Novel EM technologies for imaging neural network anatomy

用于神经网络解剖成像的新型电磁技术

• 批准号: 8618501
• 负责人: Wei-Chung Allen Lee
• 金额: $ 26.19万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8618501
• 关键词: Address; Alzheimer' s Disease; Anatomy; Autistic Disorder; Automation; Behavior; Biological Neural Networks; Brain; Cell physiology; Cellular biology; Classification; Collection; Complex; Cortical Column; Data; Data Set; Data Storage and Retrieval; Development; Electron Beam; Electron Microscope; Electron Microscopy; Electrons; Engineering; Generations; Goals; Human; Image; Imaging technology; Individual; Industry; Laboratories; Manuals; Maps; Methodology; Methods; Microtomy; Morphology; Neurodegenerative Disorders; Neurons; Neurosciences; Noise; Perception; Positioning Attribute; Process; Resolution; Sampling; Scanning Electron Microscopy; Schizophrenia; Scientist; Semiconductors; Signal Transduction; Speed; Staging; Structure; Synapses; Synaptic Vesicles; System; Techniques; Technology; Transcend; Translating; Transmission Electron Microscopy; base; brain tissue; cell type; data acquisition; density; imaging detector; imaging modality; information processing; instrumentation; interest; nano; nanometer; new technology; novel; prevent; public health relevance; reconstruction; relating to nervous system; sample collection; scale up; tool; transmission process; treatment strategy

Project Summary/Abstract Our brains contain billions of neurons, each with thousands of synapses. Together, they form a functional neural network with trillions of connections. Its scale and complexity is daunting, but from this complexity emerges perception and behavior. How do we understand the organization of such an immense and complex network? A key path forward is investigating the relationship between structure and function in neuronal circuits. The function of a neuron is fundamentally dependent on how it is connected. Therefore, understanding the relationship between circuit structure - connectivity - and cellular function will help us understand how neurons and networks process information. Unfortunately, detailed connectivity mapping remains difficult. One critical barrier is data throughput. Recently, high-throughput transmission electron microscopy (TEM) has increased the speed of imaging, but continues to rely on humans for laborious manual sample collection and handling. Current methods of automated sectioning can collect thousands of electron microscopy (EM) samples on a tape substrate, but are incompatible with fast TEM imaging because the tape prevents transmission of an electron beam. Serial sections collected in this manner are currently imaged using scanning EM, which is typically slower. This proposal aims to develop novel technologies that synergistically bridge automated sample collection and high-speed TEM imaging to transcend the throughput barrier. We will generate a novel tape substrate for sample collection that is compatible with TEM imaging and use it to collect thousands of serial thin sections. Additionally, we will engineer and build a sample stage for continuous TEM imaging of tape-collected samples. These methods would allow high-quality EM imaging of local mammalian cortical circuits to be completed in ~1 year compared to more than 100 years with conventional approaches. We expect that the routine generation of larger, high-quality datasets using these novel techniques will also accelerate advances in their analyses. We will immediately use this approach to increase our understanding of the fundamental principles underlying cortical processing and organization. Furthermore, with higher- throughput EM imaging, we will finally be poised to compare diseased and healthy brains to assess how circuit connectivity is altered, thereby directing intelligent treatment strategies.

项目摘要/摘要 我们的大脑包含数十亿个神经元，每个神经元都有数千个突触。在一起，它们形成了一个功能 拥有数万亿连接的神经网络。它的规模和复杂性令人望而生畏，但从这种复杂性来看 浮现出感知和行为。我们如何理解一个如此庞大而复杂的组织 网络？一条前进的关键路径是研究神经元结构和功能之间的关系 电路。神经元的功能从根本上取决于它是如何连接的。因此，理解 电路结构-连通性-和细胞功能之间的关系将帮助我们理解 神经元和网络处理信息。不幸的是，详细的连接映射仍然很困难。一 关键障碍是数据吞吐量。最近，高通量透射电子显微镜(TEM)已经 提高了成像速度，但仍然依赖人类进行费力的手动样本采集和 正在处理。目前的自动切片方法可以收集数千个电子显微镜(EM) 样品在胶带衬底上，但与快速透射电子显微镜成像不兼容，因为胶带防止 电子束的传输。以这种方式收集的连续切片目前使用扫描进行成像 EM，通常较慢。这项提议旨在开发新的技术，协同架起桥梁 自动样品采集和高速透射电子显微镜成像，以超越吞吐量障碍。我们会 制作一种与透射电子显微镜成像兼容的用于样品采集的新型带状衬底，并使用它来采集 数以千计的连续薄片。此外，我们还将为连续瞬变电磁设计和建造一个样台 对胶带收集的样本进行成像。这些方法将允许对当地哺乳动物进行高质量的电磁成像 皮质环路在~1年内完成，而传统方法需要100多年。 我们预计，使用这些新技术常规生成更大、更高质量的数据集也将 加快他们的分析进展。我们将立即用这种方式来增加我们对 大脑皮层处理和组织的基本原则。此外，随着更高的- 通过电磁成像，我们终于可以比较患病和健康的大脑，以评估电路如何 连接性被改变，从而指导智能治疗策略。