The general goal of this proposal is to understand the mechanisms of synaptic integration in an identified neuron in crayfish, the Lateral Giant (LG) neuron, that make it a coincidence detector for massive, converging mechanosensory input. Coincidence detection is ubiquitous in the nervous system, and has been shown to mediate binaural localization in birds, associative learning at Hebbian synapses in hippocampus, 40 Hz electrical oscillations in mammalian cortex and arthropod brain, and startle responses in vertebrates and invertebrates. Pathologies that affect coincidence detection mechanisms may affect learning, binocular depth perception, binaural localization, and motor performance. While its importance is widely recognized, little is known about the neuronal mechanisms of coincidence detection. Extensive preliminary experiments showed that LG is extremely sensitive to the timing of inputs, and will give substantially larger responses to coincident inputs than to inputs which are separated by less than 0.25 ms. LG's excitatory inputs are through rectifying electrical synapses, and analysis of the effect of converging inputs through such synapses onto a model postsynaptic neuron indicated that voltage-dependent electrical synapses provide an ideal mechanism for coincidence detection.
The specific aims are to define the stimulus conditions that promote coincidence detection by the LG neuron, to identify the mechanisms of coincidence detection that affect LG's response, and to describe the properties of the electrical synapses between primary afferents and LG, and how they contribute to coincidence detection by LG. Standard electrophysiological and anatomical techniques will be used.
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