Literature DB >> 12740414

Spindle model responsive to mixed fusimotor inputs and testable predictions of beta feedback effects.

Mitchell G Maltenfort1, R E Burke.   

Abstract

Skeletofusimotor (beta) motoneurons innervate both extrafusal muscle units and muscle fibers within muscle spindle stretch receptors. By receiving excitation from group Ia muscle spindle afferents and driving the muscle spindle afferents that excite them, they form a positive feedback loop of unknown function. To study it, we developed a computationally efficient model of group Ia afferent behavior, capable of responding to multiple fusimotor inputs, that matched experimental data. This spindle model was then incorporated into a simulation of group Ia feedback during ramp/hold and triangular stretches with and without closure of the beta loop, assuming that gamma and beta fusimotor drives of the same type (static or dynamic) have identical effects on spindle afferent firing. The effects of beta feedback were implemented by driving a fusimotor input with a delayed and filtered fraction of the spindle afferent output. During triangular stretches, feedback through static beta motoneurons enhanced Ia afferent firing during shortening of the spindle. In contrast, closure of a dynamic beta loop increased Ia firing during lengthening. The strength of beta feedback, estimated as a "loop gain" was comparable to experimental estimates. The loop gain increased with velocity and amplitude of stretch but decreased with increased superimposed gamma fusimotor rates. The strongest loop gains were seen when the beta loop and the gamma bias were of different types (static vs. dynamic).

Mesh:

Year:  2003        PMID: 12740414     DOI: 10.1152/jn.00942.2002

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


  6 in total

1.  Model-based prediction of fusimotor activity and its effect on muscle spindle activity during voluntary wrist movements.

Authors:  Bernard Grandjean; Marc A Maier
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3.  Control of Mammalian Locomotion by Somatosensory Feedback.

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Journal:  Compr Physiol       Date:  2021-12-29       Impact factor: 8.915

4.  A leg to stand on: computational models of proprioception.

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Review 5.  A review of human sensory dynamics for application to models of driver steering and speed control.

Authors:  Christopher J Nash; David J Cole; Robert S Bigler
Journal:  Biol Cybern       Date:  2016-04-16       Impact factor: 2.086

6.  Proprioceptive Feedback through a Neuromorphic Muscle Spindle Model.

Authors:  Lorenzo Vannucci; Egidio Falotico; Cecilia Laschi
Journal:  Front Neurosci       Date:  2017-06-14       Impact factor: 4.677

  6 in total

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