Computational Analysis of Hippocampal Function

海马功能的计算分析

• 批准号: 6995175
• 负责人: JAMES J KNIERIM
• 金额: $ 13.15万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6995175
• 关键词: brain mapping; computational neuroscience; computer simulation; hippocampus; intercellular connection; learning; memory; neural inhibition; neural plasticity; neurophysiology; single cell analysis

A major goal of cognitive neuroscience is to understand behavior and mental processes in terms of the physiological properties of neural circuits. Place cells of the hippocampus are an ideal system to study these issues. These cells fire robustly and specifically in restricted locations in an environment. They are thought to encode a spatial framework used to organize the items and events of experience, forming the foundation of episodic memory and flexible, context-dependent learning. A major advance in the study of these cells has been the development of techniques to record the activity of dozens of well-isolated neurons simultaneously from different parts of the hippocampal formation. These techniques provide experimenters the tools to test influential computational theories of hippocampal function that have existed for decades without rigorous testing at the level of single-unit physiology. We propose to develop a computational model of processing in the hippocampal formation to aid in the analysis and interpretation of ensemble unit recording from our laboratory. The goal is to understand the mechanisms that transform the input properties at each level into the output properties, and to deduce functional roles from these mechanisms. To this end, it will be necessary to implement computer simulations of the response properties, in order to engender insights into the data that would not arise from less formal analysis; to stimulate additional analysis of the data that would not have otherwise been conceived; and to inspire new experiments to address issues and hypotheses that result from the computational analyses. These analyses will investigate (1) the role of global inhibitory mechanisms in the remapping of place fields, (2) the role of recurrent collateral circuitry in the dynamic responses of place fields to controlled environmental manipulations, and (3) the role of neural plasticity, in particular spike-timing dependent plasticity, in the dynamic responses of place cells to controlled environmental manipulations. The devastating neurological effects of such diseases as Alzheimer's Disease and epilepsy are intimately tied to dysfunctions of the hippocampus and related brain areas. These studies will generate fundamental insights into the neural interactions between these brain areas that underlie learning and memory, as well as insights into how these mechanisms go awry in these debilitating diseases.

认知神经科学的一个主要目标是根据神经回路的生理特性来理解行为和心理过程。海马的位置细胞是研究这些问题的理想系统。这些细胞在环境中的受限位置中强烈且特异性地发射。它们被认为编码一个空间框架，用于组织经验的项目和事件，形成情景记忆和灵活的，依赖于上下文的学习的基础。研究这些细胞的一个主要进展是发展了记录几十个分离良好的神经元活动的技术 同时从海马结构的不同部分。这些技术为实验者提供了测试海马功能的有影响力的计算理论的工具，这些理论已经存在了几十年，没有在单单位生理学水平上进行严格的测试。 我们建议开发一个计算模型的处理在海马结构，以帮助我们的实验室合奏单位记录的分析和解释。我们的目标是理解将每个级别的输入属性转换为输出属性的机制，并从这些机制中推断出功能角色。为此，有必要对响应特性进行计算机模拟，以便对不太正式的分析所不能产生的数据产生深刻的见解;刺激对否则无法设想的数据进行更多的分析;并激发新的实验，以解决计算分析所产生的问题和假设。 这些分析将研究（1）在位置场的重新映射中的全局抑制机制的作用，（2）在位置场对受控环境操作的动态响应中的循环侧支回路的作用，以及（3）在位置细胞对受控环境操作的动态响应中神经可塑性的作用，特别是尖峰时间依赖的可塑性。阿尔茨海默病和癫痫等疾病的破坏性神经影响与海马体和相关脑区的功能障碍密切相关。这些研究将对这些大脑区域之间的神经相互作用产生基本的见解，这些大脑区域是学习和记忆的基础，以及对这些机制在这些使人衰弱的疾病中如何出错的见解。