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Jiang T, Gong H, Yuan J. Whole-brain Optical Imaging: A Powerful Tool for Precise Brain Mapping at the Mesoscopic Level. Neurosci Bull 2023; 39:1840-1858. [PMID: 37715920 PMCID: PMC10661546 DOI: 10.1007/s12264-023-01112-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/08/2023] [Indexed: 09/18/2023] Open
Abstract
The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons. Precise dissection of neural circuits at the mesoscopic level can provide important structural information for understanding the brain. Optical approaches can achieve submicron lateral resolution and achieve "optical sectioning" by a variety of means, which has the natural advantage of allowing the observation of neural circuits at the mesoscopic level. Automated whole-brain optical imaging methods based on tissue clearing or histological sectioning surpass the limitation of optical imaging depth in biological tissues and can provide delicate structural information in a large volume of tissues. Combined with various fluorescent labeling techniques, whole-brain optical imaging methods have shown great potential in the brain-wide quantitative profiling of cells, circuits, and blood vessels. In this review, we summarize the principles and implementations of various whole-brain optical imaging methods and provide some concepts regarding their future development.
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Affiliation(s)
- Tao Jiang
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China
| | - Hui Gong
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Jing Yuan
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China.
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.
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Zheng T, Feng Z, Wang X, Jiang T, Jin R, Zhao P, Luo T, Gong H, Luo Q, Yuan J. Review of micro-optical sectioning tomography (MOST): technology and applications for whole-brain optical imaging [Invited]. BIOMEDICAL OPTICS EXPRESS 2019; 10:4075-4096. [PMID: 31452996 PMCID: PMC6701528 DOI: 10.1364/boe.10.004075] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 06/20/2019] [Accepted: 06/25/2019] [Indexed: 05/14/2023]
Abstract
Elucidating connectivity and functionality at the whole-brain level is one of the most challenging research goals in neuroscience. Various whole-brain optical imaging technologies with submicron lateral resolution have been developed to reveal the fine structures of brain-wide neural and vascular networks at the mesoscopic level. Among them, micro-optical sectioning tomography (MOST) is attracting increasing attention, as a variety of technological variations and solutions tailored toward different biological applications have been optimized. Here, we summarize the recent development of MOST technology in whole-brain imaging and anticipate future improvements.
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Affiliation(s)
- Ting Zheng
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Equal contribution
| | - Zhao Feng
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Equal contribution
| | - Xiaojun Wang
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Tao Jiang
- HUST–Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, Jiangsu 215000, China
| | - Rui Jin
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Peilin Zhao
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Ting Luo
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Hui Gong
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- HUST–Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, Jiangsu 215000, China
| | - Qingming Luo
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- HUST–Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, Jiangsu 215000, China
| | - Jing Yuan
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- HUST–Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, Jiangsu 215000, China
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Zhang X, Chen Y, Ning K, Zhou C, Han Y, Gong H, Yuan J. Deep learning optical-sectioning method. OPTICS EXPRESS 2018; 26:30762-30772. [PMID: 30469968 DOI: 10.1364/oe.26.030762] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Current optical-sectioning methods require complex optical system or considerable computation time to improve imaging quality. Here we propose a deep learning-based method for optical sectioning of wide-field images. This method only needs one pair of contrast images for training to facilitate reconstruction of an optically sectioned image. The removal effect of background information and resolution that is achievable with our technique is similar to traditional optical-sectioning methods, but offers lower noise levels and a higher imaging depth. Moreover, reconstruction speed can be optimized to 14 Hz. This cost-effective and convenient method enables high-throughput optical sectioning techniques to be developed.
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