Novel EM technologies for imaging neural network anatomy

项目总结/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。它们共同构成了一个功能性的 拥有数万亿连接的神经网络。其规模和复杂性令人生畏，但从这种复杂性 出现感知和行为。我们如何理解如此庞大而复杂的组织 网络？一个关键的前进道路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。因此了解 电路结构-连接性-和细胞功能之间关系将帮助我们理解 神经元和网络处理信息。不幸的是，详细的连通性映射仍然很困难。一 关键的障碍是数据吞吐量。最近，高通量透射电子显微镜（TEM）已经 提高了成像速度，但仍然依赖于人类进行费力的手动样本收集， 装卸.目前的自动切片方法可以收集数千个电子显微镜（EM） 样品，但与快速TEM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成像 EM，通常较慢。该提案旨在开发新技术， 自动化样品收集和高速TEM成像，以超越通量障碍。我们将 产生与TEM成像兼容的用于样品收集的新型带衬底，并使用它来收集 数以千计的连续切片此外，我们还将设计和建造一个连续TEM样品台 磁带采集样本的成像。这些方法将允许对当地哺乳动物进行高质量的EM成像。 皮质回路将在约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，高质量的数据集也将 加快他们的分析进展。我们将立即使用这种方法来增加我们对 皮层处理和组织的基本原理。此外，随着高- 通过EM成像，我们最终将准备比较患病和健康的大脑，以评估电路如何 连通性被改变，从而指导智能治疗策略。

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.