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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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Liao Z, Gonzalez KC, Li DM, Yang CM, Holder D, McClain NE, Zhang G, Evans SW, Chavarha M, Simko J, Makinson CD, Lin MZ, Losonczy A, Negrean A. Functional architecture of intracellular oscillations in hippocampal dendrites. Nat Commun 2024; 15:6295. [PMID: 39060234 PMCID: PMC11282248 DOI: 10.1038/s41467-024-50546-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions, report an advancing gradient of dendritic theta phase along the basal-tuft axis, and describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find that spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.
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Affiliation(s)
- Zhenrui Liao
- Department of Neuroscience, Columbia University, New York, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA
| | - Kevin C Gonzalez
- Department of Neuroscience, Columbia University, New York, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA
| | - Deborah M Li
- Department of Neuroscience, Columbia University, New York, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA
| | - Catalina M Yang
- Department of Neuroscience, Columbia University, New York, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA
| | - Donald Holder
- Department of Neuroscience, Columbia University, New York, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA
| | - Natalie E McClain
- Department of Neuroscience, Columbia University, New York, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA
| | - Guofeng Zhang
- Department of Neurobiology, Stanford University, Stanford, USA
| | - Stephen W Evans
- Department of Neurobiology, Stanford University, Stanford, USA
- The Boulder Creek Research Institute, Los Altos, USA
| | - Mariya Chavarha
- Department of Bioengineering, Stanford University, Stanford, USA
| | - Jane Simko
- Department of Neuroscience, Columbia University, New York, USA
- Department of Neurology, Columbia University, New York, USA
| | - Christopher D Makinson
- Department of Neuroscience, Columbia University, New York, USA
- Department of Neurology, Columbia University, New York, USA
| | - Michael Z Lin
- Department of Neurobiology, Stanford University, Stanford, USA
- Department of Bioengineering, Stanford University, Stanford, USA
| | - Attila Losonczy
- Department of Neuroscience, Columbia University, New York, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA.
- Kavli Institute for Brain Science, Columbia University, New York, USA.
| | - Adrian Negrean
- Department of Neuroscience, Columbia University, New York, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA.
- Allen Institute for Neural Dynamics, Seattle, USA.
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3
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Mizuta K, Sato M. Multiphoton imaging of hippocampal neural circuits: techniques and biological insights into region-, cell-type-, and pathway-specific functions. NEUROPHOTONICS 2024; 11:033406. [PMID: 38464393 PMCID: PMC10923542 DOI: 10.1117/1.nph.11.3.033406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 03/12/2024]
Abstract
Significance The function of the hippocampus in behavior and cognition has long been studied primarily through electrophysiological recordings from freely moving rodents. However, the application of optical recording methods, particularly multiphoton fluorescence microscopy, in the last decade or two has dramatically advanced our understanding of hippocampal function. This article provides a comprehensive overview of techniques and biological findings obtained from multiphoton imaging of hippocampal neural circuits. Aim This review aims to summarize and discuss the recent technical advances in multiphoton imaging of hippocampal neural circuits and the accumulated biological knowledge gained through this technology. Approach First, we provide a brief overview of various techniques of multiphoton imaging of the hippocampus and discuss its advantages, drawbacks, and associated key innovations and practices. Then, we review a large body of findings obtained through multiphoton imaging by region (CA1 and dentate gyrus), cell type (pyramidal neurons, inhibitory interneurons, and glial cells), and cellular compartment (dendrite and axon). Results Multiphoton imaging of the hippocampus is primarily performed under head-fixed conditions and can reveal detailed mechanisms of circuit operation owing to its high spatial resolution and specificity. As the hippocampus lies deep below the cortex, its imaging requires elaborate methods. These include imaging cannula implantation, microendoscopy, and the use of long-wavelength light sources. Although many studies have focused on the dorsal CA1 pyramidal cells, studies of other local and inter-areal circuitry elements have also helped provide a more comprehensive picture of the information processing performed by the hippocampal circuits. Imaging of circuit function in mouse models of Alzheimer's disease and other brain disorders such as autism spectrum disorder has also contributed greatly to our understanding of their pathophysiology. Conclusions Multiphoton imaging has revealed much regarding region-, cell-type-, and pathway-specific mechanisms in hippocampal function and dysfunction in health and disease. Future technological advances will allow further illustration of the operating principle of the hippocampal circuits via the large-scale, high-resolution, multimodal, and minimally invasive imaging.
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Affiliation(s)
- Kotaro Mizuta
- RIKEN BDR, Kobe, Japan
- New York University Abu Dhabi, Department of Biology, Abu Dhabi, United Arab Emirates
| | - Masaaki Sato
- Hokkaido University Graduate School of Medicine, Department of Neuropharmacology, Sapporo, Japan
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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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Yang RZ, Wang DD, Li SM, Liu PP, Kang JS. Development and Application of a Mitochondrial Genetically Encoded Voltage Indicator in Narcosis. Neurosci Bull 2024:10.1007/s12264-024-01235-w. [PMID: 38829505 DOI: 10.1007/s12264-024-01235-w] [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: 09/27/2023] [Accepted: 01/11/2024] [Indexed: 06/05/2024] Open
Abstract
Mitochondrial membrane potential (MMP) plays a crucial role in the function of cells and organelles, involving various cellular physiological processes, including energy production, formation of reactive oxygen species (ROS), unfolded protein stress, and cell survival. Currently, there is a lack of genetically encoded fluorescence indicators (GEVIs) for MMP. In our screening of various GEVIs for their potential monitoring MMP, the Accelerated Sensor of Action Potentials (ASAP) demonstrated optimal performance in targeting mitochondria and sensitivity to depolarization in multiple cell types. However, mitochondrial ASAPs also displayed sensitivity to ROS in cardiomyocytes. Therefore, two ASAP mutants resistant to ROS were generated. A double mutant ASAP3-ST exhibited the highest voltage sensitivity but weaker fluorescence. Overall, four GEVIs capable of targeting mitochondria were obtained and named mitochondrial potential indicators 1-4 (MPI-1-4). In vivo, fiber photometry experiments utilizing MPI-2 revealed a mitochondrial depolarization during isoflurane-induced narcosis in the M2 cortex.
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Affiliation(s)
- Run-Zhou Yang
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
| | - Dian-Dian Wang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450052, China
| | - Sen-Miao Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450052, China
| | - Pei-Pei Liu
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Jian-Sheng Kang
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450052, China.
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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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Liu C, Lu J, Wu Y, Ye X, Ahrens AM, Platisa J, Pieribone VA, Chen JL, Tian L. DeepVID v2: Self-Supervised Denoising with Decoupled Spatiotemporal Enhancement for Low-Photon Voltage Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.16.594448. [PMID: 38798473 PMCID: PMC11118583 DOI: 10.1101/2024.05.16.594448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Significance Voltage imaging is a powerful tool for studying the dynamics of neuronal activities in the brain. However, voltage imaging data are fundamentally corrupted by severe Poisson noise in the low-photon regime, which hinders the accurate extraction of neuronal activities. Self-supervised deep learning denoising methods have shown great potential in addressing the challenges in low-photon voltage imaging without the need for ground truth, but usually suffer from the tradeoff between spatial and temporal performance. Aim We present DeepVID v2, a novel self-supervised denoising framework with decoupled spatial and temporal enhancement capability to significantly augment low-photon voltage imaging. Approach DeepVID v2 is built on our original DeepVID framework,1,2 which performs frame-based denoising by utilizing a sequence of frames around the central frame targeted for denoising to leverage temporal information and ensure consistency. The network further integrates multiple blind pixels in the central frame to enrich the learning of local spatial information. Additionally, DeepVID v2 introduces a new edge extraction branch to capture fine structural details in order to learn high spatial resolution information. Results We demonstrate that DeepVID v2 is able to overcome the tradeoff between spatial and temporal performance, and achieve superior denoising capability in resolving both high-resolution spatial structures and rapid temporal neuronal activities. We further show that DeepVID v2 is able to generalize to different imaging conditions, including time-series measurements with various signal-to-noise ratios (SNRs) and in extreme low-photon conditions. Conclusions Our results underscore DeepVID v2 as a promising tool for enhancing voltage imaging. This framework has the potential to generalize to other low-photon imaging modalities and greatly facilitate the study of neuronal activities in the brain.
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Affiliation(s)
- Chang Liu
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
| | - Jiayu Lu
- Boston University, Department of Electrical and Computer Engineering, Boston, MA 02215, USA
| | - Yicun Wu
- Boston University, Department of Computer Science, Boston, MA 02215, USA
| | - Xin Ye
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
- Neurophotonics Center, Boston University, Boston, MA 02215, USA
| | | | - Jelena Platisa
- Yale University, Department of Cellular and Molecular Physiology, New Haven, CT 06520, USA
- The John B. Pierce Laboratory, New Haven, CT 06519, USA
| | - Vincent A Pieribone
- Yale University, Department of Cellular and Molecular Physiology, New Haven, CT 06520, USA
- The John B. Pierce Laboratory, New Haven, CT 06519, USA
- Yale University, Department of Neuroscience, New Haven, CT 06520, USA
| | - Jerry L Chen
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
- Neurophotonics Center, Boston University, Boston, MA 02215, USA
- Boston University, Department of Biology, Boston, MA 02215, USA
| | - Lei Tian
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
- Boston University, Department of Electrical and Computer Engineering, Boston, MA 02215, USA
- Neurophotonics Center, Boston University, Boston, MA 02215, USA
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8
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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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Shaw DC, Kondabolu K, Walsh KG, Shi W, Rillosi E, Hsiung M, Eden UT, Richardson RM, Kramer MA, Chu CJ, Han X. Photothrombosis induced cortical stroke produces electrographic epileptic biomarkers in mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.01.582958. [PMID: 38496541 PMCID: PMC10942311 DOI: 10.1101/2024.03.01.582958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Objective Interictal epileptiform spikes, high-frequency ripple oscillations, and their co-occurrence (spike ripples) in human scalp or intracranial voltage recordings are well-established epileptic biomarkers. While clinically significant, the neural mechanisms generating these electrographic biomarkers remain unclear. To reduce this knowledge gap, we introduce a novel photothrombotic stroke model in mice that reproduces focal interictal electrographic biomarkers observed in human epilepsy. Methods We induced a stroke in the motor cortex of C57BL/6 mice unilaterally (N=7) using a photothrombotic procedure previously established in rats. We then implanted intracranial electrodes (2 ipsilateral and 2 contralateral) and obtained intermittent local field potential (LFP) recordings over several weeks in awake, behaving mice. We evaluated the LFP for focal slowing and epileptic biomarkers - spikes, ripples, and spike ripples - using both automated and semi-automated procedures. Results Delta power (1-4 Hz) was higher in the stroke hemisphere than the non-stroke hemisphere in all mice ( p <0.001). Automated detection procedures indicated that compared to the non-stroke hemisphere, the stroke hemisphere had an increased spike ripple ( p =0.006) and spike rates ( p =0.039), but no change in ripple rate ( p =0.98). Expert validation confirmed the observation of elevated spike ripple rates ( p =0.008) and a trend of elevated spike rate ( p =0.055) in the stroke hemisphere. Interestingly, the validated ripple rate in the stroke hemisphere was higher than the non-stroke hemisphere ( p =0.031), highlighting the difficulty of automatically detecting ripples. Finally, using optimal performance thresholds, automatically detected spike ripples classified the stroke hemisphere with the best accuracy (sensitivity 0.94, specificity 0.94). Significance Cortical photothrombosis-induced stroke in commonly used C57BL/6 mice produces electrographic biomarkers as observed in human epilepsy. This model represents a new translational cortical epilepsy model with a defined irritative zone, which can be broadly applied in transgenic mice for cell type specific analysis of the cellular and circuit mechanisms of pathologic interictal activity. Key Points Cortical photothrombosis in mice produces stroke with characteristic intermittent focal delta slowing.Cortical photothrombosis stroke in mice produces the epileptic biomarkers spikes, ripples, and spike ripples.All biomarkers share morphological features with the corresponding human correlate.Spike ripples better lateralize to the lesional cortex than spikes or ripples.This cortical model can be applied in transgenic mice for mechanistic studies.
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10
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Shimoda Y, Leite M, Graham RT, Marvin JS, Hasseman J, Kolb I, Looger LL, Magloire V, Kullmann DM. Extracellular glutamate and GABA transients at the transition from interictal spiking to seizures. Brain 2024; 147:1011-1024. [PMID: 37787057 PMCID: PMC10907087 DOI: 10.1093/brain/awad336] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/29/2023] [Accepted: 09/16/2023] [Indexed: 10/04/2023] Open
Abstract
Focal epilepsy is associated with intermittent brief population discharges (interictal spikes), which resemble sentinel spikes that often occur at the onset of seizures. Why interictal spikes self-terminate whilst seizures persist and propagate is incompletely understood. We used fluorescent glutamate and GABA sensors in an awake rodent model of neocortical seizures to resolve the spatiotemporal evolution of both neurotransmitters in the extracellular space. Interictal spikes were accompanied by brief glutamate transients which were maximal at the initiation site and rapidly propagated centrifugally. GABA transients lasted longer than glutamate transients and were maximal ∼1.5 mm from the focus where they propagated centripetally. Prior to seizure initiation GABA transients were attenuated, whilst glutamate transients increased, consistent with a progressive failure of local inhibitory restraint. As seizures increased in frequency, there was a gradual increase in the spatial extent of spike-associated glutamate transients associated with interictal spikes. Neurotransmitter imaging thus reveals a progressive collapse of an annulus of feed-forward GABA release, allowing seizures to escape from local inhibitory restraint.
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Affiliation(s)
- Yoshiteru Shimoda
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Marco Leite
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Robert T Graham
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Jonathan S Marvin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Jeremy Hasseman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Ilya Kolb
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Loren L Looger
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Vincent Magloire
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Dimitri M Kullmann
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
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11
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Liao Z, Gonzalez KC, Li DM, Yang CM, Holder D, McClain NE, Zhang G, Evans SW, Chavarha M, Yi J, Makinson CD, Lin MZ, Losonczy A, Negrean A. Functional architecture of intracellular oscillations in hippocampal dendrites. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.12.579750. [PMID: 38405778 PMCID: PMC10888786 DOI: 10.1101/2024.02.12.579750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions and report an advancing gradient of dendritic theta phase along the basal-tuft axis, then describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.
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Affiliation(s)
- Zhenrui Liao
- Department of Neuroscience, Columbia University, New York, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
| | - Kevin C. Gonzalez
- Department of Neuroscience, Columbia University, New York, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
| | - Deborah M. Li
- Department of Neuroscience, Columbia University, New York, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
| | - Catalina M. Yang
- Department of Neuroscience, Columbia University, New York, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
| | - Donald Holder
- Department of Neuroscience, Columbia University, New York, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
| | - Natalie E. McClain
- Department of Neuroscience, Columbia University, New York, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
| | - Guofeng Zhang
- Department of Neurobiology, Stanford University, Stanford, United States
| | - Stephen W. Evans
- Department of Neurobiology, Stanford University, Stanford, United States
| | - Mariya Chavarha
- Department of Bioengineering, Stanford University, Stanford, United States
| | - Jane Yi
- Department of Neuroscience, Columbia University, New York, United States
- Department of Neurology, Columbia University, New York, United States
| | - Christopher D. Makinson
- Department of Neuroscience, Columbia University, New York, United States
- Department of Neurology, Columbia University, New York, United States
| | - Michael Z. Lin
- Department of Neurobiology, Stanford University, Stanford, United States
- Department of Bioengineering, Stanford University, Stanford, United States
| | - Attila Losonczy
- Department of Neuroscience, Columbia University, New York, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
- Kavli Institute for Brain Science, Columbia University, New York, United States
| | - Adrian Negrean
- Department of Neuroscience, Columbia University, New York, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
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12
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Nikolaev DM, Shtyrov AA, Vyazmin SY, Vasin AV, Panov MS, Ryazantsev MN. Fluorescence of the Retinal Chromophore in Microbial and Animal Rhodopsins. Int J Mol Sci 2023; 24:17269. [PMID: 38139098 PMCID: PMC10743670 DOI: 10.3390/ijms242417269] [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: 11/13/2023] [Revised: 11/30/2023] [Accepted: 12/06/2023] [Indexed: 12/24/2023] Open
Abstract
Fluorescence of the vast majority of natural opsin-based photoactive proteins is extremely low, in accordance with their functions that depend on efficient transduction of absorbed light energy. However, several recently proposed classes of engineered rhodopsins with enhanced fluorescence, along with the discovery of a new natural highly fluorescent rhodopsin, NeoR, opened a way to exploit these transmembrane proteins as fluorescent sensors and draw more attention to studies on this untypical rhodopsin property. Here, we review the available data on the fluorescence of the retinal chromophore in microbial and animal rhodopsins and their photocycle intermediates, as well as different isomers of the protonated retinal Schiff base in various solvents and the gas phase.
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Affiliation(s)
- Dmitrii M. Nikolaev
- Institute of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, 198504 St. Petersburg, Russia
| | - Andrey A. Shtyrov
- Institute of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, 198504 St. Petersburg, Russia
| | - Sergey Yu. Vyazmin
- Nanotechnology Research and Education Centre RAS, Saint Petersburg Academic University, 8/3 Khlopina Street, 194021 St. Petersburg, Russia
| | - Andrey V. Vasin
- Institute of Biomedical Systems and Biotechnologies, Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., 195251 St. Petersburg, Russia
| | - Maxim S. Panov
- Institute of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, 198504 St. Petersburg, Russia
- Center for Biophysical Studies, St. Petersburg State Chemical Pharmaceutical University, Professor Popov str. 14, lit. A, 197022 St. Petersburg, Russia
| | - Mikhail N. Ryazantsev
- Institute of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, 198504 St. Petersburg, Russia
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13
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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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14
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Piatkevich KD, Boyden ES. Optogenetic control of neural activity: The biophysics of microbial rhodopsins in neuroscience. Q Rev Biophys 2023; 57:e1. [PMID: 37831008 DOI: 10.1017/s0033583523000033] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Abstract
Optogenetics, the use of microbial rhodopsins to make the electrical activity of targeted neurons controllable by light, has swept through neuroscience, enabling thousands of scientists to study how specific neuron types contribute to behaviors and pathologies, and how they might serve as novel therapeutic targets. By activating a set of neurons, one can probe what functions they can initiate or sustain, and by silencing a set of neurons, one can probe the functions they are necessary for. We here review the biophysics of these molecules, asking why they became so useful in neuroscience for the study of brain circuitry. We review the history of the field, including early thinking, early experiments, applications of optogenetics, pre-optogenetics targeted neural control tools, and the history of discovering and characterizing microbial rhodopsins. We then review the biophysical attributes of rhodopsins that make them so useful to neuroscience - their classes and structure, their photocycles, their photocurrent magnitudes and kinetics, their action spectra, and their ion selectivity. Our hope is to convey to the reader how specific biophysical properties of these molecules made them especially useful to neuroscientists for a difficult problem - the control of high-speed electrical activity, with great precision and ease, in the brain.
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Affiliation(s)
- Kiryl D Piatkevich
- School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Edward S Boyden
- McGovern Institute and Koch Institute, Departments of Brain and Cognitive Sciences, Media Arts and Sciences, and Biological Engineering, K. Lisa Yang Center for Bionics and Center for Neurobiological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Howard Hughes Medical Institute, Cambridge, MA, USA
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15
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Roland PE. How far neuroscience is from understanding brains. Front Syst Neurosci 2023; 17:1147896. [PMID: 37867627 PMCID: PMC10585277 DOI: 10.3389/fnsys.2023.1147896] [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: 01/19/2023] [Accepted: 07/31/2023] [Indexed: 10/24/2023] Open
Abstract
The cellular biology of brains is relatively well-understood, but neuroscientists have not yet generated a theory explaining how brains work. Explanations of how neurons collectively operate to produce what brains can do are tentative and incomplete. Without prior assumptions about the brain mechanisms, I attempt here to identify major obstacles to progress in neuroscientific understanding of brains and central nervous systems. Most of the obstacles to our understanding are conceptual. Neuroscience lacks concepts and models rooted in experimental results explaining how neurons interact at all scales. The cerebral cortex is thought to control awake activities, which contrasts with recent experimental results. There is ambiguity distinguishing task-related brain activities from spontaneous activities and organized intrinsic activities. Brains are regarded as driven by external and internal stimuli in contrast to their considerable autonomy. Experimental results are explained by sensory inputs, behavior, and psychological concepts. Time and space are regarded as mutually independent variables for spiking, post-synaptic events, and other measured variables, in contrast to experimental results. Dynamical systems theory and models describing evolution of variables with time as the independent variable are insufficient to account for central nervous system activities. Spatial dynamics may be a practical solution. The general hypothesis that measurements of changes in fundamental brain variables, action potentials, transmitter releases, post-synaptic transmembrane currents, etc., propagating in central nervous systems reveal how they work, carries no additional assumptions. Combinations of current techniques could reveal many aspects of spatial dynamics of spiking, post-synaptic processing, and plasticity in insects and rodents to start with. But problems defining baseline and reference conditions hinder interpretations of the results. Furthermore, the facts that pooling and averaging of data destroy their underlying dynamics imply that single-trial designs and statistics are necessary.
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Affiliation(s)
- Per E. Roland
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
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16
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Eom M, Han S, Park P, Kim G, Cho ES, Sim J, Lee KH, Kim S, Tian H, Böhm UL, Lowet E, Tseng HA, Choi J, Lucia SE, Ryu SH, Rózsa M, Chang S, Kim P, Han X, Piatkevich KD, Choi M, Kim CH, Cohen AE, Chang JB, Yoon YG. Statistically unbiased prediction enables accurate denoising of voltage imaging data. Nat Methods 2023; 20:1581-1592. [PMID: 37723246 PMCID: PMC10555843 DOI: 10.1038/s41592-023-02005-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 08/10/2023] [Indexed: 09/20/2023]
Abstract
Here we report SUPPORT (statistically unbiased prediction utilizing spatiotemporal information in imaging data), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pixel value in voltage imaging data is highly dependent on its spatiotemporal neighboring pixels, even when its temporally adjacent frames alone do not provide useful information for statistical prediction. Such dependency is captured and used by a convolutional neural network with a spatiotemporal blind spot to accurately denoise voltage imaging data in which the existence of the action potential in a time frame cannot be inferred by the information in other frames. Through simulations and experiments, we show that SUPPORT enables precise denoising of voltage imaging data and other types of microscopy image while preserving the underlying dynamics within the scene.
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Affiliation(s)
- Minho Eom
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea
| | - Seungjae Han
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea
| | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Gyuri Kim
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea
| | - Eun-Seo Cho
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea
| | - Jueun Sim
- Department of Materials Science and Engineering, KAIST, Daejeon, Republic of Korea
| | - Kang-Han Lee
- Department of Biology, Chungnam National University, Daejeon, Republic of Korea
| | - Seonghoon Kim
- School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
- Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Republic of Korea
| | - He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Urs L Böhm
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Einstein Center for Neurosciences, NeuroCure Cluster of Excellence, Charité University of Medicine Berlin, Berlin, Germany
| | - Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Hua-An Tseng
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Jieun Choi
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea
| | - Stephani Edwina Lucia
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea
| | - Seung Hyun Ryu
- Interdisciplinary Program in Neuroscience, Seoul National University, Seoul, Republic of Korea
| | - Márton Rózsa
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Sunghoe Chang
- Department of Physiology and Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Pilhan Kim
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea
- Graduate School of Nanoscience and Technology, KAIST, Daejeon, Republic of Korea
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Kiryl D Piatkevich
- Research Center for Industries of the Future and School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Myunghwan Choi
- School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
- Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Republic of Korea
| | - Cheol-Hee Kim
- Department of Biology, Chungnam National University, Daejeon, Republic of Korea
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
| | - Jae-Byum Chang
- Department of Materials Science and Engineering, KAIST, Daejeon, Republic of Korea
| | - Young-Gyu Yoon
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea.
- KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea.
- Department of Semiconductor System Engineering, KAIST, Daejeon, Republic of Korea.
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17
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Weber TD, Moya MV, Kılıç K, Mertz J, Economo MN. High-speed multiplane confocal microscopy for voltage imaging in densely labeled neuronal populations. Nat Neurosci 2023; 26:1642-1650. [PMID: 37604887 PMCID: PMC11209746 DOI: 10.1038/s41593-023-01408-2] [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: 02/09/2022] [Accepted: 07/17/2023] [Indexed: 08/23/2023]
Abstract
Genetically encoded voltage indicators (GEVIs) hold immense potential for monitoring neuronal population activity. To date, best-in-class GEVIs rely on one-photon excitation. However, GEVI imaging of dense neuronal populations remains difficult because out-of-focus background fluorescence produces low contrast and excess noise when paired with conventional one-photon widefield imaging methods. To address this challenge, we developed an imaging system capable of efficient, high-contrast GEVI imaging at near-kHz rates and demonstrate it for in vivo and ex vivo imaging applications in the mouse neocortex. Our approach uses simultaneous multiplane imaging to monitor activity within contiguous tissue volumes with no penalty in speed or requirement for high excitation power. This approach, multi-Z imaging with confocal detection (MuZIC), permits high signal-to-noise ratio voltage imaging in densely labeled neuronal populations and is compatible with imaging through micro-optics. Moreover, it minimizes artifacts associated with concurrent imaging and optogenetic photostimulation for all-optical electrophysiology.
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Affiliation(s)
- Timothy D Weber
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Maria V Moya
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Kıvılcım Kılıç
- 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
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
- Photonics Center, Boston University, Boston, MA, USA
| | - Michael N Economo
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, USA.
- Neurophotonics Center, Boston University, Boston, MA, USA.
- Photonics Center, Boston University, Boston, MA, USA.
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18
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Lowet E, Sheehan DJ, Chialva U, De Oliveira Pena R, Mount RA, Xiao S, Zhou SL, Tseng HA, Gritton H, Shroff S, Kondabolu K, Cheung C, Wang Y, Piatkevich KD, Boyden ES, Mertz J, Hasselmo ME, Rotstein HG, Han X. Theta and gamma rhythmic coding through two spike output modes in the hippocampus during spatial navigation. Cell Rep 2023; 42:112906. [PMID: 37540599 PMCID: PMC10530698 DOI: 10.1016/j.celrep.2023.112906] [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: 01/08/2023] [Revised: 05/31/2023] [Accepted: 07/14/2023] [Indexed: 08/06/2023] Open
Abstract
Hippocampal CA1 neurons generate single spikes and stereotyped bursts of spikes. However, it is unclear how individual neurons dynamically switch between these output modes and whether these two spiking outputs relay distinct information. We performed extracellular recordings in spatially navigating rats and cellular voltage imaging and optogenetics in awake mice. We found that spike bursts are preferentially linked to cellular and network theta rhythms (3-12 Hz) and encode an animal's position via theta phase precession, particularly as animals are entering a place field. In contrast, single spikes exhibit additional coupling to gamma rhythms (30-100 Hz), particularly as animals leave a place field. Biophysical modeling suggests that intracellular properties alone are sufficient to explain the observed input frequency-dependent spike coding. Thus, hippocampal neurons regulate the generation of bursts and single spikes according to frequency-specific network and intracellular dynamics, suggesting that these spiking modes perform distinct computations to support spatial behavior.
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Affiliation(s)
- Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
| | - Daniel J Sheehan
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Ulises Chialva
- Departamento de Matemática, Universidad Nacional del Sur, Buenos Aires, Argentina
| | - Rodrigo De Oliveira Pena
- Federated Department of Biological Sciences, New Jersey Institute of Technology & Rutgers University, Newark, NJ, USA
| | - Rebecca A Mount
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Sheng Xiao
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Samuel L Zhou
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Hua-An Tseng
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Howard Gritton
- Department of Comparative Biosciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Sanaya Shroff
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | | | - Cyrus Cheung
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Yangyang Wang
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Kiryl D Piatkevich
- School of Life Sciences, Westlake University, Westlake Laboratory of Life Sciences and Biomedicine, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Edward S Boyden
- McGovern Institute for Brain Research and Howard Hughes Medical Institute, MIT, Cambridge, MA, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Michael E Hasselmo
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Horacio G Rotstein
- Federated Department of Biological Sciences, New Jersey Institute of Technology & Rutgers University, Newark, NJ, USA
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
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19
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Meng X, Ganapathy S, van Roemburg L, Post M, Brinks D. Voltage Imaging with Engineered Proton-Pumping Rhodopsins: Insights from the Proton Transfer Pathway. ACS PHYSICAL CHEMISTRY AU 2023; 3:320-333. [PMID: 37520318 PMCID: PMC10375888 DOI: 10.1021/acsphyschemau.3c00003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 08/01/2023]
Abstract
Voltage imaging using genetically encoded voltage indicators (GEVIs) has taken the field of neuroscience by storm in the past decade. Its ability to create subcellular and network level readouts of electrical dynamics depends critically on the kinetics of the response to voltage of the indicator used. Engineered microbial rhodopsins form a GEVI subclass known for their high voltage sensitivity and fast response kinetics. Here we review the essential aspects of microbial rhodopsin photocycles that are critical to understanding the mechanisms of voltage sensitivity in these proteins and link them to insights from efforts to create faster, brighter and more sensitive microbial rhodopsin-based GEVIs.
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Affiliation(s)
- Xin Meng
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
| | - Srividya Ganapathy
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
- Department
of Pediatrics & Cellular and Molecular Medicine, UCSD School of Medicine, La Jolla, California 92093, United States
| | - Lars van Roemburg
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
| | - Marco Post
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
| | - Daan Brinks
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
- Department
of Molecular Genetics, Erasmus University
Medical Center, 3015 GD Rotterdam, The Netherlands
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20
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Xiao S, Cunningham WJ, Kondabolu K, Lowet E, Moya MV, Mount R, Ravasio C, Economo MN, Han X, Mertz J. Large-scale deep tissue voltage imaging with targeted illumination confocal microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.21.548930. [PMID: 37502929 PMCID: PMC10370169 DOI: 10.1101/2023.07.21.548930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Voltage imaging with cellular specificity has been made possible by the tremendous advances in genetically encoded voltage indicators (GEVIs). 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 signal-to-noise ratio (SNR) 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 SNR 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 GEVI classes.
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Affiliation(s)
- Sheng Xiao
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | | | | | - Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Maria V. Moya
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Rebecca Mount
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Cara Ravasio
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Michael N. Economo
- Department of Biomedical Engineering, Boston University, Boston MA 02215
- Neurophotonics Center, Boston University, Boston MA, 02215
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston MA 02215
- Neurophotonics Center, Boston University, Boston MA, 02215
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston MA 02215
- Neurophotonics Center, Boston University, Boston MA, 02215
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21
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Platisa J, Ye X, Ahrens AM, Liu C, Chen IA, Davison IG, Tian L, Pieribone VA, Chen JL. High-speed low-light in vivo two-photon voltage imaging of large neuronal populations. Nat Methods 2023; 20:1095-1103. [PMID: 36973547 PMCID: PMC10894646 DOI: 10.1038/s41592-023-01820-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 02/16/2023] [Indexed: 03/29/2023]
Abstract
Monitoring spiking activity across large neuronal populations at behaviorally relevant timescales is critical for understanding neural circuit function. Unlike calcium imaging, voltage imaging requires kilohertz sampling rates that reduce fluorescence detection to near shot-noise levels. High-photon flux excitation can overcome photon-limited shot noise, but photobleaching and photodamage restrict the number and duration of simultaneously imaged neurons. We investigated an alternative approach aimed at low two-photon flux, which is voltage imaging below the shot-noise limit. This framework involved developing positive-going voltage indicators with improved spike detection (SpikeyGi and SpikeyGi2); a two-photon microscope ('SMURF') for kilohertz frame rate imaging across a 0.4 mm × 0.4 mm field of view; and a self-supervised denoising algorithm (DeepVID) for inferring fluorescence from shot-noise-limited signals. Through these combined advances, we achieved simultaneous high-speed deep-tissue imaging of more than 100 densely labeled neurons over 1 hour in awake behaving mice. This demonstrates a scalable approach for voltage imaging across increasing neuronal populations.
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Affiliation(s)
- Jelena Platisa
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT, USA
- The John B. Pierce Laboratory, New Haven, CT, USA
| | - Xin Ye
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | | | - Chang Liu
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | | | - Ian G Davison
- Neurophotonics Center, Boston University, Boston, MA, USA
- Department of Biology, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Lei Tian
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA
| | - Vincent A Pieribone
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT, USA.
- The John B. Pierce Laboratory, New Haven, CT, USA.
- Department of Neuroscience, Yale University, New Haven, CT, USA.
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
- Neurophotonics Center, Boston University, Boston, MA, USA.
- Department of Biology, Boston University, Boston, MA, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, USA.
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22
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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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23
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Shroff SN, Lowet E, Sridhar S, Gritton HJ, Abumuaileq M, Tseng HA, Cheung C, Zhou SL, Kondabolu K, Han X. Striatal cholinergic interneuron membrane voltage tracks locomotor rhythms in mice. Nat Commun 2023; 14:3802. [PMID: 37365189 PMCID: PMC10293266 DOI: 10.1038/s41467-023-39497-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 06/07/2023] [Indexed: 06/28/2023] Open
Abstract
Rhythmic neural network activity has been broadly linked to behavior. However, it is unclear how membrane potentials of individual neurons track behavioral rhythms, even though many neurons exhibit pace-making properties in isolated brain circuits. To examine whether single-cell voltage rhythmicity is coupled to behavioral rhythms, we focused on delta-frequencies (1-4 Hz) that are known to occur at both the neural network and behavioral levels. We performed membrane voltage imaging of individual striatal neurons simultaneously with network-level local field potential recordings in mice during voluntary movement. We report sustained delta oscillations in the membrane potentials of many striatal neurons, particularly cholinergic interneurons, which organize spikes and network oscillations at beta-frequencies (20-40 Hz) associated with locomotion. Furthermore, the delta-frequency patterned cellular dynamics are coupled to animals' stepping cycles. Thus, delta-rhythmic cellular dynamics in cholinergic interneurons, known for their autonomous pace-making capabilities, play an important role in regulating network rhythmicity and movement patterning.
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Affiliation(s)
- Sanaya N Shroff
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
| | - Sudiksha Sridhar
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Howard J Gritton
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Department of Comparative Biosciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | - Hua-An Tseng
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Cyrus Cheung
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Samuel L Zhou
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | | | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
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24
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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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25
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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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26
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Mohebi A, Collins VL, Berke JD. Accumbens cholinergic interneurons dynamically promote dopamine release and enable motivation. eLife 2023; 12:e85011. [PMID: 37272423 PMCID: PMC10259987 DOI: 10.7554/elife.85011] [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: 11/19/2022] [Accepted: 05/30/2023] [Indexed: 06/06/2023] Open
Abstract
Motivation to work for potential rewards is critically dependent on dopamine (DA) in the nucleus accumbens (NAc). DA release from NAc axons can be controlled by at least two distinct mechanisms: (1) action potentials propagating from DA cell bodies in the ventral tegmental area (VTA), and (2) activation of β2* nicotinic receptors by local cholinergic interneurons (CINs). How CIN activity contributes to NAc DA dynamics in behaving animals is not well understood. We monitored DA release in the NAc Core of awake, unrestrained rats using the DA sensor RdLight1, while simultaneously monitoring or manipulating CIN activity at the same location. CIN stimulation rapidly evoked DA release, and in contrast to slice preparations, this DA release showed no indication of short-term depression or receptor desensitization. The sound of unexpected food delivery evoked a brief joint increase in CIN population activity and DA release, with a second joint increase as rats approached the food. In an operant task, we observed fast ramps in CIN activity during approach behaviors, either to start the trial or to collect rewards. These CIN ramps co-occurred with DA release ramps, without corresponding changes in the firing of lateral VTA DA neurons. Finally, we examined the effects of blocking CIN influence over DA release through local NAc infusion of DHβE, a selective antagonist of β2* nicotinic receptors. DHβE dose-dependently interfered with motivated approach decisions, mimicking the effects of a DA antagonist. Our results support a key influence of CINs over motivated behavior via the local regulation of DA release.
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Affiliation(s)
- Ali Mohebi
- Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Val L Collins
- Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Joshua D Berke
- Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
- Department of Psychiatry and Behavioral Sciences, University of California, San FranciscoSan FranciscoUnited States
- Neuroscience Graduate Program, University of California, San FranciscoSan FranciscoUnited States
- Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoUnited States
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27
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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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28
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Hughes C, Kozai T. Dynamic amplitude modulation of microstimulation evokes biomimetic onset and offset transients and reduces depression of evoked calcium responses in sensory cortices. Brain Stimul 2023; 16:939-965. [PMID: 37244370 PMCID: PMC10330928 DOI: 10.1016/j.brs.2023.05.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 05/15/2023] [Accepted: 05/17/2023] [Indexed: 05/29/2023] Open
Abstract
BACKGROUND Intracortical microstimulation (ICMS) is an emerging approach to restore sensation to people with neurological injury or disease. Biomimetic microstimulation, or stimulus trains that mimic neural activity in the brain through encoding of onset and offset transients, could improve the utility of ICMS for brain-computer interface (BCI) applications, but how biomimetic microstimulation affects neural activation is not understood. Current "biomimetic" ICMS trains aim to reproduce the strong onset and offset transients evoked in the brain by sensory input through dynamic modulation of stimulus parameters. Stimulus induced depression of neural activity (decreases in evoked intensity over time) is also a potential barrier to clinical implementation of sensory feedback, and dynamic microstimulation may reduce this effect. OBJECTIVE We evaluated how bio-inspired ICMS trains with dynamic modulation of amplitude and/or frequency change the calcium response, spatial distribution, and depression of neurons in the somatosensory and visual cortices. METHODS Calcium responses of neurons were measured in Layer 2/3 of visual and somatosensory cortices of anesthetized GCaMP6s mice in response to ICMS trains with fixed amplitude and frequency (Fixed) and three dynamic ICMS trains that increased the stimulation intensity during the onset and offset of stimulation by modulating the amplitude (DynAmp), frequency (DynFreq), or amplitude and frequency (DynBoth). ICMS was provided for either 1-s with 4-s breaks (Short) or for 30-s with 15-s breaks (Long). RESULTS DynAmp and DynBoth trains evoked distinct onset and offset transients in recruited neural populations, while DynFreq trains evoked population activity similar to Fixed trains. Individual neurons had heterogeneous responses primarily based on how quickly they depressed to ICMS, where neurons farther from the electrode depressed faster and a small subpopulation (1-5%) were modulated by DynFreq trains. Neurons that depressed to Short trains were also more likely to depress to Long trains, but Long trains induced more depression overall due to the increased stimulation length. Increasing the amplitude during the hold phase resulted in an increase in recruitment and intensity which resulted in more depression and reduced offset responses. Dynamic amplitude modulation reduced stimulation induced depression by 14.6 ± 0.3% for Short and 36.1 ± 0.6% for Long trains. Ideal observers were 0.031 ± 0.009 s faster for onset detection and 1.33 ± 0.21 s faster for offset detection with dynamic amplitude encoding. CONCLUSIONS Dynamic amplitude modulation evokes distinct onset and offset transients, reduces depression of neural calcium activity, and decreases total charge injection for sensory feedback in BCIs by lowering recruitment of neurons during long maintained periods of ICMS. In contrast, dynamic frequency modulation evokes distinct onset and offset transients in a small subpopulation of neurons but also reduces depression in recruited neurons by reducing the rate of activation.
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Affiliation(s)
- Christopher Hughes
- Department of Bioengineering, University of Pittsburgh, USA; Center for the Neural Basis of Cognition, USA
| | - Takashi Kozai
- Department of Bioengineering, University of Pittsburgh, USA; Center for the Neural Basis of Cognition, USA; Department of Neuroscience, University of Pittsburgh, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA; NeuroTech Center, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA.
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29
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Noguchi A, Yamashiro K, Matsumoto N, Ikegaya Y. Theta oscillations represent collective dynamics of multineuronal membrane potentials of murine hippocampal pyramidal cells. Commun Biol 2023; 6:398. [PMID: 37045975 PMCID: PMC10097823 DOI: 10.1038/s42003-023-04719-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 03/16/2023] [Indexed: 04/14/2023] Open
Abstract
Theta (θ) oscillations are one of the characteristic local field potentials (LFPs) in the hippocampus that emerge during spatial navigation, exploratory sniffing, and rapid eye movement sleep. LFPs are thought to summarize multineuronal events, including synaptic currents and action potentials. However, no in vivo study to date has directly interrelated θ oscillations with the membrane potentials (Vm) of multiple neurons, and it remains unclear whether LFPs can be predicted from multineuronal Vms. Here, we simultaneously patch-clamp up to three CA1 pyramidal neurons in awake or anesthetized mice and find that the temporal evolution of the power and frequency of θ oscillations in Vms (θVms) are weakly but significantly correlate with LFP θ oscillations (θLFP) such that a deep neural network could predict the θLFP waveforms based on the θVm traces of three neurons. Therefore, individual neurons are loosely interdependent to ensure freedom of activity, but they partially share information to collectively produce θLFP.
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Affiliation(s)
- Asako Noguchi
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, 113-0033, Japan.
| | - Kotaro Yamashiro
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, 113-0033, Japan
| | - Nobuyoshi Matsumoto
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, 113-0033, Japan
- Institute for AI and Beyond, The University of Tokyo, Tokyo, 113-0033, Japan
| | - Yuji Ikegaya
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, 113-0033, Japan
- Institute for AI and Beyond, The University of Tokyo, Tokyo, 113-0033, Japan
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita City, Osaka, 565-0871, Japan
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30
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Chen S, Yang Q, Lim S. Efficient inference of synaptic plasticity rule with Gaussian process regression. iScience 2023; 26:106182. [PMID: 36879810 PMCID: PMC9985048 DOI: 10.1016/j.isci.2023.106182] [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: 07/22/2022] [Revised: 01/24/2023] [Accepted: 02/07/2023] [Indexed: 02/16/2023] Open
Abstract
Finding the form of synaptic plasticity is critical to understanding its functions underlying learning and memory. We investigated an efficient method to infer synaptic plasticity rules in various experimental settings. We considered biologically plausible models fitting a wide range of in-vitro studies and examined the recovery of their firing-rate dependence from sparse and noisy data. Among the methods assuming low-rankness or smoothness of plasticity rules, Gaussian process regression (GPR), a nonparametric Bayesian approach, performs the best. Under the conditions measuring changes in synaptic weights directly or measuring changes in neural activities as indirect observables of synaptic plasticity, which leads to different inference problems, GPR performs well. Also, GPR could simultaneously recover multiple plasticity rules and robustly perform under various plasticity rules and noise levels. Such flexibility and efficiency, particularly at the low sampling regime, make GPR suitable for recent experimental developments and inferring a broader class of plasticity models.
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Affiliation(s)
- Shirui Chen
- Department of Applied Mathematics, University of Washington, Lewis Hall 201, Box 353925, Seattle, WA 98195-3925, USA
- Neural Science, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China
| | - Qixin Yang
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, The Suzanne and Charles Goodman Brain Sciences Building, Edmond J. Safra Campus, Jerusalem, 9190401, Israel
- Neural Science, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China
| | - Sukbin Lim
- Neural Science, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China
- NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, 3663 Zhongshan Road North, Shanghai, 200062, China
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31
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Fan LZ, Kim DK, Jennings JH, Tian H, Wang PY, Ramakrishnan C, Randles S, Sun Y, Thadhani E, Kim YS, Quirin S, Giocomo L, Cohen AE, Deisseroth K. All-optical physiology resolves a synaptic basis for behavioral timescale plasticity. Cell 2023; 186:543-559.e19. [PMID: 36669484 PMCID: PMC10327443 DOI: 10.1016/j.cell.2022.12.035] [Citation(s) in RCA: 44] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 10/19/2022] [Accepted: 12/19/2022] [Indexed: 01/20/2023]
Abstract
Learning has been associated with modifications of synaptic and circuit properties, but the precise changes storing information in mammals have remained largely unclear. We combined genetically targeted voltage imaging with targeted optogenetic activation and silencing of pre- and post-synaptic neurons to study the mechanisms underlying hippocampal behavioral timescale plasticity. In mice navigating a virtual-reality environment, targeted optogenetic activation of individual CA1 cells at specific places induced stable representations of these places in the targeted cells. Optical elicitation, recording, and modulation of synaptic transmission in behaving mice revealed that activity in presynaptic CA2/3 cells was required for the induction of plasticity in CA1 and, furthermore, that during induction of these place fields in single CA1 cells, synaptic input from CA2/3 onto these same cells was potentiated. These results reveal synaptic implementation of hippocampal behavioral timescale plasticity and define a methodology to resolve synaptic plasticity during learning and memory in behaving mammals.
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Affiliation(s)
- Linlin Z Fan
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Doo Kyung Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Joshua H Jennings
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Peter Y Wang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | - Sawyer Randles
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Yanjun Sun
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Elina Thadhani
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Yoon Seok Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Sean Quirin
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Lisa Giocomo
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA; Department of Physics, Harvard University, Cambridge, MA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford, CA, USA.
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32
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Day-Cooney J, Dalangin R, Zhong H, Mao T. Genetically encoded fluorescent sensors for imaging neuronal dynamics in vivo. J Neurochem 2023; 164:284-308. [PMID: 35285522 PMCID: PMC11322610 DOI: 10.1111/jnc.15608] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/14/2022] [Accepted: 02/25/2022] [Indexed: 11/29/2022]
Abstract
The brain relies on many forms of dynamic activities in individual neurons, from synaptic transmission to electrical activity and intracellular signaling events. Monitoring these neuronal activities with high spatiotemporal resolution in the context of animal behavior is a necessary step to achieve a mechanistic understanding of brain function. With the rapid development and dissemination of highly optimized genetically encoded fluorescent sensors, a growing number of brain activities can now be visualized in vivo. To date, cellular calcium imaging, which has been largely used as a proxy for electrical activity, has become a mainstay in systems neuroscience. While challenges remain, voltage imaging of neural populations is now possible. In addition, it is becoming increasingly practical to image over half a dozen neurotransmitters, as well as certain intracellular signaling and metabolic activities. These new capabilities enable neuroscientists to test previously unattainable hypotheses and questions. This review summarizes recent progress in the development and delivery of genetically encoded fluorescent sensors, and highlights example applications in the context of in vivo imaging.
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Affiliation(s)
- Julian Day-Cooney
- Vollum Institute, Oregon Health and Science University, Portland, Oregon, USA
| | - Rochelin Dalangin
- Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, California, USA
| | - Haining Zhong
- Vollum Institute, Oregon Health and Science University, Portland, Oregon, USA
| | - Tianyi Mao
- Vollum Institute, Oregon Health and Science University, Portland, Oregon, USA
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33
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Pedraza-González L, Barneschi L, Marszałek M, Padula D, De Vico L, Olivucci M. Automated QM/MM Screening of Rhodopsin Variants with Enhanced Fluorescence. J Chem Theory Comput 2023; 19:293-310. [PMID: 36516450 DOI: 10.1021/acs.jctc.2c00928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We present a computational protocol for the fast and automated screening of excited-state hybrid quantum mechanics/molecular mechanics (QM/MM) models of rhodopsins to be used as fluorescent probes based on the automatic rhodopsin modeling protocol (a-ARM). Such "a-ARM fluorescence screening protocol" is implemented through a general Python-based driver, PyARM, that is also proposed here. The implementation and performance of the protocol are benchmarked using different sets of rhodopsin variants whose absorption and, more relevantly, emission spectra have been experimentally measured. We show that, despite important limitations that make unsafe to use it as a black-box tool, the protocol reproduces the observed trends in fluorescence and it is capable of selecting novel potentially fluorescent rhodopsins. We also show that the protocol can be used in mechanistic investigations to discern fluorescence enhancement effects associated with a near degeneracy of the S1/S2 states or, alternatively, with a barrier generated via coupling of the S0/S1 wave functions.
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Affiliation(s)
- Laura Pedraza-González
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy
| | - Leonardo Barneschi
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy
| | - Michał Marszałek
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy.,Faculty of Chemistry, Wrocław University of Science and Technology, Wybrzeże Wyspiaǹskiego 27, 50-370 Wrocław, Poland
| | - Daniele Padula
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy
| | - Luca De Vico
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy
| | - Massimo Olivucci
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy.,Department of Chemistry, Bowling Green State University, Bowling Green, Ohio 43403, United States
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34
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Lee J, Hwang S, Hong N, Kwak J, Jang JE, Chung S, Kang H. High temporal resolution transparent thermoelectric temperature sensors for photothermal effect sensing. MATERIALS HORIZONS 2023; 10:160-170. [PMID: 36321545 DOI: 10.1039/d2mh00813k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
We propose inkjet-printed high-speed and transparent temperature sensors based on the thermoelectric effect for direct monitoring of the photothermal effect. They consist of highly transparent organic thermoelectric materials that allow excellent biocompatibility and sub-ms temporal resolution, simultaneously. Our transparent thermoelectric temperature sensors can be used to advance various photothermal biomedical applications.
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Affiliation(s)
- Junhee Lee
- Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea.
| | - Seongkwon Hwang
- Soft Hybrid Materials Research Center, Korea Institute of Science and Technology, Seoul 02792, Korea.
- Department of Electrical and Computer Engineering, Inter-University Semiconductor Research Center (ISRC), and Soft Foundry Institute, Seoul National University, Seoul 08826, Korea
| | - Nari Hong
- Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea.
| | - Jeonghun Kwak
- Department of Electrical and Computer Engineering, Inter-University Semiconductor Research Center (ISRC), and Soft Foundry Institute, Seoul National University, Seoul 08826, Korea
| | - Jae Eun Jang
- Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea.
| | - Seungjun Chung
- Soft Hybrid Materials Research Center, Korea Institute of Science and Technology, Seoul 02792, Korea.
- KHU-KIST Department of Converging Science and Technology, Kyung Hee University, Seoul, 02447, Korea
| | - Hongki Kang
- Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea.
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35
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Chiang CC, Durand DM. Subthreshold Oscillating Waves in Neural Tissue Propagate by Volume Conduction and Generate Interference. Brain Sci 2022; 13:74. [PMID: 36672054 PMCID: PMC9856930 DOI: 10.3390/brainsci13010074] [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: 11/29/2022] [Revised: 12/21/2022] [Accepted: 12/28/2022] [Indexed: 12/31/2022] Open
Abstract
Subthreshold neural oscillations have been observed in several brain regions and can influence the timing of neural spikes. However, the spatial extent and function of these spontaneous oscillations remain unclear. To study the mechanisms underlying these oscillations, we use optogenetic stimulation to generate oscillating waves in the longitudinal hippocampal slice expressing optopatch proteins. We found that optogenetic stimulation can generate two types of neural activity: suprathreshold neural spikes and subthreshold oscillating waves. Both waves could propagate bidirectionally at similar speeds and go through a transection of the tissue. The propagating speed is independent of the oscillating frequency but increases with increasing amplitudes of the waves. The endogenous electric fields generated by oscillating waves are about 0.6 mV/mm along the dendrites and about 0.3 mV/mm along the cell layer. We also observed that these oscillating waves could interfere with each other. Optical stimulation applied simultaneously at each slice end generated a larger wave in the middle of the tissue (constructive interference) or destructive interference with laser signals in opposite phase. However, the suprathreshold neural spikes were annihilated when they collided. Finally, the waves were not affected by the NMDA blocker (APV) and still propagated in the presence of tetrodotoxin (TTX) but at a significantly lower amplitude. The role of these subthreshold waves in neural function is unknown, but the results show that at low amplitude, the subthreshold propagating waves lack a refractory period allowing a novel analog form of preprocessing of neural activity by interference independent of synaptic transmission.
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Affiliation(s)
| | - Dominique M. Durand
- Neural Engineering Center, Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
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36
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Lowet E, Kondabolu K, Zhou S, Mount RA, Wang Y, Ravasio CR, Han X. Deep brain stimulation creates informational lesion through membrane depolarization in mouse hippocampus. Nat Commun 2022; 13:7709. [PMID: 36513664 PMCID: PMC9748039 DOI: 10.1038/s41467-022-35314-1] [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: 02/04/2022] [Accepted: 11/24/2022] [Indexed: 12/14/2022] Open
Abstract
Deep brain stimulation (DBS) is a promising neuromodulation therapy, but the neurophysiological mechanisms of DBS remain unclear. In awake mice, we performed high-speed membrane voltage fluorescence imaging of individual hippocampal CA1 neurons during DBS delivered at 40 Hz or 140 Hz, free of electrical interference. DBS powerfully depolarized somatic membrane potentials without suppressing spike rate, especially at 140 Hz. Further, DBS paced membrane voltage and spike timing at the stimulation frequency and reduced timed spiking output in response to hippocampal network theta-rhythmic (3-12 Hz) activity patterns. To determine whether DBS directly impacts cellular processing of inputs, we optogenetically evoked theta-rhythmic membrane depolarization at the soma. We found that DBS-evoked membrane depolarization was correlated with DBS-mediated suppression of neuronal responses to optogenetic inputs. These results demonstrate that DBS produces powerful membrane depolarization that interferes with the ability of individual neurons to respond to inputs, creating an informational lesion.
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Affiliation(s)
- Eric Lowet
- Boston University, Department of Biomedical Engineering, Boston, MA, 02215, USA.
| | - Krishnakanth Kondabolu
- grid.189504.10000 0004 1936 7558Boston University, Department of Biomedical Engineering, Boston, MA 02215 USA
| | - Samuel Zhou
- grid.189504.10000 0004 1936 7558Boston University, Department of Biomedical Engineering, Boston, MA 02215 USA
| | - Rebecca A. Mount
- grid.189504.10000 0004 1936 7558Boston University, Department of Biomedical Engineering, Boston, MA 02215 USA
| | - Yangyang Wang
- grid.189504.10000 0004 1936 7558Boston University, Department of Biomedical Engineering, Boston, MA 02215 USA
| | - Cara R. Ravasio
- grid.189504.10000 0004 1936 7558Boston University, Department of Biomedical Engineering, Boston, MA 02215 USA
| | - Xue Han
- Boston University, Department of Biomedical Engineering, Boston, MA, 02215, USA.
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37
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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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38
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Kannan M, Vasan G, Haziza S, Huang C, Chrapkiewicz R, Luo J, Cardin JA, Schnitzer MJ, Pieribone VA. Dual-polarity voltage imaging of the concurrent dynamics of multiple neuron types. Science 2022; 378:eabm8797. [PMID: 36378956 PMCID: PMC9703638 DOI: 10.1126/science.abm8797] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Genetically encoded fluorescent voltage indicators are ideally suited to reveal the millisecond-scale interactions among and between targeted cell populations. However, current indicators lack the requisite sensitivity for in vivo multipopulation imaging. We describe next-generation green and red voltage sensors, Ace-mNeon2 and VARNAM2, and their reverse response-polarity variants pAce and pAceR. Our indicators enable 0.4- to 1-kilohertz voltage recordings from >50 spiking neurons per field of view in awake mice and ~30-minute continuous imaging in flies. Using dual-polarity multiplexed imaging, we uncovered brain state–dependent antagonism between neocortical somatostatin-expressing (SST
+
) and vasoactive intestinal peptide–expressing (VIP
+
) interneurons and contributions to hippocampal field potentials from cell ensembles with distinct axonal projections. By combining three mutually compatible indicators, we performed simultaneous triple-population imaging. These approaches will empower investigations of the dynamic interplay between neuronal subclasses at single-spike resolution.
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Affiliation(s)
- Madhuvanthi Kannan
- The John B. Pierce Laboratory, New Haven, CT 06519, USA
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT 06520, USA
| | - Ganesh Vasan
- The John B. Pierce Laboratory, New Haven, CT 06519, USA
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT 06520, USA
| | - Simon Haziza
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
| | - Cheng Huang
- James H. Clark Center, 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
| | - Junjie Luo
- 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
| | - Jessica A. Cardin
- Department of Neuroscience, Yale University, New Haven, CT 06520, USA
- Kavli Institute of Neuroscience, Yale University, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06520, 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
| | - Vincent A. Pieribone
- The John B. Pierce Laboratory, New Haven, CT 06519, USA
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT 06520, USA
- Department of Neuroscience, Yale University, New Haven, CT 06520, USA
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39
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Abstract
The ability to develop effective new treatments for epilepsy may depend on improved understanding of seizure pathophysiology, about which many questions remain. Dynamic fluorescence imaging of activity at single-neuron resolution with fluorescent indicators in experimental model systems in vivo has revolutionized basic neuroscience and has the potential to do so for epilepsy research as well. Here, we review salient issues as they pertain to experimental imaging in basic epilepsy research, including commonly used imaging technologies, data processing and analysis, interpretation of results, and selected examples of how imaging-based approaches have revealed new insight into mechanisms of seizures and epilepsy.
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Affiliation(s)
- Patrick N. Lawlor
- Division of Neurology, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Ethan M. Goldberg
- Division of Neurology, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA
- The Epilepsy Neurogenetics Initiative, The Children’s Hospital of Philadelphia, Philadelphia
- Department of Neurology, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neuroscience, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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40
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Machado TA, Kauvar IV, Deisseroth K. Multiregion neuronal activity: the forest and the trees. Nat Rev Neurosci 2022; 23:683-704. [PMID: 36192596 PMCID: PMC10327445 DOI: 10.1038/s41583-022-00634-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2022] [Indexed: 12/12/2022]
Abstract
The past decade has witnessed remarkable advances in the simultaneous measurement of neuronal activity across many brain regions, enabling fundamentally new explorations of the brain-spanning cellular dynamics that underlie sensation, cognition and action. These recently developed multiregion recording techniques have provided many experimental opportunities, but thoughtful consideration of methodological trade-offs is necessary, especially regarding field of view, temporal acquisition rate and ability to guarantee cellular resolution. When applied in concert with modern optogenetic and computational tools, multiregion recording has already made possible fundamental biological discoveries - in part via the unprecedented ability to perform unbiased neural activity screens for principles of brain function, spanning dozens of brain areas and from local to global scales.
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Affiliation(s)
- Timothy A Machado
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Isaac V Kauvar
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
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41
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Hanson MA, Wester JC. Advances in approaches to study cell-type specific cortical circuits throughout development. Front Cell Neurosci 2022; 16:1031389. [PMID: 36324861 PMCID: PMC9618604 DOI: 10.3389/fncel.2022.1031389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 09/29/2022] [Indexed: 11/17/2022] Open
Abstract
Neurons in the neocortex and hippocampus are diverse and form synaptic connections that depend on their type. Recent work has improved our understanding of neuronal cell-types and how to target them for experiments. This is crucial for investigating cortical circuit architecture, as the current catalog of established cell-type specific circuit motifs is small relative to the diversity of neuronal subtypes. Some of these motifs are found throughout the cortex, suggesting they are canonical circuits necessary for basic computations. However, the extent to which circuit organization is stereotyped across the brain or varies by cortical region remains unclear. Cortical circuits are also plastic, and their organization evolves throughout each developmental stage. Thus, experimental access to neuronal subtypes with temporal control is essential for studying cortical structure and function. In this mini review, we highlight several recent advances to target specific neuronal subtypes and study their synaptic connectivity and physiology throughout development. We emphasize approaches that combine multiple techniques, provide examples of successful applications, and describe potential future applications of novel tools.
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Affiliation(s)
- Meretta A. Hanson
- Department of Neuroscience, The Ohio State University College of Medicine, Columbus, OH, United States
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42
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Penzkofer A, Silapetere A, Hegemann P. Theoretical Investigation of the Photocycle Dynamics of the Archaerhodopsin 3 Based Fluorescent Voltage Sensor Archon2. J Photochem Photobiol A Chem 2022. [DOI: 10.1016/j.jphotochem.2022.114366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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43
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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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44
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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: 26] [Impact Index Per Article: 13.0] [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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Donaldson PD, Navabi ZS, Carter RE, Fausner SML, Ghanbari L, Ebner TJ, Swisher SL, Kodandaramaiah SB. Polymer Skulls With Integrated Transparent Electrode Arrays for Cortex-Wide Opto-Electrophysiological Recordings. Adv Healthc Mater 2022; 11:e2200626. [PMID: 35869830 PMCID: PMC9573805 DOI: 10.1002/adhm.202200626] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/23/2022] [Indexed: 01/27/2023]
Abstract
Electrophysiology and optical imaging provide complementary neural sensing capabilities - electrophysiological recordings have high temporal resolution, while optical imaging allows recording of genetically-defined populations at high spatial resolution. Combining these two modalities for simultaneous large-scale, multimodal sensing of neural activity across multiple brain regions can be very powerful. Here, transparent, inkjet-printed electrode arrays with outstanding optical and electrical properties are seamlessly integrated with morphologically conformant transparent polymer skulls. Implanted on transgenic mice expressing the Calcium (Ca2+ ) indicator GCaMP6f in excitatory neurons, these "eSee-Shells" provide a robust opto-electrophysiological interface for over 100 days. eSee-Shells enable simultaneous mesoscale Ca2+ imaging and electrocorticography (ECoG) acquisition from multiple brain regions covering 45 mm2 of cortex under anesthesia and in awake animals. The clarity and transparency of eSee-Shells allow recording single-cell Ca2+ signals directly below the electrodes and interconnects. Simultaneous multimodal measurement of cortical dynamics reveals changes in both ECoG and Ca2+ signals that depend on the behavioral state.
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Affiliation(s)
- Preston D Donaldson
- Department of Electrical and Computer Engineering, University of Minnesota Twin Cities, 200 Union St SE, Minneapolis, MN, 55455, USA
| | - Zahra S Navabi
- Department of Mechanical Engineering, University of Minnesota Twin Cities, 117 Pleasant St SE, Minneapolis, MN, 55455, USA
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, Twin Cities, 312 Church St. SE, 7-105 Nils Hasselmo Hall, Minneapolis, MN, 55455, USA
| | - Skylar M L Fausner
- Department of Mechanical Engineering, University of Minnesota Twin Cities, 117 Pleasant St SE, Minneapolis, MN, 55455, USA
| | - Leila Ghanbari
- Department of Mechanical Engineering, University of Minnesota Twin Cities, 117 Pleasant St SE, Minneapolis, MN, 55455, USA
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, Twin Cities, 312 Church St. SE, 7-105 Nils Hasselmo Hall, Minneapolis, MN, 55455, USA
| | - Sarah L Swisher
- Department of Electrical and Computer Engineering, University of Minnesota Twin Cities, 200 Union St SE, Minneapolis, MN, 55455, USA
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota Twin Cities, 117 Pleasant St SE, Minneapolis, MN, 55455, USA
- Department of Neuroscience, University of Minnesota, Twin Cities, 312 Church St. SE, 7-105 Nils Hasselmo Hall, Minneapolis, MN, 55455, USA
- Department of Biomedical Engineering, University of Minnesota Twin Cities, 321 Church St SE, Minneapolis, MN, 55455, USA
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46
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Dendritic Morphology Affects the Velocity and Amplitude of Back-propagating Action Potentials. Neurosci Bull 2022; 38:1330-1346. [PMID: 35984622 PMCID: PMC9672184 DOI: 10.1007/s12264-022-00931-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 05/20/2022] [Indexed: 11/30/2022] Open
Abstract
The back-propagating action potential (bpAP) is crucial for neuronal signal integration and synaptic plasticity in dendritic trees. Its properties (velocity and amplitude) can be affected by dendritic morphology. Due to limited spatial resolution, it has been difficult to explore the specific propagation process of bpAPs along dendrites and examine the influence of dendritic morphology, such as the dendrite diameter and branching pattern, using patch-clamp recording. By taking advantage of Optopatch, an all-optical electrophysiological method, we made detailed recordings of the real-time propagation of bpAPs in dendritic trees. We found that the velocity of bpAPs was not uniform in a single dendrite, and the bpAP velocity differed among distinct dendrites of the same neuron. The velocity of a bpAP was positively correlated with the diameter of the dendrite on which it propagated. In addition, when bpAPs passed through a dendritic branch point, their velocity decreased significantly. Similar to velocity, the amplitude of bpAPs was also positively correlated with dendritic diameter, and the attenuation patterns of bpAPs differed among different dendrites. Simulation results from neuron models with different dendritic morphology corresponded well with the experimental results. These findings indicate that the dendritic diameter and branching pattern significantly influence the properties of bpAPs. The diversity among the bpAPs recorded in different neurons was mainly due to differences in dendritic morphology. These results may inspire the construction of neuronal models to predict the propagation of bpAPs in dendrites with enormous variation in morphology, to further illuminate the role of bpAPs in neuronal communication.
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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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Papaioannou S, Medini P. Advantages, Pitfalls, and Developments of All Optical Interrogation Strategies of Microcircuits in vivo. Front Neurosci 2022; 16:859803. [PMID: 35837124 PMCID: PMC9274136 DOI: 10.3389/fnins.2022.859803] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 05/30/2022] [Indexed: 12/03/2022] Open
Abstract
The holy grail for every neurophysiologist is to conclude a causal relationship between an elementary behaviour and the function of a specific brain area or circuit. Our effort to map elementary behaviours to specific brain loci and to further manipulate neural activity while observing the alterations in behaviour is in essence the goal for neuroscientists. Recent advancements in the area of experimental brain imaging in the form of longer wavelength near infrared (NIR) pulsed lasers with the development of highly efficient optogenetic actuators and reporters of neural activity, has endowed us with unprecedented resolution in spatiotemporal precision both in imaging neural activity as well as manipulating it with multiphoton microscopy. This readily available toolbox has introduced a so called all-optical physiology and interrogation of circuits and has opened new horizons when it comes to precisely, fast and non-invasively map and manipulate anatomically, molecularly or functionally identified mesoscopic brain circuits. The purpose of this review is to describe the advantages and possible pitfalls of all-optical approaches in system neuroscience, where by all-optical we mean use of multiphoton microscopy to image the functional response of neuron(s) in the network so to attain flexible choice of the cells to be also optogenetically photostimulated by holography, in absence of electrophysiology. Spatio-temporal constraints will be compared toward the classical reference of electrophysiology methods. When appropriate, in relation to current limitations of current optical approaches, we will make reference to latest works aimed to overcome these limitations, in order to highlight the most recent developments. We will also provide examples of types of experiments uniquely approachable all-optically. Finally, although mechanically non-invasive, all-optical electrophysiology exhibits potential off-target effects which can ambiguate and complicate the interpretation of the results. In summary, this review is an effort to exemplify how an all-optical experiment can be designed, conducted and interpreted from the point of view of the integrative neurophysiologist.
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de Grip WJ, Ganapathy S. Rhodopsins: An Excitingly Versatile Protein Species for Research, Development and Creative Engineering. Front Chem 2022; 10:879609. [PMID: 35815212 PMCID: PMC9257189 DOI: 10.3389/fchem.2022.879609] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 05/16/2022] [Indexed: 01/17/2023] Open
Abstract
The first member and eponym of the rhodopsin family was identified in the 1930s as the visual pigment of the rod photoreceptor cell in the animal retina. It was found to be a membrane protein, owing its photosensitivity to the presence of a covalently bound chromophoric group. This group, derived from vitamin A, was appropriately dubbed retinal. In the 1970s a microbial counterpart of this species was discovered in an archaeon, being a membrane protein also harbouring retinal as a chromophore, and named bacteriorhodopsin. Since their discovery a photogenic panorama unfolded, where up to date new members and subspecies with a variety of light-driven functionality have been added to this family. The animal branch, meanwhile categorized as type-2 rhodopsins, turned out to form a large subclass in the superfamily of G protein-coupled receptors and are essential to multiple elements of light-dependent animal sensory physiology. The microbial branch, the type-1 rhodopsins, largely function as light-driven ion pumps or channels, but also contain sensory-active and enzyme-sustaining subspecies. In this review we will follow the development of this exciting membrane protein panorama in a representative number of highlights and will present a prospect of their extraordinary future potential.
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Affiliation(s)
- Willem J. de Grip
- Leiden Institute of Chemistry, Department of Biophysical Organic Chemistry, Leiden University, Leiden, Netherlands
- Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, Netherlands
| | - Srividya Ganapathy
- Department of Imaging Physics, Delft University of Technology, Netherlands
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Lee S, Kang BE, Song YK, Baker BJ. A trafficking motif alters GEVI activity implicating persistent protein interactions at the membrane. BIOPHYSICAL REPORTS 2022; 2:100047. [PMID: 36425771 PMCID: PMC9680705 DOI: 10.1016/j.bpr.2022.100047] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 02/18/2022] [Indexed: 11/30/2022]
Abstract
Efficient plasma-membrane expression is critical for genetically encoded voltage indicators (GEVIs). To improve the plasma-membrane expression, we introduced multiple combinations of plasma-membrane trafficking motifs at different positions to members of the Bongwoori family of GEVIs. An improvement from 20% to 27% in the ΔF/F/100 mV depolarization of the plasma membrane was observed when a Golgi transport motif was inserted near the N-terminus in conjunction with an endoplasmic reticulum release motif near the C-terminus of the protein. Unfortunately, this variant was also slower. The weighted tau on of the variant (25 ms) was more than double the original construct (11 ms). The weighted tau off was >20 ms compared with 10 ms for the original GEVI. The voltage range of the GEVI was also shifted to more negative potentials. Insertion of spacer amino acids between the fluorescent-protein domain and the endoplasmic reticulum release motif at the C-terminus rescued the speed of both the tau on and tau off while restoring the voltage range and maintaining the improved voltage-dependent optical signal. These results suggest that while trafficking motifs do improve plasma-membrane expression, they may also mediate persistent associations that affect the functioning of the protein.
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