Discrete neural networks, within the central nervous system (CNS) of both vertebrates and invertebrates, are responsible for generating the patterned neural activity that mediates rhythmic behaviors. A long-term goal of this proposal is to understand the cellular mechanisms and functional consequences underlying the modulation of these networks by inputs from within the CNS. A related goal is to understand, at the cellular level, how modulation by these inputs is regulated by presynaptic influences. This proposal focuses on modulation of the pyloric and gastric mill neural networks, located in the stomatogastric ganglion (STG) of the crab, Cancer borealis. Electrophysiological techniques, based on combining intra-somatic recordings of STG network neurons with intra-axonal recordings of modulatory inputs entering the STG, will be used to attain the following goals. (1) Characterize how individual axons influence these networks, identify the axon's transmitter by combining intra-axonal dye filling and immunocytochemistry, and then determine whether the way these networks respond to axon stimulation is well-mimicked by exogenous application of it's transmitter. (2) Study local influences on these axons, and whether there are distinct membrane properties or synaptic effects of these axons, within the STG. Then determine how each one shapes the way these axons modulate pyloric and gastric mill network activity. (3) Identify the activity and outputs of these axons elsewhere in this nervous system, to determine whether a neuron can simultaneously use different impulse patterns to influence different neural networks. The results of these experiments will provide a new level of understanding, previously unobtainable, about how individual neurons use modulatory transmitters to influence rhythmically active neural networks, and how this influence is locally regulated near the terminals of the input. This will help guide conceptual understanding and experimental approaches in the similar but less accessible, vertebrate systems.
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