CRI: A Model-Driven Investigation of Hippocampal Functionality in the Rat

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ID: IBN-9634424. PI: Ali A. Minai The hippocampus is an extremely important region of the brain. It is well-established that the hippocampus is crucial to memory-related performance in most mammals, including humans. the best candidate mechanism for memory --- long-term potentiation (LTP)--- is known to occur in many parts of the hippocampus. Finally, It is also an important epileptic focus region and a prime target of Alzheimer's disease in humans. It is thus critically important to understand the functioning of this brain region. So far, most research on the hippocampus has been driven by physiological and behavioral experiments. This has produced an impressive body of data, but a systematic understanding of hippocampal function is still lacking. Such understanding is necessary if experimental research on the hippocampus is to proceed logically with mutual feedback between theory and experiment. The broad objective of the proposed research is to develop and validate a concrete quantitative model of the hippocampus as a system. This model, based on existing data, would then provide a theoretical framework for posing precise questions and designing systematic series of experiments. Further, because of its computational nature, the model will allow concrete predictions to be made on the basis of simulations, thus providing a means for continuously improving the quality of the model itself. In the short term, the project will focus on the issue of spatial learning (e.g., remembering places) for which a large amount of well-organized experimental data is available. The specific issues addressed will be: 1) The role of multiple inputs to the hippocampus; 2) Discrimination between similar places and environments; and 3) The role of timing in the storage and recall of information. The model will use methods developed in the area of neural networks and dynamical systems, proceeding from a phenomenological level to one of greater physiological detail. The hypotheses and predictions of the model will be rigorously verified using behavioral and physiological experiments. The project thus represents a significant integration of computational and experimental techniques. Future work will generalize the results to other aspects of memory function.