The Contribution of Dentate-Neural Networks to Memory Encoding

University Of California, San Diego, La Jolla CA

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Abstract

DESCRIPTION (provided by applicant): Several neuropsychiatric disorders show extensive pathology in the input layer to the hippocampus, the dentate gyrus. One set of symptoms common to these diseases is impairments in memory that are consistent with proposed dentate gyrus function, such as deficits in episodic memory and working memory. Little is known, however, about the neural network mechanisms that underlie dentate gyrus memory encoding. In Aim 1 we will elucidate the dentate gyrus network mechanisms that support memory encoding by recording from dentate neuronal populations in awake behaving animals while they perform a dentate gyrus dependent working-memory task. In Aim 2 we will look at the contribution of individual classes of dentate neurons to the neural network computations essential for memory encoding, as several diseases differentially target individual classes of neurons. Completion of these aims will provide the framework to compare healthy network processes that underlie memory formation to disease processes, and may lead to therapeutic targets.