title: Static and dynamic input-output relations of the feline medial gastrocnemius motoneuron-muscle system subjected to recurrent inhibition: a model study.
abstract: The physiological function of spinal recurrent inhibition is still a matter of debate because of the experimental difficulty or impossibility of observing recurrent inhibition at work in normally behaving animals. The purpose of this study was to investigate, by computer simulation, the role of recurrent inhibition in shaping the input-output (I/O) relationships between descending command signals (DCS) as inputs and motoneuron (MN) and Renshaw cell (RC) firing rates and muscle force as outputs. Changing the spatial (topographical) distribution of recurrent inhibition from nonhomogeneous (as in the standard model) to homogeneous did not alter the I/O relationships significantly, while changing the functional distribution related to MN types did. Altering the global gain of recurrent inhibition, as happens naturally in various motor acts, changes the slopes and positions (at high inputs) of the I/O relationships, making recurrent inhibition a suitable means of gain control. Coupling a decrease in recurrent inhibitory gain with an increase in DCS input, as could occur during slow dynamic contractions, would increase the MN and force gains during the act. Short dynamic ramp-and-hold DCS inputs generate MN firing patterns, to which recurrent inhibition contributes interspike-interval variability and damped oscillations, which are related to issues of tremor and its control.
authors: Department of Applied Physics and Physico-Informatics, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan. uchiyama@appi.keio.ac.jp
authors: Takanori
authors: T
authors: Uchiyama
authors: Håkan
authors: H
authors: Johansson
authors: Uwe
authors: U
authors: Windhorst
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D002415:Cats; D009046:Motor Neurons / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D009433:Neural Inhibition / Q000502:physiology*; D016571:Neural Networks, Computer