The Dynamics of Neural Representations for Distinct Spatial Contexts and Memory Episodes

不同空间背景和记忆片段的神经表征的动力学

• 批准号: 10620709
• 负责人: Lisa Giocomo
• 金额: $ 39.62万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-15 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10620709
• 关键词: Address; Animals; Back; Behavior; Behavioral; Behavioral Mechanisms; Brain; Brain Diseases; Brain region; Cells; Clinical; Code; Cues; Data; Disease; Dorsal; Electrophysiology (science); Environment; Etiology; Geometry; Goals; Hippocampus; Learning; Length; Link; Location; Maps; Medial; Memory; Mental Depression; Mental disorders; Moods; Mus; Neurodegenerative Disorders; Neurons; Neurophysiology - biologic function; Odors; Population; Population Dynamics; Positioning Attribute; Psychiatric therapeutic procedure; Rewards; Rotation; Running; Sampling; Sensory; Silicon; Speed; Stimulus; Structure; Symptoms; Testing; Thirst; Visual; Work; cell cortex; cortex mapping; entorhinal cortex; expectation; experience; experimental study; flexibility; improved; insight; member; network models; neural; neural circuit; optogenetics; public health relevance; rate of change; recruit; response; sensory input; spatial memory; virtual reality; virtual reality environment; way finding

A central function of the brain is to create internal representations of stimuli and experiences from the outside world to guide behavior. Here, we examine the circuit mechanisms underlying the neural representation of external space, a representation essential to spatial memory and navigation, and impacted by neurodegenerative and psychiatric diseases. The neural basis for the representation of space depends, in part, on circuits in the medial entorhinal cortex (MEC), which contains neurons that encode the spatial position, orientation and running speed of an animal. Between distinct environments, the firing fields of position and orientation cells can change their firing rate and rotate or move to a new spatial location – phenomenon known as ‘remapping’. Together with other structures in the parahippocampal region, MEC neurons can generate unique neural representations for distinct environments, potentially contributing to the encoding of different contexts or episodes. While remapping in MEC has often been studied between environments that differ in sensory features (i.e. visual or odor cues), we have found in recent and preliminary data that behavioral variables (i.e. running speed, expectation of reward) can evoke internal transitions between neural population states (i.e. remapping) in MEC. Here, we aim to test the hypotheses that a change in behavioral variables can drive transitions in MEC neural population states via key nodes in entorhinal circuitry (Aim 1) and that behaviorally driven MEC spatial maps are optimized to represent features relevant to the navigational behavior executed in the environment (Aim 3). Moreover, we aim to establish causality between changes in behavioral variables and transitions in MEC neural population states (Aim 2). To address these aims, we propose to combine electrophysiology using silicon probes with spatial and memory tasks in behaving mice. Until now, electrophysiological approaches had to contend with limited recording channel counts, contributing to a lack of studies that considered MEC neural coding at the population level or as a function of behavioral variables. However, new versions of silicon probes have allowed us to record hundreds of MEC neurons simultaneously along nearly the entire length of mouse entorhinal cortex. This, combined with virtual reality tasks that can provide dense sampling of sensory and behavioral variables, as well as optogenetic perturbations to establish causality between changes in behavioral variables and transitions in MEC neural population states, will enable us to achieve significant new insight into the mechanisms underlying transitions in MEC neural population states and the of such transitions in supporting memory and navigation.

大脑的主要功能是从外部创建刺激和经验的内部表示 指导行为的世界。在这里，我们检查了神经表示的基础电路机制 外部空间，是空间内存和导航必不可少的表示，并受神经退行性的影响 和精神病。空间表示的神经基础部分取决于电路 内侧邻次皮质（MEC），其中包含编码空间位置，方向和运行的神经元 动物的速度。在不同的环境之间，位置和方向单元格的发射场可能会改变 它们的射击率并旋转或移至新的空间位置 - 被称为“重新映射”的现象。一起 MEC神经元可以在帕拉希峰地区的其他结构中产生独特的神经元表示。 不同的环境，有可能促进不同上下文或情节的编码。重新映射 在MEC中，经常是在感觉特征（即视觉或气味提示）不同的环境之间研究的， 我们在最近和初步数据中发现了行为变量（即运行速度，对奖励的期望） 可以在MEC中引起神经群体状态之间的内部过渡（即重新映射）。在这里，我们的目标是测试 假设行为变量的变化可以通过 内河电路中的关键节点（AIM 1），并且以行为驱动的MEC空间图被优化为 表示与环境中执行的导航行为相关的特征（AIM 3）。而且，我们的目标 在行为变量的变化与MEC神经群体的过渡之间建立因果关系 （目标2）。为了解决这些目标，我们建议使用硅问题与空间和 行为小鼠的内存任务。到目前为止，电生理方法必须与记录有限的 渠道计数，导致缺乏研究MEC神经编码在人群水平或AS的研究 行为变量的函数。但是，新版本的硅问题使我们能够记录数百个 MEC神经元几乎沿着小鼠内嗅皮层的整个长度。这个，结合 虚拟现实任务可以提供感官和行为变量的密集采样以及光遗传学 扰动以在行为变量的变化与MEC中性转变之间建立因果关系 人口国家将使我们能够对中的机制实现重大的新见解 MEC神经群体和支持记忆和导航方面的此类过渡。