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

CRI：模型驱动的大鼠海马功能研究

• 批准号: 9634424
• 负责人: Ali Minai
• 金额: $ 9.99万
• 依托单位: University of Cincinnati Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-10-01 至 1998-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9634424&HistoricalAwards=false
• 关键词: CRI; Model; Driven; Investigation; Hippocampal

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.

ID：IBN-9634424。 PI：Ali A.民爱 海马体是大脑中极其重要的区域。是 海马体对于记忆相关的 在大多数哺乳动物中，包括人类。最佳候选机制 长时程增强（long-term potentiation，LTP）是一种记忆增强效应， 海马体的一部分最后，它也是癫痫的一个重要病灶 该地区是人类阿尔茨海默病的主要目标。因此 这对理解这个大脑区域的功能至关重要。 到目前为止，大多数关于海马体的研究都是由生理学驱动的， 和行为实验。这产生了一系列令人印象深刻的数据， 但对海马的功能仍缺乏系统的了解。 如果对海马的实验研究 是在理论和实验的相互反馈下逻辑地进行。 拟议研究的广泛目标是开发和验证一个 海马作为一个系统的具体定量模型。该模型基于 根据现有数据，然后将提供一个理论框架， 问题和设计系统的系列实验。此外，由于其计算性质，该模型将允许具体的预测， 在模拟的基础上，从而提供了一种手段， 提高模型本身的质量。在短期内，该项目将侧重于空间学习问题（例如，记住地点）， 其中有大量组织良好的实验数据。 所处理的具体问题将是：1）多种投入的作用， 2）对相似地点和环境的区分; （3）时间在信息存储和回忆中的作用。 该模型将使用神经网络领域开发的方法， 动力系统，从现象学层面到 更多的生理细节 模型的假设和预测 将通过行为和生理实验进行严格验证。 因此，该项目代表了计算和 实验技术未来的工作将把结果推广到其他领域。 记忆功能方面。