The scaling of motor noise with muscle strength and motor unit number in humans View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2004-08

AUTHORS

Antonia F. de C. Hamilton, Kelvin E. Jones, Daniel M. Wolpert

ABSTRACT

Understanding the origin of noise, or variability, in the motor system is an important step towards understanding how accurate movements are performed. Variability of joint torque during voluntary activation is affected by many factors such as the precision of the descending motor commands, the number of muscles that cross the joint, their size and the number of motor units in each. To investigate the relationship between the peripheral factors and motor noise, the maximum voluntary torque produced at a joint and the coefficient of variation of joint torque were recorded from six adult human subjects for four muscle/joint groups in the arm. It was found that the coefficient of variation of torque decreases systematically as the maximum voluntary torque increases. This decreasing coefficient of variation means that a given torque or force can be more accurately generated by a stronger muscle than a weaker muscle. Simulations demonstrated that muscles with different strengths and different numbers of motor units could account for the experimental data. In the simulations, the magnitude of the coefficient of variation of muscle force depended primarily on the number of motor units innervating the muscle, which relates positively to muscle strength. This result can be generalised to the situation where more than one muscle is available to perform a task, and a muscle activation pattern must be selected. The optimal muscle activation pattern required to generate a target torque using a group of muscles, while minimizing the consequences of signal dependent noise, is derived. More... »

PAGES

417-430

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00221-004-1856-7

    DOI

    http://dx.doi.org/10.1007/s00221-004-1856-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1023586403

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/15014922


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