Temporal pattern analysis is crucial for hearing. Echolocating bats use temporal patterns to determine the distance of objects and to identify insect prey. For humans, temporal patterns are a fundamental aspect of music and speech. Previous work shows that neurons in the nuclei of the lateral lemniscus (NLL) integrate inputs from lower brainstem auditory nuclei. This work also indicates that the process of integration results in transformations of the acoustic signal that may be important for analyzing the temporal pattern of sound. The broad aim of the proposed work is to examine the relationship between signal transformations in the NLL and behavior based on temporal patterns of sound, and to investigate the circuitry responsible for the observed transformations. These experiments will be conducted in the big brown bat, Eptesicus fuscus, an animal with highly differentiated subdivisions in the NLL.
The specific aims are: 1. To characterize responses of NLL neurons to temporal patterns of sound with well-documented behavioral correlates; 2. To Identify behaviorally relevant transformations that occur at the NLL by comparing the responses of NLL neurons with those of neurons in the cochlear nucleus, using the same set of stimuli as in (1); 3. To identify mechanisms for signal transformation and temporal processing by pharmacological blocking of inputs to NLL; 4. To identify the sources of GABAergic and glycinergic inhibitory inputs to NLL using combined retrograde labeling and immunohistochemistry; 5. To examine possible connections among NLL subdivisions that may contribute to signal transformations. The proposed research is intended to provide new insight into the broad issues of how and why the multiple parallel and serial auditory pathways of the brainstem interact with one another and how the various transformations that are accomplished relate to behaviors that depend on analysis of temporal patterns. It is likely that the results of these experiments will be widely applicable to mammalian hearing. Understanding how temporal patterns are analyzed in the auditory system could provide insight not only into mechanisms for hearing, but into general mechanisms that operate in all neural systems dealing with patterns of time-varying information.
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