BRAIN CONNECTS: A Center for High-throughput Integrative Mouse Connectomics

项目摘要/摘要 拟议的项目将证明生成完整的突触水平脑图的可行性。 (连接体)通过开发一种可扩展到整个小鼠的连续截面电子显微镜管道 大脑。这项工作将成像10立方毫米，这本身就是一个史无前例的数据集，可能会超过数十个 以PB为单位。然而，老鼠的大脑要大50倍。实现这一雄心勃勃的目标将需要在以下方面取得进展 全脑染色、成像、图像处理、分析和传播工具。我们将进行扩展和测试 这些工具通过产生海马体结构的连接体，一个关键的大脑记忆区域和 空间导航。具体地说，我们将通过对整个大脑的微型CT扫描来定义我们感兴趣的体积。 然后我们将它切成半薄的连续切片，并用多光束扫描电子显微镜成像 和离子束研磨。这种技术成像一层薄薄的组织，然后将其移除以揭示下一层 直到每个切片都完全成像，将以前的超薄切片方法造成的扭曲降至最低。 成像数据将通过我们最先进的管道的改进版本进行处理。售后质量 监控和图像压缩，我们的自动化系统将从成像切片中组装完整的体积 然后标记组织元素：神经元、神经胶质细胞、血管、髓鞘、细胞体和突触。这 然后重建将被校对并注册到艾伦研究所的脑图集，使我们能够讲述我们的 数据转换为其他类型的数据。我们的分析将按区域和层识别细胞类型，并揭示详细的 海马体结构回路的连通性。使用定制软件，我们将整合这些结构结果 用基于光学显微镜和单细胞基因表达的其他方法来研究细胞类型，使我们能够 将我们的结果与大量关于海马结构结构和功能的文献联系起来。为了促进 不同的视角，我们将让来自不具代表性背景的本科生参与校对 以及我们工作的科学发现阶段，为他们提供指导和研究经验。 我们将通过扩大规模，将这些数据转化为科学界和公众的持久资源 通过在线共享工具免费访问，允许任何感兴趣的各方提交、校对或以其他方式分析 这本书中的电池和电路。为了说明如何将此资源与其他发现相结合，我们将 根据细胞的形态和连通性定义细胞类型，描述它们之间的关系 任务和基于转录的分类，并将这些信息与以前的工作结合起来。 最后，我们将在我们的数据中定义本地和远程微电路主题，并使用它来识别电路原理 以及记忆和空间认知的机制，通过测试和改进海马体模型 队形。在整个项目中，我们将监控关键性能参数，例如 单个显微镜，以评估扩大到整个小鼠脑连接体的可行性和成本。

Project Summary/Abstract The proposed project will demonstrate the feasibility of generating a complete synapse-level brain map (connectome) by developing a serial-section electron microscopy pipeline that could scale to a whole mouse brain. This work will image 10 cubic millimeters, itself an unprecedentedly large dataset that may exceed tens of petabytes. Yet the mouse brain is 50 times larger. Reaching this ambitious goal will require advances in whole-brain staining, imaging, image-processing, analysis, and dissemination tools. We will scale and test these tools by producing a connectome of the hippocampal formation, a critical brain region for memory and spatial navigation. Specifically, we will define our volume of interest via microCT scanning of a whole brain. Then we will cut it into semithin serial sections and image them with multibeam scanning electron microscopy and ion beam milling. This technique images a thin layer of tissue and then removes it to reveal the next layer until each section is fully imaged, minimizing distortions caused by previous ultra-thin sectioning approaches. The imaging data will be processed by an improved version of our state-of-the-art pipeline. After quality monitoring and image compression, our automated system will assemble the full volume from imaged slices and then label tissue elements: neurons, glia, blood vessels, myelin, cell bodies, and synapses. This reconstruction will then be proofread and registered to the Allen Institute brain atlas, allowing us to relate our data to other types of data. Our analysis will identify cell types by region and layer, and reveal the detailed connectivity of hippocampal formation circuits. Using custom software, we will integrate these structural results on cell types with other approaches based on light microscopy and single-cell gene expression, allowing us to relate our results to the extensive literature on hippocampal formation structure and function. To promote diverse perspectives, we will involve undergraduates from underrepresented backgrounds in the proofreading and scientific discovery phases of our work, offering them mentoring as well as research experience. We will turn these data into a lasting resource for the scientific community and the public by scaling up free access via online sharing tools to allow any interested party to render, proofread, or otherwise analyze the cells and circuits in this volume. To illustrate how this resource can be combined with other discoveries, we will define cell types based on their morphology and connectivity, characterize the relationship between these assignments and transcriptomic-based classifications, and integrate this information with previous work. Finally, we will define local and long-range microcircuit motifs in our data and use it to identify circuit principles and mechanisms of memory and spatial cognition, by testing and improving models of the hippocampal formation. Throughout the project, we will monitor key performance parameters, such as imaging throughput of a single microscope, to evaluate the feasibility and cost of scaling up to a whole mouse brain connectome.