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

描述(申请人提供)：这项提案将研究内侧嗅觉皮质-海马区网络的生物学特性，使其能够执行空间处理功能。这项研究将集中在网格细胞形成和theta相进动的生物学机制上。网格细胞是内侧嗅觉皮质中的空间敏感细胞，每当动物被定位在细胞的发射场，在环境中的六角形位置阵列中时，网格细胞就会被激发。内嗅觉皮质中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在整体空间功能中非常重要，例如编码动物的位置和规划未来的路径。Theta位相进动是一种发生在位置细胞中的现象(当动物处于环境的某个位置时，空间敏感细胞就会触发)。位置细胞相对于网络theta节律振荡改变了它们的放电阶段，这表明细胞群体组织它们的活动，以允许代表轨迹的压缩神经活动。这种表示对于记忆中轨迹的编码和未来轨迹的规划可能是有用的。这项研究将使用一个大规模的、生物受限的内侧内嗅觉皮质-海马网络模型来评估生物现实网络支持先前提出的网格细胞形成和theta阶段进动的各种模型的能力。从这项工作中获得的知识将使人们能够更广泛地了解癫痫和阿尔茨海默病等各种神经疾病可能对空间处理和记忆等认知功能产生不利影响的机制。此外，这项工作产生的计算模型将免费共享，并可用于搜索和量化各种疾病的潜在治疗目标。

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.