Literature DB >> 3703248

Coordination of arm muscles during flexion and supination: application of the tensor analysis approach.

C C Gielen, E J van Zuylen.   

Abstract

In order to obtain a good understanding of the coordination of the motor system several problems have to be solved. Two major issues are: (1) that muscles do not form an orthogonal coordinate system, and (2) that the number of muscles that may contribute to a movement in general exceeds the number of degrees of freedom of the movement. The latter allows the movement to be executed by an infinite variety of muscle activations. A theoretical solution to these problems has been elaborated by Pellionisz and Llinás. However, convincing experimental support for this theory is still lacking. In this paper the theory has been applied to the activation of arm muscles which contribute to flexion/extension and supination/pronation of the arm. Motor unit activity was recorded with fine wire electrodes. As reported in previous papers, the recruitment threshold of motor units in arm muscles during isometric contraction depends on a combination of forces in flexion and supination directions. This dependence is characteristic for motor units in a single muscle, but is very different for motor units in different muscles. The theoretical results are in good agreement with the behavior of the recruitment threshold for flexion, which decreases (such as m. biceps brachii), or increases (such as for m. brachialis and m. brachioradialis) with force in supination direction. The theory also correctly predicts how the recruitment threshold for motor units changes as a function of the angle between forearm and upper arm. These results give firm support to the hypothesis that the central nervous system uses a tensorial approach for the activation of the motor system, as originally proposed by Pellionisz and Llinás.

Mesh:

Year:  1986        PMID: 3703248     DOI: 10.1016/0306-4522(86)90028-x

Source DB:  PubMed          Journal:  Neuroscience        ISSN: 0306-4522            Impact factor:   3.590


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9.  The Role of Motor Learning on Measures of Physical Requirements and Motor Variability During Repetitive Screwing.

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