IDBR: A GPU-accelerated 3D-imaging and 3D-Illumination Sytem for Feedback Control of Light Fields in Biological Light Microscopy

IDBR：GPU 加速的 3D 成像和 3D 照明系统，用于生物光学显微镜中光场的反馈控制

• 批准号: 0964204
• 负责人: Marc Levoy
• 金额: $ 13万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-15 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0964204&HistoricalAwards=false
• 关键词: IDBR; GPU; accelerated; 3D; imaging

Recent developments in molecular neuroscience allow scientists to both optically record neuronal activity and to cause neurons to fire by stimulating them with light. In genetic model organisms like zebrafish and mice, these technologies can be used to observe and manipulate the activity patterns of thousands of neurons at once using non-invasive all-optical methods. While such techniques promise to revolutionize how we look at brain circuits, neural circuits are fundamentally three-dimensional structures. As a result, optical tools able to both image and selectively stimulate 3D volumes of brain tissue must be developed.This project will develop a device that can record a volume of neurons at each camera exposure, extract information from thousands of these neurons over time, and then use this information to choose which groups of individual neurons in the volume to stimulate with light. This feedback loop will allow scientists to test causal hypotheses about brain network function and its relationship to behavior in a fast and powerful way, leveraging feedback-control technologies currently used in robotics and aeronautics to build and refine dynamical models of the brain online. At the core of this device are new developments in computational microscopy: the light field microscope (LFM), which can computationally reconstruct an entire volume from a single snapshot, and the light field illuminator (LFI), which can create (nearly) arbitrary patterns of light in three dimensions. The project will couple these two devices and accelerate their performance using commercial graphics cards (GPUs) to allow real-time control of biological neural networks in behaving animals.Project outcomes, including scientific findings resulting from the application of the device to biological specimens, detailed directions on how to construct the physical device, and free, open-source software to run the device, will be provided online at http://graphics.stanford.edu/projects/lfmicroscope/.

分子神经科学的最新发展使科学家能够光学记录神经元活动，并通过用光刺激神经元来引起神经元放电。 在斑马鱼和小鼠等遗传模型生物中，这些技术可用于使用非侵入性全光学方法同时观察和操纵数千个神经元的活动模式。 虽然这些技术有望彻底改变我们对大脑回路的看法，但神经回路基本上是三维结构。 因此，必须开发能够对脑组织进行成像和选择性刺激的3D体积的光学工具。该项目将开发一种设备，该设备可以在每次相机曝光时记录一定体积的神经元，随着时间的推移从数千个神经元中提取信息，然后使用这些信息选择体积中的哪组单个神经元进行光刺激。这种反馈回路将使科学家能够以快速而强大的方式测试有关大脑网络功能及其与行为关系的因果假设，利用目前用于机器人和航空学的反馈控制技术在线构建和完善大脑的动态模型。 该设备的核心是计算显微镜的新发展：光场显微镜（LFM），它可以从单个快照中计算重建整个体积，以及光场照明器（LFI），它可以在三维中创建（几乎）任意的光图案。 该项目将把这两个设备结合起来，并使用商用图形卡（GPU）来加速它们的性能，从而实现对动物行为的生物神经网络的实时控制。项目成果，包括将该设备应用于生物标本所产生的科学发现、如何构建物理设备的详细说明以及运行该设备的免费开源软件，将在http://graphics.stanford.edu/projects/lfmicroscope/上在线提供。