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Role of neural variation in hippocampal coding and plasticity

$177,874P50FY2010MHNIH

University Of California, San Francisco, San Francisco CA

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Abstract

Numerous researchers have shown that, in humans, the hippocampal formation is necessary for the formation of new memories of facts or events. In rodents these same structures play an essential role in an animal's ability to learn about and remember complex associations, including tasks where the animal must learn and remember information about a set of spatial cues in order to navigate through an environment. Both event / fact memory in humans and spatial memory in rodents requires learning complex relationships, and that parallel strongly suggests that qualitatively similar processing occurs in the human and the rat hippocampus, making the rat hippocampus an attractive model system for investigating memory processing. Memory storage and recall require a balance between seemingly contradictory requirements: the system must be sufficiently plastic to allow new patterns of activity to be rapidly stored, yet sufficiently stable to allow previously stored memories to be retrieved without great distortion. The aim of this proposal is to compare neural variability among the inputs to the hippocampus, the hippocampus itself and the outputs of the hippocampus and to determine whether variability is related to behavior and dynamically regulated during learning. We will test the following hypotheses: 1) the hippocampal circuit creates a low variability representation of space from highly variable inputs, 2) variability in the hippocampal circuit is decreased in the context of memory tasks, and 3) learning causes rapid changes in variability in the hippocampus but slower changes in the downstream deep layers of the entorhinal cortex (EC), reflecting the specialization of the hippocampus for rapid learning and of the deep EC for slower learning of the relationships between locations and behaviors. Integrating our findings with those of the other projects will help us better understand the role of variation in the neural code across brain systems.

View original record on NIH RePORTER →