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.