Grid Cells and Precession in a Biophysical Entorhinal-Hippocampal Network Model

描述（由申请人提供）：本提案将研究内侧内嗅皮层-海马网络的生物学特性，使其能够执行空间处理功能。本研究将重点研究网格细胞形成和θ相进动的生物学机制。网格细胞是位于内嗅皮层的空间敏感细胞，当动物处于细胞的放电场中时，它们就会在环境中以六边形的位置排列。内嗅皮层的网格细胞和海马体中的位置细胞之间的相互作用被认为对整体空间功能很重要，例如对动物的位置进行编码和规划未来的路径。θ波相位进动是一种发生在位置细胞（当动物处于环境的特定位置时，空间敏感细胞就会放电）中的现象。位置细胞的放电阶段相对于网络θ节奏振荡的变化表明，细胞群组织它们的活动，以允许压缩的神经活动代表一个轨迹。这种表示可以用于记忆轨迹的编码和未来轨迹的规划。本研究将使用一个大规模的、生物受限的内鼻皮层-海马网络模型来评估一个生物现实网络的能力，以支持之前提出的各种网格细胞形成和θ波相进动模型。从这项工作中获得的知识将使我们更广泛地了解各种神经系统疾病（如癫痫和阿尔茨海默病）对认知功能（如空间处理和记忆）产生不利影响的机制。此外，由这项工作产生的计算模型将被自由共享，并可用于搜索和量化各种疾病的潜在治疗靶点。

DESCRIPTION (provided by applicant): This proposal will study the biological properties of the medial entorhinal cortical-hippocampal network that enable it to perform spatial processing functions. This research will focus on biological mechanisms of grid cell formation and theta phase precession. Grid cells are spatially sensitive cells in medial entorhinal cortex that fire whenever an animal is positioned in the firing fields of the cell, in a hexagonal array of position in the environment. Interactions between grid cells in entorhinal cortex and place cells in the hippocampus are thought to be important in overall spatial functions, such as coding the position of the animal and planning future paths. Theta phase precession is a phenomenon that occurs in place cells (spatially sensitive cells that fire whenever an animal is in a certain locaton of an environment). Place cells shift their phase of firing relative to network theta rhythm oscillations in a manner suggesting that populations of cells organize their activity to allow for compressed neural activity representing a trajectory. This representation could be useful for encoding of trajectories in memory and planning of future trajectories. This research will use a large scale, biologically constrained model of the medial entorhinal cortical- hippocampal network to assess the ability of a biologically realistic network to support the various models of grid cell formation and theta phase precession that have been previously proposed. The knowledge gained from this work will allow a broader understanding of the mechanisms by which various neurological disorders such as epilepsy and Alzheimer's disease can adversely affect cognitive functions such as spatial processing and memory. Further, the computational model produced by this work will be freely shared and can be used to search for and quantify potential therapeutic targets for various disorders.