C4: Neuroanatomy

项目摘要/摘要：核心4，神经解剖学 这项U19合作的总体目标是阐明工作记忆和决策是如何 由相互作用的神经元和大脑区域支持。为了实现这一目标，我们的研究项目将需要 尖端的神经解剖学工具，神经解剖学核心将提供。正如它在第一届U19中所做的那样 在资助期间，该核心将继续支持光片显微镜的协议、软件和标准， 与病毒示踪剂一起用于绘制大脑区域之间的远程连接。我们还将增加两个 最先进的成像技术：对整个小鼠大脑进行光片显微镜检查， 全脑神经记录点成像和即刻早期基因表达，以及连续切片 透射电子显微镜（TEM），以提供快速自动化的超微结构分析。 第一个目标是支持全脑范围内的神经记录点，激活模式， 连通性。我们将支持我们开发的自动图像处理和大脑配准管道 并将其扩展到新的研究目标。我们的管道将确定记录地点登记到一个标准化的地图集， 以及大脑区域在学习过程中是如何被激活的。我们将提供我们成像的转录谱， 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次图像分析管道处理，以搜索 序列连接性是序列神经活动的基础。从长远来看，千万亿次连接组学可能是 应用于U19的其他项目，以研究各种大脑区域的认知回路机制。我们 TEM系统具有世界上同类产品中最高的原始吞吐量，但需要进一步的工作， 实现其全部潜力。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， 用我们新的X射线辅助技术，在立方毫米的组织中进行对比。我们还将优化我们的 自动带收集超薄切片机系统，将连续切片从4，000个切片扩大到 数以万计的部分。第三个目标将是自动化高通量，并行TEM成像。当 完成后，我们的高通量技术将在几周内实现对20毫米数据集的成像 而不是现在的6-12个月。新功能将延长工作周期，从目前的8小时 人工监测自动24小时，使每个TEM在24小时内产生超过20 TB的数据， 小时能够处理这种规模的数据吞吐量的软件将被构建，以实现我们的 成像流水线。更广泛地说，我们希望我们的开创性方法，自动化光片和电子 显微镜，当与更广泛的社区分享时，将提高效率，严谨性和可重复性， 神经科学领域的解剖学研究，并使千万亿次连接组学民主化。

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.