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有关神经元如何代表和的大量信息 在人群层面上编码行为相关的信息，这是个人如何的基本问题 选择神经元并招募到内存编码的集合很难解决。我们的小组有 一直处于开发实验方法的最前沿，该方法允许对已识别的高分辨率监视 神经元，监测树突和轴突中的亚细胞事件，现在所有这些都可以在醒着的行为中进行 动物。我们建议将这些实验方法与电路建模结合使用以提供深度 了解如何将小鼠海马中的神经元募集到神经集合期间 上下文记忆编码。因为关于涉及的兴奋性和抑制性细胞类型的了解众所周知 他们在啮齿动物海马的主要CA1输出节点上的网络连接，该电路代表一个 可进行的可行目标，首先要阐明细胞的微电路/细胞/亚细胞机制 与简单无脊椎动物系统的研究相当的机械水平选择。目标1是 旨在在上下文学习过程中表征CA1中的集体抑制动态。 AIM 2处理 在上下文倾斜期间，在CA1锥体细胞的细胞体和树突中发生的事件，包括针对性 通过确定的抑制细胞类型操作，并通过了解基本网络体系结构 哪些细胞活性模式有助于记忆编码。 AIM 3处理如何 在上下文学习中编码的信息会收敛到单个CA1锥体细胞中 上下文学习。最后，AIM 4基于最近的工作，表明CA1锥体细胞可以可靠 通过需要树突状尖峰的可塑性机制招募到内存编码合奏 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造射击场并确定 这些单元是否可以编码与上下文相关和增强相关的信号；我们还将干扰当地 电路抑制以确定是否通过抑制来调节细胞的选择。自始至终 提案我们将通过使用一个 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 实验性观察，我们可以使用它来了解基本的网络原则和设计 介入实验以验证这种理解。在模型无法解释结果的范围内 它将帮助我们指出需要进一步阐明的网络功能的各个方面。总之，目标1-4 在理解认知重要的神经活动方面，提供了一个重大突破的寓意途径 动力学是在微电路，细胞和亚细胞水平上产生的。