This paper reports the development of a large-scale model of some spinal reflex circuitry, useful for studying the dynamic interactions among neuronal populations during simple behaviors. The included populations and properties of the neurons and terminals were derived from the literature, mainly on cat spinal cord. The model was conceived as a symmetrical controller of a pair of antagonistic muscles, within the behavioral domain of the stretch and Golgi-tendon-organ reflexes, and was scaled to include realistic numbers of motoneurons. Inputs to the model were fiber populations providing random synaptic drive to some of the populations and sensory stimuli appropriate for the reflexes. The resulting model contained roughly 2300 neurons in six pairs of populations. The total number of connections in the model was about 600,000, and individual postsynaptic potentials were small (0.1-0.6 mV). Model responses were calibrated by examination of their ability to reproduce known aspects of the reflexes. Published algorithms were used to construct the environment, which is easily expandable, in terms of membrane channels, neuronal geometry, and synaptic properties. The system was built to combine a system-level perspective of spinal circuitry with the single-unit perspective common in electrophysiological investigation. It provides a computational tool for system-level investigations of spinal cord similar to the tools available at the level of membrane currents.
Electromyography (EMG) was used to examine muscle activity of the major hip, knee, and ankle extensors during both hopping and swimming in leopard frogs. Chronic EMG electrodes were implanted for periods of 7-10 days. This permitted us to record EMG activities during both hopping and swimming from the same electrode, allowing a direct comparison of the timing and amplitudes of muscle activity between the two behaviors. We could then relate these activities to the kinematics of locomotion. In both behaviors, all three extensors were synchronously activated 30-50 ms before limb extension began. However, the hip extensor turned on relatively earlier in hopping than in swimming when on time was expressed as percent of stride. The hip and knee extensors were activated relatively longer in hopping and the ankle extensor relatively longer in swimming. The amplitudes of the rectified, integrated EMG signals were roughly twice as large in hopping as in swimming for all three muscles, supporting the notion that propulsion in hopping requires more force than in swimming. The EMG burst durations differed little between the muscles or, in relative duration, between the behaviors. As has been found in other quadrupeds, the EMG bursts began before visible movement and ceased at or before hindlimb extension was completed. In our animals, however, we found a consistent, low level (10-30% of maximum amplitude) of EMG activity that continued 60-200 ms past the end of the burst and into the suspension periods in both hopping and swimming. We hypothesize that this unusual activity may be present in frogs so that the hind limb remains aero(hydro)dynamically stable as the frog arches through its leap or glides in swimming following completed limb extension. Thus, the timing and pattern of the EMG bursts are consistent with those present in other tetrapods and support conservatism of neural control. However, the prolonged low-level activity suggests flexibility in the control pattern and variation according to specific behaviors.
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