Electroanatomy of hippocampal networks: Topographic distribution of co-active cells and its plasticity

海马网络的电解剖学：共活性细胞的拓扑分布及其可塑性

• 批准号: 351649465
• 负责人: Privatdozent Dr. Martin Both
• 金额: --
• 依托单位: Abteilung Neuro- und Sinnesphysiologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/351649465?language=en
• 关键词: Electroanatomy; hippocampal; networks; Topographic; distribution

Local neuronal networks express highly coordinated spatiotemporal activity patterns. The participating neurons form functional ensembles which are believed to constitute elementary representations of percepts, actions, or memories. In line with their different cognitive-behavioral functions, characteristic properties of such ensembles (number of neurons, sparsity of firing, overlap between different representations, spatial arrangement) are likely to differ between different networks. However, there is very little quantitative, comparative data on these parameters. We want to provide such a comparison in a prominent model system for spatial memory formation, the hippocampal-entorhinal network. This structure contains several interconnected local networks with different connectivity and behavioral significance. Recent work has revealed specific operations performed by the sub-networks, e.g. the decorrelation of incoming information in the dentate gyrus (pattern separation) and the attractor dynamics of CA3 (pattern completion). The basic circuitry, cell types, short- and long-range connections, and patterns of collective network behavior have been well studied. Little is known, however, about the size, overlap and spatial organization of ensembles in each hippocampal-entorhinal sub-network. The heterogeneity of local, interconnected networks, the laminar organization of the brain area, and the good knowledge of cellular and network properties make this system ideal for a comparative study of the ensembles. Using a high-resolution electrode microarray as a unique new tool, we will simultaneously record from large numbers (hundreds to thousands) of cells. This will allow studying the geometry of ensembles throughout the hippocampal-entorhinal system, and to compare the location, extent, separation and topology of ensembles. Propagating activity patterns can be followed through different local networks, revealing whether topological orders are maintained or systematically changed. Complementary approaches at the cellular level will unravel distinct cell-to-network coupling mechanisms, and experiments at the behavioral level will validate findings from in vitro recordings in native networks. Specifically, we will (1) map the spatial organization of ensembles within each network; (2) search for topologically organized input-output relationships between different local networks; (3) correlate the activity of single cells with network-level activity patterns; (4) assess the effect of neuromodulators on the respective patterns; (5) test the findings from (i)-(iv) in recordings from behaving mice in vivo.Together, we aim at a comprehensive network-level comparison of different hippocampal-entorhinal networks, resulting in a functional 'electroanatomy' of this important brain region.

局部神经元网络表达高度协调的时空活动模式。参与的神经元形成功能性集合，这些功能性集合被认为构成感知、动作或记忆的基本表征。根据它们不同的认知行为功能，这些集合的特征属性（神经元的数量，放电的稀疏性，不同表征之间的重叠，空间排列）可能在不同的网络之间存在差异。然而，关于这些参数的定量比较数据很少。我们想在一个著名的空间记忆形成模型系统中提供这样的比较，即大脑-内嗅网络。这种结构包含几个相互连接的局部网络，具有不同的连接性和行为意义。最近的工作揭示了子网络执行的特定操作，例如齿状回（模式分离）和CA 3（模式完成）的吸引子动力学中传入信息的去相关。基本的电路、细胞类型、短距离和长距离连接以及集体网络行为的模式已经得到了很好的研究。然而，鲜为人知的是，在每个campal-entorhinal子网络的大小，重叠和空间组织的合奏。局部互连网络的异质性，大脑区域的层状组织，以及对细胞和网络特性的良好了解，使该系统成为比较研究合奏的理想选择。使用高分辨率电极微阵列作为一种独特的新工具，我们将同时记录大量（数百到数千）细胞。这将使研究的几何形状的合奏整个campal-entorhinal系统，并比较的位置，范围，分离和拓扑结构的合奏。通过不同的局部网络，可以追踪不同的活动模式，揭示拓扑秩序是否得到维持或系统地改变。在细胞水平上的互补方法将解开不同的细胞与网络耦合机制，在行为水平上的实验将验证在原生网络中的体外记录的结果。具体来说，我们将（1）映射每个网络内的集合空间组织;（2）搜索不同局部网络之间拓扑组织的输入输出关系;（3）将单细胞的活动与网络水平的活动模式相关联;（4）评估神经调质对相应模式的影响;（5）研究神经元的活动。（5）在体内行为小鼠的记录中测试（i）-（iv）的发现。我们的目标是对不同的海马-内嗅网络进行全面的网络水平比较，从而对这个重要的大脑区域进行功能“电解剖学”。