Physiological studies in walking cats have indicated that two sensory signals are involved in terminating stance in the hind legs: one related to unloading of the leg and the other to hip extension. To study the relative importance of these two signals, we developed a three-dimensional computer simulation of the cat hind legs in which the timing of the swing-to-stance transition was controlled by signals related to the force in ankle extensor muscles, the angle at the hip joint, or a combination of both. Even in the absence of direct coupling between the controllers for each leg, stable stepping was easily obtained using either a combination of ankle force and hip position signals or the ankle force signal alone. Stable walking did not occur when the hip position signal was used alone. Coupling the two controllers by mutual inhibition restored stability, but it did not restore the correct timing of stepping of the two hind legs. Small perturbations applied during the swing phase altered the movement of the contralateral leg in a manner that tended to maintain alternating stepping when the ankle force signal was included but tended to shift coordination away from alternating when the hip position signal was used alone. We conclude that coordination of stepping of the hind legs depends critically on load-sensitive signals from each leg and that mechanical linkages between the legs, mediated by these signals, play a significant role in establishing the alternating gait.
Abstract.A simulated neural network has been connected to a simulated mechanical environment. The network is based on a model of the spinal central pattern generator producing rhythmic swimming movements in the lamprey and the model is similar to that used in earlier simulations of fictive swimming. Here, the network has been extended with a model of how motoneuron activity is transformed via the muscles to mechanical forces. Further, these forces are used in a two-dimensional mechanical model including interaction with the surrounding water, giving the movements of the different parts of the body. Finally, these movements are fed back through stretch receptors interacting with the central pattern generator. The combined model provides a platform for various simulation experiments relating the currently known neural properties and connectivity to the behavior of the animal in vivo. By varying a small set of parameters, corresponding to brainstem input to the spinal network, a variety of basic locomotor behaviors, like swimming at different speeds and turning can be produced. This paper describes the combined model and its basic properties.
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