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The Journal of Neurophysiology Vol. 83 No. 1 January 2000, pp. 207-231
Copyright ©2000 by the American Physiological Society
Department of Physiology and Biophysics and Fishberg Research Center for Neurobiology, Mount Sinai School of Medicine, New York, New York 10029
Brezina, Vladimir,
Irina V. Orekhova, and
Klaudiusz R. Weiss.
The Neuromuscular Transform: The Dynamic, Nonlinear Link Between
Motor Neuron Firing Patterns and Muscle Contraction in Rhythmic
Behaviors. J. Neurophysiol. 83: 207-231, 2000. The nervous system issues motor commands to
muscles to generate behavior. All such commands must, however, pass
through a filter that we call here the neuromuscular transform (NMT).
The NMT transforms patterns of motor neuron firing to muscle
contractions. This work is motivated by the fact that the NMT is far
from being a straightforward, transparent link between motor neuron and
muscle. The NMT is a dynamic, nonlinear, and modifiable filter.
Consequently motor neuron firing translates to muscle contraction in a
complex way. This complexity must be taken into account by the nervous system when issuing its motor commands, as well as by us when assessing
their significance. This is the first of three papers in which we
consider the properties and the functional role of the NMT.
Physiologically, the motor neuron-muscle link comprises multiple steps
of presynaptic and postsynaptic Ca2+ elevation, transmitter
release, and activation of the contractile machinery. The NMT
formalizes all these into an overall input-output relation between
patterns of motor neuron firing and shapes of muscle contractions. We
develop here an analytic framework, essentially an elementary dynamical
systems approach, with which we can study the global properties of the
transformation. We analyze the principles that determine how different
firing patterns are transformed to contractions, and different
parameters of the former to parameters of the latter. The key
properties of the NMT are its nonlinearity and its time dependence,
relative to the time scale of the firing pattern. We then discuss
issues of neuromuscular prediction, control, and coding. Does the
firing pattern contain a code by means of which particular parameters
of motor neuron firing control particular parameters of muscle
contraction? What information must the motor neuron, and the nervous
system generally, have about the periphery to be able to control it
effectively? We focus here particularly on cyclical, rhythmic
contractions which reveal the principles particularly clearly. Where
possible, we illustrate the principles in an experimentally
advantageous model system, the accessory radula closer (ARC)-opener
neuromuscular system of Aplysia. In the following papers, we
use the framework developed here to examine how the properties of the
NMT govern functional performance in different rhythmic behaviors that
the nervous system may command.
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