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.

项目概要/摘要 我们南加州大学 (MCP) 的鼠标连接组项目的目标是绘制 ~800 个鼠标的远程连接图 描绘小鼠大脑的结构，以揭示其网络组织。第一阶段（2009-2010）， 我们建立了高效的数据生产、采集和图像处理工作流程，致力于编译 最高质量的连接组学数据。我们采用了一种产生最有利数据的注入策略 通过同时揭示任何大脑区域（即 A）的网络分析，其 (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CB）。在第二阶段（2011-2016），我们追踪了大约 2000 条路径 注射遍及整个大脑半球和丘脑。根据提议，第三阶段（2017-2022） 我们将收集并分析下丘脑、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，这些途径将被用来构建最 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组的第一步。接下来的 挑战是分析大量数据以提取有关网络组织的信息。基于图表 通过对 600 条手动注释路径的理论分析，我们组装了哺乳动物的全球网络 新皮质（Zingg 等人，Cell，2014）。尽管黄金标准，手动分析是费力、耗时的， 对于我们生成全脑连接图和网络的最终目标来说效率不高。因此，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，可以高效可靠地注册、 重建并注释大规模连接数据。该工作流程将应用于第三阶段，以加速 图像处理、连接图创建、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（具体目标 2）。我们基于连接的细胞类型 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 使用 2D 和 3D 图像分析每种细胞类型。新型狂犬病病毒追踪将用于系统地揭示狂犬病病毒 这些不同细胞群的神经元输入。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 允许用户在自己的明场尼氏光路内查看多个荧光标记路径的图像 标准小鼠大脑图谱的背景和相应水平； (2) iConnectome 地图查看器允许 访问连接图，其中包含数百条在神经解剖学上编译的重建路径 框架; (3) iConnectome Cell Type Viewer，它将显示所有细胞类型电路的图像； (4) 细胞类型 地图查看器将托管特定于细胞类型的连接图； (5) 在线网络连接矩阵将呈现 矩阵中的连接； (6) 我们的 3D 查看器将提供所有连接的 3D 概览。