit RT, MUCV and action potential amplitude were estimated. Established relations between muscle fibre diameter and CV were used to estimate the fibre size. RESULTS: Within individual subjects, the distributions of MUCV and fibre diameters were unimodal and did not show distinct populations. MUCV was strongly correlated with RT (mean (SD) R2 = 0.7 (0.09), P < 0.001; 406 motor units), which supported the hypothesis that fibre diameter is associated with RT. CONCLUSION: The results provide further evidence for the relations between motor neurone and muscle fibre properties for large samples of motor units. The proposed methodology for motor unit analysis has also the potential to open new perspectives in the study of chronic and acute neuromuscular adaptations to ageing, training and pathology.
AIM: Motor units are recruited in an orderly manner according to the size of motor neurones. Moreover, because larger motor neurones innervate fibres with larger diameters than smaller motor neurones, motor units should be recruited orderly according to their conduction velocity (MUCV). Because of technical limitations, these relations have been previously tested either indirectly or in small motor unit samples that revealed weak associations between motor unit recruitment threshold (RT) and MUCV. Here, we analyse the relation between MUCV and RT for large samples of motor units. METHODS: Ten healthy volunteers completed a series of isometric ankle dorsiflexions at forces up to 70% of the maximum. Multi-channel surface electromyographic signals recorded from the tibialis anterior muscle were decomposed into single motor unit action potentials, from which the corresponding motor unit RT, MUCV and action potential amplitude were estimated. Established relations between muscle fibre diameter and CV were used to estimate the fibre size. RESULTS: Within individual subjects, the distributions of MUCV and fibre diameters were unimodal and did not show distinct populations. MUCV was strongly correlated with RT (mean (SD) R2 = 0.7 (0.09), P < 0.001; 406 motor units), which supported the hypothesis that fibre diameter is associated with RT. CONCLUSION: The results provide further evidence for the relations between motor neurone and muscle fibre properties for large samples of motor units. The proposed methodology for motor unit analysis has also the potential to open new perspectives in the study of chronic and acute neuromuscular adaptations to ageing, training and pathology.
Authors: Jonathan D Miller; C J Lund; Marissa D Gingrich; Kyle L Schtul; Mandy E Wray; Trent J Herda Journal: Exp Brain Res Date: 2019-08-08 Impact factor: 1.972
Authors: Hannah L Dimmick; Jonathan D Miller; Adam J Sterczala; Michael A Trevino; Trent J Herda Journal: Eur J Appl Physiol Date: 2018-06-11 Impact factor: 3.078
Authors: Alessandro Del Vecchio; Francesco Negro; Ales Holobar; Andrea Casolo; Jonathan P Folland; Francesco Felici; Dario Farina Journal: J Physiol Date: 2019-03-01 Impact factor: 5.182
Authors: Babak Afsharipour; Nagib Manzur; Jennifer Duchcherer; Keith F Fenrich; Christopher K Thompson; Francesco Negro; Katharina A Quinlan; David J Bennett; Monica A Gorassini Journal: J Neurophysiol Date: 2020-05-27 Impact factor: 2.714
Authors: Altamash S Hassan; Melissa E Fajardo; Mark Cummings; Laura Miller McPherson; Francesco Negro; Julius P A Dewald; C J Heckman; Gregory E P Pearcey Journal: J Physiol Date: 2021-09-30 Impact factor: 5.182
Authors: Altamash S Hassan; Edward H Kim; Obaid U Khurram; Mark Cummings; Christopher K Thompson; Laura Miller McPherson; C J Heckman; Julius P A Dewald; Francesco Negro Journal: Conf Proc IEEE Eng Med Biol Soc Date: 2019-07
Authors: Victoria L Volk; Landon D Hamilton; Donald R Hume; Kevin B Shelburne; Clare K Fitzpatrick Journal: Sci Rep Date: 2021-11-26 Impact factor: 4.379