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: 8739330
• 负责人: Wei-Chung Allen Lee
• 金额: $ 16.78万
• 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/8739330
• 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

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：我们的大脑包含数十亿个神经元，每个神经元有数千个突触。它们共同构成了一个具有数万亿个连接的功能性神经网络。它的规模和复杂性令人生畏，但从这种复杂性中产生了感知和行为。我们如何理解这样一个庞大而复杂的网络的组织？研究神经回路的结构和功能之间的关系是一个关键的途径。神经元的功能从根本上取决于它的连接方式。因此，理解电路结构（连通性）和细胞功能之间的关系将有助于我们理解神经元和网络如何处理信息。不幸的是，详细的连接映射仍然很困难。一个关键的障碍是数据吞吐量。最近,

项目成果

A petascale automated imaging pipeline for mapping neuronal circuits with high-throughput transmission electron microscopy.

• DOI: 10.1038/s41467-020-18659-3
• 发表时间: 2020-10-02
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Yin W;Brittain D;Borseth J;Scott ME;Williams D;Perkins J;Own CS;Murfitt M;Torres RM;Kapner D;Mahalingam G;Bleckert A;Castelli D;Reid D;Lee WA;Graham BJ;Takeno M;Bumbarger DJ;Farrell C;Reid RC;da Costa NM
• 通讯作者: da Costa NM