Brain-wide Neuronal Circuit Mapping with X-ray Nano-Holography

利用 X 射线纳米全息术绘制全脑神经元回路

• 批准号: 10877549
• 负责人: Aaron Kuan
• 金额: $ 24.89万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10877549
• 关键词: Affect; Algorithms; Anatomy; Area; Atlases; Auditory area; Axon; Biological Models; Brain; Brain Mapping; Brain imaging; Calcium; Cells; Cognition; Complex; Data; Data Set; Decision Making; Detection; Development; Electron Microscopy; European; Functional Imaging; Generations; Geometry; Goals; Holography; Human; Image; Imaging Techniques; Imaging technology; Individual; Label; Length; Machine Learning; Maps; Mediating; Mental disorders; Morphology; Mus; Neocortex; Neurons; Neurosciences; Outcome; Parietal Lobe; Performance; Protocols documentation; Reporter; Resolution; Roentgen Rays; Sampling; Sensory; Software Tools; Source; Speed; Stains; Synapses; Synchrotrons; Techniques; Tissue Sample; Tissues; Training; Visual Cortex; Visualization; Work; X-Ray Medical Imaging; anatomic imaging; beamline; cognitive function; convolutional neural network; deep learning; detector; experimental study; high resolution imaging; image reconstruction; imaging approach; imaging capabilities; imaging modality; improved; in vivo; insight; light microscopy; machine vision; microscopic imaging; millimeter; multimodal data; multisensory; nano; nanoimaging; nanoscale; neocortical; neural circuit; neuronal circuitry; reconstruction; sample fixation; segmentation algorithm; sensor; sensory input; software development; support network; tool; two-photon; white matter

Project Summary This proposal's objective is to develop synchrotron-based X-ray imaging technologies to enable high-resolution imaging of brain-wide neuronal circuits. Comprehensively mapping brain-wide circuits is not currently feasible, even in small mammalian model systems, because light microscopy (LM) lacks sufficient resolution and electron microscopy (EM) cannot be applied over large volumes. Leveraging the unprecedented qualities of the new 4th generation synchrotron source at the European Synchrotron, we will develop X-ray nano-holography (XNH) imaging techniques for large-scale imaging of brain circuits. Taking advantage of improvements in source coherence and brightness, we will improve imaging resolution to allow direct visualization of synaptic connections between neurons, and develop imaging protocols that allow imaging of centimeter-scale circuit volumes within a typical beamline experiment. We will combine non- destructive XNH with EM and LM imaging techniques to rigorously and quantitatively validate the accuracy of XNH- based circuit reconstruction. We will then use this correlative workflow to study the relationships between long-range sensory inputs, local synaptic micro-circuitry, and single-neuron activity, investigating how circuits in the posterior parietal cortex (PPC) support perceptual decision-making. Lastly, we will apply XNH circuit-mapping over an entire cortical hemisphere, and utilize deep-learning based machine vision algorithms to obtain a comprehensive atlas of cortical connectivity. This atlas will in principle resolve all long-range connections between cortical areas at single-axon resolution, lending insight into how distinct cortical areas achieve specialized function, and how distributed cortical networks support cognition and are affected by psychiatric disorders.

项目概要 该提案的目标是开发基于同步加速器的 X 射线成像技术，以实现高分辨率成像 全脑神经元回路。全面绘制全脑回路目前还不可行，即使是在小范围内 哺乳动物模型系统，因为光学显微镜 (LM) 和电子显微镜 (EM) 缺乏足够的分辨率 不能大量应用。利用全新第四代同步加速器前所未有的品质 欧洲同步加速器的来源，我们将开发用于大规模的X射线纳米全息（XNH）成像技术 脑回路成像。利用光源相干性和亮度的改进，我们将改进 成像分辨率，允许直接可视化神经元之间的突触连接，并开发成像协议 允许在典型的光束线实验中对厘米级电路体积进行成像。我们将结合非 使用 EM 和 LM 成像技术来严格定量验证 XNH 的准确性 基于电路重构。然后，我们将使用这个相关工作流程来研究远程之间的关系 感觉输入、局部突触微电路和单神经元活动，研究后部电路如何 顶叶皮层（PPC）支持感知决策。最后，我们将在整个电路上应用 XNH 电路映射 大脑半球，利用基于深度学习的机器视觉算法获得大脑半球的综合图谱 连接性。该图谱原则上将解决单轴突皮质区域之间的所有远程连接 分辨率，有助于深入了解不同的皮质区域如何实现专门的功能，以及分布式皮质区域如何 网络支持认知并受到精神疾病的影响。