System for Volumetric 2-photon Imaging of Neuroactivity Using Light Beads Microscopy

使用光珠显微镜对神经活动进行体积 2 光子成像的系统

基本信息

  • 批准号:
    10755027
  • 负责人:
  • 金额:
    $ 99.98万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-09-05 至 2026-08-31
  • 项目状态:
    未结题

项目摘要

Abstract This project aims to develop and commercialize the Volumetric Calcium Imaging 2-Photon Activity Microscope, vCAm™, a revolutionary new 2-photon microscope based on a technological breakthrough called Light Beads Microscopy (LBM) that was recently developed by Dr. Alipasha Vaziri and co-workers (Lab. Neurotechnol. Biophys., Rockefeller Univ., New York, NY). The game-changing innovation in the vCAm is the ability to perform unparalleled in vivo calcium imaging of individual neurons at cellular resolution nearly simultaneously in one or more cytoarchitectonic regions of the mouse cerebral cortex, and nearly simultaneously in 30 imaging planes each ~16 µm apart (i.e., up to a total depth of 500 µm, encompassing layers I-V) at a full-frame rate of at least 12 Hertz. These capabilities are crucial for ultimately correlating stimuli and/or behavioral states of an animal discretely, in a context-dependent manner, with the activity of all neurons in the brain of the animal that are involved in this process, which requires simultaneous recording of the activity of hundreds of thousands of neurons in a multi-regional and multi-layer manner. However, contemporary 2-photon microscopy suffers from a fundamental limitation. Neuroscience researchers need to record simultaneous interactions between the sensory, motor and visual regions of the brain, but it is difficult to capture the activity in such a broad volume of the brain without sacrificing resolution or speed. The LBM technology pushes the limits of imaging speed to the physical nature of fluorescence itself by eliminating the “dead time” between sequential laser pulses when no neuroactivity is recorded and at the same time the need for scanning. With this approach, the only limit to the rate at which samples can be recorded is the time that it takes the tags to fluoresce, meaning wide volumes of the brain can be recorded within the same time it would take a conventional two-photon microscope to capture a much smaller number of brain cells. Other technology, such as miniaturized 2-photon microscopes that can be carried on the head of freely moving rodents, functional magnetic resonance imaging, inserting electrodes into the brain, or fiber photometry do not fulfill this need. This project will improve upon the original LBM invention to create a commercial product for disseminating this important new technology. Based on pilot work performed at Dr. Vaziri's laboratory, it is clear that the vCAm will make a significant impact on the field of neuroscience research, including advancing studies focused on alterations in the circuitry of the central nervous system associated with neurodevelopmental, neuropsychiatric and neurodegenerative disorders. Ultimately, this will result in an improved basis for developing novel treatment strategies for a wide spectrum of complex brain diseases. In Phase I we will demonstrate the feasibility of this novel technology by developing prototype hardware and software; work in Phase II will focus on creating the full functionality of the vCAm for commercial release. We will perform extensive feasibility studies, product validation and usability studies of the vCAm in close collaboration with Dr. Vaziri. A competing technology is not commercially available.
摘要 该项目旨在开发和商业化体积钙成像双光子活性显微镜, vCAm™,一种革命性的新型双光子显微镜,基于称为Light Beads的技术突破 显微镜(LBM),最近开发的博士Alipasha Vaziri和同事(实验室。神经技术 生物物理学,洛克菲勒大学,纽约,NY)。vCAm中改变游戏规则的创新是能够执行 几乎同时在一个或多个细胞中以细胞分辨率对单个神经元进行无与伦比的体内钙成像, 小鼠大脑皮层的更多细胞结构区域,并且几乎同时在30个成像平面中 每个间隔约16 μm(即,总深度达500 µm,包括层I-V),全帧速率至少为 12赫兹这些能力对于最终关联动物的刺激和/或行为状态至关重要 离散地,以上下文依赖的方式,与动物大脑中所有神经元的活动相关联, 参与这一过程,这需要同时记录数十万人的活动, 神经元以多区域和多层次的方式。然而,当代的双光子显微镜遭受 一个基本的限制。神经科学研究人员需要记录大脑中神经元之间的同时相互作用。 大脑的感觉,运动和视觉区域,但很难在如此广泛的体积中捕捉活动。 而不牺牲分辨率或速度。LBM技术将成像速度的极限推到了 通过消除连续激光脉冲之间的“死时间”, 记录神经活动,同时需要扫描。通过这种方法, 可以记录样品的速率是标签发荧光所需的时间,这意味着大量的 大脑可以在同一时间内被记录下来, 脑细胞数量少得多。其他技术,如微型双光子显微镜,可以 携带在自由活动的啮齿动物的头上,功能性磁共振成像,将电极插入 大脑或纤维光度测定不能满足这种需要。该项目将改进原始LBM发明, 创造一种商业产品来传播这一重要的新技术。根据在下列地点进行的试点工作: 博士Vaziri的实验室,很明显,vCAm将对神经科学领域产生重大影响 研究,包括推进集中在中枢神经系统电路改变的研究 与神经发育、神经精神和神经退行性疾病相关。最终,这将 为开发用于广泛复杂脑疾病的新型治疗策略奠定了更好的基础。 疾病在第一阶段,我们将通过开发原型硬件来证明这项新技术的可行性 第二阶段的工作重点是为商业版本创建vCAm的全部功能。 我们将进行广泛的可行性研究,产品验证和vCAm的可用性研究, 与Vaziri博士合作。竞争性技术还没有商业化。

项目成果

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JACOB R GLASER其他文献

JACOB R GLASER的其他文献

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{{ truncateString('JACOB R GLASER', 18)}}的其他基金

Microscope system for large scale optical imaging of neuronal activity using kilohertz frame rates
使用千赫兹帧速率对神经元活动进行大规模光学成像的显微镜系统
  • 批准号:
    10541683
  • 财政年份:
    2022
  • 资助金额:
    $ 99.98万
  • 项目类别:
System for Volumetric 2-photon Imaging of Neuroactivity Using Light Beads Microscopy
使用光珠显微镜对神经活动进行体积 2 光子成像的系统
  • 批准号:
    10603310
  • 财政年份:
    2022
  • 资助金额:
    $ 99.98万
  • 项目类别:
Microscope system for large scale optical imaging of neuronal activity using kilohertz frame rates
使用千赫兹帧速率对神经元活动进行大规模光学成像的显微镜系统
  • 批准号:
    10384932
  • 财政年份:
    2022
  • 资助金额:
    $ 99.98万
  • 项目类别:
AI based system for longitudinal, repeated measure analyses of freely moving C. elegans worms
基于人工智能的系统,用于对自由移动的秀丽隐杆线虫进行纵向、重复测量分析
  • 批准号:
    10258638
  • 财政年份:
    2021
  • 资助金额:
    $ 99.98万
  • 项目类别:
NeuroExM
神经ExM
  • 批准号:
    10686269
  • 财政年份:
    2021
  • 资助金额:
    $ 99.98万
  • 项目类别:
NeuroExM
神经ExM
  • 批准号:
    10156966
  • 财政年份:
    2021
  • 资助金额:
    $ 99.98万
  • 项目类别:
Next generation axonal quantification and classification using AI
使用人工智能的下一代轴突量化和分类
  • 批准号:
    10698843
  • 财政年份:
    2021
  • 资助金额:
    $ 99.98万
  • 项目类别:
ClearScope
清晰范围
  • 批准号:
    10159328
  • 财政年份:
    2018
  • 资助金额:
    $ 99.98万
  • 项目类别:
ClearScope
清晰范围
  • 批准号:
    10403446
  • 财政年份:
    2018
  • 资助金额:
    $ 99.98万
  • 项目类别:
ClearScope
清晰范围
  • 批准号:
    10019728
  • 财政年份:
    2018
  • 资助金额:
    $ 99.98万
  • 项目类别:

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  • 批准号:
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  • 财政年份:
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用于大视场和体积成像的开源小型双光子显微镜
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双光子显微镜和光学透明技术用于黑色素瘤手术切缘的体积成像
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使用光珠显微镜对神经活动进行体积 2 光子成像的系统
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用于散射大脑神经活动高速介观体积记录的成像模块的优化、应用和传播
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