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.

项目摘要 该提议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 大脑范围的神经元电路。目前，即使在小的 哺乳动物模型系统，因为光学显微镜（LM）缺乏足够的分辨率和电子显微镜（EM） 不能在大量上应用。利用新第四代同步器的前所未有的品质 欧洲同步器的来源，我们将开发X射线纳米 - 叙事（XNH）成像技术 大脑电路的成像。利用改善源连贯性和亮度，我们将改善 成像分辨率可以直接可视化神经元之间的突触连接，并开发成像协议 这允许在典型的光束线实验中对厘米尺度的电路体积进行成像。我们将结合非 - 具有EM和LM成像技术的破坏性XNH，以严格而定量地验证XNH-的准确性 基于电路重建。然后，我们将使用此相关工作流来研究远程的关系 感觉输入，局部突触微路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 皮质半球，并利用基于深度学习的机器视觉算法来获得全面的皮质地图集 连接性。该地图集原则将解决单轴皮质区域之间的所有远程连接 解决方案，借贷洞察不同的皮质区域如何实现专业功能以及分布式皮质的方式 网络支持认知，并受到精神疾病的影响。