The Mouse Connectome Project Phase III: Assembling the global neural networks of the mouse brain

小鼠连接组项目第三阶段：组装小鼠大脑的全局神经网络

• 批准号: 10226677
• 负责人: Hong-Wei Dong
• 金额: $ 78.37万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-11-06 至 2022-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10226677
• 关键词: Mouse; Connectome; Project; Phase; III

PROJECT SUMMARY/ABSTRACT The objective of our Mouse Connectome Project at USC (MCP) is to chart the long-range connectivity of ~800 delineated structures of the mouse brain in an effort to reveal its network organization. In Phase I (2009-2010), we established an efficient data production, collection, and image processing workflow dedicated to compiling connectomics data of the highest quality. We adopted an injection strategy that produced data most conducive for network analysis by simultaneously revealing, for any brain region (i.e. A), its (1) inputs (AB); (2) outputs (AB); (3) reciprocal or recurrent connections (AB); and (4) intermediate stations, which bridge brain structures that are not directly connected (ACB). In Phase II (2011-2016), we traced ~2000 pathways from injections placed across the entire cerebral hemisphere and thalamus. As proposed, in Phase III (2017-2022) we will collect and analyze connections data for the hypothalamus, midbrain, pons, medulla, and cerebellum (~1400 additional pathways) (Specific Aim 1). Combined, these pathways will be used to construct the most comprehensive mesoscale connectome that charts all point-to-point connections of the entire mouse brain. Compiling these connectivity data sets however is only the first step in constructing the connectome. The ensuing challenge is to analyze the enormous data to extract information regarding network organization. Based on graph theoretical analysis of 600 manually annotated pathways, we assembled the global networks of the mammalian neocortex (Zingg et al., Cell, 2014). Although the gold standard, manual analysis was laborious, time consuming, and not efficient for our ultimate goal of generating brain-wide connectivity maps and networks. Therefore, in Phase II, we designed and created an innovative informatics workflow that efficiently and reliably registers, reconstructs, and annotates large-scale connections data. This workflow will be applied in Phase III to accelerate image processing, creation of connectivity maps, data annotation, and analysis. In Phase III, we will also initiate the first stage of constructing cell type specific neural networks (Specific Aim 2). Our connectivity-based cell type classification strategy will be used to identify all cell types of the medial prefrontal cortex and to gain a census of each cell type using 2D and 3D images. Novel rabies viral tracing will be employed to systematically reveal the neuronal inputs to these distinct cell populations. All of our data will be available as open resources (www.MouseConnctome.org) (Specific Aim 3): (1) the iConnectome viewer is the only visualization tool that allows users to view images of multiple fluorescently-labeled pathways within their own bright-field Nissl background and corresponding level of a standard mouse brain atlas; (2) the iConnectome Map Viewer allows access to connectivity maps, which feature hundreds of reconstructed pathways compiled atop a neuroanatomic frame; (3) the iConnectome Cell Type Viewer, which will feature images of all cell type circuits; (4) the Cell Type Map Viewer will host cell type specific connectivity maps; (5) the online Web Connectivity Matrix will present connections in a matrix; and (6) our 3D viewer will provide an overview of all connections in 3D.

项目总结/摘要 我们在南加州大学（MCP）的小鼠连接组项目的目标是绘制约800的远程连接图。 描绘了小鼠大脑的结构，试图揭示其网络组织。在第一阶段（2009-2010年）， 我们建立了一个高效的数据生产、收集和图像处理工作流程， 最高质量的连接组学数据。我们采用了一种注入策略， 对于网络分析，通过同时揭示任何脑区（即A）的（1）输入（A → B）;（2）输出 （A → B）;（3）相互或循环连接（A → B）;（4）中间站，连接大脑 不直接连接的结构（A B）。在第二阶段（2011-2016年），我们追踪了约2000种途径， 注射到整个大脑半球和丘脑。按照提议，第三阶段（2017-2022年） 我们将收集和分析下丘脑、中脑、脑桥、延髓和小脑的连接数据 （~1400个额外途径）（具体目标1）。结合起来，这些途径将用于构建最 全面的中尺度连接组，绘制了整个小鼠大脑的所有点对点连接。 然而，编译这些连接数据集只是构建连接体的第一步。随后的 挑战在于分析大量数据以提取关于网络组织的信息。基于图 通过对600个人工注释的通路进行理论分析，我们组装了哺乳动物的全球网络， 新皮层（Zingg等人，Cell，2014）。虽然黄金标准，人工分析是费力，耗时， 而对于我们最终的目标，即生成全脑连接图和网络来说，这并不有效。因此在 在第二阶段，我们设计并创建了一个创新的信息学工作流程， 重建和注释大型连接数据。这一工作流程将在第三阶段应用， 图像处理、连通图创建、数据注释和分析。在第三阶段，我们还将启动 构建细胞类型特异性神经网络的第一阶段（特异性目标2）。我们基于连通性的细胞类型 分类策略将用于识别内侧前额叶皮层的所有细胞类型，并获得 每个细胞类型使用2D和3D图像。新的狂犬病病毒追踪将系统地揭示 神经元输入到这些不同的细胞群。我们所有的数据都将作为开放资源提供 （www.MouseConnctome.org）（具体目标3）：（1）iConnectome查看器是唯一的可视化工具， 允许用户在自己的亮场Nissl内查看多个荧光标记路径的图像 标准小鼠脑图谱的背景和相应水平;（2）iConnectome Map Viewer允许 访问连接图，其中包含在神经解剖学基础上编译的数百条重建路径 框架;（3）iConnectome细胞类型查看器，将显示所有细胞类型回路的图像;（4）细胞类型 Map Viewer将托管特定于细胞类型的连接图;（5）在线Web连接矩阵将显示 矩阵中的连接;以及（6）我们的3D查看器将提供3D中所有连接的概述。