MODELING A MOTOR PATTERN GENERATING NEURONAL NETWORK

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We have analyzed in detail the neuronal network that generates heartbeat in the leech. Reciprocally inhibitory pairs of heart interneurons form oscillators that pace the heartbeat rhythm. Other heart interneurons coordinate these oscillators; these coordinating interneurons with the oscillator interneurons form an 8 cell timing oscillator network for heartbeat. Still other interneurons, along with the oscillator interneurons, inhibit heart motor neurons, sculpting their activity into rhythmic bursts. Critical switch interneurons interface between the oscillator interneurons and the other premotor interneurons to produce two alternating coordination states of the motor neurons. The period of the rhythm generating interneurons are modulated by endogenous RFamide neuropeptides. We have explored the ionic currents, and graded and spike-mediated synaptic transmission that promote oscillation in the oscillator interneurons and have incorporated these data into a conductance based computer model. This model has been of considerable predictive value and has led to new insights into how reciprocally inhibitory neurons produce oscillation. We are now in a strong position to expand this model upward, to encompass the entire heartbeat network, horizontally, to elucidate the mechanisms of FMRFamide modulation, and downward, to incorporate cellular morphology. These modeling studies in conjunction with parallel physiological experiments, either proposed herein or already ongoing in the lab, will contribute to our understanding of how rhythmic motor acts are generated, coordinated intersegmentally, modulated and reconfigured at the network, cellular, ionic current, and synaptic levels. By studying the processes for motor pattern formation in the leech we will uncover important insights into the function of more complex motor systems. The computational approach that we propose will also generate insights into the function of distributed neural networks in general.