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Mazzella L, Mangeat T, Giroussens G, Rogez B, Li H, Creff J, Saadaoui M, Martins C, Bouzignac R, Labouesse S, Idier J, Galland F, Allain M, Sentenac A, LeGoff L. Extended-depth of field random illumination microscopy, EDF-RIM, provides super-resolved projective imaging. LIGHT, SCIENCE & APPLICATIONS 2024; 13:285. [PMID: 39384765 DOI: 10.1038/s41377-024-01612-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 08/15/2024] [Accepted: 08/27/2024] [Indexed: 10/11/2024]
Abstract
The ultimate aim of fluorescence microscopy is to achieve high-resolution imaging of increasingly larger biological samples. Extended depth of field presents a potential solution to accelerate imaging of large samples when compression of information along the optical axis is not detrimental to the interpretation of images. We have implemented an extended depth of field (EDF) approach in a random illumination microscope (RIM). RIM uses multiple speckled illuminations and variance data processing to double the resolution. It is particularly adapted to the imaging of thick samples as it does not require the knowledge of illumination patterns. We demonstrate highly-resolved projective images of biological tissues and cells. Compared to a sequential scan of the imaged volume with conventional 2D-RIM, EDF-RIM allows an order of magnitude improvement in speed and light dose reduction, with comparable resolution. As the axial information is lost in an EDF modality, we propose a method to retrieve the sample topography for samples that are organized in cell sheets.
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Affiliation(s)
- Lorry Mazzella
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Thomas Mangeat
- LITC Core Facility, Centre de Biologie Integrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Guillaume Giroussens
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Benoit Rogez
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Hao Li
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Justine Creff
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Mehdi Saadaoui
- Aix Marseille University, CNRS, IBDM UMR7288, Turing Centre for Living Systems, Marseille, France
| | - Carla Martins
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Ronan Bouzignac
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Simon Labouesse
- LITC Core Facility, Centre de Biologie Integrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Jérome Idier
- LS2N, CNRS UMR 6004, F44321, Nantes Cedex 3, France
| | - Frédéric Galland
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Marc Allain
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Anne Sentenac
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France.
| | - Loïc LeGoff
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France.
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Uhlířová H, Stibůrek M, Pikálek T, Gomes A, Turtaev S, Kolbábková P, Čižmár T. "There's plenty of room at the bottom": deep brain imaging with holographic endo-microscopy. NEUROPHOTONICS 2024; 11:S11504. [PMID: 38250297 PMCID: PMC10798506 DOI: 10.1117/1.nph.11.s1.s11504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/09/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024]
Abstract
Significance Over more than 300 years, microscopic imaging keeps providing fundamental insights into the mechanisms of living organisms. Seeing microscopic structures beyond the reach of free-space light-based microscopy, however, requires dissection of the tissue-an intervention seriously disturbing its physiological functions. The hunt for low-invasiveness tools has led a growing community of physicists and engineers into the realm of complex media photonics. One of its activities represents exploiting multimode optical fibers (MMFs) as ultra-thin endoscopic probes. Employing wavefront shaping, these tools only recently facilitated the first peeks at cells and their sub-cellular compartments at the bottom of the mouse brain with the impact of micro-scale tissue damage. Aim Here, we aim to highlight advances in MMF-based holographic endo-microscopy facilitating microscopic imaging throughout the whole depth of the mouse brain. Approach We summarize the important technical and methodological prerequisites for stabile high-resolution imaging in vivo. Results We showcase images of the microscopic building blocks of brain tissue, including neurons, neuronal processes, vessels, intracellular calcium signaling, and red blood cell velocity in individual vessels. Conclusions This perspective article helps to understand the complexity behind the technology of holographic endo-microscopy, summarizes its recent advances and challenges, and stimulates the mind of the reader for further exploitation of this tool in the neuroscience research.
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Affiliation(s)
- Hana Uhlířová
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Miroslav Stibůrek
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Tomáš Pikálek
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - André Gomes
- Leibniz Institute of Photonic Technology, Jena, Germany
| | | | - Petra Kolbábková
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Tomáš Čižmár
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
- Leibniz Institute of Photonic Technology, Jena, Germany
- Friedrich Schiller University Jena, Institute of Applied Optics, Jena, Germany
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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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Lin S, Gong L, Huang Z. Time-of-flight resolved stimulated Raman scattering microscopy using counter-propagating ultraslow Bessel light bullets generation. LIGHT, SCIENCE & APPLICATIONS 2024; 13:148. [PMID: 38951517 PMCID: PMC11217417 DOI: 10.1038/s41377-024-01498-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 05/20/2024] [Accepted: 05/30/2024] [Indexed: 07/03/2024]
Abstract
We present a novel time-of-flight resolved Bessel light bullet-enabled stimulated Raman scattering (B2-SRS) microscopy for deeper tissue 3D chemical imaging with high resolution without a need for mechanical z-scanning. To accomplish the tasks, we conceive a unique method to enable optical sectioning by generating the counter-propagating pump and Stokes Bessel light bullets in the sample, in which the group velocities of the Bessel light bullets are made ultraslow (e.g., vg ≈ 0.1c) and tunable by introducing programmable angular dispersions with a spatial light modulator. We theoretically analyze the working principle of the collinear multicolor Bessel light bullet generations and velocity controls with the relative time-of-flight resolved detection for SRS 3D deep tissue imaging. We have also built the B2-SRS imaging system and present the first demonstration of B2-SRS microscopy with Bessel light bullets for 3D chemical imaging in a variety of samples (e.g., polymer bead phantoms, biological samples such as spring onion tissue and porcine brain) with high resolution. The B2-SRS technique provides a > 2-fold improvement in imaging depth in porcine brain tissue compared to conventional SRS microscopy. The method of optical sectioning in tissue using counter-propagating ultraslow Bessel light bullets developed in B2-SRS is generic and easy to perform and can be readily extended to other nonlinear optical imaging modalities to advance 3D microscopic imaging in biological and biomedical systems and beyond.
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Affiliation(s)
- Shulang Lin
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Li Gong
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Zhiwei Huang
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, 117576, Singapore.
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Chen W, Ge X, Zhang Q, Natan RG, Fan JL, Scanziani M, Ji N. High-throughput volumetric mapping of synaptic transmission. Nat Methods 2024; 21:1298-1305. [PMID: 38898094 DOI: 10.1038/s41592-024-02309-3] [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: 09/26/2023] [Accepted: 05/15/2024] [Indexed: 06/21/2024]
Abstract
Volumetric imaging of synaptic transmission in vivo requires high spatial and high temporal resolution. Shaping the wavefront of two-photon fluorescence excitation light, we developed Bessel-droplet foci for high-contrast and high-resolution volumetric imaging of synapses. Applying our method to imaging glutamate release, we demonstrated high-throughput mapping of excitatory inputs at >1,000 synapses per volume and >500 dendritic spines per neuron in vivo and unveiled previously unseen features of functional synaptic organization in the mouse primary visual cortex.
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Affiliation(s)
- Wei Chen
- Department of Physics, University of California, Berkeley, CA, USA
- School of Mechanical Science and Engineering - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, China
| | - Xinxin Ge
- Department of Physiology, University of California, San Francisco, San Francisco, CA, USA
- Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Qinrong Zhang
- Department of Physics, University of California, Berkeley, CA, USA
| | - Ryan G Natan
- Department of Physics, University of California, Berkeley, CA, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Jiang Lan Fan
- Joint Bioengineering Graduate Program, University of California, Berkeley, CA, USA
- Joint Bioengineering Graduate Program, University of California, San Francisco, CA, USA
| | - Massimo Scanziani
- Department of Physiology, University of California, San Francisco, San Francisco, CA, USA
- Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Na Ji
- Department of Physics, University of California, Berkeley, CA, USA.
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA.
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
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6
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Phil Brooks F, Davis HC, Wong-Campos JD, Cohen AE. Optical constraints on two-photon voltage imaging. NEUROPHOTONICS 2024; 11:035007. [PMID: 39139631 PMCID: PMC11321468 DOI: 10.1117/1.nph.11.3.035007] [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: 05/28/2024] [Revised: 07/23/2024] [Accepted: 07/25/2024] [Indexed: 08/15/2024]
Abstract
Significance Genetically encoded voltage indicators (GEVIs) are a valuable tool for studying neural circuits in vivo, but the relative merits and limitations of one-photon (1P) versus two-photon (2P) voltage imaging are not well characterized. Aim We consider the optical and biophysical constraints particular to 1P and 2P voltage imaging and compare the imaging properties of commonly used GEVIs under 1P and 2P excitation. Approach We measure the brightness and voltage sensitivity of voltage indicators from commonly used classes under 1P and 2P illumination. We also measure the decrease in fluorescence as a function of depth in the mouse brain. We develop a simple model of the number of measurable cells as a function of reporter properties, imaging parameters, and desired signal-to-noise ratio (SNR). We then discuss how the performance of voltage imaging would be affected by sensor improvements and by recently introduced advanced imaging modalities. Results Compared with 1P excitation, 2P excitation requires ∼ 10 4 -fold more illumination power per cell to produce similar photon count rates. For voltage imaging with JEDI-2P in the mouse cortex with a target SNR of 10 (spike height to baseline shot noise), a measurement bandwidth of 1 kHz, a thermally limited laser power of 200 mW, and an imaging depth of > 300 μ m , 2P voltage imaging using an 80-MHz source can record from no more than ∼ 12 neurons simultaneously. Conclusions Due to the stringent photon-count requirements of voltage imaging and the modest voltage sensitivity of existing reporters, 2P voltage imaging in vivo faces a stringent tradeoff between shot noise and tissue photodamage. 2P imaging of hundreds of neurons with high SNR at a depth of > 300 μ m will require either major improvements in 2P GEVIs or qualitatively new approaches to imaging.
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Affiliation(s)
- F. Phil Brooks
- Harvard University, Department of Chemistry and Chemical Biology, Cambridge, Massachusetts, United States
| | - Hunter C. Davis
- Harvard University, Department of Chemistry and Chemical Biology, Cambridge, Massachusetts, United States
| | - J. David Wong-Campos
- Harvard University, Department of Chemistry and Chemical Biology, Cambridge, Massachusetts, United States
| | - Adam E. Cohen
- Harvard University, Department of Chemistry and Chemical Biology, Cambridge, Massachusetts, United States
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Sarafraz H, Nöbauer T, Kim H, Soldevila F, Gigan S, Vaziri A. Speckle-enabled in vivo demixing of neural activity in the mouse brain. BIOMEDICAL OPTICS EXPRESS 2024; 15:3586-3608. [PMID: 38867774 PMCID: PMC11166431 DOI: 10.1364/boe.524521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/11/2024] [Accepted: 04/14/2024] [Indexed: 06/14/2024]
Abstract
Functional imaging of neuronal activity in awake animals, using a combination of fluorescent reporters of neuronal activity and various types of microscopy modalities, has become an indispensable tool in neuroscience. While various imaging modalities based on one-photon (1P) excitation and parallel (camera-based) acquisition have been successfully used for imaging more transparent samples, when imaging mammalian brain tissue, due to their scattering properties, two-photon (2P) microscopy systems are necessary. In 2P microscopy, the longer excitation wavelengths reduce the amount of scattering while the diffraction-limited 3D localization of excitation largely eliminates out-of-focus fluorescence. However, this comes at the cost of time-consuming serial scanning of the excitation spot and more complex and expensive instrumentation. Thus, functional 1P imaging modalities that can be used beyond the most transparent specimen are highly desirable. Here, we transform light scattering from an obstacle into a tool. We use speckles with their unique patterns and contrast, formed when fluorescence from individual neurons propagates through rodent cortical tissue, to encode neuronal activity. Spatiotemporal demixing of these patterns then enables functional recording of neuronal activity from a group of discriminable sources. For the first time, we provide an experimental, in vivo characterization of speckle generation, speckle imaging and speckle-assisted demixing of neuronal activity signals in the scattering mammalian brain tissue. We found that despite an initial fast speckle decorrelation, substantial correlation was maintained over minute-long timescales that contributed to our ability to demix temporal activity traces in the mouse brain in vivo. Informed by in vivo quantifications of speckle patterns from single and multiple neurons excited using 2P scanning excitation, we recorded and demixed activity from several sources excited using 1P oblique illumination. In our proof-of-principle experiments, we demonstrate in vivo speckle-assisted demixing of functional signals from groups of sources in a depth range of 220-320 µm in mouse cortex, limited by available speckle contrast. Our results serve as a basis for designing an in vivo functional speckle imaging modality and for maximizing the key resource in any such modality, the speckle contrast. We anticipate that our results will provide critical quantitative guidance to the community for designing techniques that overcome light scattering as a fundamental limitation in bioimaging.
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Affiliation(s)
- Hossein Sarafraz
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
| | - Tobias Nöbauer
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
| | - Fernando Soldevila
- Laboratoire Kastler Brossel, ENS–Université PSL, CNRS, Sorbonne Université, College de France, 24 Rue Lhomond, F-75005 Paris, France
| | - Sylvain Gigan
- Laboratoire Kastler Brossel, ENS–Université PSL, CNRS, Sorbonne Université, College de France, 24 Rue Lhomond, F-75005 Paris, France
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY, USA
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Liu G, Chen B, Tian Z, Zhong Q, Chen SC. Compressive sensing-based multi-focus line-scanning two-photon microscopy for fast 3D imaging. OPTICS EXPRESS 2024; 32:17143-17151. [PMID: 38858904 DOI: 10.1364/oe.522671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 04/03/2024] [Indexed: 06/12/2024]
Abstract
Fast 3D volume imaging methods have been playing increasingly important roles in biological studies. In this article, we present the design and characterization of a multi-focus line-scanning two-photon microscope. Specifically, a digital micromirror device (DMD) is employed to generate a randomly distributed focus array on a plane (i.e., x-z) via binary holography. Next, a galvanometric mirror scans the focus array in a direction normal to the plane (i.e., y-axis) over the imaging volume. For sparse samples, e.g., neural networks in a brain, 1-3 foci are used together with compressive sensing algorithm to achieve a volume imaging rate of 15.5 volumes/sec over 77 × 120 × 40 µm3. High-resolution optical cross-sectional images on selected planes and regions can be generated by sequentially scanning the laser focus generated on the x-z plane with good imaging speeds (e.g., 107 frames/sec over 80 × 120 × 40 µm3). In the experiments, microbeads, pollens, and mouse brain slices have been imaged to characterize the point spread function and volume image rate and quality at different sampling ratios. The results show that the multi-focus line-scanning microscope presents a fast and versatile 3D imaging platform for deep tissue imaging and dynamic live animal studies.
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9
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Mahdy S, Abuelmakarem HS. Alzheimer's disease progression detection based on optical fluence rate measurements using alternative laser wavelengths. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2024; 40:e3816. [PMID: 38523567 DOI: 10.1002/cnm.3816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 01/14/2024] [Accepted: 03/11/2024] [Indexed: 03/26/2024]
Abstract
Alzheimer's disease (AD) levels have increased globally, which is considered the sixth reason for deaths. So, a requirement exists for economic and quantitative methods to follow up the gradual progression of AD. The current study presents a simulation for a non-irradiated, safe, wearable, and noninvasive mobile approach for detecting the progression of Alzheimer's brain atrophy using the optical diffusion technique and for investigating the difference between the normal and the diseased brain. The virtual study was accomplished using COMSOL Multiphysics. The simulated head is implemented as the following: scalp, skull, cerebrospinal fluid, gray matter, and white matter. The optical properties of the heterogeneous tissue are observed using the fluence rate after irradiating the head with different wavelengths (630, 700, 810, 915, and 1000 nm) of lasers. Two assessment techniques were applied to evaluate the brain atrophy measurements; the first technique was an array of photodetectors, which were lined at the head posterior, while a matrix of photodetectors was applied over the head surface in the second technique. The results show that the surface photodetectors approach differentiates the normal from AD brains without measuring the brain atrophy percentages by applying 630 nm. The array of photodetectors distinguishes normal from AD brains without detecting the brain atrophy percentages when the wavelengths 630, 700, and 810 nm were applied. The line detector at 1000 nm evaluates the brain atrophy percentages with AD. The future explores applying those techniques in vivo and analyzing the information by the spectrometer for extensively safer early detection of neural disorders.
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Affiliation(s)
- Shimaa Mahdy
- Department of Electrical Engineering, Egyptian Academy for Engineering and Advanced Technology (EAE&AT), Affiliated to the Ministry of Military Production, El-Nahda, Al Salam First, Egypt
| | - Hala S Abuelmakarem
- SBME Department, The Higher Institute of Engineering, El Shrouk Academy, Cairo, Egypt
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10
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Chen B, Chang BJ, Daetwyler S, Zhou F, Sharma S, Lee DM, Nayak A, Noh J, Dubrovinski K, Chen EH, Glotzer M, Fiolka R. Projective light-sheet microscopy with flexible parameter selection. Nat Commun 2024; 15:2755. [PMID: 38553438 PMCID: PMC10980818 DOI: 10.1038/s41467-024-46693-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Accepted: 03/07/2024] [Indexed: 04/02/2024] Open
Abstract
Projection imaging accelerates volumetric interrogation in fluorescence microscopy, but for multi-cellular samples, the resulting images may lack contrast, as many structures and haze are summed up. Here, we demonstrate rapid projective light-sheet imaging with parameter selection (props) of imaging depth, position and viewing angle. This allows us to selectively image different sub-volumes of a sample, rapidly switch between them and exclude background fluorescence. Here we demonstrate the power of props by functional imaging within distinct regions of the zebrafish brain, monitoring calcium firing inside muscle cells of moving Drosophila larvae, super-resolution imaging of selected cell layers, and by optically unwrapping the curved surface of a Drosophila embryo. We anticipate that props will accelerate volumetric interrogation, ranging from subcellular to mesoscopic scales.
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Affiliation(s)
- Bingying Chen
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bo-Jui Chang
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Stephan Daetwyler
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Felix Zhou
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Shiv Sharma
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Donghoon M Lee
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Amruta Nayak
- Department of Molecular Genetics and Cell Biology, University of Chicago, Chicago, IL, USA
| | - Jungsik Noh
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Konstantin Dubrovinski
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Elizabeth H Chen
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Michael Glotzer
- Department of Molecular Genetics and Cell Biology, University of Chicago, Chicago, IL, USA
| | - Reto Fiolka
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
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11
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Luu P, Fraser SE, Schneider F. More than double the fun with two-photon excitation microscopy. Commun Biol 2024; 7:364. [PMID: 38531976 DOI: 10.1038/s42003-024-06057-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 03/15/2024] [Indexed: 03/28/2024] Open
Abstract
For generations researchers have been observing the dynamic processes of life through the lens of a microscope. This has offered tremendous insights into biological phenomena that span multiple orders of time- and length-scales ranging from the pure magic of molecular reorganization at the membrane of immune cells, to cell migration and differentiation during development or wound healing. Standard fluorescence microscopy techniques offer glimpses at such processes in vitro, however, when applied in intact systems, they are challenged by reduced signal strengths and signal-to-noise ratios that result from deeper imaging. As a remedy, two-photon excitation (TPE) microscopy takes a special place, because it allows us to investigate processes in vivo, in their natural environment, even in a living animal. Here, we review the fundamental principles underlying TPE aimed at basic and advanced microscopy users interested in adopting TPE for intravital imaging. We focus on applications in neurobiology, present current trends towards faster, wider and deeper imaging, discuss the combination with photon counting technologies for metabolic imaging and spectroscopy, as well as highlight outstanding issues and drawbacks in development and application of these methodologies.
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Affiliation(s)
- Peter Luu
- Translational Imaging Center, Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Biological Sciences, Division of Molecular and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
| | - Scott E Fraser
- Translational Imaging Center, Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Biological Sciences, Division of Molecular and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
- Alfred Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Falk Schneider
- Translational Imaging Center, Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, CA, 90089, USA.
- Dana and David Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, 90089, USA.
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12
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Kume D, Kozawa Y, Kawakami R, Ishii H, Watakabe Y, Uesugi Y, Imamura T, Nemoto T, Sato S. Graded arc beam in light needle microscopy for axially resolved, rapid volumetric imaging without nonlinear processes. OPTICS EXPRESS 2024; 32:7289-7306. [PMID: 38439413 DOI: 10.1364/oe.516437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/06/2024] [Indexed: 03/06/2024]
Abstract
High-speed three-dimensional (3D) imaging is essential for revealing the structure and functions of biological specimens. Confocal laser scanning microscopy has been widely employed for this purpose. However, it requires a time-consuming image-stacking procedure. As a solution, we previously developed light needle microscopy using a Bessel beam with a wavefront-engineered approach [Biomed. Opt. Express13, 1702 (2022)10.1364/BOE.449329]. However, this method applies only to multiphoton excitation microscopy because of the requirement to reduce the sidelobes of the Bessel beam. Here, we introduce a beam that produces a needle spot while eluding the intractable artifacts due to the sidelobes. This beam can be adopted even in one-photon excitation fluorescence 3D imaging. The proposed method can achieve real-time, rapid 3D observation of 200-nm particles in water at a rate of over 50 volumes per second. In addition, fine structures, such as the spines of neurons in fixed mouse brain tissue, can be visualized in 3D from a single raster scan of the needle spot. The proposed method can be applied to various modalities in biological imaging, enabling rapid 3D image acquisition.
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13
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Ataka M, Otomo K, Enoki R, Ishii H, Tsutsumi M, Kozawa Y, Sato S, Nemoto T. Multibeam continuous axial scanning two-photon microscopy for in vivo volumetric imaging in mouse brain. BIOMEDICAL OPTICS EXPRESS 2024; 15:1089-1101. [PMID: 38404301 PMCID: PMC10890896 DOI: 10.1364/boe.514826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/12/2024] [Accepted: 01/15/2024] [Indexed: 02/27/2024]
Abstract
This study presents an alternative approach for two-photon volumetric imaging that combines multibeam lateral scanning with continuous axial scanning using a confocal spinning-disk scanner and an electrically focus tunable lens. Using this proposed system, the brain of a living mouse could be imaged at a penetration depth of over 450 μm from the surface. In vivo volumetric Ca2+ imaging at a volume rate of 1.5 Hz within a depth range of 130-200 μm, was segmented with an axial pitch of approximately 5-µm and revealed spontaneous activity of neurons with their 3D positions. This study offers a practical microscope design equipped with compact scanners, a simple control system, and readily adjustable imaging parameters, which is crucial for the widespread adoption of two-photon volumetric imaging.
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Affiliation(s)
- Mitsutoshi Ataka
- National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8787, Japan
| | - Kohei Otomo
- National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Ryosuke Enoki
- National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- School of Life Sciences, The Graduate School of Advanced Studies, SOKENDAI, Okazaki 444-8787, Japan
| | - Hirokazu Ishii
- National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- School of Life Sciences, The Graduate School of Advanced Studies, SOKENDAI, Okazaki 444-8787, Japan
| | - Motosuke Tsutsumi
- National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- School of Life Sciences, The Graduate School of Advanced Studies, SOKENDAI, Okazaki 444-8787, Japan
| | - Yuichi Kozawa
- Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan
| | - Shunichi Sato
- Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan
| | - Tomomi Nemoto
- National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki 444-8787, Japan
- School of Life Sciences, The Graduate School of Advanced Studies, SOKENDAI, Okazaki 444-8787, Japan
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14
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Fernholz MHP, Guggiana Nilo DA, Bonhoeffer T, Kist AM. DeepD3, an open framework for automated quantification of dendritic spines. PLoS Comput Biol 2024; 20:e1011774. [PMID: 38422112 PMCID: PMC10903918 DOI: 10.1371/journal.pcbi.1011774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 12/20/2023] [Indexed: 03/02/2024] Open
Abstract
Dendritic spines are the seat of most excitatory synapses in the brain, and a cellular structure considered central to learning, memory, and activity-dependent plasticity. The quantification of dendritic spines from light microscopy data is usually performed by humans in a painstaking and error-prone process. We found that human-to-human variability is substantial (inter-rater reliability 82.2±6.4%), raising concerns about the reproducibility of experiments and the validity of using human-annotated 'ground truth' as an evaluation method for computational approaches of spine identification. To address this, we present DeepD3, an open deep learning-based framework to robustly quantify dendritic spines in microscopy data in a fully automated fashion. DeepD3's neural networks have been trained on data from different sources and experimental conditions, annotated and segmented by multiple experts and they offer precise quantification of dendrites and dendritic spines. Importantly, these networks were validated in a number of datasets on varying acquisition modalities, species, anatomical locations and fluorescent indicators. The entire DeepD3 open framework, including the fully segmented training data, a benchmark that multiple experts have annotated, and the DeepD3 model zoo is fully available, addressing the lack of openly available datasets of dendritic spines while offering a ready-to-use, flexible, transparent, and reproducible spine quantification method.
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Affiliation(s)
| | | | - Tobias Bonhoeffer
- Max-Planck-Institute for Biological Intelligence, Martinsried, Bavaria, Germany
| | - Andreas M. Kist
- Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Bavaria, Germany
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15
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Lees RM, Bianco IH, Campbell RAA, Orlova N, Peterka DS, Pichler B, Smith SL, Yatsenko D, Yu CH, Packer AM. Standardised Measurements for Monitoring and Comparing Multiphoton Microscope Systems. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576417. [PMID: 38328224 PMCID: PMC10849699 DOI: 10.1101/2024.01.23.576417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The goal of this protocol is to enable better characterisation of multiphoton microscopy hardware across a large user base. The scope of this protocol is purposefully limited to focus on hardware, touching on software and data analysis routines only where relevant. The intended audiences are scientists using and building multiphoton microscopes in their laboratories. The goal is that any scientist, not only those with optical expertise, can test whether their multiphoton microscope is performing well and producing consistent data over the lifetime of their system.
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Affiliation(s)
- Robert M Lees
- Science and Technology Facilities Council, Octopus imaging facility, Research Complex at Harwell, Harwell Campus, Oxfordshire, UK
| | - Isaac H Bianco
- Department of Neuroscience, Physiology & Pharmacology, University College London, UK
| | | | | | - Darcy S Peterka
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Bruno Pichler
- Independent NeuroScience Services INSS Ltd, Lewes, East Sussex, UK
| | - Spencer LaVere Smith
- Department of Electrical and Computer Engineering, University of California Santa Barbara, USA
| | | | - Che-Hang Yu
- Department of Electrical and Computer Engineering, University of California Santa Barbara, USA
| | - Adam M Packer
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
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16
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Chen Y, Luo C, Wang S, Li Y, Shen B, Hu R, Qu J, Liu L. Rapid, high-contrast, and steady volumetric imaging with Bessel-beam-based two-photon fluorescence microscopy. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:016501. [PMID: 38269082 PMCID: PMC10807873 DOI: 10.1117/1.jbo.29.1.016501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 12/24/2023] [Accepted: 01/02/2024] [Indexed: 01/26/2024]
Abstract
Significance Two-photon fluorescence microscopy (TPFM) excited by Gaussian beams requires axial tomographic scanning for three-dimensional (3D) volumetric imaging, which is a time-consuming process, and the slow imaging speed hinders its application for in vivo brain imaging. The Bessel focus, characterized by an extended depth of focus and constant resolution, facilitates the projection of a 3D volume onto a two-dimensional image, which significantly enhances the speed of volumetric imaging. Aim We aimed to demonstrate the ability of a TPFM with a sidelobe-free Bessel beam to provide a promising tool for research in live biological specimens. Approach Comparative in vivo imaging was conducted in live mouse brains and transgenic zebrafish to evaluate the performance of TPFM and Bessel-beam-based TPFM. Additionally, an image-difference method utilizing zeroth-order and third-order Bessel beams was introduced to effectively suppress background interference introduced by sidelobes. Results In comparison with traditional TPFM, the Bessel-beams-based TPFM demonstrated a 30-fold increase in imaging throughput and speed. Furthermore, the effectiveness of the image-difference method was validated in live biological specimens, resulting in a substantial enhancement of image contrast. Importantly, our TPFM with a sidelobe-free Bessel beam exhibited robustness against axial displacements, a feature of considerable value for in vivo experiments. Conclusions We achieved rapid, high-contrast, and robust volumetric imaging of the vasculature in live mouse brains and transgenic zebrafish using our TPFM with a sidelobe-free Bessel beam.
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Affiliation(s)
- Yongqiang Chen
- Shenzhen University, College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province, Ministry of Education, Shenzhen, China
| | - Chenggui Luo
- Shenzhen University, College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province, Ministry of Education, Shenzhen, China
| | - Shiqi Wang
- Shenzhen University, College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province, Ministry of Education, Shenzhen, China
| | - Yanping Li
- Shenzhen University, College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province, Ministry of Education, Shenzhen, China
| | - Binglin Shen
- Shenzhen University, College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province, Ministry of Education, Shenzhen, China
| | - Rui Hu
- Shenzhen University, College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province, Ministry of Education, Shenzhen, China
| | - Junle Qu
- Shenzhen University, College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province, Ministry of Education, Shenzhen, China
| | - Liwei Liu
- Shenzhen University, College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province, Ministry of Education, Shenzhen, China
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17
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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: 6] [Impact Index Per Article: 6.0] [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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18
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Shymkiv Y, Yuste R. Aberration-free holographic microscope for simultaneous imaging and stimulation of neuronal populations. OPTICS EXPRESS 2023; 31:33461-33474. [PMID: 37859128 PMCID: PMC10544954 DOI: 10.1364/oe.498051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 08/26/2023] [Accepted: 09/07/2023] [Indexed: 10/21/2023]
Abstract
A technical challenge in neuroscience is to record and specifically manipulate the activity of neurons in living animals. This can be achieved in some preparations with two-photon calcium imaging and photostimulation. These methods can be extended to three dimensions by holographic light sculpting with spatial light modulators (SLMs). At the same time, performing simultaneous holographic imaging and photostimulation is still cumbersome, requiring two light paths with separate SLMs. Here we present an integrated optical design using a single SLM for simultaneous imaging and photostimulation. Furthermore, we applied axially dependent adaptive optics to make the system aberration-free, and developed software for calibrations and closed-loop neuroscience experiments. Finally, we demonstrate the performance of the system with simultaneous calcium imaging and optogenetics in mouse primary auditory cortex in vivo. Our integrated holographic system could facilitate the systematic investigation of neural circuit function in awake behaving animals.
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Affiliation(s)
- Yuriy Shymkiv
- Neurotechnology Center, Dept. Biological Sciences, Columbia University, New York, NY, USA
| | - Rafael Yuste
- Neurotechnology Center, Dept. Biological Sciences, Columbia University, New York, NY, USA
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19
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Pasarkar A, Kinsella I, Zhou P, Wu M, Pan D, Fan JL, Wang Z, Abdeladim L, Peterka DS, Adesnik H, Ji N, Paninski L. maskNMF: A denoise-sparsen-detect approach for extracting neural signals from dense imaging data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.14.557777. [PMID: 37745388 PMCID: PMC10515957 DOI: 10.1101/2023.09.14.557777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
A number of calcium imaging methods have been developed to monitor the activity of large populations of neurons. One particularly promising approach, Bessel imaging, captures neural activity from a volume by projecting within the imaged volume onto a single imaging plane, therefore effectively mixing signals and increasing the number of neurons imaged per pixel. These signals must then be computationally demixed to recover the desired neural activity. Unfortunately, currently-available demixing methods can perform poorly in the regime of high imaging density (i.e., many neurons per pixel). In this work we introduce a new pipeline (maskNMF) for demixing dense calcium imaging data. The main idea is to first denoise and temporally sparsen the observed video; this enhances signal strength and reduces spatial overlap significantly. Next we detect neurons in the sparsened video using a neural network trained on a library of neural shapes. These shapes are derived from segmented electron microscopy images input into a Bessel imaging model; therefore no manual selection of "good" neural shapes from the functional data is required here. After cells are detected, we use a constrained non-negative matrix factorization approach to demix the activity, using the detected cells' shapes to initialize the factorization. We test the resulting pipeline on both simulated and real datasets and find that it is able to achieve accurate demixing on denser data than was previously feasible, therefore enabling faithful imaging of larger neural populations. The method also provides good results on more "standard" two-photon imaging data. Finally, because much of the pipeline operates on a significantly compressed version of the raw data and is highly parallelizable, the algorithm is fast, processing large datasets faster than real time.
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Affiliation(s)
- Amol Pasarkar
- Center for Theoretical Neuroscience and Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
- Department of Computer Science, Columbia University, New York, NY, 10027, USA
| | - Ian Kinsella
- Center for Theoretical Neuroscience and Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
- Department of Statistics, Columbia University, New York, NY, 10027, USA
| | - Pengcheng Zhou
- Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China
| | - Melissa Wu
- Department of Biomedical Engineering, Duke University, Durham, NC 27708
| | - Daisong Pan
- Department of Physics, University of California, Berkeley, California 94720, USA
| | - Jiang Lan Fan
- Joint Bioengineering Graduate Program, University of California, Berkeley, CA 94720
| | - Zhen Wang
- Department of Electrical and Computer Engineering, UCLA, Los Angeles, CA, 90095, USA
| | - Lamiae Abdeladim
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Darcy S Peterka
- Center for Theoretical Neuroscience and Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Hillel Adesnik
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Na Ji
- Department of Physics, University of California, Berkeley, California 94720, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Liam Paninski
- Center for Theoretical Neuroscience and Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
- Department of Statistics, Columbia University, New York, NY, 10027, USA
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20
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Chen R, Peng S, Zhu L, Meng J, Fan X, Feng Z, Zhang H, Qian J. Enhancing Total Optical Throughput of Microscopy with Deep Learning for Intravital Observation. SMALL METHODS 2023; 7:e2300172. [PMID: 37183924 DOI: 10.1002/smtd.202300172] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/17/2023] [Indexed: 05/16/2023]
Abstract
The significance of performing large-depth dynamic microscopic imaging in vivo for life science research cannot be overstated. However, the optical throughput of the microscope limits the available information per unit of time, i.e., it is difficult to obtain both high spatial and temporal resolution at once. Here, a method is proposed to construct a kind of intravital microscopy with high optical throughput, by making near-infrared-II (NIR-II, 900-1880 nm) wide-field fluorescence microscopy learn from two-photon fluorescence microscopy based on a scale-recurrent network. Using this upgraded NIR-II fluorescence microscope, vessels in the opaque brain of a rodent are reconstructed three-dimensionally. Five-fold axial and thirteen-fold lateral resolution improvements are achieved without sacrificing temporal resolution and light utilization. Also, tiny cerebral vessel dilatations in early acute respiratory failure mice are observed, with this high optical throughput NIR-II microscope at an imaging speed of 30 fps.
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Affiliation(s)
- Runze Chen
- College of Optical Science and Engineering, State Key Laboratory of Modern Optical Instrumentations, International Research Center for Advanced Photonics, Centre for Optical and Electromagnetic Research, Zhejiang University, 310058, Hangzhou, China
| | - Shiyi Peng
- College of Optical Science and Engineering, State Key Laboratory of Modern Optical Instrumentations, International Research Center for Advanced Photonics, Centre for Optical and Electromagnetic Research, Zhejiang University, 310058, Hangzhou, China
| | - Liang Zhu
- College of Biomedical Engineering and Instrument Science, Interdisciplinary Institute of Neuroscience and Technology (ZIINT), Zhejiang University, 310027, Hangzhou, China
| | - Jia Meng
- College of Optical Science and Engineering, State Key Laboratory of Modern Optical Instrumentations, International Research Center for Advanced Photonics, Centre for Optical and Electromagnetic Research, Zhejiang University, 310058, Hangzhou, China
| | - Xiaoxiao Fan
- College of Optical Science and Engineering, State Key Laboratory of Modern Optical Instrumentations, International Research Center for Advanced Photonics, Centre for Optical and Electromagnetic Research, Zhejiang University, 310058, Hangzhou, China
| | - Zhe Feng
- College of Optical Science and Engineering, State Key Laboratory of Modern Optical Instrumentations, International Research Center for Advanced Photonics, Centre for Optical and Electromagnetic Research, Zhejiang University, 310058, Hangzhou, China
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Zhejiang University, 310058, Hangzhou, China
| | - Hequn Zhang
- College of Optical Science and Engineering, State Key Laboratory of Modern Optical Instrumentations, International Research Center for Advanced Photonics, Centre for Optical and Electromagnetic Research, Zhejiang University, 310058, Hangzhou, China
| | - Jun Qian
- College of Optical Science and Engineering, State Key Laboratory of Modern Optical Instrumentations, International Research Center for Advanced Photonics, Centre for Optical and Electromagnetic Research, Zhejiang University, 310058, Hangzhou, China
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Zhejiang University, 310058, Hangzhou, China
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21
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Liang Y, Lu R, Borges K, Ji N. Stimulus edges induce orientation tuning in superior colliculus. Nat Commun 2023; 14:4756. [PMID: 37553352 PMCID: PMC10409754 DOI: 10.1038/s41467-023-40444-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 07/27/2023] [Indexed: 08/10/2023] Open
Abstract
Orientation columns exist in the primary visual cortex (V1) of cat and primates but not mouse. Intriguingly, some recent studies reported the presence of orientation and direction columns in the mouse superficial superior colliculus (sSC), while others reported a lack of columnar organization therein. Using in vivo calcium imaging of sSC in the awake mouse brain, we found that the presence of columns is highly stimulus dependent. Specifically, we observed orientation and direction columns formed by sSC neurons retinotopically mapped to the edge of grating stimuli. For both excitatory and inhibitory neurons in sSC, orientation selectivity can be induced by the edge with their preferred orientation perpendicular to the edge orientation. Furthermore, we found that this edge-induced orientation selectivity is associated with saliency encoding. These findings indicate that the tuning properties of sSC neurons are not fixed by circuit architecture but rather dependent on the spatiotemporal properties of the stimulus.
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Affiliation(s)
- Yajie Liang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20148, USA
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Rongwen Lu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20148, USA
| | - Katharine Borges
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA
| | - Na Ji
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20148, USA.
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA.
- Department of Physics, University of California, Berkeley, CA, 94720, USA.
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA.
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
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22
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Tucker SS, Giblin JT, Kiliç K, Chen A, Tang J, Boas DA. Optical coherence tomography-based design for a real-time motion corrected scanning microscope. OPTICS LETTERS 2023; 48:3805-3808. [PMID: 37450755 DOI: 10.1364/ol.490087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023]
Abstract
While two-photon fluorescence microscopy is a powerful platform for the study of functional dynamics in living cells and tissues, the bulk motion inherent to these applications causes distortions. We have designed a motion tracking module based on spectral domain optical coherence tomography which compliments a laser scanning two-photon microscope with real-time corrective feedback. The module can be added to fluorescent imaging microscopes using a single dichroic and without additional contrast agents. We demonstrate that the system can track lateral displacements as large as 10 μm at 5 Hz with latency under 14 ms and propose a scheme to extend the system to 3D correction with the addition of a remote focusing module. We also propose several ways to improve the module's performance by reducing the feedback latency. We anticipate that this design can be adapted to other imaging modalities, enabling the study of samples subject to motion artifacts at higher resolution.
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23
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Guo Y, Wang L, Luo Z, Zhu Y, Gao X, Weng X, Wang Y, Yan W, Qu J. Dynamic Volumetric Imaging of Mouse Cerebral Blood Vessels In Vivo with an Ultralong Anti-Diffracting Beam. Molecules 2023; 28:4936. [PMID: 37446598 DOI: 10.3390/molecules28134936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 06/19/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
Volumetric imaging of a mouse brain in vivo with one-photon and two-photon ultralong anti-diffracting (UAD) beam illumination was performed. The three-dimensional (3D) structure of blood vessels in the mouse brain were mapped to a two-dimensional (2D) image. The speed of volumetric imaging was significantly improved due to the long focal length of the UAD beam. Comparing one-photon and two-photon UAD beam volumetric imaging, we found that the imaging depth of two-photon volumetric imaging (80 μm) is better than that of one-photon volumetric imaging (60 μm), and the signal-to-background ratio (SBR) of two-photon volumetric imaging is two times that of one-photon volumetric imaging. Therefore, we used two-photon UAD volumetric imaging to perform dynamic volumetric imaging of mouse brain blood vessels in vivo, and obtained the blood flow velocity.
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Affiliation(s)
- Yong Guo
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
| | - Luwei Wang
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
| | - Ziyi Luo
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
| | - Yinru Zhu
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
| | - Xinwei Gao
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
| | - Xiaoyu Weng
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
| | - Yiping Wang
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
| | - Wei Yan
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
| | - Junle Qu
- State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, China
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24
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Zhao Z, Zhou Y, Liu B, He J, Zhao J, Cai Y, Fan J, Li X, Wang Z, Lu Z, Wu J, Qi H, Dai Q. Two-photon synthetic aperture microscopy for minimally invasive fast 3D imaging of native subcellular behaviors in deep tissue. Cell 2023; 186:2475-2491.e22. [PMID: 37178688 DOI: 10.1016/j.cell.2023.04.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/21/2023] [Accepted: 04/10/2023] [Indexed: 05/15/2023]
Abstract
Holistic understanding of physio-pathological processes requires noninvasive 3D imaging in deep tissue across multiple spatial and temporal scales to link diverse transient subcellular behaviors with long-term physiogenesis. Despite broad applications of two-photon microscopy (TPM), there remains an inevitable tradeoff among spatiotemporal resolution, imaging volumes, and durations due to the point-scanning scheme, accumulated phototoxicity, and optical aberrations. Here, we harnessed the concept of synthetic aperture radar in TPM to achieve aberration-corrected 3D imaging of subcellular dynamics at a millisecond scale for over 100,000 large volumes in deep tissue, with three orders of magnitude reduction in photobleaching. With its advantages, we identified direct intercellular communications through migrasome generation following traumatic brain injury, visualized the formation process of germinal center in the mouse lymph node, and characterized heterogeneous cellular states in the mouse visual cortex, opening up a horizon for intravital imaging to understand the organizations and functions of biological systems at a holistic level.
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Affiliation(s)
- Zhifeng Zhao
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China; Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou 311100, China
| | - Yiliang Zhou
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China; Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou 311100, China
| | - Bo Liu
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China; Laboratory of Dynamic Immunobiology, Institute for Immunology, Tsinghua University, Beijing 100084, China; Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Jing He
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Jiayin Zhao
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518071, China
| | - Yeyi Cai
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Jingtao Fan
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China
| | - Xinyang Li
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou 311100, China; Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518071, China
| | - Zilin Wang
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Department of Anesthesiology, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Zhi Lu
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China; Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou 311100, China
| | - Jiamin Wu
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China.
| | - Hai Qi
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China; Laboratory of Dynamic Immunobiology, Institute for Immunology, Tsinghua University, Beijing 100084, China; Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory for Immunological Research on Chronic Diseases, Tsinghua University, Beijing 100084, China; Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing 100084, China.
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China.
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25
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Romero-Ferrero F, Heras FJH, Rance D, de Polavieja GG. A study of transfer of information in animal collectives using deep learning tools. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220073. [PMID: 36802786 PMCID: PMC9939271 DOI: 10.1098/rstb.2022.0073] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2023] Open
Abstract
We studied how the interactions among animals in a collective allow for the transfer of information. We performed laboratory experiments to study how zebrafish in a collective follow a subset of trained animals that move towards a light when it turns on because they expect food at that location. We built some deep learning tools to distinguish from video which are the trained and the naïve animals and to detect when each animal reacts to the light turning on. These tools gave us the data to build a model of interactions that we designed to have a balance between transparency and accuracy. The model finds a low-dimensional function that describes how a naïve animal weights neighbours depending on focal and neighbour variables. According to this low-dimensional function, neighbour speed plays an important role in the interactions. Specifically, a naïve animal weights more a neighbour in front than to the sides or behind, and more so the faster the neighbour is moving; and if the neighbour moves fast enough, the differences coming from the neighbour's relative position largely disappear. From the lens of decision-making, neighbour speed acts as confidence measure about where to go. This article is part of a discussion meeting issue 'Collective behaviour through time'.
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Affiliation(s)
| | | | - Dean Rance
- Champalimaud Research, Champalimaud Foundation, 1400-038 Lisbon, Portugal
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26
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Hernández IC, Yau J, Rishøj L, Cui N, Minderler S, Jowett N. Tutorial: multiphoton microscopy to advance neuroscience research. Methods Appl Fluoresc 2023; 11. [PMID: 36753763 DOI: 10.1088/2050-6120/acba66] [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: 10/03/2022] [Accepted: 02/08/2023] [Indexed: 02/10/2023]
Abstract
Multiphoton microscopy (MPM) employs ultrafast infrared lasers for high-resolution deep three-dimensional imaging of live biological samples. The goal of this tutorial is to provide a practical guide to MPM imaging for novice microscopy developers and life-science users. Principles of MPM, microscope setup, and labeling strategies are discussed. Use of MPM to achieve unprecedented imaging depth of whole mounted explants and intravital imaging via implantable glass windows of the mammalian nervous system is demonstrated.
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Affiliation(s)
- Iván Coto Hernández
- Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Harvard Medical School, 243 Charles St, Boston, MA, United States of America
| | - Jenny Yau
- Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Harvard Medical School, 243 Charles St, Boston, MA, United States of America
| | - Lars Rishøj
- Technical University of Denmark, DTU Electro, Ørsteds Plads 343, 2800 Kgs. Lyngby, Denmark
| | - Nanke Cui
- Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Harvard Medical School, 243 Charles St, Boston, MA, United States of America
| | - Steven Minderler
- Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Harvard Medical School, 243 Charles St, Boston, MA, United States of America
| | - Nate Jowett
- Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Harvard Medical School, 243 Charles St, Boston, MA, United States of America
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27
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Xiao Y, Deng P, Zhao Y, Yang S, Li B. Three-photon excited fluorescence imaging in neuroscience: From principles to applications. Front Neurosci 2023; 17:1085682. [PMID: 36891460 PMCID: PMC9986337 DOI: 10.3389/fnins.2023.1085682] [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: 10/31/2022] [Accepted: 02/02/2023] [Indexed: 02/22/2023] Open
Abstract
The development of three-photon microscopy (3PM) has greatly expanded the capability of imaging deep within biological tissues, enabling neuroscientists to visualize the structure and activity of neuronal populations with greater depth than two-photon imaging. In this review, we outline the history and physical principles of 3PM technology. We cover the current techniques for improving the performance of 3PM. Furthermore, we summarize the imaging applications of 3PM for various brain regions and species. Finally, we discuss the future of 3PM applications for neuroscience.
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Affiliation(s)
| | | | | | | | - Bo Li
- State Key Laboratory of Medical Neurobiology, Department of Neurology, Ministry of Education (MOE), Frontiers Center for Brain Science, Institute for Translational Brain Research, Huashan Hospital, Fudan University, Shanghai, China
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28
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Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit. Nat Biotechnol 2023; 41:282-292. [PMID: 36163547 PMCID: PMC9931589 DOI: 10.1038/s41587-022-01450-8] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 07/29/2022] [Indexed: 11/09/2022]
Abstract
A fundamental challenge in fluorescence microscopy is the photon shot noise arising from the inevitable stochasticity of photon detection. Noise increases measurement uncertainty and limits imaging resolution, speed and sensitivity. To achieve high-sensitivity fluorescence imaging beyond the shot-noise limit, we present DeepCAD-RT, a self-supervised deep learning method for real-time noise suppression. Based on our previous framework DeepCAD, we reduced the number of network parameters by 94%, memory consumption by 27-fold and processing time by a factor of 20, allowing real-time processing on a two-photon microscope. A high imaging signal-to-noise ratio can be acquired with tenfold fewer photons than in standard imaging approaches. We demonstrate the utility of DeepCAD-RT in a series of photon-limited experiments, including in vivo calcium imaging of mice, zebrafish larva and fruit flies, recording of three-dimensional (3D) migration of neutrophils after acute brain injury and imaging of 3D dynamics of cortical ATP release. DeepCAD-RT will facilitate the morphological and functional interrogation of biological dynamics with a minimal photon budget.
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29
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Liu Y, Shuai K, Sun Y, Zhu L, Wu XM. Advances in the study of axon-associated vesicles. Front Mol Neurosci 2022; 15:1045778. [PMID: 36545123 PMCID: PMC9760877 DOI: 10.3389/fnmol.2022.1045778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022] Open
Abstract
The central nervous system is the most important and difficult to study system in the human body and is known for its complex functions, components, and mechanisms. Neurons are the basic cellular units realizing neural functions. In neurons, vesicles are one of the critical pathways for intracellular material transport, linking information exchanges inside and outside cells. The axon is a vital part of neuron since electrical and molecular signals must be conducted through axons. Here, we describe and explore the formation, trafficking, and sorting of cellular vesicles within axons, as well as related-diseases and practical implications. Furthermore, with deepening of understanding and the development of new approaches, accumulating evidence proves that besides signal transmission between synapses, the material exchange and vesicular transmission between axons and extracellular environment are involved in physiological processes, and consequently to neural pathology. Recent studies have also paid attention to axonal vesicles and their physiological roles and pathological effects on axons themselves. Therefore, this review mainly focuses on these two key nodes to explain the role of intracellular vesicles and extracellular vesicles migrated from cells on axons and neurons, providing innovative strategy for future researches.
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Affiliation(s)
- Yanling Liu
- Institute of Special Environmental Medicine, Nantong University, Nantong, Jiangsu, China
| | - Ke Shuai
- Institute of Special Environmental Medicine, Nantong University, Nantong, Jiangsu, China
| | - Yiyan Sun
- Institute of Special Environmental Medicine, Nantong University, Nantong, Jiangsu, China
| | - Li Zhu
- Institute of Special Environmental Medicine, Nantong University, Nantong, Jiangsu, China,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu, China
| | - Xiao-Mei Wu
- Institute of Special Environmental Medicine, Nantong University, Nantong, Jiangsu, China,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu, China,*Correspondence: Xiao-Mei Wu,
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30
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Bai L, Zhang Z, Ye L, Cong L, Zhao Y, Zhang T, Shi Z, Wang K. Volumetric Imaging of Neural Activity by Light Field Microscopy. Neurosci Bull 2022; 38:1559-1568. [PMID: 35939199 PMCID: PMC9723040 DOI: 10.1007/s12264-022-00923-9] [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: 03/18/2022] [Accepted: 06/10/2022] [Indexed: 10/15/2022] Open
Abstract
Recording the highly diverse and dynamic activities in large populations of neurons in behaving animals is crucial for a better understanding of how the brain works. To meet this challenge, extensive efforts have been devoted to developing functional fluorescent indicators and optical imaging techniques to optically monitor neural activity. Indeed, optical imaging potentially has extremely high throughput due to its non-invasive access to large brain regions and capability to sample neurons at high density, but the readout speed, such as the scanning speed in two-photon scanning microscopy, is often limited by various practical considerations. Among different imaging methods, light field microscopy features a highly parallelized 3D fluorescence imaging scheme and therefore promises a novel and faster strategy for functional imaging of neural activity. Here, we briefly review the working principles of various types of light field microscopes and their recent developments and applications in neuroscience studies. We also discuss strategies and considerations of optimizing light field microscopy for different experimental purposes, with illustrative examples in imaging zebrafish and mouse brains.
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Affiliation(s)
- Lu Bai
- Institute of Neuroscience, State Key Laboratory of Neuroscience, 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
| | - Zhenkun Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, 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
| | - Lichen Ye
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Lin Cong
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuchen Zhao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, 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
| | - Tianlei Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, 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
| | - Ziqi Shi
- Institute of Neuroscience, State Key Laboratory of Neuroscience, 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
| | - Kai Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, 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.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 201210, China.
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31
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Zhou Y, Sun N, Hu S. Deep Learning-Powered Bessel-Beam Multiparametric Photoacoustic Microscopy. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:3544-3551. [PMID: 35788453 PMCID: PMC9767649 DOI: 10.1109/tmi.2022.3188739] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Enabling simultaneous and high-resolution quantification of the total concentration of hemoglobin ( [Formula: see text]), oxygen saturation of hemoglobin (sO2), and cerebral blood flow (CBF), multi-parametric photoacoustic microscopy (PAM) has emerged as a promising tool for functional and metabolic imaging of the live mouse brain. However, due to the limited depth of focus imposed by the Gaussian-beam excitation, the quantitative measurements become inaccurate when the imaging object is out of focus. To address this problem, we have developed a hardware-software combined approach by integrating Bessel-beam excitation and conditional generative adversarial network (cGAN)-based deep learning. Side-by-side comparison of the new cGAN-powered Bessel-beam multi-parametric PAM against the conventional Gaussian-beam multi-parametric PAM shows that the new system enables high-resolution, quantitative imaging of [Formula: see text], sO2, and CBF over a depth range of [Formula: see text] in the live mouse brain, with errors 13-58 times lower than those of the conventional system. Better fulfilling the rigid requirement of light focusing for accurate hemodynamic measurements, the deep learning-powered Bessel-beam multi-parametric PAM may find applications in large-field functional recording across the uneven brain surface and beyond (e.g., tumor imaging).
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32
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Benisty H, Song A, Mishne G, Charles AS. Review of data processing of functional optical microscopy for neuroscience. NEUROPHOTONICS 2022; 9:041402. [PMID: 35937186 PMCID: PMC9351186 DOI: 10.1117/1.nph.9.4.041402] [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: 01/04/2022] [Accepted: 07/15/2022] [Indexed: 05/04/2023]
Abstract
Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.
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Affiliation(s)
- Hadas Benisty
- Yale Neuroscience, New Haven, Connecticut, United States
| | - Alexander Song
- Max Planck Institute for Intelligent Systems, Stuttgart, Germany
| | - Gal Mishne
- UC San Diego, Halıcığlu Data Science Institute, Department of Electrical and Computer Engineering and the Neurosciences Graduate Program, La Jolla, California, United States
| | - Adam S. Charles
- Johns Hopkins University, Kavli Neuroscience Discovery Institute, Center for Imaging Science, Department of Biomedical Engineering, Department of Neuroscience, and Mathematical Institute for Data Science, Baltimore, Maryland, United States
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33
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Grienberger C, Giovannucci A, Zeiger W, Portera-Cailliau C. Two-photon calcium imaging of neuronal activity. NATURE REVIEWS. METHODS PRIMERS 2022; 2:67. [PMID: 38124998 PMCID: PMC10732251 DOI: 10.1038/s43586-022-00147-1] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/07/2022] [Indexed: 12/23/2023]
Abstract
In vivo two-photon calcium imaging (2PCI) is a technique used for recording neuronal activity in the intact brain. It is based on the principle that, when neurons fire action potentials, intracellular calcium levels rise, which can be detected using fluorescent molecules that bind to calcium. This Primer is designed for scientists who are considering embarking on experiments with 2PCI. We provide the reader with a background on the basic concepts behind calcium imaging and on the reasons why 2PCI is an increasingly powerful and versatile technique in neuroscience. The Primer explains the different steps involved in experiments with 2PCI, provides examples of what ideal preparations should look like and explains how data are analysed. We also discuss some of the current limitations of the technique, and the types of solutions to circumvent them. Finally, we conclude by anticipating what the future of 2PCI might look like, emphasizing some of the analysis pipelines that are being developed and international efforts for data sharing.
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Affiliation(s)
- Christine Grienberger
- Department of Biology and Volen National Center for Complex Systems, Brandeis University, Waltham, MA, USA
| | - Andrea Giovannucci
- Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - William Zeiger
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Carlos Portera-Cailliau
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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34
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Meng Q, Li Y, Yu Y, Chu K, Smith ZJ. A Drop-in, Focus-Extending Phase Mask Simplifies Microscopic and Microfluidic Imaging Systems for Cost-Effective Point-of-Care Diagnostics. Anal Chem 2022; 94:11000-11007. [PMID: 35895976 DOI: 10.1021/acs.analchem.2c01421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Microscopic imaging and imaging flow cytometry have wide potential in point-of-care assays; however, their narrow depth of focus necessitates precise mechanical or fluidic focus control of a sample in order to acquire high-quality images that can be used for downstream analysis, increasing the cost and complexity of the imaging system. This complexity represents a barrier to miniaturization and translation of point-of-care assays based on microscopic imaging or imaging flow cytometry. To address this challenge, we present a simple drop-in phase mask with a physics-informed, circularly symmetric asphere phase profile that extends the depth of focus by >5-fold while largely preserving the image quality compared to other depth extending methods. We show that such a focus-extended system overcomes manufacturing tolerances in low-cost sample chambers, enlarges the useable field-of-view of low-cost objectives, and permits increased throughput and precision in flow imaging systems without the need for complex flow-focusing. As the image quality is preserved without the need for postacquisition image restoration, our solution is also highly appropriate for on-line applications such as cell sorting.
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Affiliation(s)
- Qi Meng
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yaning Li
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yajun Yu
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Kaiqin Chu
- Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, China
| | - Zachary J Smith
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230027, China
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35
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Xu D, Ding JB, Peng L. Depth random-access two-photon Bessel light-sheet imaging in brain tissue. OPTICS EXPRESS 2022; 30:26396-26406. [PMID: 36236832 PMCID: PMC9363024 DOI: 10.1364/oe.456871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 05/27/2022] [Accepted: 06/07/2022] [Indexed: 06/16/2023]
Abstract
Two-photon light-sheet fluorescence microscopy enables high-resolution imaging of neural activity in brain tissue at a high frame rate. Traditionally, light-sheet microscopy builds up a 3D stack by multiple depth scans with uniform spatial intervals, which substantially limits the volumetric imaging speed. Here, we introduce the depth random-access light-sheet microscopy, allowing rapid switching scanning depth for light-sheet imaging. With a low-cost electrically tunable lens and minimum modification of an existing two-photon light-sheet imaging instrument, we demonstrated fast random depth hopping light-sheet imaging at 100 frames per second in the live brain slice. Through depth random-access, calcium activities for an astrocyte were recorded on four user-selected detection planes at a refreshing rate of 25 Hz.
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Affiliation(s)
- Dongli Xu
- College of Optical Science, The University of Arizona, Tucson, AZ 85721, USA
- Department of Neurosurgery, Department of Neurology and Neurological Sciences, Wu-Tsai Neuroscience Institute, Stanford University, Stanford, CA 94305, USA
| | - Jun B. Ding
- Department of Neurosurgery, Department of Neurology and Neurological Sciences, Wu-Tsai Neuroscience Institute, Stanford University, Stanford, CA 94305, USA
| | - Leilei Peng
- College of Optical Science, The University of Arizona, Tucson, AZ 85721, USA
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36
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Wlodkowic D, Bownik A, Leitner C, Stengel D, Braunbeck T. Beyond the behavioural phenotype: Uncovering mechanistic foundations in aquatic eco-neurotoxicology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 829:154584. [PMID: 35306067 DOI: 10.1016/j.scitotenv.2022.154584] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 03/09/2022] [Accepted: 03/11/2022] [Indexed: 06/14/2023]
Abstract
During the last decade, there has been an increase in awareness of how anthropogenic pollution can alter behavioural traits of diverse aquatic organisms. Apart from understanding profound ecological implications, alterations in neuro-behavioural indices have emerged as sensitive and physiologically integrative endpoints in chemical risk assessment. Accordingly, behavioural ecotoxicology and broader eco-neurotoxicology are becoming increasingly popular fields of research that span a plethora of fundamental laboratory experimentations as well as applied field-based studies. Despite mounting interest in aquatic behavioural ecotoxicology studies, there is, however, a considerable paucity in deciphering the mechanistic foundations underlying behavioural alterations upon exposure to pollutants. The behavioural phenotype is indeed the highest-level integrative neurobiological phenomenon, but at its core lie myriads of intertwined biochemical, cellular, and physiological processes. Therefore, the mechanisms that underlie changes in behavioural phenotypes can stem among others from dysregulation of neurotransmitter pathways, electrical signalling, and cell death of discrete cell populations in the central and peripheral nervous systems. They can, however, also be a result of toxicity to sensory organs and even metabolic dysfunctions. In this critical review, we outline why behavioural phenotyping should be the starting point that leads to actual discovery of fundamental mechanisms underlying actions of neurotoxic and neuromodulating contaminants. We highlight potential applications of the currently existing and emerging neurobiology and neurophysiology analytical strategies that should be embraced and more broadly adopted in behavioural ecotoxicology. Such strategies can provide new mechanistic discoveries instead of only observing the end sum phenotypic effects.
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Affiliation(s)
- Donald Wlodkowic
- The Neurotox Laboratory, School of Science, RMIT University, Melbourne, Australia.
| | - Adam Bownik
- Department of Hydrobiology and Protection of Ecosystems, Faculty of Environmental Biology, University of Life Sciences, Lublin, Poland
| | - Carola Leitner
- Aquatic Ecology and Toxicology, Centre for Organismal Studies, University of Heidelberg, Im Neuenheimer Feld 504, D-69120 Heidelberg, Germany
| | - Daniel Stengel
- Aquatic Ecology and Toxicology, Centre for Organismal Studies, University of Heidelberg, Im Neuenheimer Feld 504, D-69120 Heidelberg, Germany
| | - Thomas Braunbeck
- Aquatic Ecology and Toxicology, Centre for Organismal Studies, University of Heidelberg, Im Neuenheimer Feld 504, D-69120 Heidelberg, Germany
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37
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Shi L, Jiang Y, Zheng N, Cheng JX, Yang C. High-precision neural stimulation through optoacoustic emitters. NEUROPHOTONICS 2022; 9:032207. [PMID: 35355658 PMCID: PMC8941197 DOI: 10.1117/1.nph.9.3.032207] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 02/25/2022] [Indexed: 05/03/2023]
Abstract
Neuromodulation poses an invaluable role in deciphering neural circuits and exploring clinical treatment of neurological diseases. Optoacoustic neuromodulation is an emerging modality benefiting from the merits of ultrasound with high penetration depth as well as the merits of photons with high spatial precision. We summarize recent development in a variety of optoacoustic platforms for neural modulation, including fiber, film, and nanotransducer-based devices, highlighting the key advantages of each platform. The possible mechanisms and main barriers for optoacoustics as a viable neuromodulation tool are discussed. Future directions in fundamental and translational research are proposed.
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Affiliation(s)
- Linli Shi
- Boston University, Department of Chemistry, Boston, Massachusetts, United States
| | - Ying Jiang
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Nan Zheng
- Boston University, Division of Materials Science and Engineering, Boston, Massachusetts, United States
| | - Ji-Xin Cheng
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Boston University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States
- Address all correspondence to Chen Yang, ; Ji-Xin Cheng,
| | - Chen Yang
- Boston University, Department of Chemistry, Boston, Massachusetts, United States
- Boston University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States
- Address all correspondence to Chen Yang, ; Ji-Xin Cheng,
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38
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Russell LE, Dalgleish HWP, Nutbrown R, Gauld OM, Herrmann D, Fişek M, Packer AM, Häusser M. All-optical interrogation of neural circuits in behaving mice. Nat Protoc 2022; 17:1579-1620. [PMID: 35478249 PMCID: PMC7616378 DOI: 10.1038/s41596-022-00691-w] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 02/09/2022] [Indexed: 12/22/2022]
Abstract
Recent advances combining two-photon calcium imaging and two-photon optogenetics with computer-generated holography now allow us to read and write the activity of large populations of neurons in vivo at cellular resolution and with high temporal resolution. Such 'all-optical' techniques enable experimenters to probe the effects of functionally defined neurons on neural circuit function and behavioral output with new levels of precision. This greatly increases flexibility, resolution, targeting specificity and throughput compared with alternative approaches based on electrophysiology and/or one-photon optogenetics and can interrogate larger and more densely labeled populations of neurons than current voltage imaging-based implementations. This protocol describes the experimental workflow for all-optical interrogation experiments in awake, behaving head-fixed mice. We describe modular procedures for the setup and calibration of an all-optical system (~3 h), the preparation of an indicator and opsin-expressing and task-performing animal (~3-6 weeks), the characterization of functional and photostimulation responses (~2 h per field of view) and the design and implementation of an all-optical experiment (achievable within the timescale of a normal behavioral experiment; ~3-5 h per field of view). We discuss optimizations for efficiently selecting and targeting neuronal ensembles for photostimulation sequences, as well as generating photostimulation response maps from the imaging data that can be used to examine the impact of photostimulation on the local circuit. We demonstrate the utility of this strategy in three brain areas by using different experimental setups. This approach can in principle be adapted to any brain area to probe functional connectivity in neural circuits and investigate the relationship between neural circuit activity and behavior.
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Affiliation(s)
- Lloyd E Russell
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Henry W P Dalgleish
- Wolfson Institute for Biomedical Research, University College London, London, UK
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Rebecca Nutbrown
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Oliver M Gauld
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Dustin Herrmann
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Mehmet Fişek
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Adam M Packer
- Wolfson Institute for Biomedical Research, University College London, London, UK.
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK.
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39
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Lee S, Lee K, Choi M, Park J. Implantable acousto-optic window for monitoring ultrasound-mediated neuromodulation in vivo. NEUROPHOTONICS 2022; 9:032203. [PMID: 35874142 PMCID: PMC9298854 DOI: 10.1117/1.nph.9.3.032203] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 07/01/2022] [Indexed: 06/15/2023]
Abstract
Significance: Ultrasound has recently received considerable attention in neuroscience because it provides noninvasive control of deep brain activity. Although the feasibility of ultrasound stimulation has been reported in preclinical and clinical settings, its mechanistic understanding remains limited. While optical microscopy has become the "gold standard" tool for investigating population-level neural functions in vivo, its application for ultrasound neuromodulation has been technically challenging, as most conventional ultrasonic transducers are not designed to be compatible with optical microscopy. Aim: We aimed to develop a transparent acoustic transducer based on a glass coverslip called the acousto-optic window (AOW), which simultaneously provides ultrasound neuromodulation and microscopic monitoring of neural responses in vivo. Approach: The AOW was fabricated by the serial deposition of transparent acoustic stacks on a circular glass coverslip, comprising a piezoelectric material, polyvinylidene fluoride-trifluoroethylene, and indium-tin-oxide electrodes. The fabricated AOW was implanted into a transgenic neural-activity reporter mouse after open craniotomy. Two-photon microscopy was used to observe neuronal activity in response to ultrasonic stimulation through the AOW. Results: The AOW allowed microscopic imaging of calcium activity in cortical neurons in response to ultrasound stimulation. The optical transparency was ∼ 40 % over the visible and near-infrared spectra, and the ultrasonic pressure was 0.035 MPa at 10 MHz corresponding to 10 mW / cm 2 . In anesthetized Gad2-GCaMP6-tdTomato mice, we observed robust ultrasound-evoked activation of inhibitory cortical neurons at depths up to 200 μ m . Conclusions: The AOW is an implantable ultrasonic transducer that is broadly compatible with optical imaging modalities. The AOW will facilitate our understanding of ultrasound neuromodulation in vivo.
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Affiliation(s)
- Sungho Lee
- Seoul National University, School of Biological Sciences, Seoul, Republic of Korea
- Seoul National University, Institute of Molecular Biology and Genetics, Seoul, Republic of Korea
| | - Keunhyung Lee
- Sungkyunkwan University, Department of Intelligent Precision Healthcare Convergence, Suwon, Republic of Korea
| | - Myunghwan Choi
- Seoul National University, School of Biological Sciences, Seoul, Republic of Korea
- Seoul National University, Institute of Molecular Biology and Genetics, Seoul, Republic of Korea
| | - Jinhyoung Park
- Sungkyunkwan University, Department of Intelligent Precision Healthcare Convergence, Suwon, Republic of Korea
- Sungkyunkwan University, Department of Biomedical Engineering, Suwon, Republic of Korea
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Single-scan volumetric imaging throughout thick tissue specimens by one-touch installable light-needle creating device. Sci Rep 2022; 12:10468. [PMID: 35729283 PMCID: PMC9213396 DOI: 10.1038/s41598-022-14647-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 06/09/2022] [Indexed: 11/23/2022] Open
Abstract
Biological tissues and their networks frequently change dynamically across large volumes. Understanding network operations requires monitoring their activities in three dimensions (3D) with single-cell resolution. Several researchers have proposed various volumetric imaging technologies. However, most technologies require large-scale and complicated optical setups, as well as deep expertise for microscopic technologies, resulting in a high threshold for biologists. In this study, we propose an easy-to-use light-needle creating device for conventional two-photon microscopy systems. By only installing the device in one position for a filter cube that conventional fluorescent microscopes have, single scanning of the excitation laser light beam excited fluorophores throughout over 200 μm thickness specimens simultaneously. Furthermore, the developed microscopy system successfully demonstrated single-scan visualization of the 3D structure of transparent YFP-expressing brain slices. Finally, in acute mouse cortical slices with a thickness of approximately 250 μm, we detected calcium activities with 7.5 Hz temporal resolution in the neuronal population.
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41
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Sinefeld D, Xia F, Wang M, Wang T, Wu C, Yang X, Paudel HP, Ouzounov DG, Bifano TG, Xu C. Three-Photon Adaptive Optics for Mouse Brain Imaging. Front Neurosci 2022; 16:880859. [PMID: 35692424 PMCID: PMC9185169 DOI: 10.3389/fnins.2022.880859] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/05/2022] [Indexed: 11/24/2022] Open
Abstract
Three-photon microscopy (3PM) was shown to allow deeper imaging than two-photon microscopy (2PM) in scattering biological tissues, such as the mouse brain, since the longer excitation wavelength reduces tissue scattering and the higher-order non-linear excitation suppresses out-of-focus background fluorescence. Imaging depth and resolution can further be improved by aberration correction using adaptive optics (AO) techniques where a spatial light modulator (SLM) is used to correct wavefront aberrations. Here, we present and analyze a 3PM AO system for in vivo mouse brain imaging. We use a femtosecond source at 1300 nm to generate three-photon (3P) fluorescence in yellow fluorescent protein (YFP) labeled mouse brain and a microelectromechanical (MEMS) SLM to apply different Zernike phase patterns. The 3P fluorescence signal is used as feedback to calculate the amount of phase correction without direct phase measurement. We show signal improvement in the cortex and the hippocampus at greater than 1 mm depth and demonstrate close to diffraction-limited imaging in the cortical layers of the brain, including imaging of dendritic spines. In addition, we characterize the effective volume for AO correction within brain tissues, and discuss the limitations of AO correction in 3PM of mouse brain.
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Affiliation(s)
- David Sinefeld
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
- Department of Applied Physics, Electro-Optics Engineering Faculty, Jerusalem College of Technology, Jerusalem, Israel
- *Correspondence: David Sinefeld,
| | - Fei Xia
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Mengran Wang
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
| | - Tianyu Wang
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
| | - Chunyan Wu
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
| | - Xusan Yang
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
| | - Hari P. Paudel
- Photonics Center, Boston University, Boston, MA, United States
| | - Dimitre G. Ouzounov
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
| | | | - Chris Xu
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
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42
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Charles AS, Cermak N, Affan RO, Scott BB, Schiller J, Mishne G. GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2022; 31:3509-3524. [PMID: 35533160 PMCID: PMC9278524 DOI: 10.1109/tip.2022.3171414] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Optical imaging of calcium signals in the brain has enabled researchers to observe the activity of hundreds-to-thousands of individual neurons simultaneously. Current methods predominantly use morphological information, typically focusing on expected shapes of cell bodies, to better identify neurons in the field-of-view. The explicit shape constraints limit the applicability of automated cell identification to other important imaging scales with more complex morphologies, e.g., dendritic or widefield imaging. Specifically, fluorescing components may be broken up, incompletely found, or merged in ways that do not accurately describe the underlying neural activity. Here we present Graph Filtered Temporal Dictionary (GraFT), a new approach that frames the problem of isolating independent fluorescing components as a dictionary learning problem. Specifically, we focus on the time-traces-the main quantity used in scientific discovery-and learn a time trace dictionary with the spatial maps acting as the presence coefficients encoding which pixels the time-traces are active in. Furthermore, we present a novel graph filtering model which redefines connectivity between pixels in terms of their shared temporal activity, rather than spatial proximity. This model greatly eases the ability of our method to handle data with complex non-local spatial structure. We demonstrate important properties of our method, such as robustness to morphology, simultaneously detecting different neuronal types, and implicitly inferring number of neurons, on both synthetic data and real data examples. Specifically, we demonstrate applications of our method to calcium imaging both at the dendritic, somatic, and widefield scales.
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43
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Ul Alam S, Kumar Soni N, Srinivasa Rao A, He H, Ren YX, Wong KKY. Two-photon microscopy with enhanced resolution and signal-to-background ratio using hollow Gaussian beam excitation. OPTICS LETTERS 2022; 47:2048-2051. [PMID: 35427333 DOI: 10.1364/ol.454140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 03/18/2022] [Indexed: 06/14/2023]
Abstract
Two-photon microscopy (TPM) offers deeper imaging depth inside the scattering medium, however, it suffers from limited resolution owing to the longer excitation wavelength. We demonstrate the use of a hollow Gaussian beam (HGB) at the therapeutic window to improve the resolution and signal-to-background ratio (SBR). The HGB was produced by omitting the azimuthal phase term from the vortex mode, and the excitation point spread function (PSF) can be readily tuned by the mode order. The performance of the TPM with HGB was evaluated by experimentally imaging 100 nm fluorescent beads to estimate the PSF. The HGB improved the lateral resolution of the TPM by 36% in contrast to the conventional TPM. The HGB also furnishes an improvement of SBR by eliminating the out-of-focus light owing to its ring shape. Furthermore, we have used a translating lens-based module for additional lateral resolution tuning and reduced the resolution further down to 44% with respect to conventional TPM. Finally, we have performed imaging with merely two-dimensional scanning of a 50 µm thick mouse brain slice (Thy-YFP H-line) using the developed TPM with HGB. Our compact, robust, and low-cost design of the HGB generation scheme can easily be integrated into the commercial TPM to accommodate the improvements.
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44
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Tran CHT. Toolbox for studying neurovascular coupling in vivo, with a focus on vascular activity and calcium dynamics in astrocytes. NEUROPHOTONICS 2022; 9:021909. [PMID: 35295714 PMCID: PMC8920490 DOI: 10.1117/1.nph.9.2.021909] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 02/23/2022] [Indexed: 05/14/2023]
Abstract
Significance: Insights into the cellular activity of each member of the neurovascular unit (NVU) is critical for understanding their contributions to neurovascular coupling (NVC)-one of the key control mechanisms in cerebral blood flow regulation. Advances in imaging and genetic tools have enhanced our ability to observe, manipulate and understand the cellular activity of NVU components, namely neurons, astrocytes, microglia, endothelial cells, vascular smooth muscle cells, and pericytes. However, there are still many unresolved questions. Since astrocytes are considered electrically unexcitable,Ca 2 + signaling is the main parameter used to monitor their activity. It is therefore imperative to study astrocyticCa 2 + dynamics simultaneously with vascular activity using tools appropriate for the question of interest. Aim: To highlight currently available genetic and imaging tools for studying the NVU-and thus NVC-with a focus on astrocyteCa 2 + dynamics and vascular activity, and discuss the utility, technical advantages, and limitations of these tools for elucidating NVC mechanisms. Approach: We draw attention to some outstanding questions regarding the mechanistic basis of NVC and emphasize the role of astrocyticCa 2 + elevations in functional hyperemia. We further discuss commonly used genetic, and optical imaging tools, as well as some newly developed imaging modalities for studying NVC at the cellular level, highlighting their advantages and limitations. Results: We provide an overview of the current state of NVC research, focusing on the role of astrocyticCa 2 + elevations in functional hyperemia; summarize recent advances in genetically engineeredCa 2 + indicators, fluorescence microscopy techniques for studying NVC; and discuss the unmet challenges for future imaging development. Conclusions: Advances in imaging techniques together with improvements in genetic tools have significantly contributed to our understanding of NVC. Many pieces of the puzzle have been revealed, but many more remain to be discovered. Ultimately, optimizing NVC research will require a concerted effort to improve imaging techniques, available genetic tools, and analytical software.
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Affiliation(s)
- Cam Ha T. Tran
- University of Nevada, Reno School of Medicine, Department of Physiology and Cell Biology, Reno, Nevada, United States
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45
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Ito KN, Isobe K, Osakada F. Fast z-focus controlling and multiplexing strategies for multiplane two-photon imaging of neural dynamics. Neurosci Res 2022; 179:15-23. [DOI: 10.1016/j.neures.2022.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 03/18/2022] [Indexed: 10/18/2022]
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46
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Kozawa Y, Nakamura T, Uesugi Y, Sato S. Wavefront engineered light needle microscopy for axially resolved rapid volumetric imaging. BIOMEDICAL OPTICS EXPRESS 2022; 13:1702-1717. [PMID: 35415006 PMCID: PMC8973193 DOI: 10.1364/boe.449329] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/09/2022] [Accepted: 02/15/2022] [Indexed: 06/14/2023]
Abstract
Increasing the acquisition speed of three-dimensional volumetric images is important-particularly in biological imaging-to unveil the structural dynamics and functionalities of specimens in detail. In conventional laser scanning fluorescence microscopy, volumetric images are constructed from optical sectioning images sequentially acquired by changing the observation plane, limiting the acquisition speed. Here, we present a novel method to realize volumetric imaging from two-dimensional raster scanning of a light needle spot without sectioning, even in the traditional framework of laser scanning microscopy. Information from multiple axial planes is simultaneously captured using wavefront engineering for fluorescence signals, allowing us to readily survey the entire depth range while maintaining spatial resolution. This technique is applied to real-time and video-rate three-dimensional tracking of micrometer-sized particles, as well as the prompt visualization of thick fixed biological specimens, offering substantially faster volumetric imaging.
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Affiliation(s)
- Yuichi Kozawa
- Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan
| | - Tomoya Nakamura
- SANKEN, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan
| | - Yuuki Uesugi
- Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan
| | - Shunichi Sato
- Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan
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47
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Janiak FK, Bartel P, Bale MR, Yoshimatsu T, Komulainen E, Zhou M, Staras K, Prieto-Godino LL, Euler T, Maravall M, Baden T. Non-telecentric two-photon microscopy for 3D random access mesoscale imaging. Nat Commun 2022; 13:544. [PMID: 35087041 PMCID: PMC8795402 DOI: 10.1038/s41467-022-28192-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 01/04/2022] [Indexed: 01/07/2023] Open
Abstract
Diffraction-limited two-photon microscopy permits minimally invasive optical monitoring of neuronal activity. However, most conventional two-photon microscopes impose significant constraints on the size of the imaging field-of-view and the specific shape of the effective excitation volume, thus limiting the scope of biological questions that can be addressed and the information obtainable. Here, employing a non-telecentric optical design, we present a low-cost, easily implemented and flexible solution to address these limitations, offering a several-fold expanded three-dimensional field of view. Moreover, rapid laser-focus control via an electrically tunable lens allows near-simultaneous imaging of remote regions separated in three dimensions and permits the bending of imaging planes to follow natural curvatures in biological structures. Crucially, our core design is readily implemented (and reversed) within a matter of hours, making it highly suitable as a base platform for further development. We demonstrate the application of our system for imaging neuronal activity in a variety of examples in zebrafish, mice and fruit flies.
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Affiliation(s)
- F K Janiak
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK.
| | - P Bartel
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK
| | - M R Bale
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK
| | - T Yoshimatsu
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK
| | - E Komulainen
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK
| | - M Zhou
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK
| | - K Staras
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK
| | | | - T Euler
- Institute of Ophthalmic Research, University of Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
| | - M Maravall
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK
| | - T Baden
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK.
- Institute of Ophthalmic Research, University of Tübingen, Tübingen, Germany.
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48
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Kim TH, Schnitzer MJ. Fluorescence imaging of large-scale neural ensemble dynamics. Cell 2022; 185:9-41. [PMID: 34995519 PMCID: PMC8849612 DOI: 10.1016/j.cell.2021.12.007] [Citation(s) in RCA: 75] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/14/2022]
Abstract
Recent progress in fluorescence imaging allows neuroscientists to observe the dynamics of thousands of individual neurons, identified genetically or by their connectivity, across multiple brain areas and for extended durations in awake behaving mammals. We discuss advances in fluorescent indicators of neural activity, viral and genetic methods to express these indicators, chronic animal preparations for long-term imaging studies, and microscopes to monitor and manipulate the activity of large neural ensembles. Ca2+ imaging studies of neural activity can track brain area interactions and distributed information processing at cellular resolution. Across smaller spatial scales, high-speed voltage imaging reveals the distinctive spiking patterns and coding properties of targeted neuron types. Collectively, these innovations will propel studies of brain function and dovetail with ongoing neuroscience initiatives to identify new neuron types and develop widely applicable, non-human primate models. The optical toolkit's growing sophistication also suggests that "brain observatory" facilities would be useful open resources for future brain-imaging studies.
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Affiliation(s)
- Tony Hyun Kim
- James Clark Center for Biomedical Engineering & Sciences, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
| | - Mark J Schnitzer
- James Clark Center for Biomedical Engineering & Sciences, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
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49
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Li B, Tan S, Dong J, Lian X, Zhang Y, Ji X, Veeraraghavan A. Deep-3D microscope: 3D volumetric microscopy of thick scattering samples using a wide-field microscope and machine learning. BIOMEDICAL OPTICS EXPRESS 2022; 13:284-299. [PMID: 35154871 PMCID: PMC8803017 DOI: 10.1364/boe.444488] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 12/02/2021] [Accepted: 12/03/2021] [Indexed: 06/14/2023]
Abstract
Confocal microscopy is a standard approach for obtaining volumetric images of a sample with high axial and lateral resolution, especially when dealing with scattering samples. Unfortunately, a confocal microscope is quite expensive compared to traditional microscopes. In addition, the point scanning in confocal microscopy leads to slow imaging speed and photobleaching due to the high dose of laser energy. In this paper, we demonstrate how the advances in machine learning can be exploited to "teach" a traditional wide-field microscope, one that's available in every lab, into producing 3D volumetric images like a confocal microscope. The key idea is to obtain multiple images with different focus settings using a wide-field microscope and use a 3D generative adversarial network (GAN) based neural network to learn the mapping between the blurry low-contrast image stacks obtained using a wide-field microscope and the sharp, high-contrast image stacks obtained using a confocal microscope. After training the network with widefield-confocal stack pairs, the network can reliably and accurately reconstruct 3D volumetric images that rival confocal images in terms of its lateral resolution, z-sectioning and image contrast. Our experimental results demonstrate generalization ability to handle unseen data, stability in the reconstruction results, high spatial resolution even when imaging thick (∼40 microns) highly-scattering samples. We believe that such learning-based microscopes have the potential to bring confocal imaging quality to every lab that has a wide-field microscope.
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Affiliation(s)
- Bowen Li
- Department of Automation & BNRist, Tsinghua University, Beijing, China
| | - Shiyu Tan
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
| | - Jiuyang Dong
- Tsinghua Shenzhen International Graduate School, Shenzhen, China
| | - Xiaocong Lian
- Department of Automation & BNRist, Tsinghua University, Beijing, China
| | - Yongbing Zhang
- Harbin Institute of Technology (Shenzhen), Shenzhen, China
| | - Xiangyang Ji
- Department of Automation & BNRist, Tsinghua University, Beijing, China
| | - Ashok Veeraraghavan
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
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Abdelfattah AS, Ahuja S, Akkin T, Allu SR, Brake J, Boas DA, Buckley EM, Campbell RE, Chen AI, Cheng X, Čižmár T, Costantini I, De Vittorio M, Devor A, Doran PR, El Khatib M, Emiliani V, Fomin-Thunemann N, Fainman Y, Fernandez-Alfonso T, Ferri CGL, Gilad A, Han X, Harris A, Hillman EMC, Hochgeschwender U, Holt MG, Ji N, Kılıç K, Lake EMR, Li L, Li T, Mächler P, Miller EW, Mesquita RC, Nadella KMNS, Nägerl UV, Nasu Y, Nimmerjahn A, Ondráčková P, Pavone FS, Perez Campos C, Peterka DS, Pisano F, Pisanello F, Puppo F, Sabatini BL, Sadegh S, Sakadzic S, Shoham S, Shroff SN, Silver RA, Sims RR, Smith SL, Srinivasan VJ, Thunemann M, Tian L, Tian L, Troxler T, Valera A, Vaziri A, Vinogradov SA, Vitale F, Wang LV, Uhlířová H, Xu C, Yang C, Yang MH, Yellen G, Yizhar O, Zhao Y. Neurophotonic tools for microscopic measurements and manipulation: status report. NEUROPHOTONICS 2022; 9:013001. [PMID: 35493335 PMCID: PMC9047450 DOI: 10.1117/1.nph.9.s1.013001] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Ahmed S. Abdelfattah
- Brown University, Department of Neuroscience, Providence, Rhode Island, United States
| | - Sapna Ahuja
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Taner Akkin
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, Minnesota, United States
| | - Srinivasa Rao Allu
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - David A. Boas
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Erin M. Buckley
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University, Department of Pediatrics, Atlanta, Georgia, United States
| | - Robert E. Campbell
- University of Tokyo, Department of Chemistry, Tokyo, Japan
- University of Alberta, Department of Chemistry, Edmonton, Alberta, Canada
| | - Anderson I. Chen
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Xiaojun Cheng
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Tomáš Čižmár
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Irene Costantini
- University of Florence, European Laboratory for Non-Linear Spectroscopy, Department of Biology, Florence, Italy
- National Institute of Optics, National Research Council, Rome, Italy
| | - Massimo De Vittorio
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Anna Devor
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Patrick R. Doran
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Mirna El Khatib
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | | | - Natalie Fomin-Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Yeshaiahu Fainman
- University of California San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
| | - Tomas Fernandez-Alfonso
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Christopher G. L. Ferri
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Ariel Gilad
- The Hebrew University of Jerusalem, Institute for Medical Research Israel–Canada, Department of Medical Neurobiology, Faculty of Medicine, Jerusalem, Israel
| | - Xue Han
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Andrew Harris
- Weizmann Institute of Science, Department of Brain Sciences, Rehovot, Israel
| | | | - Ute Hochgeschwender
- Central Michigan University, Department of Neuroscience, Mount Pleasant, Michigan, United States
| | - Matthew G. Holt
- University of Porto, Instituto de Investigação e Inovação em Saúde (i3S), Porto, Portugal
| | - Na Ji
- University of California Berkeley, Department of Physics, Berkeley, California, United States
| | - Kıvılcım Kılıç
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Evelyn M. R. Lake
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, Connecticut, United States
| | - Lei Li
- California Institute of Technology, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, Pasadena, California, United States
| | - Tianqi Li
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, Minnesota, United States
| | - Philipp Mächler
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Evan W. Miller
- University of California Berkeley, Departments of Chemistry and Molecular & Cell Biology and Helen Wills Neuroscience Institute, Berkeley, California, United States
| | | | | | - U. Valentin Nägerl
- Interdisciplinary Institute for Neuroscience University of Bordeaux & CNRS, Bordeaux, France
| | - Yusuke Nasu
- University of Tokyo, Department of Chemistry, Tokyo, Japan
| | - Axel Nimmerjahn
- Salk Institute for Biological Studies, Waitt Advanced Biophotonics Center, La Jolla, California, United States
| | - Petra Ondráčková
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Francesco S. Pavone
- National Institute of Optics, National Research Council, Rome, Italy
- University of Florence, European Laboratory for Non-Linear Spectroscopy, Department of Physics, Florence, Italy
| | - Citlali Perez Campos
- Columbia University, Zuckerman Mind Brain Behavior Institute, New York, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behavior Institute, New York, United States
| | - Filippo Pisano
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Ferruccio Pisanello
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Francesca Puppo
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Bernardo L. Sabatini
- Harvard Medical School, Howard Hughes Medical Institute, Department of Neurobiology, Boston, Massachusetts, United States
| | - Sanaz Sadegh
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Sava Sakadzic
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Shy Shoham
- New York University Grossman School of Medicine, Tech4Health and Neuroscience Institutes, New York, New York, United States
| | - Sanaya N. Shroff
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - R. Angus Silver
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Ruth R. Sims
- Sorbonne University, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Spencer L. Smith
- University of California Santa Barbara, Department of Electrical and Computer Engineering, Santa Barbara, California, United States
| | - Vivek J. Srinivasan
- New York University Langone Health, Departments of Ophthalmology and Radiology, New York, New York, United States
| | - Martin Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Lei Tian
- Boston University, Departments of Electrical Engineering and Biomedical Engineering, Boston, Massachusetts, United States
| | - Lin Tian
- University of California Davis, Department of Biochemistry and Molecular Medicine, Davis, California, United States
| | - Thomas Troxler
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Antoine Valera
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Alipasha Vaziri
- Rockefeller University, Laboratory of Neurotechnology and Biophysics, New York, New York, United States
- The Rockefeller University, The Kavli Neural Systems Institute, New York, New York, United States
| | - Sergei A. Vinogradov
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Flavia Vitale
- Center for Neuroengineering and Therapeutics, Departments of Neurology, Bioengineering, Physical Medicine and Rehabilitation, Philadelphia, Pennsylvania, United States
| | - Lihong V. Wang
- California Institute of Technology, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, Pasadena, California, United States
| | - Hana Uhlířová
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Chris Xu
- Cornell University, School of Applied and Engineering Physics, Ithaca, New York, United States
| | - Changhuei Yang
- California Institute of Technology, Departments of Electrical Engineering, Bioengineering and Medical Engineering, Pasadena, California, United States
| | - Mu-Han Yang
- University of California San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
| | - Gary Yellen
- Harvard Medical School, Department of Neurobiology, Boston, Massachusetts, United States
| | - Ofer Yizhar
- Weizmann Institute of Science, Department of Brain Sciences, Rehovot, Israel
| | - Yongxin Zhao
- Carnegie Mellon University, Department of Biological Sciences, Pittsburgh, Pennsylvania, United States
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