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.

项目摘要/摘要 我们在南加州大学(MCP)的鼠标连接组项目的目标是绘制~800的远程连接 描绘了小鼠大脑的结构，以努力揭示其网络组织。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，致力于汇编 最高质量的连接性数据。我们采用了注入策略，产生了最有利的数据 对于网络分析，对于任何大脑区域(即A)，同时揭示其(1)输入(AB)；(2)输出 (AB)；(3)相互或重复的连接(AB)；以及(4)连接大脑的中间站 非直接连接的结构(ACB)。在第二阶段(2011-2016)，我们从 在整个大脑半球和丘脑进行注射。如建议的，在第三阶段(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。 (约1400条额外路径)(具体目标1)。综合起来，这些路径将被用来构建最 全面的中尺度连接体，绘制了整个小鼠大脑的所有点对点连接。 然而，汇编这些连接性数据集只是构建连接体的第一步。接下来的事情 挑战在于分析海量数据以提取有关网络组织的信息。基于图形 通过对600条人工标注的通路进行理论分析，我们组装了哺乳动物的全球网络 新大脑皮层(Zingg等人，Cell，2014)。尽管黄金标准、手工分析费时费力， 而且对于我们生成全脑连接地图和网络的最终目标来说，效率并不高。因此，在 第二阶段，我们设计和创建了一个创新的信息学工作流程，高效可靠地注册、 重新构建并注释大规模连接数据。此工作流将在第三阶段应用，以加速 图像处理、创建连接图、数据注释和分析。在第三阶段，我们还将启动 构建细胞类型特定神经网络的第一阶段(特定目标2)。我们基于连接的蜂窝类型 分类策略将用于识别内侧前额叶皮质的所有细胞类型，并获得 每种细胞类型使用2D和3D图像。新的狂犬病病毒追踪将被系统地揭示 这些不同细胞群的神经元输入。我们的所有数据都将作为开放资源提供 (www.MouseConnctome.org)(特定目标3)：(1)iConnectome查看器是唯一 允许用户在自己的明视场尼斯里查看多个标记有荧光的路径的图像 标准小鼠脑图谱的背景和相应水平；(2)iConnectome Map Viewer允许 访问连接地图，其中包含数百条重建的路径，这些路径汇编在神经解剖学的顶部 框；(3)iConnectome单元类型查看器，它将显示所有单元类型电路的图像；(4)单元类型 地图查看器将托管特定像元类型的连通性地图；(5)将显示在线Web连通性矩阵 矩阵中的连接；以及(6)我们的3D查看器将以3D形式提供所有连接的概览。