Neural Network Model for Muscle Force Control Based on the Size Principle and Recurrent Inhibition of Renshaw Cells
A neural network model for muscle force control was constructed. The model contained a single motor-cortex output cell, the actual number of a motoneurons found in human muscles, Renshaw cells and muscle units. The size of the motor units (motoneurons and muscle units) was distributed as the human brachialis muscle, the extensor digitorum muscle and the first dorsal interosseous muscle. The relationship between the model’s muscle force and the firing rate of a motoneurons was investigated. The relationship depended on the absolute refractory time of a motoneurons, RIPSP by Renshaw cells and the firing pattern of Renshaw cells. When these parameters were selected appropriately, the model showed a relationship similar to that observed in isometric contraction of human skeletal muscles. The size distribution of the motor units had a dominant effects on the relationship.
KeywordsFiring Rate Motor Unit Neural Network Model Muscle Force Isometric Contraction
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