Examining simultaneous encoding of local and remote space across distinct hippocampal subnetworks

项目摘要/摘要 当前的经历、记忆和想象的未来都会影响行为。有证据表明， 海马体(HPC)可以代表过去的位置、现在的位置和未来可能的轨迹。高性能计算机， 但是，通常指的是一次只能表示一种类型的单个结构，但 HPC可沿其背腹轴划分为亚区。有证据表明存在不同的职能角色 背侧和腹侧HPC在空间导航中的作用，但最近的基因表达研究表明 背腹轴至少可分为三个亚区：背侧、中间和腹侧。与之形成鲜明对比的是 这些隔板、电生理特征沿着HPC纵轴逐渐演变，表明 功能的逐步演变。背侧HPC(DHPC)和中间HPC(IHPC)是否表现为 分子细分所暗示的不同网络或作为更大功能梯度的一部分是未知的。 众所周知，这两个亚区都代表空间，dHPC中的研究表明， 局域和非局域空间在时间上围绕场势的规则振荡形成图案。这 在IHPC中存在振荡但相移，因此局域和非局域的时间图样 表达可能与dHPC中的阵列不同。这意味着HPC可以同时 表示过去、现在和未来的位置，如果是这样的话，这两个子区域应该被视为不同的 都对空间进行编码的网络。通过实验和分析相结合 方法，这个项目检验了dHPC和IHPC被最好地理解为不同亚区的假设 不连贯地表示空间。 我们将通过在大鼠dHPC和IHPC中同时记录空间 导航任务和研究空间表征的结构和时间组织(目标1 作为使用网络活动模型(AIM)的跨两个子区域的相关活动的特征 2)。此计算模型可作为理解关联的性质的补充方法 HPC中的活动；它完全不知道神经元可能编码什么，也没有自由参数来 调整一下。通过将这两种实验方法与尖端分析技术相结合，提出的目标是 有可能发现HPC中以前未知的丰富表示，这将进一步提供 洞察未来的记忆和模拟如何与现在的体验相协调。这个 这些表征的同时存在可以用作将过去、现在、 和未来的经历跨越时间相互联系。

Project Summary/Abstract Current experiences, memories, and imagined futures all affect behavior. Evidence demonstrates that the hippocampus (HPC) can represent past locations, present position, and possible future trajectories. The HPC, however, is often referred to as a single structure capable of only one type of representation at a time, but the HPC can be divided into subregions along its dorsoventral axis. There is evidence for different functional roles of the dorsal and ventral HPC in spatial navigation, but recent gene expression studies suggest the dorsoventral axis can be divided into at least three subregions: dorsal, intermediate, and ventral. In contrast to these partitions, electrophysiology signatures evolve gradually along the HPC longitudinal axis, suggesting a gradual evolution of function. Whether the dorsal HPC (dHPC) and intermediate HPC (iHPC) behave as distinct networks as suggested by molecular subdivisions or as parts of a larger functional gradient is unknown. Both subregions are known to represent space, and studies in the dHPC have shown that representations of local and nonlocal space are temporally patterned around a regular oscillation in the field potential. This oscillation is present but phase-shifted in the iHPC, so the temporal patterning of local and nonlocal representations may differ from the patterning in the dHPC. This means that the HPC may simultaneously represent past, present, and future locations, and if so, the two subregions should be viewed as distinct networks that both contribute to encoding space. Through a combination of experimental and analytic methods, this project tests the hypothesis that dHPC and iHPC are best understood as distinct subregions that represent space noncoherently. We will test these hypotheses by recording simultaneously in the rat dHPC and iHPC during a spatial navigation task and studying the structure and temporal organization of spatial representations (Aim 1) as well as the characteristics of correlated activity across the two subregions using a model of network activity (Aim 2). This computational model serves as a complementary approach to understanding the nature of correlated activity in the HPC; it is completely agnostic to what neurons may encode and has no free parameters to adjust. By combining both experimental methods with cutting edge analytic techniques, the proposed aims have the potential to uncover previously unknown richness of representations in the HPC that will give further insight into how memories and simulations of the future are coordinated with present experiences. The simultaneous existence of these representations may serve as a neural substrate for relating past, present, and future experiences to one another across time.