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Haziza S, Chrapkiewicz R, Zhang Y, Kruzhilin V, Li J, Li J, Delamare G, Swanson R, Buzsáki G, Kannan M, Vasan G, Lin MZ, Zeng H, Daigle TL, Schnitzer MJ. Imaging high-frequency voltage dynamics in multiple neuron classes of behaving mammals. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.15.607428. [PMID: 39185175 PMCID: PMC11343216 DOI: 10.1101/2024.08.15.607428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Fluorescent genetically encoded voltage indicators report transmembrane potentials of targeted cell-types. However, voltage-imaging instrumentation has lacked the sensitivity to track spontaneous or evoked high-frequency voltage oscillations in neural populations. Here we describe two complementary TEMPO voltage-sensing technologies that capture neural oscillations up to ~100 Hz. Fiber-optic TEMPO achieves ~10-fold greater sensitivity than prior photometry systems, allows hour-long recordings, and monitors two neuron-classes per fiber-optic probe in freely moving mice. With it, we uncovered cross-frequency-coupled theta- and gamma-range oscillations and characterized excitatory-inhibitory neural dynamics during hippocampal ripples and visual cortical processing. The TEMPO mesoscope images voltage activity in two cell-classes across a ~8-mm-wide field-of-view in head-fixed animals. In awake mice, it revealed sensory-evoked excitatory-inhibitory neural interactions and traveling gamma and 3-7 Hz waves in the visual cortex, and previously unreported propagation directions for hippocampal theta and beta waves. These technologies have widespread applications probing diverse oscillations and neuron-type interactions in healthy and diseased brains.
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Affiliation(s)
- Simon Haziza
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
| | - Radosław Chrapkiewicz
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
| | - Yanping Zhang
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Vasily Kruzhilin
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
| | - Jane Li
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
| | - Jizhou Li
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | | | - Rachel Swanson
- Neuroscience Institute, Langone Medical Center, New York University, New York, NY 10016, USA
| | - György Buzsáki
- Neuroscience Institute, Langone Medical Center, New York University, New York, NY 10016, USA
- Department of Neurology, Langone Medical Center, New York University, New York, NY 10016, USA
| | - Madhuvanthi Kannan
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Ganesh Vasan
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Michael Z Lin
- Departments of Bioengineering & Pediatrics, Stanford University, Stanford CA 94305, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Tanya L Daigle
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Mark J Schnitzer
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
- Lead contact
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2
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Leong LM, Storace DA. Imaging different cell populations in the mouse olfactory bulb using the genetically encoded voltage indicator ArcLight. NEUROPHOTONICS 2024; 11:033402. [PMID: 38288247 PMCID: PMC10823906 DOI: 10.1117/1.nph.11.3.033402] [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: 09/01/2023] [Revised: 11/30/2023] [Accepted: 12/14/2023] [Indexed: 01/31/2024]
Abstract
Genetically encoded voltage indicators (GEVIs) are protein-based optical sensors that allow for measurements from genetically defined populations of neurons. Although in vivo imaging in the mammalian brain with early generation GEVIs was difficult due to poor membrane expression and low signal-to-noise ratio, newer and more sensitive GEVIs have begun to make them useful for answering fundamental questions in neuroscience. We discuss principles of imaging using GEVIs and genetically encoded calcium indicators, both useful tools for in vivo imaging of neuronal activity, and review some of the recent mechanistic advances that have led to GEVI improvements. We provide an overview of the mouse olfactory bulb (OB) and discuss recent studies using the GEVI ArcLight to study different cell types within the bulb using both widefield and two-photon microscopy. Specific emphasis is placed on using GEVIs to begin to study the principles of concentration coding in the OB, how to interpret the optical signals from population measurements in the in vivo brain, and future developments that will push the field forward.
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Affiliation(s)
- Lee Min Leong
- Florida State University, Department of Biological Science, Tallahassee, Florida, United States
| | - Douglas A. Storace
- Florida State University, Department of Biological Science, Tallahassee, Florida, United States
- Florida State University, Program in Neuroscience, Tallahassee, Florida, United States
- Florida State University, Institute of Molecular Biophysics, Tallahassee, Florida, United States
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3
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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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4
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Sakamoto M, Yokoyama T. Probing neuronal activity with genetically encoded calcium and voltage fluorescent indicators. Neurosci Res 2024:S0168-0102(24)00076-2. [PMID: 38885881 DOI: 10.1016/j.neures.2024.06.004] [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: 02/06/2024] [Revised: 04/09/2024] [Accepted: 06/08/2024] [Indexed: 06/20/2024]
Abstract
Monitoring neural activity in individual neurons is crucial for understanding neural circuits and brain functions. The emergence of optical imaging technologies has dramatically transformed the field of neuroscience, enabling detailed observation of large-scale neuronal populations with both cellular and subcellular resolution. This transformation will be further accelerated by the integration of these imaging technologies and advanced big data analysis. Genetically encoded fluorescent indicators to detect neural activity with high signal-to-noise ratios are pivotal in this advancement. In recent years, these indicators have undergone significant developments, greatly enhancing the understanding of neural dynamics and networks. This review highlights the recent progress in genetically encoded calcium and voltage indicators and discusses the future direction of imaging techniques with big data analysis that deepens our understanding of the complexities of the brain.
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Affiliation(s)
- Masayuki Sakamoto
- Graduate School of Biostudies, Kyoto University, 53 Shogoin Kawara-cho, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Tatsushi Yokoyama
- Graduate School of Biostudies, Kyoto University, 53 Shogoin Kawara-cho, Sakyo-ku, Kyoto 606-8507, Japan
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5
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Sims RR, Bendifallah I, Grimm C, Lafirdeen ASM, Domínguez S, Chan CY, Lu X, Forget BC, St-Pierre F, Papagiakoumou E, Emiliani V. Scanless two-photon voltage imaging. Nat Commun 2024; 15:5095. [PMID: 38876987 PMCID: PMC11178882 DOI: 10.1038/s41467-024-49192-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 05/28/2024] [Indexed: 06/16/2024] Open
Abstract
Two-photon voltage imaging has long been heralded as a transformative approach capable of answering many long-standing questions in modern neuroscience. However, exploiting its full potential requires the development of novel imaging approaches well suited to the photophysical properties of genetically encoded voltage indicators. We demonstrate that parallel excitation approaches developed for scanless two-photon photostimulation enable high-SNR two-photon voltage imaging. We use whole-cell patch-clamp electrophysiology to perform a thorough characterization of scanless two-photon voltage imaging using three parallel illumination approaches and lasers with different repetition rates and wavelengths. We demonstrate voltage recordings of high-frequency spike trains and sub-threshold depolarizations from neurons expressing the soma-targeted genetically encoded voltage indicator JEDI-2P-Kv. Using a low repetition-rate laser, we perform multi-cell recordings from up to fifteen targets simultaneously. We co-express JEDI-2P-Kv and the channelrhodopsin ChroME-ST and capitalize on their overlapping two-photon absorption spectra to simultaneously evoke and image action potentials using a single laser source. We also demonstrate in vivo scanless two-photon imaging of multiple cells simultaneously up to 250 µm deep in the barrel cortex of head-fixed, anaesthetised mice.
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Affiliation(s)
- Ruth R Sims
- Institut de la Vision, Sorbonne Université, INSERM, CNRS, Paris, France
| | - Imane Bendifallah
- Institut de la Vision, Sorbonne Université, INSERM, CNRS, Paris, France
| | - Christiane Grimm
- Institut de la Vision, Sorbonne Université, INSERM, CNRS, Paris, France
| | | | - Soledad Domínguez
- Institut de la Vision, Sorbonne Université, INSERM, CNRS, Paris, France
| | - Chung Yuen Chan
- Institut de la Vision, Sorbonne Université, INSERM, CNRS, Paris, France
| | - Xiaoyu Lu
- Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX, USA
| | - Benoît C Forget
- Institut de la Vision, Sorbonne Université, INSERM, CNRS, Paris, France
| | - François St-Pierre
- Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Department of Biochemistry and Molecular Pharmacology, Baylor College of Medicine, Houston, TX, USA
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | | | - Valentina Emiliani
- Institut de la Vision, Sorbonne Université, INSERM, CNRS, Paris, France.
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6
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Xiao S, Cunningham WJ, Kondabolu K, Lowet E, Moya MV, Mount RA, Ravasio C, Bortz E, Shaw D, Economo MN, Han X, Mertz J. Large-scale deep tissue voltage imaging with targeted-illumination confocal microscopy. Nat Methods 2024; 21:1094-1102. [PMID: 38840033 DOI: 10.1038/s41592-024-02275-w] [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: 07/04/2023] [Accepted: 04/09/2024] [Indexed: 06/07/2024]
Abstract
Voltage imaging with cellular specificity has been made possible by advances in genetically encoded voltage indicators. However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines the signal-to-noise ratio and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating while also maximizing signal detection efficiency. The resulting benefits in signal-to-noise ratio and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different genetically encoded voltage indicator classes.
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Affiliation(s)
- Sheng Xiao
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
| | | | | | - Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
| | - Maria V Moya
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Rebecca A Mount
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Cara Ravasio
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Emma Bortz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Dana Shaw
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Michael N Economo
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
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7
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Gonzalez-Ramos A, Puigsasllosas-Pastor C, Arcas-Marquez A, Tornero D. Updated Toolbox for Assessing Neuronal Network Reconstruction after Cell Therapy. Bioengineering (Basel) 2024; 11:487. [PMID: 38790353 PMCID: PMC11118929 DOI: 10.3390/bioengineering11050487] [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: 03/30/2024] [Revised: 05/02/2024] [Accepted: 05/10/2024] [Indexed: 05/26/2024] Open
Abstract
Cell therapy has proven to be a promising treatment for a range of neurological disorders, including Parkinson Disease, drug-resistant epilepsy, and stroke, by restoring function after brain damage. Nevertheless, evaluating the true effectiveness of these therapeutic interventions requires a deep understanding of the functional integration of grafted cells into existing neural networks. This review explores a powerful arsenal of molecular techniques revolutionizing our ability to unveil functional integration of grafted cells within the host brain. From precise manipulation of neuronal activity to pinpoint the functional contribution of transplanted cells by using opto- and chemo-genetics, to real-time monitoring of neuronal dynamics shedding light on functional connectivity within the reconstructed circuits by using genetically encoded (calcium) indicators in vivo. Finally, structural reconstruction and mapping communication pathways between grafted and host neurons can be achieved by monosynaptic tracing with viral vectors. The cutting-edge toolbox presented here holds immense promise for elucidating the impact of cell therapy on neural circuitry and guiding the development of more effective treatments for neurological disorders.
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Affiliation(s)
- Ana Gonzalez-Ramos
- Stanley Center for Psychiatric Research at Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Claudia Puigsasllosas-Pastor
- Laboratory of Neural Stem Cells and Brain Damage, Department of Biomedical Sciences, Institute of Neurosciences, University of Barcelona, 08036 Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Ainhoa Arcas-Marquez
- Laboratory of Neural Stem Cells and Brain Damage, Department of Biomedical Sciences, Institute of Neurosciences, University of Barcelona, 08036 Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Daniel Tornero
- Laboratory of Neural Stem Cells and Brain Damage, Department of Biomedical Sciences, Institute of Neurosciences, University of Barcelona, 08036 Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
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8
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Zhang J, Newman J, Wang Z, Qian Y, Feliciano-Ramos P, Guo W, Honda T, Chen ZS, Linghu C, Etienne-Cummings R, Fossum E, Boyden E, Wilson M. Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.27.546748. [PMID: 37425952 PMCID: PMC10327006 DOI: 10.1101/2023.06.27.546748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
High-speed wide-field fluorescence microscopy has the potential to capture biological processes with exceptional spatiotemporal resolution. However, conventional cameras suffer from low signal-to-noise ratio at high frame rates, limiting their ability to detect faint fluorescent events. Here, we introduce an image sensor where each pixel has individually programmable sampling speed and phase, so that pixels can be arranged to simultaneously sample at high speed with a high signal-to-noise ratio. In high-speed voltage imaging experiments, our image sensor significantly increases the output signal-to-noise ratio compared to a low-noise scientific CMOS camera (~2-3 folds). This signal-to-noise ratio gain enables the detection of weak neuronal action potentials and subthreshold activities missed by the standard scientific CMOS cameras. Our camera with flexible pixel exposure configurations offers versatile sampling strategies to improve signal quality in various experimental conditions.
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Affiliation(s)
- Jie Zhang
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Jonathan Newman
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Zeguan Wang
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Yong Qian
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Pedro Feliciano-Ramos
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Wei Guo
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Takato Honda
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Zhe Sage Chen
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Changyang Linghu
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Ralph Etienne-Cummings
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Eric Fossum
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
| | - Edward Boyden
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Matthew Wilson
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
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9
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Song C, Matlashov ME, Shcherbakova DM, Antic SD, Verkhusha VV, Knöpfel T. Characterization of two near-infrared genetically encoded voltage indicators. NEUROPHOTONICS 2024; 11:024201. [PMID: 38090225 PMCID: PMC10712888 DOI: 10.1117/1.nph.11.2.024201] [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: 07/25/2023] [Revised: 10/20/2023] [Accepted: 11/08/2023] [Indexed: 01/06/2024]
Abstract
Significance Efforts starting more than 20 years ago led to increasingly well performing genetically encoded voltage indicators (GEVIs) for optical imaging at wavelengths < 600 nm . Although optical imaging in the > 600 nm wavelength range has many advantages over shorter wavelength approaches for mesoscopic in vivo monitoring of neuronal activity in the mammalian brain, the availability and evaluation of well performing near-infrared GEVIs are still limited. Aim Here, we characterized two recent near-infrared GEVIs, Archon1 and nirButterfly, to support interested tool users in selecting a suitable near-infrared GEVI for their specific research question requirements. Approach We characterized side-by-side the brightness, sensitivity, and kinetics of both near-infrared GEVIs in a setting focused on population imaging. Results We found that nirButterfly shows seven-fold higher brightness than Archon1 under the same conditions and faster kinetics than Archon1 for population imaging without cellular resolution. But Archon1 showed larger signals than nirButterfly. Conclusions Neither GEVI characterized here surpasses in all three key parameters (brightness, kinetics, and sensitivity), so there is no unequivocal preference for one of the two. Our side-by-side characterization presented here provides new information for future in vitro and ex vivo experimental designs.
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Affiliation(s)
- Chenchen Song
- Imperial College, Laboratory for Neuronal Circuit Dynamics, London, United Kingdom
- Nanyang Technological University, Singapore
| | - Mikhail E. Matlashov
- Albert Einstein College of Medicine, Gruss-Lipper Biophotonics Center, Department of Genetics, Bronx, New York, United States
| | - Daria M. Shcherbakova
- Albert Einstein College of Medicine, Gruss-Lipper Biophotonics Center, Department of Genetics, Bronx, New York, United States
| | - Srdjan D. Antic
- Institute for Systems Genomics, UConn Health, Department of Neuroscience, Farmington, Connecticut, United States
| | - Vladislav V. Verkhusha
- Albert Einstein College of Medicine, Gruss-Lipper Biophotonics Center, Department of Genetics, Bronx, New York, United States
- University of Helsinki, Medicum, Faculty of Medicine, Helsinki, Finland
| | - Thomas Knöpfel
- Imperial College, Laboratory for Neuronal Circuit Dynamics, London, United Kingdom
- Hong Kong Baptist University, Laboratory for Neuronal Circuit Dynamics, Hong Kong, China
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10
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Milicevic KD, Barbeau BL, Lovic DD, Patel AA, Ivanova VO, Antic SD. Physiological features of parvalbumin-expressing GABAergic interneurons contributing to high-frequency oscillations in the cerebral cortex. CURRENT RESEARCH IN NEUROBIOLOGY 2023; 6:100121. [PMID: 38616956 PMCID: PMC11015061 DOI: 10.1016/j.crneur.2023.100121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 11/13/2023] [Accepted: 12/01/2023] [Indexed: 04/16/2024] Open
Abstract
Parvalbumin-expressing (PV+) inhibitory interneurons drive gamma oscillations (30-80 Hz), which underlie higher cognitive functions. In this review, we discuss two groups/aspects of fundamental properties of PV+ interneurons. In the first group (dubbed Before Axon), we list properties representing optimal synaptic integration in PV+ interneurons designed to support fast oscillations. For example: [i] Information can neither enter nor leave the neocortex without the engagement of fast PV+ -mediated inhibition; [ii] Voltage responses in PV+ interneuron dendrites integrate linearly to reduce impact of the fluctuations in the afferent drive; and [iii] Reversed somatodendritic Rm gradient accelerates the time courses of synaptic potentials arriving at the soma. In the second group (dubbed After Axon), we list morphological and biophysical properties responsible for (a) short synaptic delays, and (b) efficient postsynaptic outcomes. For example: [i] Fast-spiking ability that allows PV+ interneurons to outpace other cortical neurons (pyramidal neurons). [ii] Myelinated axon (which is only found in the PV+ subclass of interneurons) to secure fast-spiking at the initial axon segment; and [iii] Inhibitory autapses - autoinhibition, which assures brief biphasic voltage transients and supports postinhibitory rebounds. Recent advent of scientific tools, such as viral strategies to target PV cells and the ability to monitor PV cells via in vivo imaging during behavior, will aid in defining the role of PV cells in the CNS. Given the link between PV+ interneurons and cognition, in the future, it would be useful to carry out physiological recordings in the PV+ cell type selectively and characterize if and how psychiatric and neurological diseases affect initiation and propagation of electrical signals in this cortical sub-circuit. Voltage imaging may allow fast recordings of electrical signals from many PV+ interneurons simultaneously.
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Affiliation(s)
- Katarina D. Milicevic
- University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT, 06030, USA
- University of Belgrade, Faculty of Biology, Center for Laser Microscopy, Belgrade, 11000, Serbia
| | - Brianna L. Barbeau
- University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT, 06030, USA
| | - Darko D. Lovic
- University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT, 06030, USA
- University of Belgrade, Faculty of Biology, Center for Laser Microscopy, Belgrade, 11000, Serbia
| | - Aayushi A. Patel
- University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT, 06030, USA
| | - Violetta O. Ivanova
- University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT, 06030, USA
| | - Srdjan D. Antic
- University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT, 06030, USA
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11
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Zhou ZC, Gordon-Fennell A, Piantadosi SC, Ji N, Smith SL, Bruchas MR, Stuber GD. Deep-brain optical recording of neural dynamics during behavior. Neuron 2023; 111:3716-3738. [PMID: 37804833 PMCID: PMC10843303 DOI: 10.1016/j.neuron.2023.09.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/24/2023] [Accepted: 09/06/2023] [Indexed: 10/09/2023]
Abstract
In vivo fluorescence recording techniques have produced landmark discoveries in neuroscience, providing insight into how single cell and circuit-level computations mediate sensory processing and generate complex behaviors. While much attention has been given to recording from cortical brain regions, deep-brain fluorescence recording is more complex because it requires additional measures to gain optical access to harder to reach brain nuclei. Here we discuss detailed considerations and tradeoffs regarding deep-brain fluorescence recording techniques and provide a comprehensive guide for all major steps involved, from project planning to data analysis. The goal is to impart guidance for new and experienced investigators seeking to use in vivo deep fluorescence optical recordings in awake, behaving rodent models.
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Affiliation(s)
- Zhe Charles Zhou
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Adam Gordon-Fennell
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Sean C Piantadosi
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Na Ji
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Spencer LaVere Smith
- Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Michael R Bruchas
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA; Department of Pharmacology, University of Washington, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
| | - Garret D Stuber
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA; Department of Pharmacology, University of Washington, Seattle, WA 98195, USA.
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12
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Han Y, Yang J, Li Y, Chen Y, Ren H, Ding R, Qian W, Ren K, Xie B, Deng M, Xiao Y, Chu J, Zou P. Bright and sensitive red voltage indicators for imaging action potentials in brain slices and pancreatic islets. SCIENCE ADVANCES 2023; 9:eadi4208. [PMID: 37992174 PMCID: PMC10664999 DOI: 10.1126/sciadv.adi4208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 10/20/2023] [Indexed: 11/24/2023]
Abstract
Genetically encoded voltage indicators (GEVIs) allow the direct visualization of cellular membrane potential at the millisecond time scale. Among these, red-emitting GEVIs have been reported to support multichannel recordings and manipulation of cellular activities with reduced autofluorescence background. However, the limited sensitivity and dimness of existing red GEVIs have restricted their applications in neuroscience. Here, we report a pair of red-shifted opsin-based GEVIs, Cepheid1b and Cepheid1s, with improved dynamic range, brightness, and photostability. The improved dynamic range is achieved by a rational design to raise the electrochromic Förster resonance energy transfer efficiency, and the higher brightness and photostability are approached with separately engineered red fluorescent proteins. With Cepheid1 indicators, we recorded complex firings and subthreshold activities of neurons on acute brain slices and observed heterogeneity in the voltage‑calcium coupling on pancreatic islets. Overall, Cepheid1 indicators provide a strong tool to investigate excitable cells in various sophisticated biological systems.
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Affiliation(s)
- Yi Han
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Junqi Yang
- Peking University–Tsinghua University–National Institute of Biological Sciences Joint Graduate Program, School of Life Sciences, Peking University, Beijing 100871, China
| | - Yuan Li
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Chinese Institute for Brain Research (CIBR), Beijing 102206, China
| | - Yu Chen
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Huixia Ren
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Peking University, Beijing 100871, China
| | - Ran Ding
- Institute for Translational Neuroscience of the Second Affiliated Hospital of Nantong University, Center for Neural Developmental and Degenerative Research of Nantong University, Nantong 226001, China
| | - Weiran Qian
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing 100871, China
| | - Keyuan Ren
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Beichen Xie
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Mengying Deng
- Research Center for Biomedical Optics and Molecular Imaging, Shenzhen Key Laboratory for Molecular Imaging, Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yinghan Xiao
- Research Center for Biomedical Optics and Molecular Imaging, Shenzhen Key Laboratory for Molecular Imaging, Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jun Chu
- Research Center for Biomedical Optics and Molecular Imaging, Shenzhen Key Laboratory for Molecular Imaging, Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Peng Zou
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
- Peking University–Tsinghua University–National Institute of Biological Sciences Joint Graduate Program, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Chinese Institute for Brain Research (CIBR), Beijing 102206, China
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13
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Kim SJ, Affan RO, Frostig H, Scott BB, Alexander AS. Advances in cellular resolution microscopy for brain imaging in rats. NEUROPHOTONICS 2023; 10:044304. [PMID: 38076724 PMCID: PMC10704261 DOI: 10.1117/1.nph.10.4.044304] [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: 05/05/2023] [Revised: 09/23/2023] [Accepted: 11/07/2023] [Indexed: 02/12/2024]
Abstract
Rats are used in neuroscience research because of their physiological similarities with humans and accessibility as model organisms, trainability, and behavioral repertoire. In particular, rats perform a wide range of sophisticated social, cognitive, motor, and learning behaviors within the contexts of both naturalistic and laboratory environments. Further progress in neuroscience can be facilitated by using advanced imaging methods to measure the complex neural and physiological processes during behavior in rats. However, compared with the mouse, the rat nervous system offers a set of challenges, such as larger brain size, decreased neuron density, and difficulty with head restraint. Here, we review recent advances in in vivo imaging techniques in rats with a special focus on open-source solutions for calcium imaging. Finally, we provide suggestions for both users and developers of in vivo imaging systems for rats.
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Affiliation(s)
- Su Jin Kim
- Johns Hopkins University, Department of Psychological and Brain Sciences, Baltimore, Maryland, United States
| | - Rifqi O. Affan
- Boston University, Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston, Massachusetts, United States
- Boston University, Graduate Program in Neuroscience, Boston, Massachusetts, United States
| | - Hadas Frostig
- Boston University, Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston, Massachusetts, United States
| | - Benjamin B. Scott
- Boston University, Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston, Massachusetts, United States
- Boston University, Neurophotonics Center and Photonics Center, Boston, Massachusetts, United States
| | - Andrew S. Alexander
- University of California Santa Barbara, Department of Psychological and Brain Sciences, Santa Barbara, California, United States
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14
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Osanai H, Nair IR, Kitamura T. Dissecting cell-type-specific pathways in medial entorhinal cortical-hippocampal network for episodic memory. J Neurochem 2023; 166:172-188. [PMID: 37248771 PMCID: PMC10538947 DOI: 10.1111/jnc.15850] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/07/2023] [Accepted: 05/10/2023] [Indexed: 05/31/2023]
Abstract
Episodic memory, which refers to our ability to encode and recall past events, is essential to our daily lives. Previous research has established that both the entorhinal cortex (EC) and hippocampus (HPC) play a crucial role in the formation and retrieval of episodic memories. However, to understand neural circuit mechanisms behind these processes, it has become necessary to monitor and manipulate the neural activity in a cell-type-specific manner with high temporal precision during memory formation, consolidation, and retrieval in the EC-HPC networks. Recent studies using cell-type-specific labeling, monitoring, and manipulation have demonstrated that medial EC (MEC) contains multiple excitatory neurons that have differential molecular markers, physiological properties, and anatomical features. In this review, we will comprehensively examine the complementary roles of superficial layers of neurons (II and III) and the roles of deeper layers (V and VI) in episodic memory formation and recall based on these recent findings.
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Affiliation(s)
- Hisayuki Osanai
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Indrajith R Nair
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Takashi Kitamura
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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15
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Tian H, Davis HC, Wong-Campos JD, Park P, Fan LZ, Gmeiner B, Begum S, Werley CA, Borja GB, Upadhyay H, Shah H, Jacques J, Qi Y, Parot V, Deisseroth K, Cohen AE. Video-based pooled screening yields improved far-red genetically encoded voltage indicators. Nat Methods 2023; 20:1082-1094. [PMID: 36624211 PMCID: PMC10329731 DOI: 10.1038/s41592-022-01743-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 11/28/2022] [Indexed: 01/11/2023]
Abstract
Video-based screening of pooled libraries is a powerful approach for directed evolution of biosensors because it enables selection along multiple dimensions simultaneously from large libraries. Here we develop a screening platform, Photopick, which achieves precise phenotype-activated photoselection over a large field of view (2.3 × 2.3 mm, containing >103 cells, per shot). We used the Photopick platform to evolve archaerhodopsin-derived genetically encoded voltage indicators (GEVIs) with improved signal-to-noise ratio (QuasAr6a) and kinetics (QuasAr6b). These GEVIs gave improved signals in cultured neurons and in live mouse brains. By combining targeted in vivo optogenetic stimulation with high-precision voltage imaging, we characterized inhibitory synaptic coupling between individual cortical NDNF (neuron-derived neurotrophic factor) interneurons, and excitatory electrical synapses between individual hippocampal parvalbumin neurons. The QuasAr6 GEVIs are powerful tools for all-optical electrophysiology and the Photopick approach could be adapted to evolve a broad range of biosensors.
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Affiliation(s)
- He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hunter C Davis
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - J David Wong-Campos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Linlin Z Fan
- Department of Bioengineering, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Benjamin Gmeiner
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Shahinoor Begum
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | | | | | | | | | | | - Yitong Qi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Vicente Parot
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Karl Deisseroth
- Department of Bioengineering, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MA, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Department of Physics, Harvard University, Cambridge, MA, USA.
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16
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Bowman AJ, Huang C, Schnitzer MJ, Kasevich MA. Wide-field fluorescence lifetime imaging of neuron spiking and subthreshold activity in vivo. Science 2023; 380:1270-1275. [PMID: 37347862 PMCID: PMC10361454 DOI: 10.1126/science.adf9725] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 05/16/2023] [Indexed: 06/24/2023]
Abstract
The development of voltage-sensitive fluorescent probes suggests fluorescence lifetime as a promising readout for electrical activity in biological systems. Existing approaches fail to achieve the speed and sensitivity required for voltage imaging in neuroscience applications. We demonstrated that wide-field electro-optic fluorescence lifetime imaging microscopy (EO-FLIM) allows lifetime imaging at kilohertz frame-acquisition rates, spatially resolving action potential propagation and subthreshold neural activity in live adult Drosophila. Lifetime resolutions of <5 picoseconds at 1 kilohertz were achieved for single-cell voltage recordings. Lifetime readout is limited by photon shot noise, and the method provides strong rejection of motion artifacts and technical noise sources. Recordings revealed local transmembrane depolarizations, two types of spikes with distinct fluorescence lifetimes, and phase locking of spikes to an external mechanical stimulus.
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Affiliation(s)
- Adam J. Bowman
- Physics Department, Stanford University; 382 Via Pueblo Mall, Stanford, California 94305, USA
| | - Cheng Huang
- James H. Clark Center, Stanford University; 318 Campus Dr., Stanford, CA 94305, USA
- Present Address: Department of Neuroscience, Washington University School of Medicine St. Louis, MO 63110, USA
| | - Mark J. Schnitzer
- James H. Clark Center, Stanford University; 318 Campus Dr., Stanford, CA 94305, USA
- CNC Program, Stanford University; Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University; Stanford, CA, USA
| | - Mark A. Kasevich
- Physics Department, Stanford University; 382 Via Pueblo Mall, Stanford, California 94305, USA
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17
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Aseyev N, Ivanova V, Balaban P, Nikitin E. Current Practice in Using Voltage Imaging to Record Fast Neuronal Activity: Successful Examples from Invertebrate to Mammalian Studies. BIOSENSORS 2023; 13:648. [PMID: 37367013 DOI: 10.3390/bios13060648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 06/09/2023] [Accepted: 06/12/2023] [Indexed: 06/28/2023]
Abstract
The optical imaging of neuronal activity with potentiometric probes has been credited with being able to address key questions in neuroscience via the simultaneous recording of many neurons. This technique, which was pioneered 50 years ago, has allowed researchers to study the dynamics of neural activity, from tiny subthreshold synaptic events in the axon and dendrites at the subcellular level to the fluctuation of field potentials and how they spread across large areas of the brain. Initially, synthetic voltage-sensitive dyes (VSDs) were applied directly to brain tissue via staining, but recent advances in transgenic methods now allow the expression of genetically encoded voltage indicators (GEVIs), specifically in selected neuron types. However, voltage imaging is technically difficult and limited by several methodological constraints that determine its applicability in a given type of experiment. The prevalence of this method is far from being comparable to patch clamp voltage recording or similar routine methods in neuroscience research. There are more than twice as many studies on VSDs as there are on GEVIs. As can be seen from the majority of the papers, most of them are either methodological ones or reviews. However, potentiometric imaging is able to address key questions in neuroscience by recording most or many neurons simultaneously, thus providing unique information that cannot be obtained via other methods. Different types of optical voltage indicators have their advantages and limitations, which we focus on in detail. Here, we summarize the experience of the scientific community in the application of voltage imaging and try to evaluate the contribution of this method to neuroscience research.
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Affiliation(s)
- Nikolay Aseyev
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova 5A, Moscow 117485, Russia
| | - Violetta Ivanova
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova 5A, Moscow 117485, Russia
| | - Pavel Balaban
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova 5A, Moscow 117485, Russia
| | - Evgeny Nikitin
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova 5A, Moscow 117485, Russia
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18
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Abdelfattah AS, Zheng J, Singh A, Huang YC, Reep D, Tsegaye G, Tsang A, Arthur BJ, Rehorova M, Olson CVL, Shuai Y, Zhang L, Fu TM, Milkie DE, Moya MV, Weber TD, Lemire AL, Baker CA, Falco N, Zheng Q, Grimm JB, Yip MC, Walpita D, Chase M, Campagnola L, Murphy GJ, Wong AM, Forest CR, Mertz J, Economo MN, Turner GC, Koyama M, Lin BJ, Betzig E, Novak O, Lavis LD, Svoboda K, Korff W, Chen TW, Schreiter ER, Hasseman JP, Kolb I. Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator. Neuron 2023; 111:1547-1563.e9. [PMID: 37015225 PMCID: PMC10280807 DOI: 10.1016/j.neuron.2023.03.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/15/2023] [Accepted: 03/07/2023] [Indexed: 04/05/2023]
Abstract
The ability to optically image cellular transmembrane voltages at millisecond-timescale resolutions can offer unprecedented insight into the function of living brains in behaving animals. Here, we present a point mutation that increases the sensitivity of Ace2 opsin-based voltage indicators. We use the mutation to develop Voltron2, an improved chemigeneic voltage indicator that has a 65% higher sensitivity to single APs and 3-fold higher sensitivity to subthreshold potentials than Voltron. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, although with lower baseline fluorescence. In multiple in vitro and in vivo comparisons with its predecessor across multiple species, we found Voltron2 to be more sensitive to APs and subthreshold fluctuations. Finally, we used Voltron2 to study and evaluate the possible mechanisms of interneuron synchronization in the mouse hippocampus. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.
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Affiliation(s)
| | - Jihong Zheng
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Amrita Singh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Yi-Chieh Huang
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Daniel Reep
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Getahun Tsegaye
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Arthur Tsang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Benjamin J Arthur
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Monika Rehorova
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Carl V L Olson
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Yichun Shuai
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Lixia Zhang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Tian-Ming Fu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Daniel E Milkie
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Maria V Moya
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Timothy D Weber
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Andrew L Lemire
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Natalie Falco
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Qinsi Zheng
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jonathan B Grimm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Mighten C Yip
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Deepika Walpita
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | | | | | - Allan M Wong
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Michael N Economo
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Glenn C Turner
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Minoru Koyama
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Bei-Jung Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Eric Betzig
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Departments of Molecular and Cell Biology and Physics, Howard Hughes Medical Institute, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA; Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Ondrej Novak
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Luke D Lavis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Wyatt Korff
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Tsai-Wen Chen
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| | - Eric R Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
| | - Jeremy P Hasseman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
| | - Ilya Kolb
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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19
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Lu Z, Liu Y, Jin M, Luo X, Yue H, Wang Z, Zuo S, Zeng Y, Fan J, Pang Y, Wu J, Yang J, Dai Q. Virtual-scanning light-field microscopy for robust snapshot high-resolution volumetric imaging. Nat Methods 2023; 20:735-746. [PMID: 37024654 PMCID: PMC10172145 DOI: 10.1038/s41592-023-01839-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 03/07/2023] [Indexed: 04/08/2023]
Abstract
High-speed three-dimensional (3D) intravital imaging in animals is useful for studying transient subcellular interactions and functions in health and disease. Light-field microscopy (LFM) provides a computational solution for snapshot 3D imaging with low phototoxicity but is restricted by low resolution and reconstruction artifacts induced by optical aberrations, motion and noise. Here, we propose virtual-scanning LFM (VsLFM), a physics-based deep learning framework to increase the resolution of LFM up to the diffraction limit within a snapshot. By constructing a 40 GB high-resolution scanning LFM dataset across different species, we exploit physical priors between phase-correlated angular views to address the frequency aliasing problem. This enables us to bypass hardware scanning and associated motion artifacts. Here, we show that VsLFM achieves ultrafast 3D imaging of diverse processes such as the beating heart in embryonic zebrafish, voltage activity in Drosophila brains and neutrophil migration in the mouse liver at up to 500 volumes per second.
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Affiliation(s)
- Zhi Lu
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Yu Liu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Manchang Jin
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Xin Luo
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Huanjing Yue
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Zian Wang
- Department of Automation, Tsinghua University, Beijing, China
| | - Siqing Zuo
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Yunmin Zeng
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Jiaqi Fan
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Yanwei Pang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Jiamin Wu
- Department of Automation, Tsinghua University, Beijing, China.
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China.
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.
| | - Jingyu Yang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China.
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing, China.
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China.
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.
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20
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Xu J, Shirinkami H, Hwang S, Jeong HS, Kim G, Jun SB, Chun H. Fast Reconfigurable Electrode Array Based on Titanium Oxide for Localized Stimulation of Cultured Neural Network. ACS APPLIED MATERIALS & INTERFACES 2023; 15:19092-19101. [PMID: 37036145 DOI: 10.1021/acsami.2c21649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Planar microelectrode arrays have become standard tools for in vitro neural-network analysis. However, these predefined micropatterned devices lack adaptability to target-specific cells within a cultured network. Herein, we fabricated a reconfigurable TiO2 electrode array with an anatase-brookite bicrystalline polymorphous mesoporous layer. Because of its selective absorption of ultraviolet (UV) light and corresponding photoconductivity, TiO2 electrode array was identified as a promising tool for high-resolution light-addressing. The TiO2 film was used as a semitransparent semiconductor with a high Roff/Ron ratio of 105 and a fast response time of 400 ms. In addition, the effect of UV radiation on the resistance of the TiO2 film over 30 d in an aqueous environment was analyzed, with the film exhibiting high stability. An arbitrary UV pattern was applied to a reconfigurable TiO2 electrode using a digital micromirror device (DMD), affording highly localized neural stimulation at the single-cell level. The reconfigurable TiO2 electrode with a patterned indium tin oxide (ITO) substrate enabled the independent connection of up to 60 points with external stimulators and signal recorders. We believe this technique would be helpful for electrophysiological research requiring the analysis of cell and neural-network features using a highly localized neural interface.
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Affiliation(s)
- Jiaxin Xu
- Department of Biomedical Engineering, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
| | - Hamidreza Shirinkami
- Department of Biomedical Engineering, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
| | - Seoyoung Hwang
- Department of Electronic and Electrical Engineering, Ewha Womans University, Asan Engineering Building, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
| | - Hee Soo Jeong
- Department of Electronic and Electrical Engineering, Ewha Womans University, Asan Engineering Building, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
| | - Gijung Kim
- Department of Biomedical Engineering, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
- BK21 Four Institute of Precision Public Health, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
| | - Sang Beom Jun
- Department of Electronic and Electrical Engineering, Ewha Womans University, Asan Engineering Building, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
- Graduate Program in Smart Factory, Ewha Womans University, Asan Engineering Building, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
| | - Honggu Chun
- Department of Biomedical Engineering, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
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21
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Silic MR, Zhang G. Bioelectricity in Developmental Patterning and Size Control: Evidence and Genetically Encoded Tools in the Zebrafish Model. Cells 2023; 12:cells12081148. [PMID: 37190057 DOI: 10.3390/cells12081148] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 04/03/2023] [Accepted: 04/10/2023] [Indexed: 05/17/2023] Open
Abstract
Developmental patterning is essential for regulating cellular events such as axial patterning, segmentation, tissue formation, and organ size determination during embryogenesis. Understanding the patterning mechanisms remains a central challenge and fundamental interest in developmental biology. Ion-channel-regulated bioelectric signals have emerged as a player of the patterning mechanism, which may interact with morphogens. Evidence from multiple model organisms reveals the roles of bioelectricity in embryonic development, regeneration, and cancers. The Zebrafish model is the second most used vertebrate model, next to the mouse model. The zebrafish model has great potential for elucidating the functions of bioelectricity due to many advantages such as external development, transparent early embryogenesis, and tractable genetics. Here, we review genetic evidence from zebrafish mutants with fin-size and pigment changes related to ion channels and bioelectricity. In addition, we review the cell membrane voltage reporting and chemogenetic tools that have already been used or have great potential to be implemented in zebrafish models. Finally, new perspectives and opportunities for bioelectricity research with zebrafish are discussed.
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Affiliation(s)
- Martin R Silic
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA
| | - GuangJun Zhang
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA
- Center for Cancer Research, Purdue University, West Lafayette, IN 47907, USA
- Purdue Institute for Inflammation, Immunology and Infectious Diseases (PI4D), Purdue University, West Lafayette, IN 47907, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, 625 Harrison Street, West Lafayette, IN 47907, USA
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22
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Nietz AK, Popa LS, Streng ML, Carter RE, Kodandaramaiah SB, Ebner TJ. Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo. BIOLOGY 2022; 11:1601. [PMID: 36358302 PMCID: PMC9687960 DOI: 10.3390/biology11111601] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/28/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022]
Abstract
A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca2+ imaging, which uses single photon excitation and improved genetically encoded Ca2+ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca2+ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca2+ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca2+ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.
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Affiliation(s)
- Angela K. Nietz
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Laurentiu S. Popa
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Martha L. Streng
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Russell E. Carter
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Timothy J. Ebner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
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