NeuroNex Technology Hub: Nemonic: Next generation multiphoton neuroimaging consortium

NeuroNex 技术中心：Nemonic：下一代多光子神经影像联盟

• 批准号: 1934288
• 负责人: Spencer Smith
• 金额: $ 115.08万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1934288&HistoricalAwards=false
• 关键词: NeuroNex; Technology; Hub; Nemonic; Next

Multiphoton neuroimaging is a powerful approach for measuring neural activity in the brain, offering subcellular resolution of thousands or more neurons at time. However, current technology has technical limitations that restrict what experiments are possible. Therefore, this project will create new technology through a NeuroNex neurotechnology hub, called Nemonic (NExt generation Multiphoton NeuroImaging Consortium). The Nemonic project has three parts. First, the development component will create new systems in a series of Case Studies to enable currently impossible neuroscience experiments. Second, the dissemination component will spread this technology broadly to other neuroscience labs through open source resources, workshops, and industry partnerships. Third, the advancement component will push the fundamental technology of multiphoton neuroimaging into the next frontier. Two specific technologies will be developed: miniaturized photonic systems for multiphoton neuroimaging; and super-resolution imaging to image submicron structures. Also, a series of meetings will foster novel collaborations to more rapidly advance engineering technologies that are relevant to multiphoton neuroimaging in the future. Technology developed in the Nemonic project will also be relevant to manufacturing, 3D printing, and photonics. This work will also increase partnerships between academia and industry, enhance STEM training, and recruit and support the scientific training and careers of women and URM scientists.The Case Studies will develop new instrumentation for large field-of-view two- photon and three-photon imaging, scalable temporal multiplexing, and integrated behavior. This technology will be developed for compatibility with an array of model systems. The focus will be on calcium and glutamate imaging, in cell bodies and processes, and other fluorescent indicators can be employed. The workshops will cover optical design, fabrication, assembly, and use, for an audience of neuroscientists and engineers. One advancement project will develop high peak power ultrafast lasers with transform limited pulses, with integrated, beam conditioning, beam steering, focusing, and detection systems. The other advancement project will develop super-resolution multiphoton imaging using spatial frequency modulation, adaptive optics, and novel pulse conditioning. Together, this work will advance multiphoton neuroimaging and a suite of related technology, through research, enhanced training, and industry partnerships. This NeuroTechnology Hub award is co-funded by the Division of Emerging Frontiers within the Directorate for Biological Sciences as part of the BRAIN Initiative and NSF's Understanding the Brain activities.

多光子神经成像是测量大脑神经活动的一种强大方法，可同时提供数千个或更多神经元的亚细胞分辨率。然而，目前的技术存在技术局限性，限制了实验的可能性。因此，该项目将通过NeuroNex神经技术中心创建新技术，称为Nemonic（下一代多光子神经成像联盟）。Nemonic项目有三个部分。首先，开发部分将在一系列案例研究中创建新系统，以实现目前不可能的神经科学实验。其次，传播部分将通过开源资源、研讨会和行业合作伙伴关系将这项技术广泛传播到其他神经科学实验室。第三，先进的组件将推动多光子神经成像的基础技术进入下一个前沿。将开发两种具体技术：用于多光子神经成像的微型光子系统;以及用于亚微米结构成像的超分辨率成像。此外，一系列会议将促进新的合作，以更快地推进与未来多光子神经成像相关的工程技术。Nemonic项目开发的技术也将与制造、3D打印和光子学相关。这项工作还将增加学术界和工业界之间的合作伙伴关系，加强STEM培训，招募和支持女性和URM科学家的科学培训和职业生涯。案例研究将为大视场双光子和三光子成像，可扩展的时间复用和综合行为开发新的仪器。这项技术的开发将与一系列模型系统兼容。重点将是钙和谷氨酸成像，在细胞体和过程中，可以采用其他荧光指示剂。研讨会将涵盖光学设计，制造，组装和使用，为神经科学家和工程师的观众。其中一个先进的项目将开发具有变换限制脉冲的高峰功率超快激光器，具有集成的光束调节、光束转向、聚焦和检测系统。另一个进步项目将使用空间频率调制、自适应光学和新型脉冲调节开发超分辨率多光子成像。这项工作将通过研究、加强培训和行业合作，共同推进多光子神经成像和一套相关技术。这个神经技术中心奖由生物科学理事会新兴前沿部门共同资助，作为BRAIN计划和NSF理解大脑活动的一部分。

项目成果

Tomographic single pixel spatial frequency projection imaging

• DOI: 10.1016/j.optcom.2022.128401
• 发表时间: 2022-04
• 期刊: Optics Communications
• 影响因子: 2.4
• 作者: Patrick A Stockton;G. Murray;J. Field;J. Squier;A. Pezeshki;R. Bartels

Diverse coactive neurons encode stimulus-driven and stimulus-independent variables

不同的协同神经元编码刺激驱动和刺激无关的变量

• DOI: 10.1152/jn.00431.2020
• 发表时间: 2020
• 期刊: Journal of Neurophysiology
• 影响因子: 2.5
• 作者: Xia, Ji;Marks, Tyler D.;Goard, Michael J.;Wessel, Ralf
• 通讯作者: Wessel, Ralf

Spectral Phase and Amplitude Retrieval and Compensation for Random Access Microscopy

随机存取显微镜的光谱相位和幅度检索与补偿

• DOI: 10.1364/cleo_at.2019.am2i.4
• 发表时间: 2019
• 作者: Allende Motz, Alyssa M.;Durfee, Charles G.;Squier, Jeff A.;Adams, Daniel E.
• 通讯作者: Adams, Daniel E.

Distributed and retinotopically asymmetric processing of coherent motion in mouse visual cortex

小鼠视觉皮层相干运动的分布式和视网膜局部不对称处理

• DOI: 10.1038/s41467-020-17283-5
• 发表时间: 2020
• 期刊: Nature Communications
• 影响因子: 16.6
• 作者: Sit, Kevin K.;Goard, Michael J.
• 通讯作者: Goard, Michael J.

Super-Resolution Imaging by Computationally Fusing Quantum and Classical Optical Information

通过计算融合量子和经典光学信息实现超分辨率成像

• DOI: 10.34133/icomputing.0003
• 发表时间: 2022
• 期刊: Intelligent Computing
• 作者: Bartels, Randy A.;Murray, Gabe;Field, Jeff;Squier, Jeff
• 通讯作者: Squier, Jeff