Towards a Complete Description of the Circuitry Underlying Memory replay.

实现内存重放底层电路的完整描述。

• 批准号: 8935978
• 负责人: IVAN SOLTESZ
• 金额: $ 70.7万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8935978
• 关键词: Area; Behavioral; Brain; Brain region; Cells; Computer Simulation; Data; Detection; Episodic memory; Event; Generations; Health; Hippocampus (Brain); Image; Interneurons; Invertebrates; Measurement; Measures; Medial; Mediating; Memory; Memory Disorders; Methods; Modeling; Neurons; Optical Methods; Optics; Pattern; Process; Property; Pyramidal Cells; Radial; Recurrence; Role; Running; Synapses; System; Technology; Test Result; Testing; Time; Transfection; Work; arm; base; brain cell; cell type; cognitive function; dentate gyrus; entorhinal cortex; in vivo; insight; interest; meetings; memory recall; novel; novel strategies; optical imaging; optogenetics; reconstitution; research study; supercomputer; tool

 DESCRIPTION (provided by applicant): The function of a brain region is an emergent property of many cell types. The criteria needed to understand a network have been established in studies of invertebrate "simple" networks, but there has not yet been an attempt to provide such a full, mechanistic understanding of any network in the vertebrate brain. We believe that the time is now ripe for such an effort. Specifically, we propose to understand how the CA3 network in the hippocampus generates sharp-wave-ripples (SWR). These events are of great interest because of their cognitive function: they represent replay of episodic memory sequences and are required for subsequent memory recall, as demonstrated at the behavioral level. Our efforts to understand the SWR will build on previous work establishing the cell types of the hippocampus. However, to meet the criteria for "understanding", a great deal of additional information about connectivity and intrinsic properties of cells must be obtained. We will use recently developed large-scale electrical and optical recording methods and ontogenetic to obtain this information. In addition, several new methods/tools will be developed. Notably, we propose to optimize a novel synapse localization optical method to obtain high-throughput cell type-specific information about the connective of the CA3 network. We will also construct the first full-scale computational model of the CA3 region of the hippocampus, in which every cell and synaptic connection is explicitly represented. This strictly data-driven, full-scale model will provide a widely applicable tool for synthesizing experimental results and testing our ability to understand the principles that underlie SWR generation.

 描述（由申请人提供）：大脑区域的功能是许多细胞类型的新兴特性。理解网络所需的标准已经在无脊椎动物“简单”网络的研究中建立，但尚未尝试对脊椎动物大脑中的任何网络提供如此全面、机械的理解。我们认为，现在进行此类努力的时机已经成熟。具体来说，我们建议了解海马体中的 CA3 网络如何产生尖波波纹 (SWR)。这些事件因其认知功能而引起人们极大的兴趣：它们代表情景记忆序列的重播，并且是后续记忆回忆所必需的，正如行为层面所证明的那样。我们对 SWR 的理解将建立在之前建立海马细胞类型的工作的基础上。然而，为了满足“理解”的标准，必须获得大量有关细胞连接性和内在特性的附加信息。我们将使用最近开发的大规模电学和光学记录方法以及个体发生来获取这些信息。此外，还将开发几种新方法/工具。值得注意的是，我们建议优化一种新型突触定位光学方法，以获得有关 CA3 网络连接的高通量细胞类型特异性信息。我们还将构建海马 CA3 区域的第一个全尺寸计算模型，其中每个细胞和突触连接都被明确表示。这个严格由数据驱动的全面模型将 提供了一个广泛适用的工具来综合实验结果并测试我们理解 SWR 生成原理的能力。