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Xia F, Rimoli CV, Akemann W, Ventalon C, Bourdieu L, Gigan S, de Aguiar HB. Neurophotonics beyond the surface: unmasking the brain's complexity exploiting optical scattering. NEUROPHOTONICS 2024; 11:S11510. [PMID: 38617592 PMCID: PMC11014413 DOI: 10.1117/1.nph.11.s1.s11510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 03/07/2024] [Accepted: 03/14/2024] [Indexed: 04/16/2024]
Abstract
The intricate nature of the brain necessitates the application of advanced probing techniques to comprehensively study and understand its working mechanisms. Neurophotonics offers minimally invasive methods to probe the brain using optics at cellular and even molecular levels. However, multiple challenges persist, especially concerning imaging depth, field of view, speed, and biocompatibility. A major hindrance to solving these challenges in optics is the scattering nature of the brain. This perspective highlights the potential of complex media optics, a specialized area of study focused on light propagation in materials with intricate heterogeneous optical properties, in advancing and improving neuronal readouts for structural imaging and optical recordings of neuronal activity. Key strategies include wavefront shaping techniques and computational imaging and sensing techniques that exploit scattering properties for enhanced performance. We discuss the potential merger of the two fields as well as potential challenges and perspectives toward longer term in vivo applications.
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Affiliation(s)
- Fei Xia
- Sorbonne Université, Collège de France, Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Paris, France
| | - Caio Vaz Rimoli
- Sorbonne Université, Collège de France, Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Paris, France
- Université PSL, Institut de Biologie de l’ENS, École Normale Supérieure, CNRS, INSERM, Paris, France
| | - Walther Akemann
- Université PSL, Institut de Biologie de l’ENS, École Normale Supérieure, CNRS, INSERM, Paris, France
| | - Cathie Ventalon
- Université PSL, Institut de Biologie de l’ENS, École Normale Supérieure, CNRS, INSERM, Paris, France
| | - Laurent Bourdieu
- Université PSL, Institut de Biologie de l’ENS, École Normale Supérieure, CNRS, INSERM, Paris, France
| | - Sylvain Gigan
- Sorbonne Université, Collège de France, Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Paris, France
| | - Hilton B. de Aguiar
- Sorbonne Université, Collège de France, Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Paris, France
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2
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Xu C, Nedergaard M, Fowell DJ, Friedl P, Ji N. Multiphoton fluorescence microscopy for in vivo imaging. Cell 2024; 187:4458-4487. [PMID: 39178829 PMCID: PMC11373887 DOI: 10.1016/j.cell.2024.07.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/18/2024] [Accepted: 07/22/2024] [Indexed: 08/26/2024]
Abstract
Multiphoton fluorescence microscopy (MPFM) has been a game-changer for optical imaging, particularly for studying biological tissues deep within living organisms. MPFM overcomes the strong scattering of light in heterogeneous tissue by utilizing nonlinear excitation that confines fluorescence emission mostly to the microscope focal volume. This enables high-resolution imaging deep within intact tissue and has opened new avenues for structural and functional studies. MPFM has found widespread applications and has led to numerous scientific discoveries and insights into complex biological processes. Today, MPFM is an indispensable tool in many research communities. Its versatility and effectiveness make it a go-to technique for researchers investigating biological phenomena at the cellular and subcellular levels in their native environments. In this Review, the principles, implementations, capabilities, and limitations of MPFM are presented. Three application areas of MPFM, neuroscience, cancer biology, and immunology, are reviewed in detail and serve as examples for applying MPFM to biological research.
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Affiliation(s)
- Chris Xu
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14850, USA
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Nørre Alle 3B, 2200 Copenhagen, Denmark; University of Rochester Medical School, 601 Elmwood Avenue, Rochester, NY 14642, USA
| | - Deborah J Fowell
- Department of Microbiology & Immunology, Cornell University, Ithaca, NY 14853, USA
| | - Peter Friedl
- Department of Medical BioSciences, Radboud University Medical Centre, Geert Grooteplein 26-28, Nijmegen HB 6500, the Netherlands
| | - Na Ji
- Department of Neuroscience, Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA.
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Rimoli CV, Moretti C, Soldevila F, Brémont E, Ventalon C, Gigan S. Demixing fluorescence time traces transmitted by multimode fibers. Nat Commun 2024; 15:6286. [PMID: 39060262 PMCID: PMC11282286 DOI: 10.1038/s41467-024-50306-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 07/05/2024] [Indexed: 07/28/2024] Open
Abstract
Optical methods based on thin multimode fibers (MMFs) are promising tools for measuring neuronal activity in deep brain regions of freely moving mice thanks to their small diameter. However, current methods are limited: while fiber photometry provides only ensemble activity, imaging techniques using of long multimode fibers are very sensitive to bending and have not been applied to unrestrained rodents yet. Here, we demonstrate the fundamentals of a new approach using a short MMF coupled to a miniscope. In proof-of-principle in vitro experiments, we disentangled spatio-temporal fluorescence signals from multiple fluorescent sources transmitted by a thin (200 µm) and short (8 mm) MMF, using a general unconstrained non-negative matrix factorization algorithm directly on the raw video data. Furthermore, we show that low-cost open-source miniscopes have sufficient sensitivity to image the same fluorescence patterns seen in our proof-of-principle experiment, suggesting a new avenue for novel minimally invasive deep brain studies using multimode fibers in freely behaving mice.
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Affiliation(s)
- Caio Vaz Rimoli
- Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Sorbonne Université, Collège de France, 24 Rue Lhomond, Paris, F-75005, France
- Institut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, 75005, Paris, France
| | - Claudio Moretti
- Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Sorbonne Université, Collège de France, 24 Rue Lhomond, Paris, F-75005, France
| | - Fernando Soldevila
- Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Sorbonne Université, Collège de France, 24 Rue Lhomond, Paris, F-75005, France
| | - Enora Brémont
- Institut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, 75005, Paris, France
| | - Cathie Ventalon
- Institut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, 75005, Paris, France.
| | - Sylvain Gigan
- Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Sorbonne Université, Collège de France, 24 Rue Lhomond, Paris, F-75005, France.
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4
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Chemerkouh MJHN, Zhou X, Yang Y, Wang S. Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy. Anal Chem 2024; 96:11299-11308. [PMID: 38953225 PMCID: PMC11283340 DOI: 10.1021/acs.analchem.4c01179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/03/2024]
Abstract
Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recently, plasmonic-based electrochemical impedance microscopy (P-EIM) was demonstrated for the label-free mapping of the ignition and propagation of action potentials in neuron cells with subcellular resolution. However, limited by the signal-to-noise ratio in the high-speed P-EIM video, action potential mapping was achieved by averaging 90 cycles of signals. Such extensive averaging is not desired and may not always be feasible due to factors such as neuronal desensitization. In this study, we utilized advanced signal processing techniques to detect action potentials in P-EIM extracted signals with fewer averaged cycles. Matched filtering successfully detected action potential signals with as few as averaging five cycles of signals. Long short-term memory (LSTM) recurrent neural network achieved the best performance and was able to detect single-cycle stimulated action potential successfully [satisfactory area under the receiver operating characteristic curve (AUC) equal to 0.855]. Therefore, we show that deep learning-based signal processing can dramatically improve the usability of P-EIM mapping of neuronal electrical signals.
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Affiliation(s)
- Mohammad Javad Haji Najafi Chemerkouh
- Biodesign Center for Biosensors and Bioelectronics, Arizona State University, Tempe, AZ 85287, USA
- School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA
| | - Xinyu Zhou
- Biodesign Center for Biosensors and Bioelectronics, Arizona State University, Tempe, AZ 85287, USA
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
| | - Yunze Yang
- Biodesign Center for Biosensors and Bioelectronics, Arizona State University, Tempe, AZ 85287, USA
| | - Shaopeng Wang
- Biodesign Center for Biosensors and Bioelectronics, Arizona State University, Tempe, AZ 85287, USA
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
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5
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Broomer MC, Beacher NJ, Wang MW, Lin DT. Examining a punishment-related brain circuit with miniature fluorescence microscopes and deep learning. ADDICTION NEUROSCIENCE 2024; 11:100154. [PMID: 38680653 PMCID: PMC11044849 DOI: 10.1016/j.addicn.2024.100154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/01/2024]
Abstract
In humans experiencing substance use disorder (SUD), abstinence from drug use is often motivated by a desire to avoid some undesirable consequence of further use: health effects, legal ramifications, etc. This process can be experimentally modeled in rodents by training and subsequently punishing an operant response in a context-induced reinstatement procedure. Understanding the biobehavioral mechanisms underlying punishment learning is critical to understanding both abstinence and relapse in individuals with SUD. To date, most investigations into the neural mechanisms of context-induced reinstatement following punishment have utilized discrete loss-of-function manipulations that do not capture ongoing changes in neural circuitry related to punishment-induced behavior change. Here, we describe a two-pronged approach to analyzing the biobehavioral mechanisms of punishment learning using miniature fluorescence microscopes and deep learning algorithms. We review recent advancements in both techniques and consider a target neural circuit.
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Affiliation(s)
- Matthew C. Broomer
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, 333 Cassell Drive, Baltimore, MD 21224, USA
| | - Nicholas J. Beacher
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, 333 Cassell Drive, Baltimore, MD 21224, USA
| | - Michael W. Wang
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, 333 Cassell Drive, Baltimore, MD 21224, USA
| | - Da-Ting Lin
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, 333 Cassell Drive, Baltimore, MD 21224, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, 725 N. Wolfe Street, Baltimore, MD 21205, USA
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6
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LaViolette AK, Rebec MR, Xu C. Measurement of third order coherence by in situ autocorrelation for determining three-photon cross-sections. BIOMEDICAL OPTICS EXPRESS 2024; 15:3555-3562. [PMID: 38867794 PMCID: PMC11166442 DOI: 10.1364/boe.521529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/20/2024] [Accepted: 04/21/2024] [Indexed: 06/14/2024]
Abstract
We show theoretically that the third order coherence at zero delay can be obtained by measuring the second and third order autocorrelation traces of a pulsed laser. Our theory enables the measurement of a fluorophore's three-photon cross-section without prior knowledge of the temporal profile of the excitation pulse by using the same fluorescent medium for both the measurement of the third order coherence at zero delay as well as the cross-section. Such an in situ measurement needs no assumptions about the pulse shape nor group delay dispersion of the optical system. To verify the theory experimentally, we measure the three-photon action cross-section of Alexa Fluor 350 and show that the measured value of the three-photon cross-section remains approximately constant despite varied amounts of chirp on the excitation pulses.
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Affiliation(s)
- Aaron K. LaViolette
- School of Applied and Engineering Physics. Cornell University, Ithaca, New York 14853, USA
| | | | - Chris Xu
- School of Applied and Engineering Physics. Cornell University, Ithaca, New York 14853, USA
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7
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Li X, Du Y, Huang JF, Li WW, Song W, Fan RN, Zhou H, Jiang T, Lu CG, Guan Z, Wang XF, Gong H, Li XN, Li A, Fu L, Sun YG. Link Brain-Wide Projectome to Neuronal Dynamics in the Mouse Brain. Neurosci Bull 2024:10.1007/s12264-024-01232-z. [PMID: 38819707 DOI: 10.1007/s12264-024-01232-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 01/28/2024] [Indexed: 06/01/2024] Open
Abstract
Knowledge about the neuronal dynamics and the projectome are both essential for understanding how the neuronal network functions in concert. However, it remains challenging to obtain the neural activity and the brain-wide projectome for the same neurons, especially for neurons in subcortical brain regions. Here, by combining in vivo microscopy and high-definition fluorescence micro-optical sectioning tomography, we have developed strategies for mapping the brain-wide projectome of functionally relevant neurons in the somatosensory cortex, the dorsal hippocampus, and the substantia nigra pars compacta. More importantly, we also developed a strategy to achieve acquiring the neural dynamic and brain-wide projectome of the molecularly defined neuronal subtype. The strategies developed in this study solved the essential problem of linking brain-wide projectome to neuronal dynamics for neurons in subcortical structures and provided valuable approaches for understanding how the brain is functionally organized via intricate connectivity patterns.
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Affiliation(s)
- Xiang Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
| | - Yun Du
- Institute of Neuroscience, Key Laboratory of Brain Coginition and Brain-inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jiang-Feng Huang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
| | - Wen-Wei Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
| | - Wei Song
- Institute of Neuroscience, Key Laboratory of Brain Coginition and Brain-inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ruo-Nan Fan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
| | - Hua Zhou
- Institute of Neuroscience, Key Laboratory of Brain Coginition and Brain-inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Tao Jiang
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, 215123, China
| | - Chang-Geng Lu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
| | - Zhuang Guan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
| | - Xiao-Fei Wang
- Institute of Neuroscience, Key Laboratory of Brain Coginition and Brain-inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, 215123, China
| | - Xiang-Ning Li
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, 215123, China
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, 215123, China
| | - Ling Fu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.
- MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.
- Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China.
- School of Physics and Optoelectronics Engineering, Hainan University, Haikou, 570228, Hainan, China.
| | - Yan-Gang Sun
- Institute of Neuroscience, Key Laboratory of Brain Coginition and Brain-inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
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8
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Gilinsky SD, Jung DN, Futia GL, Zohrabi M, Welton TA, Supekar OD, Gibson EA, Restrepo D, Bright VM, Gopinath JT. Tunable liquid lens for three-photon excitation microscopy. BIOMEDICAL OPTICS EXPRESS 2024; 15:3285-3300. [PMID: 38855666 PMCID: PMC11161341 DOI: 10.1364/boe.516956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 03/28/2024] [Accepted: 04/06/2024] [Indexed: 06/11/2024]
Abstract
We demonstrate a novel electrowetting liquid combination using a room temperature ionic liquid (RTIL) and a nonpolar liquid, 1-phenyl-1-cyclohexene (PCH) suitable for focus-tunable 3-photon microscopy. We show that both liquids have over 90% transmission at 1300 nm over a 1.1 mm pathlength and an index of refraction contrast of 0.123. A lens using these liquids can be tuned from a contact angle of 133 to 48° with applied voltages of 0 and 60 V, respectively. Finally, a three-photon imaging system including an RTIL electrowetting lens was used to image a mouse brain slice. Axial scans taken with an electrowetting lens show excellent agreement with images acquired using a mechanically scanned objective.
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Affiliation(s)
- Samuel D. Gilinsky
- Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, Colorado 80309, USA
| | - Diane N. Jung
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado 80309, USA
| | - Greg L. Futia
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, USA
| | - Mo Zohrabi
- Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, Colorado 80309, USA
| | - Tarah A. Welton
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, USA
| | - Omkar D. Supekar
- Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, Colorado 80309, USA
| | - Emily A. Gibson
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, USA
| | - Diego Restrepo
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, USA
| | - Victor M. Bright
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado 80309, USA
| | - Juliet T. Gopinath
- Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, Colorado 80309, USA
- Department of Physics, University of Colorado Boulder, Boulder, Colorado 80309, USA
- Materials Science and Engineering Program, University of Colorado Boulder, Boulder, Colorado 80309, USA
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9
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Xue F, Li F, Zhang KM, Ding L, Wang Y, Zhao X, Xu F, Zhang D, Sun M, Lau PM, Zhu Q, Zhou P, Bi GQ. Multi-region calcium imaging in freely behaving mice with ultra-compact head-mounted fluorescence microscopes. Natl Sci Rev 2024; 11:nwad294. [PMID: 38288367 PMCID: PMC10824555 DOI: 10.1093/nsr/nwad294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/26/2023] [Accepted: 11/23/2023] [Indexed: 01/31/2024] Open
Abstract
To investigate the circuit-level neural mechanisms of behavior, simultaneous imaging of neuronal activity in multiple cortical and subcortical regions is highly desired. Miniature head-mounted microscopes offer the capability of calcium imaging in freely behaving animals. However, implanting multiple microscopes on a mouse brain remains challenging due to space constraints and the cumbersome weight of the equipment. Here, we present TINIscope, a Tightly Integrated Neuronal Imaging microscope optimized for electronic and opto-mechanical design. With its compact and lightweight design of 0.43 g, TINIscope enables unprecedented simultaneous imaging of behavior-relevant activity in up to four brain regions in mice. Proof-of-concept experiments with TINIscope recorded over 1000 neurons in four hippocampal subregions and revealed concurrent activity patterns spanning across these regions. Moreover, we explored potential multi-modal experimental designs by integrating additional modules for optogenetics, electrical stimulation or local field potential recordings. Overall, TINIscope represents a timely and indispensable tool for studying the brain-wide interregional coordination that underlies unrestrained behaviors.
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Affiliation(s)
- Feng Xue
- Department of Precision Machinery and Precision Instruments, University of Science and Technology of China, Hefei 230026, China
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
| | - Fei Li
- Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Faculty of Life and Health Sciences, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Ke-ming Zhang
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Lufeng Ding
- Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Yang Wang
- Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
| | - Xingtao Zhao
- Department of Modern Life Sciences and Biotecnology, Xiongan Institute of Innovation, Xiongan New Area, Xiongan 071899, China
| | - Fang Xu
- Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Faculty of Life and Health Sciences, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
| | - Danke Zhang
- Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Mingzhai Sun
- Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou 215123, China
| | - Pak-Ming Lau
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
- Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
| | - Qingyuan Zhu
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
| | - Pengcheng Zhou
- Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Faculty of Life and Health Sciences, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Guo-Qiang Bi
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
- Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
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10
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Year in review 2023. Nat Methods 2024; 21:1-2. [PMID: 38212549 DOI: 10.1038/s41592-023-02158-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
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11
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Zhou ZC, Gordon-Fennell A, Piantadosi SC, Ji N, Smith SL, Bruchas MR, Stuber GD. Deep-brain optical recording of neural dynamics during behavior. Neuron 2023; 111:3716-3738. [PMID: 37804833 PMCID: PMC10843303 DOI: 10.1016/j.neuron.2023.09.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/24/2023] [Accepted: 09/06/2023] [Indexed: 10/09/2023]
Abstract
In vivo fluorescence recording techniques have produced landmark discoveries in neuroscience, providing insight into how single cell and circuit-level computations mediate sensory processing and generate complex behaviors. While much attention has been given to recording from cortical brain regions, deep-brain fluorescence recording is more complex because it requires additional measures to gain optical access to harder to reach brain nuclei. Here we discuss detailed considerations and tradeoffs regarding deep-brain fluorescence recording techniques and provide a comprehensive guide for all major steps involved, from project planning to data analysis. The goal is to impart guidance for new and experienced investigators seeking to use in vivo deep fluorescence optical recordings in awake, behaving rodent models.
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Affiliation(s)
- Zhe Charles Zhou
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Adam Gordon-Fennell
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Sean C Piantadosi
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Na Ji
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Spencer LaVere Smith
- Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Michael R Bruchas
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA; Department of Pharmacology, University of Washington, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
| | - Garret D Stuber
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA; Department of Pharmacology, University of Washington, Seattle, WA 98195, USA.
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12
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Lee CH, Park YK, Lee K. Recent strategies for neural dynamics observation at a larger scale and wider scope. Biosens Bioelectron 2023; 240:115638. [PMID: 37647685 DOI: 10.1016/j.bios.2023.115638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/15/2023] [Accepted: 08/24/2023] [Indexed: 09/01/2023]
Abstract
The tremendous technical progress in neuroscience offers opportunities to observe a more minor or/and broader dynamic picture of the brain. Moreover, the large-scale neural activity of individual neurons enables the dissection of detailed mechanistic links between neural populations and behaviors. To measure neural activity in-vivo, multi-neuron recording, and neuroimaging techniques are employed and developed to acquire more neurons. The tools introduced concurrently recorded dozens to hundreds of neurons in the coordinated brain regions and elucidated the neuronal ensembles from a massive population perspective of diverse neurons at cellular resolution. In particular, the increasing spatiotemporal resolution of neuronal monitoring across the whole brain dramatically facilitates our understanding of additional nervous system functions in health and disease. Here, we will introduce state-of-the-art neuroscience tools involving large-scale neural population recording and the long-range connections spanning multiple brain regions. Their synergic effects provide to clarify the controversial circuitry underlying neuroscience. These challenging neural tools present a promising outlook for the fundamental dynamic interplay across levels of synaptic cellular, circuit organization, and brain-wide. Hence, more observations of neural dynamics will provide more clues to elucidate brain functions and push forward innovative technology at the intersection of neural engineering disciplines. We hope this review will provide insight into the use or development of recent neural techniques considering spatiotemporal scales of brain observation.
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Affiliation(s)
- Chang Hak Lee
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea
| | - Young Kwon Park
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea
| | - Kwang Lee
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea.
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13
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Thornton MA, Futia GL, Stockton ME, Budoff SA, Ramirez AN, Ozbay B, Tzang O, Kilborn K, Poleg-Polsky A, Restrepo D, Gibson EA, Hughes EG. Long-term in vivo three-photon imaging reveals region-specific differences in healthy and regenerative oligodendrogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.29.564636. [PMID: 37961298 PMCID: PMC10634963 DOI: 10.1101/2023.10.29.564636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The generation of new myelin-forming oligodendrocytes in the adult CNS is critical for cognitive function and regeneration following injury. Oligodendrogenesis varies between gray and white matter regions suggesting that local cues drive regional differences in myelination and the capacity for regeneration. Yet, the determination of regional variability in oligodendrocyte cell behavior is limited by the inability to monitor the dynamics of oligodendrocytes and their transcriptional subpopulations in white matter of the living brain. Here, we harnessed the superior imaging depth of three-photon microscopy to permit long-term, longitudinal in vivo three-photon imaging of an entire cortical column and underlying subcortical white matter without cellular damage or reactivity. Using this approach, we found that the white matter generated substantially more new oligodendrocytes per volume compared to the gray matter, yet the rate of population growth was proportionally higher in the gray matter. Following demyelination, the white matter had an enhanced population growth that resulted in higher oligodendrocyte replacement compared to the gray matter. Finally, deep cortical layers had pronounced deficits in regenerative oligodendrogenesis and restoration of the MOL5/6-positive oligodendrocyte subpopulation following demyelinating injury. Together, our findings demonstrate that regional microenvironments regulate oligodendrocyte population dynamics and heterogeneity in the healthy and diseased brain.
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Affiliation(s)
- Michael A. Thornton
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
| | | | - Michael E. Stockton
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
| | - Samuel A. Budoff
- Physiology and Biophysics, University of Colorado Anschutz Medical Campus
| | - Alexandra N Ramirez
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
| | - Baris Ozbay
- Intelligent Imaging Innovations (3i), Denver, CO, USA
| | - Omer Tzang
- Intelligent Imaging Innovations (3i), Denver, CO, USA
| | - Karl Kilborn
- Intelligent Imaging Innovations (3i), Denver, CO, USA
| | - Alon Poleg-Polsky
- Physiology and Biophysics, University of Colorado Anschutz Medical Campus
| | - Diego Restrepo
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
| | - Emily A. Gibson
- Bioengineering, University of Colorado Anschutz Medical Campus
| | - Ethan G. Hughes
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
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14
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Zhao C, Zhu Y, Zhang D, Fu Q, Pan M, Wu R, Wang A, Cheng H. Millimeter field-of-view miniature two-photon microscopy for brain imaging in freely moving mice. OPTICS EXPRESS 2023; 31:32925-32934. [PMID: 37859084 DOI: 10.1364/oe.492674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 09/07/2023] [Indexed: 10/21/2023]
Abstract
Development of miniature two-photon microscopy (m2PM) has made it possible to observe fine structure and activity of neurons in the brain of freely moving animals. However, the imaging field-of-view of existing m2PM is still significantly smaller than that of miniature single-photon microscopy. Here we report that, through the design of low-magnification objective, large field-of-view scan lens and small tilt angle microscanner, a 2.5-g m2PM achieved a field-of-view of 1000 × 788 µm2, comparable to that of a typical single-photon miniscope. We demonstrated its capability by imaging neurons, dendrites and spines in the millimeter field-of-view, and simultaneous recording calcium activities, through a gradient-index lens, of approximately 400 neurons in the dorsal hippocampal CA1 in a freely moving mouse. Integrated with a detachable 1.2-g fast z-scanning module, it enables a 1000 × 788 × 500 µm3 volumetric neuronal imaging in the cerebral cortex. Thus, millimeter FOV m2PM provides a powerful tool for deciphering neuronal population dynamics in experimental paradigms allowing for animal's free movement.
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15
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LaViolette AK, Ouzounov DG, Xu C. Measurement of three-photon excitation cross-sections of fluorescein from 1154 nm to 1500 nm. BIOMEDICAL OPTICS EXPRESS 2023; 14:4369-4382. [PMID: 37799679 PMCID: PMC10549759 DOI: 10.1364/boe.498214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/17/2023] [Accepted: 07/19/2023] [Indexed: 10/07/2023]
Abstract
Measurements of three-photon action cross-sections for fluorescein (dissolved in water, pH ∼11.5) are presented in the excitation wavelength range from 1154 to 1500 nm in ∼50 nm steps. The excitation source is a femtosecond wavelength tunable non-collinear optical parametric amplifier, which has been spectrally filtered with 50 nm full width at half maximum band pass filters. Cube-law power dependance is confirmed at the measurement wavelengths. The three-photon excitation spectrum is found to differ from both the one- and two-photon excitation spectra. The three-photon action cross-section at 1154 nm is more than an order of magnitude larger than those at 1450 and 1500 nm (approximately three times the wavelength of the one-photon excitation peak), which possibly indicates the presence of resonance enhancement.
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Affiliation(s)
- Aaron K. LaViolette
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14853, USA
| | - Dimitre G. Ouzounov
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14853, USA
| | - Chris Xu
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14853, USA
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16
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Gu M, Li X, Liang S, Zhu J, Sun P, He Y, Yu H, Li R, Zhou Z, Lyu J, Li SC, Budinger E, Zhou Y, Jia H, Zhang J, Chen X. Rabies virus-based labeling of layer 6 corticothalamic neurons for two-photon imaging in vivo. iScience 2023; 26:106625. [PMID: 37250327 PMCID: PMC10214394 DOI: 10.1016/j.isci.2023.106625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 03/03/2023] [Accepted: 04/03/2023] [Indexed: 05/31/2023] Open
Abstract
Neocortical layer 6 (L6) is less understood than other more superficial layers, largely owing to limitations of performing high-resolution investigations in vivo. Here, we show that labeling with the Challenge Virus Standard (CVS) rabies virus strain enables high-quality imaging of L6 neurons by conventional two-photon microscopes. CVS virus injection into the medial geniculate body can selectively label L6 neurons in the auditory cortex. Only three days after injection, dendrites and cell bodies of L6 neurons could be imaged across all cortical layers. Ca2+ imaging in awake mice showed that sound stimulation evokes neuronal responses from cell bodies with minimal contamination from neuropil signals. In addition, dendritic Ca2+ imaging revealed significant responses from spines and trunks across all layers. These results demonstrate a reliable method capable of rapid, high-quality labeling of L6 neurons that can be readily extended to other brain regions.
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Affiliation(s)
- Miaoqing Gu
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
- Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning 530004, China
| | - Xiuli Li
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing 400038, China
| | - Shanshan Liang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing 400038, China
| | - Jiahui Zhu
- Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning 530004, China
| | - Pei Sun
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing 400038, China
| | - Yong He
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing 400038, China
| | - Haipeng Yu
- Department of Neurobiology, Chongqing Key Laboratory of Neurobiology, School of Basic Medicine, Third Military Medical University, Chongqing 400038, China
| | - Ruijie Li
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing 400038, China
| | - Zhenqiao Zhou
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Jing Lyu
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Sunny C. Li
- Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning 530004, China
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, 39118 Magdeburg, Germany
| | - Yi Zhou
- Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning 530004, China
- Department of Neurobiology, Chongqing Key Laboratory of Neurobiology, School of Basic Medicine, Third Military Medical University, Chongqing 400038, China
| | - Hongbo Jia
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, 39118 Magdeburg, Germany
| | - Jianxiong Zhang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing 400038, China
| | - Xiaowei Chen
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing 400038, China
- Guangyang Bay Laboratory, Chongqing Institute for Brain and Intelligence, Chongqing 400064, China
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17
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Lecoq JA, Boehringer R, Grewe BF. Deep brain imaging on the move. Nat Methods 2023; 20:495-496. [PMID: 36869123 DOI: 10.1038/s41592-023-01808-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Affiliation(s)
| | - Roman Boehringer
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Benjamin F Grewe
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
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