Comprehensive and multi-resolution mapping of cell morphology and wiring through X-ray holographic nano-tomography

通过 X 射线全息纳米断层扫描对细胞形态和布线进行全面的多分辨率绘图

• 批准号: 10376584
• 负责人: Alexandra Teodora JOITA PACUREANU
• 金额: $ 188.93万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-17 至 2024-09-16
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10376584
• 关键词: Affect; Algorithms; Anatomy; Brain; Cells; Cellular Morphology; Cerebellar Cortex; Cerebellar Nuclei; Cerebellum; Collaborations; Complex; Computer Models; Contrast Media; Data; Data Set; Electron Microscopy; Elements; Engineering; European; Foundations; Goals; Image; Label; Link; Machine Learning; Maps; Methods; Modeling; Molecular Genetics; Morphology; Mus; Neurodegenerative Disorders; Neurons; Neurosciences; Output; Physiology; Preparation; Process; Reporter; Research; Resolution; Resources; Roentgen Rays; Role; Sampling; Scanning; Scientist; Social Behavior; Specimen; Structure; Sulfur; Synapses; Synchrotrons; System; Techniques; Therapeutic; X ray microscopy; base; cell type; cellular imaging; connectome; data acquisition; deep learning; effective therapy; flexibility; imaging modality; improved; microscopic imaging; motor control; nano; nervous system disorder; network models; neural circuit; neural network; neuronal circuitry; next generation; novel strategies; reconstruction; relating to nervous system; stability testing; tomography; tool; treatment strategy

Project Summary / Abstract A fundamental goal in neuroscience is understanding how information is processed in neuronal circuits. However, the immense complexity of most brain networks has been a significant barrier to progress. Neurons are a primary computational component of the brain, yet we do not have a comprehensive list of their types for even the simplest mammalian neuronal circuit. Moreover, a neuron’s function is dependent on how it is connected, yet mammalian neuronal networks consist of billions of cells with trillions of connections. How do we approach such a complex computational system? Recent advances in X-ray microscopy, electron microscopy, and molecular genetic tools have allowed us to begin detailed mapping of neural network anatomy and connectivity. The cerebellum is an excellent system to scale and validate a new platform to systematically reverse engineer a functional neural circuit that is involved in motor control and social behavior. Its basic structure is well ordered, relatively simple and sufficiently studied to have inspired computational models that capture aspects of cerebellar function. However, even the most advanced models are limited by an incomplete characterization of the cell types and their connectivity within the cerebellum. Here, we propose to scale and validate our next-generation X-ray holographic nanotomography (XNH) platform and provide a comprehensive characterization of cerebellar circuitry. We will use tools recently established in our labs to disentangle a circuit that offers the advantages of relative simplicity and a strong starting foundation. These studies will allow us to understand principles of cerebellar circuit and cell type organization, and may help us determine the role of specific cell types in neurodegenerative disorders.

项目总结/摘要 神经科学的一个基本目标是了解信息如何在神经元回路中处理。 然而，大多数大脑网络的巨大复杂性一直是进步的重大障碍。神经元 是大脑的主要计算组件，但我们没有一个完整的列表， 甚至是最简单的哺乳动物神经回路。此外，神经元的功能取决于它是如何工作的。 然而，哺乳动物的神经网络是由数十亿个细胞和数万亿个连接组成的。怎么 我们如何处理这样一个复杂的计算系统？X射线显微镜、电子显微镜 显微镜和分子遗传学工具使我们能够开始详细绘制神经网络解剖图 和连通性。小脑是一个很好的系统，可以扩展和验证一个新的平台， 逆向工程一个功能性神经回路，涉及运动控制和社会行为。其基本 结构是有序的，相对简单，经过充分的研究，激发了计算模型， 捕捉小脑功能的各个方面然而，即使是最先进的模型也受到不完整的 表征小脑内的细胞类型及其连接。在这里，我们建议扩大规模， 验证我们的下一代X射线全息纳米层析成像（XNH）平台，并提供全面的 小脑回路的特征。我们将使用实验室中最近建立的工具来解开电路 这提供了相对简单和坚实的起始基础的优点。这些研究将使我们能够 了解小脑回路和细胞类型组织的原理，并可能帮助我们确定 神经退行性疾病中的特定细胞类型。