Article

Dynamic behaviour of a model of the muscle stretch reflex

Details

Citation

Graham B & Redman S (1993) Dynamic behaviour of a model of the muscle stretch reflex. Neural Networks, 6 (7), pp. 947-962. https://doi.org/10.1016/S0893-6080%2809%2980005-1

Abstract
A computer simulation is used to examine the ability of the muscle stretch reflex circuitry to control limb position when all signals from higher levels of the nervous system are assumed to be constant. The computer model allows the easy incision and excision of different neuronal types so that their roles in the reflex response can be examined in a way that is not possible experimentally. Motoneurone excitation from Group Ia and II afférents, and inhibition from Group Ia inhibitory interneurones, Renshaw cells, and Group Ib afférents, are considered. A circuit in which moloneurone excitation comes purely from Group Ia afférents, which respond to muscle length and rate of change of length, exhibits oscillations in limb position at a frequency comparable to the tremor known as clonus. Good, nonoscillatory dynamic performance is achieved if most of the motoneurone excitation has no velocity component. For certain strengths of the inhibitory synapses, reciprocal inhibition from Group Ia inhibitory interneurones, and inhibition of the homonymous motoneurones by Renshaw cells and Group Ib afférents, results in improvements in the dynamic performance. For large loads, performance is enhanced if the damping from the Renshaw cells and Group Ib afférents is reduced. A simple adaptive scheme that involves inhibition of the Renshaw cells and the Group Ib interneurones by the Group II afférents provides a mechanism by which the damping is automatically attenuated for large loads.

Keywords
Stretch reflex; Spinal cord circuitry; Movement control; Adaptive control

Journal
Neural Networks: Volume 6, Issue 7

StatusPublished
Publication date31/12/1993
PublisherElsevier
ISSN0893-6080

People (1)

Professor Bruce Graham

Professor Bruce Graham

Emeritus Professor, Computing Science