Experimental and modeling investigations into microcircuit, cellular and subcellular determinants of hippocampal ensemble recruitment to contextual representations

对海马体集合招募到情境表征的微电路、细胞和亚细胞决定因素的实验和建模研究

• 批准号: 10097137
• 负责人: Attila Losonczy
• 金额: $ 73.8万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10097137
• 关键词: Address; Animals; Area; Association Learning; Axon; Behavior; Behavioral; Behavioral Model; Biophysics; Calcium; Cell physiology; Cells; Code; Cognitive; Coupled; Dendrites; Dendritic Spines; Environment; Event; Exhibits; Experimental Models; Generations; Heterogeneity; Hippocampus (Brain); Image; Individual; Interneurons; Invertebrates; Investigation; Knowledge; Learning; Mediating; Memory; Memory Disorders; Methods; Modeling; Molecular; Monitor; Mus; Neurons; Neurosciences; Organism; Outcome; Output; Pattern; Pharmacogenetics; Physiological; Play; Population; Process; Property; Psychological reinforcement; Pyramidal Cells; Regulation; Research; Resolution; Rodent; Role; Sensory; Signal Transduction; Stimulus; Stream; Structure; Study models; Surveys; Synapses; Synaptic plasticity; System; Technology; Testing; Thinness; Time; Work; awake; behavior influence; cell type; cognitive function; experimental study; in vivo; insight; memory encoding; multimodality; network architecture; network models; novel strategies; optogenetics; presynaptic; programs; recruit; relating to nervous system; therapy design; two-photon

Although neuroscience has recently provided a great deal of information about how neurons represent and encode behaviorally relevant information at the population level, the fundamental question of how individual neurons are selected and recruited to memory coding ensembles has been difficult to address. Our group has been at the forefront of developing experimental methods that allow high-resolution monitoring of identified neurons, monitoring subcellular events in dendrites and axons, all of which can now be done in awake behaving animals. We propose to use these experimental methods in combination with circuit modeling to provide a deep understanding of how the neurons in the mouse hippocampus are recruited to neural ensembles during contextual memory encoding. Because much is known about the excitatory and inhibitory cell types involved and their network connections at the main CA1 output node of the rodent hippocampus, this circuit represents a tractable target for the first major effort to elucidate the microcircuit/cellular/subcellular mechanisms of cell- selection at a mechanistic level comparable to that achieved in the study of simple invertebrate systems. Aim 1 is aimed at characterizing collective inhibitory dynamics in CA1 during contextual learning. Aim 2 deals with the events that occur in cell bodies and dendrites of CA1 pyramidal cells during contextual leaning, including targeted manipulation in identified inhibitory cells types and understanding the fundamental network architecture by which cellular activity patterns conducive to memory encoding are regulated. Aim 3 deals with how the information that is encoded during contextual learning converges onto individual CA1 pyramidal cells during contextual learning. Finally, Aim 4 builds upon recent work indicating that CA1 pyramidal cells can be reliably recruited to memory coding ensembles through a plasticity mechanism that requires dendritic spikes and somatic bursting activity. We will use optogenetic means to create artificial firing fields in neurons and determine whether these cells can encode context-related and reinforcement related signals; we will also interfere with local circuit inhibition to determine whether cell selection through plasticity is regulated by inhibition. Throughout the proposal we will leverage unprecedentedly close interplay between experiment and computation by using a biophysically detailed model of the hippocampal CA1 microcircuit. To the extent that the model can account for the experimental observations, we can use it to understand underlying network principles and design interventional experiments to validate this understanding. To the extent that the model cannot explain results, it will help point us to aspects of network function that require further elucidation. Taken together, Aims 1-4 provide a tractable path to a major breakthrough in understanding how cognitively important neural activity dynamics are generated at the microcircuit-, cellular- and subcellular-levels.

尽管神经科学最近提供了大量关于神经元如何表示和 在群体层面对行为相关信息进行编码，这是个体如何 神经元被选择并招募到记忆编码整体中一直很难解决。我们组有 一直处于开发实验方法的最前沿，这些方法可以对已识别的物质进行高分辨率监测 神经元，监测树突和轴突的亚细胞事件，所有这些现在都可以在清醒的情况下完成 动物。我们建议将这些实验方法与电路建模相结合，以提供深入的研究 了解小鼠海马体中的神经元如何在 上下文记忆编码。因为我们对所涉及的兴奋性和抑制性细胞类型了解很多，并且 它们的网络连接在啮齿动物海马体的主要 CA1 输出节点上，该电路代表 阐明细胞的微电路/细胞/亚细胞机制的第一个重大努力的易于处理的目标 机械水平上的选择与简单无脊椎动物系统研究中实现的选择相当。目标 1 是 旨在表征情境学习期间 CA1 的集体抑制动态。目标 2 涉及 情境学习期间 CA1 锥体细胞的细胞体和树突中发生的事件，包括目标 对已识别的抑制细胞类型进行操作并通过以下方式了解基本网络架构 有利于记忆编码的细胞活动模式受到调节。目标 3 涉及如何 情境学习过程中编码的信息会汇聚到各个 CA1 锥体细胞上 情境学习。最后，目标 4 基于最近的工作，表明 CA1 锥体细胞可以可靠地 通过可塑性机制被招募到记忆编码集合中，该机制需要树突尖峰和 体细胞爆发活动。我们将使用光遗传学手段在神经元中创建人工放电场并确定 这些细胞是否可以编码与情境相关和强化相关的信号；我们也会干扰当地 电路抑制以确定通过可塑性进行的细胞选择是否受到抑制的调节。自始至终 该提案中，我们将通过使用 海马 CA1 微电路的生物物理详细模型。在模型可以解释的范围内 实验观察，我们可以用它来理解底层网络原理和设计 介入实验来验证这一理解。在模型无法解释结果的情况下， 它将帮助我们指出网络功能中需要进一步阐明的方面。综合起来，目标 1-4 为理解神经活动对认知的重要性取得重大突破提供了一条容易处理的途径 动力学是在微电路、细胞和亚细胞水平上产生的。