EM Core

电磁核心

• 批准号: 10241481
• 负责人: Jeff W Lichtman
• 金额: $ 57.38万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-25 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10241481
• 关键词: 3-Dimensional; Atlases; Axon; Behavior; Brain; Cell model; Cells; Communities; Comprehension; Computer Assisted; Computer software; Consumption; Custom; Data; Data Set; Decision Making; Development; Electron Microscope; Electron Microscopy; Electron Microscopy Facility; Feedback; Fishes; Fluorescence; Functional Imaging; Generations; Goals; Grant; High Performance Computing; Human; Human Resources; Illusions; Image; Infrastructure; Lateral; Learning; Manuals; Methods; Microtomy; Modeling; Nervous System Physiology; Nervous system structure; Neurons; Neurosciences; Physiological; Procedures; Process; Production; Research; Research Personnel; Resolution; Roentgen Rays; Sampling; Speed; Standardization; Structure; Synapses; Technology; Testing; Thick; Time; Training; X ray microscopy; Zebrafish; automated segmentation; base; cell type; cluster computing; design; image registration; innovation; insight; interest; live cell imaging; machine vision; microCT; model building; nanometer; nanometer resolution; nanoscale; neural circuit; programs; relating to nervous system; theories; tool; user-friendly

EM Core - Abstract While the neural circuits that underlie behavior are of interest to all of the investigators on this grant (and a substantial part of the entire neuroscience community), there have been very few technical approaches that actually provide this kind of information across all levels at which circuits function, including the level of synaptic connections. This electron microscopy core is explicitly designed to provide the “wiring diagrams” of neural circuits in an efficient way. Much of our effort over the past 5 years has been to transform serial electron microscopy of large volumes (such as the fish nervous system) from a heroic to a more mundane enterprise. This transformation required innovations in hardware and software to abbreviate all the time-consuming steps in the connectomic pipeline. In particular we: 1) automated ultra-thin sectioning (using a tape-based approach), 2) automated image acquisition (using a custom multibeam serial electron microscope), 3) automated stitching and registration of the image data on high performance computing clusters, 4) automated segmentation of neurons and synapses on a GPU cluster, and 5) semi-automated proofreading and rendering of the neural circuits with custom software. Because of these developments, we can routinely collect tens of thousands of sections losslessly at 30 nm thickness and acquire images of them at lateral resolutions of 4 x 4 nanometers. This voxel size (480 nm3​ ​) provides enough detail for human or machine vision methods to trace out the finest aspects of neural connectivity. Obtaining this information about neural circuits is relevant inasmuch as it provides insight into circuit function. Hence the tremendous benefit of doing electron microscopy on functionally imaged samples - a main goal of this proposal. Acquiring these circuits is also relevant if neuronal connectivity can be associated with cells of particular types, hence the significant benefit of doing analysis of cell types that have been defined in the fish atlas associated with this proposal. Finally, these circuit diagrams provide ground truth for testing and refining computational theories of brain function, another important prong of this proposal. Because of the speed of the EM Core approaches, we have the ability to acquire datasets of many different fish that each have been used in particular experimental or live-cell imaging contexts. The overarching goal being to provide synaptic level structural information for all research questions where such detailed data can enhance our comprehension of the way fish behavior is instantiated in its nervous system.

EM核心-摘要 虽然行为背后的神经回路对该基金的所有研究人员都很感兴趣（而且很大一部分 在整个神经科学界），很少有技术方法，实际上提供这种 信息跨越电路功能的所有水平，包括突触连接的水平。该电子 显微镜核心被明确设计为以有效的方式提供神经回路的“接线图”。我们的大部分 在过去的5年里，我们一直在努力改变大体积的连续电子显微镜（如鱼类神经）。 系统）从一个英雄到一个更平凡的企业。这种转变需要硬件和软件的创新 以简化连接管道中所有耗时的步骤。特别是我们：1）自动化超薄 切片（使用基于带的方法），2）自动图像采集（使用定制的多束连续电子 显微镜），3）在高性能计算集群上自动拼接和配准图像数据，4） 在GPU集群上自动分割神经元和突触，以及5）半自动校对和渲染 用定制软件来控制神经回路由于这些发展，我们可以定期收集成千上万的 切片在30 nm厚度下进行激光扫描，并以4 × 4纳米的横向分辨率获取它们的图像。该体素 尺寸（480 nm 3 ）为人类或机器视觉方法提供了足够的细节，以跟踪神经网络的最佳方面。 连通性。获得这些关于神经回路的信息是相关的，因为它提供了对回路的洞察力。 功能因此，在功能成像样品上进行电子显微镜检查的巨大好处-这是本研究的一个主要目标。 提议 如果神经元连接可以与特定类型的细胞相关联，则获得这些回路也是相关的，因此， 对与本提案相关的鱼类图谱中定义的细胞类型进行分析的显著益处。 最后，这些电路图为测试和完善大脑功能的计算理论提供了基础事实， 这一提议的另一个重要方面。由于EM核心接近的速度，我们有能力获得 许多不同的鱼的数据集，每一个都被用于特定的实验或活细胞成像环境。的 总体目标是为所有研究问题提供突触水平的结构信息， 可以增强我们对鱼类行为在其神经系统中体现的方式的理解。