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.

项目概要/摘要 神经科学的一个基本目标是了解信息在神经回路中是如何处理的。 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。 是大脑的主要计算组件，但我们没有其类型的完整列表 此外，即使是最简单的哺乳动物神经回路，神经元的功能也取决于它的状态。 哺乳动物的神经网络由数十亿个细胞和数万亿个连接组成。 我们如何处理如此复杂的计算系统？X射线显微镜、电子学的最新进展？ 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 小脑是一个出色的系统，可以系统地扩展和验证新平台。 逆向工程涉及运动控制和社会行为的功能神经回路。 结构井然有序，相对简单，经过充分研究，激发了计算模型 然而，即使是最先进的模型也受到不完整的限制。 在这里，我们建议对小脑内的细胞类型及其连接性进行表征。 验证我们的下一代 X 射线全息纳米断层扫描 (XNH) 平台并提供全面的 我们将使用实验室最近建立的工具来解开电路。 这提供了相对简单的优点和强大的起始基础，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。