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Real-time Aberration Sensor for Large-Scale Microscopy Deep in the Mouse and Adult Zebrafish Brain

用于小鼠和成年斑马鱼大脑深处的大规模显微镜检查的实时像差传感器

基本信息

批准号：
10166305
负责人：
Steven Graham Adie
金额：
$ 198.23万
依托单位：
CORNELL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-05-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10166305
关键词：
Address Adult Algorithms Biological Biological Process Brain Brain Diseases Brain imaging Brain region Budgets Calibration Cells Cerebellum Consumption Financial compensation Fluorescence Goals Hybrids Image Imaging Techniques Imaging technology Individual Label Lasers Maps Methods Microscope Microscopy Modality Morphologic artifacts Motion Mus Neurons Neurosciences Neurosciences Research Noise Optical Coherence Tomography Optics Penetration Phase Photobleaching Photons Phototoxicity Physiologic pulse Population Positioning Attribute Procedures Pupil Research Resolution Sampling Shapes Signal Transduction Source Specificity Speed Structure System Techniques Technology Time Tissues Training Zebrafish adaptive optics awake base biological systems brain tissue data acquisition dentate gyrus digital imaging approach imaging study imaging system in vivo interest microscopic imaging mouse model multimodality multiphoton microscopy novel optical imaging parallel computer parallel processing programs relating to nervous system sensor spatiotemporal superior colliculus Corpora quadrigemina three photon microscopy two photon microscopy

项目摘要

ABSTRACT Optical imaging holds tremendous promise in our endeavor to understand brain functions. The major challenges for optical brain imaging are depth and speed. Due to optical aberrations and tissue scattering, the penetration depth and imaging speed of optical microscopy in the brains (e.g., mouse) is limited. The constraints in depth and speed make large-scale, deep imaging of mouse brain activity out of reach of current imaging techniques. Hardware adaptive optics (AO) has proven to be valuable for in vivo brain imaging with two-photon microscopy (2PM), and will have even larger impact for deep brain 3-photon microscopy (3PM); however, existing AO techniques require iterative optimization using multiphoton excited fluorescence signal. While adequate for imaging relatively shallow regions of the brain (< 1 mm deep), iterative optimization is impractical with ultra-deep imaging since the fluorescence signal deceases exponentially with imaging depth. The required integration time to obtain the necessary signal-to-noise ratio for iterative optimization becomes prohibitively long. In this program, we will leverage the advantages provided by computational adaptive optics (CAO) in optical coherence microscopy (OCM), specifically the strong OCT signal (from linear backscattering), and parallel computing on a high-end graphics processing unit (GPU), to provide orders of magnitude speed-up for the sensing of sample-induced aberrations throughout a volume of interest. A long-wavelength OCM system and CAO aberration sensor will be utilized to drive a hardware AO system to correct depth-dependent aberrations, push 3PM imaging depth beyond currently demonstrated limits, and increase imaging speed by at least one order of magnitude. Additionally, by combining with recently developed adaptive excitation laser technology, we will achieve approximately 300-fold increase in photon budget, which will enable truly unprecedented 3PM imaging speed and depth. Successful completion of this program will enable rapid aberration sensing at the depth range of 1 to 2 mm, and will open the exciting new opportunity of recording the neural activity of the dentate gyrus of adult mice through the intact brain. With its high-speed and deep-tissue aberration sensing capability, and zero additional photobleaching and phototoxicity, our novel method for real-time aberration sensing and correction is ideally positioned to transform our ability for large-scale, deep recording of mouse and adult zebrafish brain activity. This imaging approach will significantly extend the information available for neuroscience studies on individual cell-cell as well as circuit interactions that underlie normal and diseased brain function. The technology developed by this proposal will be applicable to imaging in other biological systems where large-scale, deep imaging at high spatiotemporal resolution is needed.

摘要