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: 10435250
• 负责人: Lisa Giocomo
• 金额: $ 39.61万
• 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/10435250
• 关键词: Address; Animals; Attention; Back; Behavior; Behavioral; Behavioral Mechanisms; Brain; Brain Diseases; Brain region; Cells; Clinical; Code; Cues; Data; Disease; Dorsal; Electrophysiology (science); Environment; Etiology; Geometry; Goals; Hippocampus (Brain); Lead; 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; Running; Sampling; Sensory; Silicon; Speed; Stimulus; Structure; Symptoms; Testing; Thirst; Time; Visual; Work; cell cortex; entorhinal cortex; expectation; experience; experimental study; flexibility; improved; insight; network models; neural circuit; optogenetics; public health relevance; rate of change; recruit; relating to nervous system; 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.

大脑的核心功能是创建外部刺激和体验的内部表征 世界来指导行为。在这里，我们检查神经表征背后的电路机制 外部空间，对空间记忆和导航至关重要的表示，并受到神经退行性疾病的影响 和精神疾病。空间表征的神经基础部分取决于神经回路 内侧内嗅皮层 (MEC)，包含编码空间位置、方向和跑步的神经元 动物的速度。在不同的环境之间，位置和方向细胞的发射场可能会发生变化 它们的发射率会旋转或移动到新的空间位置——这种现象被称为“重新映射”。连同 与海马旁区域的其他结构相比，MEC 神经元可以生成独特的神经表征 不同的环境，可能有助于不同背景或情节的编码。重新映射时 MEC 中的 MEC 经常在感官特征（即视觉或气味线索）不同的环境之间进行研究， 我们在最近和初步的数据中发现，行为变量（即跑步速度、奖励期望） 可以引起 MEC 中神经群体状态之间的内部转换（即重新映射）。在这里，我们的目的是测试 假设行为变量的变化可以通过以下方式驱动 MEC 神经群体状态的转变 内嗅电路中的关键节点（目标 1）以及行为驱动的 MEC 空间图经过优化 表示与环境中执行的导航行为相关的特征（目标 3）。此外，我们的目标是 建立行为变量变化与 MEC 神经群体状态转变之间的因果关系 （目标 2）。为了实现这些目标，我们建议将使用硅探针的电生理学与空间和 行为小鼠的记忆任务。到目前为止，电生理学方法必须应对有限的记录 通道计数，导致缺乏在人群水平或作为考虑 MEC 神经编码的研究 行为变量的函数。然而，新版本的硅探针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同时分布。这，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 扰动以建立行为变量变化与 MEC 神经转变之间的因果关系 人口国家，将使我们能够对人口转型的机制获得重要的新见解 MEC 神经群体状态以及此类转变在支持记忆和导航方面的作用。