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A robust, low-cost platform for EM connectomics

强大、低成本的 EM 连接组学平台

基本信息

批准号：
10273540
负责人：
Daniel Joseph Bumbarger
金额：
$ 281.14万
依托单位：
ALLEN INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-15 至 2024-07-14
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10273540
关键词：
3-Dimensional Adoption Alzheimer&apos s Disease Animal Model Archives Autopsy Biological Assay Brain Brain region Cells Collaborations Collection Communities Complex Computer software Custom Data Set Dementia Development Diagnostic Disease Electron Microscopy Electrons Epilepsy Equipment Film Functional disorder Goals Gold Human Image Industrialization Institutes Intervention Invertebrates Mammals Manuals Medical Mental Depression Mental disorders Methods Microscope Microscopy Monitor Mus Neurological Models Optics Organism Pathologic Patients Property Public Health Publishing Research Personnel Retina Risk Reduction Robot Scanning Scanning Electron Microscopy Schizophrenia Series Side Silicon Stains Stroke Structure System Techniques Technology Testing Thick Thinness Tissues Translations Transmission Electron Microscopy Work autism spectrum disorder base clinical application comparative cost cost effective cost efficient data quality design experimental study flexibility human tissue imaging modality improved industry partner instrumentation interest large datasets lens light microscopy machine vision nervous system disorder neural circuit next generation novel novel strategies open source programs prototype reconstruction routine imaging sensor silicon nitride software systems success tool transmission process

项目摘要

Project Summary/Abstract Over the past decade, serial-section electron microscopy has come into its own as a method to study the connectivity of neural circuits, from local circuits in mammals to entire invertebrate brains. Recently, the emphasis in the field has been to create increasingly large data sets, while comparatively little effort has been spent on making the tools of EM connectomics available to a large number of circuit neuroscientists. Obstacles exist at multiple levels. Manual approaches to serial sectioning are prohibitively difficult, while automated approaches require complex, expensive equipment that is difficult to deploy. High throughput scanning EM is limited to multi- beam approaches that are extremely expensive. Transmission EM is far less expensive, but automated approaches to sectioning remain challenging and require expensive substrates that are hard to manufacture and difficult to use. We propose to develop a new approach, already prototyped by our group and our industry partner, to establish a robust platform optimized to achieve the widest possible adoption. The system will center on an open source serial sectioning robot implementing a novel collection approach. The goal is to create a system that can be used at a variety of scales, from the current state of the art (1 mm3 or greater), to small volumes that can be sectioned and imaged routinely. Up to now, each published EM volume for connectomics has required a multi-year effort. Instead, our goal is to use volume reconstruction as an assay, rather than an end unto itself, in the context of other experiments. In the final year, we will create data sets that test the flexibility and robustness of the approach by creating EM volumes ranging from 50µm on a side to very large volumes encompassing >1 mm3.

项目总结/摘要在过去的十年里，连续切片电子显微镜已经成为一种研究细胞凋亡的方法。从哺乳动物的局部神经回路到整个无脊椎动物的大脑。最近，强调在该领域，一直在创建越来越大的数据集，而相对较少的努力已经花在使EM连接组学的工具可用于大量的电路神经科学家。障碍存在于多层次的手动方法进行连续切片非常困难，而自动方法需要复杂、昂贵的设备，难以部署。高通量扫描EM仅限于多个非常昂贵的光束方法。传输EM远没有那么昂贵，但自动化切片的方法仍然具有挑战性，并且需要昂贵的基底，其难以制造，难以使用。我们建议开发一种新的方法，我们的团队和我们的行业合作伙伴已经建立了原型，一个经过优化的强大平台，以实现尽可能广泛的采用。该系统将集中在一个开放源代码一种实现新型收集方法的连续切片机器人。我们的目标是创建一个系统，在各种规模下，从当前的最新技术水平（1 mm 3或更大）到可以切片的小体积并常规成像。到目前为止，每一个已出版的连接组学EM卷都需要多年的努力。相反，我们的目标是使用体积重建作为一种分析，而不是结束本身，其他实验。在最后一年，我们将创建数据集，以测试该方法的灵活性和鲁棒性通过创建从一侧50µm到包含>1 mm 3的非常大的体积的EM体积。