Grid Cell Dynamics During Navigation In Virtual Reality

描述(申请人提供)：内侧内嗅皮层(MEC)有助于导航和情景记忆，在许多退行性和精神障碍中基本认知功能退化。网格单元的发现提供了MEC功能的关键，网格单元在一组镶嵌空间的六边形格子的顶点上点火。网格单元系统被假设为在导航期间执行路径整合，并成为空间环境的地图。由于其激发电场的惊人规律性，网格单元引起了广泛的理论兴趣，并提出了许多模型来解释网格是如何形成的，它们是如何在微电路中组织的，以及它们如何利用独有的(自运动)信息来进行路径整合。因此，网格单元系统提供了在机械水平上研究具有认知意义的神经计算的机会。在这里，我们利用最新的技术进步，包括我们实验室以前开发的啮齿动物虚拟现实方法，从三个方面研究GRI细胞的细胞内、微电路和集成特性：1)目前的网格细胞模型可以再现六角晶格放电模式，但它们预测了不同的细胞膜电位时间进程，反映了不同的潜在细胞或网络机制。为了验证这些预测，在目标1中，我们将利用我们的虚拟现实系统实现的头部固定导航，在行为过程中从网格细胞中进行细胞内记录。将对膜电压时间序列进行统计分析，以检查是否存在斜坡和theta振荡等特征特征，以及它们是否与激发场的位置相关。例如，我们将检查激发场中的theta振荡幅度是否更大，以及theta频率是否如网格细胞的theta干扰模型所预测的那样随着鼠标速度的增加而增加。2.)网格细胞不是完全相同的，但具有不同的尺度和相移，可能反映不同的功能模块。与这一观点一致的是，越来越多的证据表明，在MEC中存在着解剖学上定义的细胞团。为了描绘功能模块和解剖簇之间的联系，在目标2中，我们将在虚拟导航过程中使用细胞分辨率双光子钙成像，以提供微电路尺度上对MEC中已识别的网格细胞的空间组织的第一次测量。特别是，我们将绘制网格细胞属性(空间尺度和相位)与富含细胞色素氧化酶的斑块之间的关系，并确定沿背腹轴的空间尺度是否有尖锐的突变。3.)网格细胞被认为执行路径整合，这一想法主导了目前关于MEC功能角色的想法。在目标3中，我们将使用虚拟现实来控制所有提供位置信息的感觉线索，以严格检验路径整合假说。总而言之，这些目标应该会促进我们对网格单元的单电池、微电路和计算属性的理解。

DESCRIPTION (provided by applicant): The medial entorhinal cortex (MEC) contributes to navigation and episodic memory, essential cognitive functions degraded in many degenerative and psychiatric disorders. A key to MEC function was provided by the discovery of grid cells, which fire on the vertices of a set of hexagonal lattices tessellating space. The grid cell system has been hypothesized to perform path integration during navigation and to be a map of the spatial environment. Because of the striking regularity of their firing fields, grid cells have generated widespread theoretical interest, and numerous models have been proposed to explain how grids are formed, how they are organized in microcircuits, and how they might use idiothetic (self motion) information to path integrate. The grid cell system therefore offers the opportunity to study a cognitively meaningful neural computation at a mechanistic level. Here we leverage recent technical advances, including virtual reality methods for rodents previously developed in our lab, to examine the intracellular, microcircuit, and integrative properties of gri cells in three aims: 1.) Current grid cell models can reproduce hexagonal lattice firing patterns but they predict different intracellular membrane potential time courses that reflect different underlying cellular or network mechanisms. To test these predictions, in Aim 1, we will take advantage of head-fixed navigation enabled by our virtual reality system to make intracellular recordings from grid cells during behavior. Statistical analysis will be performed on the membrane voltage time series to examine if characteristic features such as ramps and theta oscillations are present and if they correlate with the location of the firing fields. For example,we will examine if theta oscillation amplitude is larger in firing fields, and if theta frequency increases with mouse velocity, as predicted by theta interference models of grid cells. 2.) Grid cells are not identical, but have different scales and phase shifts that may reflect distinct functional modules. Consistent with this idea, converging evidence points to the existence of anatomically defined clusters of cells in MEC. To delineate the link between functional modules and anatomical clusters, in Aim 2 we will use cellular-resolution two-photon calcium imaging during virtual navigation to provide the first measurements of spatial organization, at the microcircuit scale, of identified grid cells in MEC. In particular, we will map the relationship between grid cell properties (spatial scale and phase) and cytochrome oxidase rich patches, and determine whether there are sharp breaks in spatial scale along the dorsoventral axis. 3.) Grid cells are thought to perform path integration, an idea that dominates the current thinking about the functional role of the MEC. In Aim 3 we will use virtual reality to control all sensory cues providing information about position in order to rigorously test the path integration hypothesis. Together, these aims should advance our understanding of the single-cell, microcircuit, and computational properties of grid cells.