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代表和 在群体水平上对行为相关信息进行编码，这是一个基本问题， 神经元被选择并被招募到记忆编码集合中一直难以解决。我们集团 一直处于开发实验方法的最前沿，这些方法可以高分辨率地监测已识别的 神经元，监测树突和轴突中的亚细胞事件，所有这些现在都可以在清醒时完成 动物我们建议使用这些实验方法与电路建模相结合，以提供一个深入的 了解在小鼠海马中的神经元如何被招募到神经系综中， 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， 它们在啮齿动物海马体的主要CA 1输出节点的网络连接，这个电路代表了一个 第一个主要努力阐明微电路/细胞/亚细胞机制的易处理的目标， 在机械水平上的选择与简单的无脊椎动物系统的研究中所取得的结果相当。目标1是 目的是表征集体抑制动态在CA 1在上下文学习。目标2涉及 事件发生在CA 1锥体细胞的细胞体和树突在上下文学习，包括针对 操纵已识别的抑制细胞类型，并通过以下方式了解基本网络结构： 哪些有助于记忆编码的细胞活动模式受到调节。目标3涉及如何 在情境学习过程中编码的信息在学习过程中会聚到单个CA 1锥体细胞上。 情境学习最后，目标4建立在最近的工作基础上，表明CA 1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体中，这需要树突棘波， 体细胞爆发活性我们将使用光遗传学方法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上下文相关和与强化相关的信号;我们还将干扰局部 回路抑制，以确定是否通过抑制调节可塑性的细胞选择。在整个 我们将利用实验和计算之间前所未有的密切相互作用， 海马CA 1微回路的生物病理学详细模型。在某种程度上，模型可以解释 实验观察，我们可以用它来理解潜在的网络原理和设计 实验来验证这种理解。如果模型无法解释结果， 它将帮助我们指出需要进一步阐明网络功能方面。总体而言，目标1-4 提供了一个易于处理的途径，以实现重大突破，了解认知重要的神经活动， 在微电路、细胞和亚细胞水平上产生动力学。