C4: Neuroanatomy

C4：神经解剖学

• 批准号: 10705971
• 负责人: Samuel Sheng-Hung Wang
• 金额: $ 50.22万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-08 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10705971
• 关键词: Anatomy; Area; Atlases; Brain; Brain region; Cognition; Collaborations; Communities; Computer software; Data; Data Science; Data Set; Decision Making; Democracy; Electron Microscopy; Funding; Gene Expression; Gene Expression Profiling; Geometry; Goals; Histology; Hour; Human; Image; Image Analysis; Imaging technology; Immediate-Early Genes; Laboratories; Learning; Light; Maps; Methods; Microscopy; Monitor; Mus; Neuroanatomy; Neurons; Neurosciences; Optics; Pattern; Preparation; Process; Protocols documentation; Quality Control; Reproducibility; Research; Research Project Grants; Roentgen Rays; Sampling; Short-Term Memory; Site; Stains; Standardization; System; Techniques; Thick; Time; Tissue imaging; Tissues; Tracer; Transmission Electron Microscopy; Viral; Work; analysis pipeline; cell type; data exchange; high throughput technology; image processing; improved; in situ sequencing; in vivo imaging; microscopic imaging; millimeter; neural; neural circuit; neuroimaging; neuromechanism; programs; reconstruction; relational database; scale up; tool; transcriptomics

Project Summary/Abstract: Core 4, Neuroanatomy The overall goal of this U19 collaboration is to elucidate how working memory and decision-making are supported by interacting neurons and brain regions. To achieve this goal, our research projects will need cutting-edge neuroanatomy tools, which the Neuroanatomy Core will provide. As it has done in the first U19 funding period, this core will continue to support protocols, software, and standards for light-sheet microscopy, used with viral tracers to map long-range connectivity between brain regions. We will also add two state-of-the-art imaging technologies: light-sheet microscopy of cleared whole mouse brains to enable brainwide imaging of neural recording sites and immediate-early gene expression, and serial-section transmission electron microscopy (TEM) to provide rapid automated ultrastructural analysis. The first aim will be to support brainwide imaging of neural recording sites, activation patterns, and connectivity. We will support the automated image processing and brain-registration pipeline that we developed and extend it to new research aims. Our pipeline will identify recording sites registered to a standardized atlas, and how brain regions are activated throughout learning. We will provide transcriptional profiling of our imaged tissue for post-hoc identification of cell types in our imaging datasets. The second aim will be to optimize electron-microscopy sample preparation and serial sectioning. Datasets from the TEM system will be processed by our petascale image-analysis pipeline to search for sequential connectivity underlying sequential neural activity. In the long term, petascale connectomics may be applied to other projects in the U19 to investigate circuit mechanisms of cognition in various brain areas. Our TEM system has the highest raw throughput capacity of its kind in the world, but further work is needed to realize its full potential. This core will optimize sample preparation and serial sectioning for TEM, and complete software required to fully automate TEM imaging. We will optimize EM staining protocols for uniform, high contrast in cubic millimeters of tissue, using our new X-ray-assisted technique. We will also optimize our automated tape-collecting ultramicrotome system, to scale up serial sectioning from 4,000 ultrathin sections to tens of thousands of sections. The third aim will be to automate high-throughput, parallel TEM imaging. When complete, our high-throughput technology will enable imaging of cubic-millimeter datasets in a few weeks instead of the current 6-12 months. New functionalities will extend the duty cycle from the current eight hours with human monitoring to 24 hours automatically, enabling each TEM to produce over 20 TB of data in 24 hours. Software that can handle data throughput at this scale will be built to realize the full potential of our imaging pipeline. More broadly, we expect that our pioneering methods for automating light-sheet and electron microscopy, when shared with the broader community, will improve efficiency, rigor, and reproducibility in anatomical research across the field of neuroscience and democratize access to petascale connectomics.

项目摘要/摘要：核心 4，神经解剖学 U19 合作的总体目标是阐明工作记忆和决策是如何发挥作用的 由相互作用的神经元和大脑区域支持。为了实现这一目标，我们的研究项目需要 神经解剖学核心将提供尖端的神经解剖学工具。正如第一届U19比赛中所做的那样 资助期间，该核心将继续支持光片显微镜的协议、软件和标准， 与病毒示踪剂一起使用来绘制大脑区域之间的远程连接。我们还将添加两个 最先进的成像技术：对透明的整个小鼠大脑进行光片显微镜检查，以实现 神经记录位点和早期基因表达的全脑成像，以及连续切片 透射电子显微镜 (TEM) 可提供快速自动化超微结构分析。 第一个目标是支持神经记录位点、激活模式和神经记录位点的全脑成像。 连接性。我们将支持我们开发的自动图像处理和大脑注册管道 并将其扩展到新的研究目标。我们的管道将识别注册到标准化地图集的记录站点， 以及在学习过程中大脑区域如何被激活。我们将提供我们的成像的转录分析 用于事后识别我们的成像数据集中的细胞类型的组织。 第二个目标是优化电子显微镜样品制备和连续切片。 来自 TEM 系统的数据集将由我们的千万亿级图像分析管道进行处理，以搜索 顺序连接是顺序神经活动的基础。从长远来看，千万亿级连接组学可能是 应用于U19的其他项目，以研究不同大脑区域的认知回路机制。我们的 TEM 系统具有世界上同类产品中最高的原始吞吐能力，但还需要进一步的工作 充分发挥其潜力。该核心将优化 TEM 的样品制备和连续切片，并完成 完全自动化 TEM 成像所需的软件。我们将优化 EM 染色方案，以实现均匀、高 使用我们新的 X 射线辅助技术以立方毫米的组织进行对比。我们也会优化我们的 自动磁带收集超薄切片机系统，可将连续切片从 4,000 个超薄切片扩大到 数以万计的部分。第三个目标是实现高通量并行 TEM 成像的自动化。什么时候 完成后，我们的高通量技术将在几周内实现立方毫米数据集的成像 而不是现在的 6-12 个月。新功能将把工作周期从目前的八小时延长 24小时自动人工监控，使每个TEM在24小时内产生超过20TB的数据 小时。将构建能够处理如此规模的数据吞吐量的软件，以充分发挥我们的潜力 成像管道。更广泛地说，我们期望我们用于自动化光片和电子的开创性方法 当与更广泛的社区共享时，显微镜将提高实验的效率、严谨性和可重复性 跨神经科学领域的解剖研究，并使千万亿级连接组学的普及化。