Literature DB >> 8120594

Models of recruitment and rate coding organization in motor-unit pools.

A J Fuglevand1, D A Winter, A E Patla.   

Abstract

1. Isometric muscle force and the surface electromyogram (EMG) were simulated from a model that predicted recruitment and firing times in a pool of 120 motor units under different levels of excitatory drive. The EMG-force relationships that emerged from simulations using various schedules of recruitment and rate coding were compared with those observed experimentally to determine which of the modeled schemes were plausible representations of the actual organization in motor-unit pools. 2. The model was comprised of three elements: a motoneuron model, a motor-unit force model, and a model of the surface EMG. Input to the neuron model was an excitatory drive function representing the net synaptic input to motoneurons during voluntary muscle contractions. Recruitment thresholds were assigned such that many motoneurons had low thresholds and relatively few neurons had high thresholds. Motoneuron firing rate increased as a linear function of excitatory drive between recruitment threshold and peak firing rate levels. The sequence of discharge times for each motoneuron was simulated as a random renewal process. 3. Motor-unit twitch force was estimated as an impulse response of a critically damped, second-order system. Twitch amplitudes were assigned according to rank in the recruitment order, and twitch contraction times were inversely related to twitch amplitude. Nonlinear force-firing rate behavior was simulated by varying motor-unit force gain as a function of the instantaneous firing rate and the contraction time of the unit. The total force exerted by the muscle was computed as the sum of the motor-unit forces. 4. Motor-unit action potentials were simulated on the basis of estimates of the number and location of motor-unit muscle fibers and the propagation velocity of the fiber action potentials. The number of fibers innervated by each unit was assumed to be directly proportional to the twitch force. The area of muscle encompassing unit fibers was proportional to the number of fibers innervated, and the location of motor-unit territories were randomly assigned within the muscle cross section. Action-potential propagation velocities were estimated from an inverse function of contraction time. The train of discharge times predicted from the motoneuron model determined the occurrence of each motor-unit action potential. The surface EMG was synthesized as the sum of all motor-unit action-potential trains. 5. Two recruitment conditions were tested: narrow (limit of recruitment < 50% maximum excitation) and broad recruitment range conditions (limit of recruitment > 70% maximum excitation).(ABSTRACT TRUNCATED AT 400 WORDS)

Mesh:

Year:  1993        PMID: 8120594     DOI: 10.1152/jn.1993.70.6.2470

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  174 in total

1.  Motor unit identification in two neighboring recording positions of the human trapezius muscle during prolonged computer work.

Authors:  Daniel Zennaro; Thomas Läubli; Helmut Krueger
Journal:  Eur J Appl Physiol       Date:  2003-04-24       Impact factor: 3.078

Review 2.  Surface electromyogram signal modelling.

Authors:  K C McGill
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

3.  Motor unit recruitment strategies and muscle properties determine the influence of synaptic noise on force steadiness.

Authors:  Jakob L Dideriksen; Francesco Negro; Roger M Enoka; Dario Farina
Journal:  J Neurophysiol       Date:  2012-03-14       Impact factor: 2.714

4.  Discharge properties of motor units during steady isometric contractions performed with the dorsiflexor muscles.

Authors:  Mark Jesunathadas; Malgorzata Klass; Jacques Duchateau; Roger M Enoka
Journal:  J Appl Physiol (1985)       Date:  2012-03-22

Review 5.  Mechanical properties and neural control of human hand motor units.

Authors:  Andrew J Fuglevand
Journal:  J Physiol       Date:  2011-10-17       Impact factor: 5.182

6.  Hierarchical control of motor units in voluntary contractions.

Authors:  Carlo J De Luca; Paola Contessa
Journal:  J Neurophysiol       Date:  2011-10-05       Impact factor: 2.714

7.  Extraction of individual muscle mechanical action from endpoint force.

Authors:  Jason J Kutch; Arthur D Kuo; William Z Rymer
Journal:  J Neurophysiol       Date:  2010-04-14       Impact factor: 2.714

8.  Recruitment and derecruitment characteristics of motor units in a hand muscle of young and old adults.

Authors:  Mark Jesunathadas; Adam R Marmon; James M Gibb; Roger M Enoka
Journal:  J Appl Physiol (1985)       Date:  2010-03-25

9.  A muscle architecture model offering control over motor unit fiber density distributions.

Authors:  Javier Navallas; Armando Malanda; Luis Gila; Javier Rodríguez; Ignacio Rodríguez
Journal:  Med Biol Eng Comput       Date:  2010-06-10       Impact factor: 2.602

10.  Robust and accurate decoding of motoneuron behaviour and prediction of the resulting force output.

Authors:  Christopher K Thompson; Francesco Negro; Michael D Johnson; Matthew R Holmes; Laura Miller McPherson; Randall K Powers; Dario Farina; Charles J Heckman
Journal:  J Physiol       Date:  2018-06-09       Impact factor: 5.182

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