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Li Y, Cheng Z, Wang C, Lin J, Jiang H, Cui M. Geometric transformation adaptive optics (GTAO) for volumetric deep brain imaging through gradient-index lenses. Nat Commun 2024; 15:1031. [PMID: 38310087 PMCID: PMC10838304 DOI: 10.1038/s41467-024-45434-5] [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: 07/27/2023] [Accepted: 01/22/2024] [Indexed: 02/05/2024] Open
Abstract
The advance of genetic function indicators has enabled the observation of neuronal activities at single-cell resolutions. A major challenge for the applications on mammalian brains is the limited optical access depth. Currently, the method of choice to access deep brain structures is to insert miniature optical components. Among these validated miniature optics, the gradient-index (GRIN) lens has been widely employed for its compactness and simplicity. However, due to strong fourth-order astigmatism, GRIN lenses suffer from a small imaging field of view, which severely limits the measurement throughput and success rate. To overcome these challenges, we developed geometric transformation adaptive optics (GTAO), which enables adaptable achromatic large-volume correction through GRIN lenses. We demonstrate its major advances through in vivo structural and functional imaging of mouse brains. The results suggest that GTAO can serve as a versatile solution to enable large-volume recording of deep brain structures and activities through GRIN lenses.
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Affiliation(s)
- Yuting Li
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA
- Bindley Bioscience Center, Purdue University, West Lafayette, IN, 47907, USA
| | - Zongyue Cheng
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA
- Bindley Bioscience Center, Purdue University, West Lafayette, IN, 47907, USA
| | - Chenmao Wang
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA
- Bindley Bioscience Center, Purdue University, West Lafayette, IN, 47907, USA
| | - Jianian Lin
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA
- Bindley Bioscience Center, Purdue University, West Lafayette, IN, 47907, USA
| | - Hehai Jiang
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA
- Bindley Bioscience Center, Purdue University, West Lafayette, IN, 47907, USA
| | - Meng Cui
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA.
- Bindley Bioscience Center, Purdue University, West Lafayette, IN, 47907, USA.
- Department of Biology, Purdue University, West Lafayette, IN, 47907, USA.
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2
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Chia XW, Tan JK, Ang LF, Kamigaki T, Makino H. Emergence of cortical network motifs for short-term memory during learning. Nat Commun 2023; 14:6869. [PMID: 37898638 PMCID: PMC10613236 DOI: 10.1038/s41467-023-42609-4] [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: 10/28/2022] [Accepted: 10/16/2023] [Indexed: 10/30/2023] Open
Abstract
Learning of adaptive behaviors requires the refinement of coordinated activity across multiple brain regions. However, how neural communications develop during learning remains poorly understood. Here, using two-photon calcium imaging, we simultaneously recorded the activity of layer 2/3 excitatory neurons in eight regions of the mouse dorsal cortex during learning of a delayed-response task. Across learning, while global functional connectivity became sparser, there emerged a subnetwork comprising of neurons in the anterior lateral motor cortex (ALM) and posterior parietal cortex (PPC). Neurons in this subnetwork shared a similar choice code during action preparation and formed recurrent functional connectivity across learning. Suppression of PPC activity disrupted choice selectivity in ALM and impaired task performance. Recurrent neural networks reconstructed from ALM activity revealed that PPC-ALM interactions rendered choice-related attractor dynamics more stable. Thus, learning constructs cortical network motifs by recruiting specific inter-areal communication channels to promote efficient and robust sensorimotor transformation.
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Affiliation(s)
- Xin Wei Chia
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Jian Kwang Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Lee Fang Ang
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Tsukasa Kamigaki
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Hiroshi Makino
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
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3
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Wang J, Li Y, Qi L, Mamtilahun M, Liu C, Liu Z, Shi R, Wu S, Yang GY. Advanced rehabilitation in ischaemic stroke research. Stroke Vasc Neurol 2023:svn-2022-002285. [PMID: 37788912 DOI: 10.1136/svn-2022-002285] [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: 12/30/2022] [Accepted: 03/20/2023] [Indexed: 10/05/2023] Open
Abstract
At present, due to the rapid progress of treatment technology in the acute phase of ischaemic stroke, the mortality of patients has been greatly reduced but the number of disabled survivors is increasing, and most of them are elderly patients. Physicians and rehabilitation therapists pay attention to develop all kinds of therapist techniques including physical therapy techniques, robot-assisted technology and artificial intelligence technology, and study the molecular, cellular or synergistic mechanisms of rehabilitation therapies to promote the effect of rehabilitation therapy. Here, we discussed different animal and in vitro models of ischaemic stroke for rehabilitation studies; the compound concept and technology of neurological rehabilitation; all kinds of biological mechanisms of physical therapy; the significance, assessment and efficacy of neurological rehabilitation; the application of brain-computer interface, rehabilitation robotic and non-invasive brain stimulation technology in stroke rehabilitation.
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Affiliation(s)
- Jixian Wang
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medical, Shanghai, China
| | - Yongfang Li
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medical, Shanghai, China
| | - Lin Qi
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Muyassar Mamtilahun
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chang Liu
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ze Liu
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Rubing Shi
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Shengju Wu
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Guo-Yuan Yang
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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4
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Sato M, Nakai N, Fujima S, Choe KY, Takumi T. Social circuits and their dysfunction in autism spectrum disorder. Mol Psychiatry 2023; 28:3194-3206. [PMID: 37612363 PMCID: PMC10618103 DOI: 10.1038/s41380-023-02201-0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 07/17/2023] [Accepted: 07/21/2023] [Indexed: 08/25/2023]
Abstract
Social behaviors, how individuals act cooperatively and competitively with conspecifics, are widely seen across species. Rodents display various social behaviors, and many different behavioral paradigms have been used for investigating their neural circuit bases. Social behavior is highly vulnerable to brain network dysfunction caused by neurological and neuropsychiatric conditions such as autism spectrum disorders (ASDs). Studying mouse models of ASD provides a promising avenue toward elucidating mechanisms of abnormal social behavior and potential therapeutic targets for treatment. In this review, we outline recent progress and key findings on neural circuit mechanisms underlying social behavior, with particular emphasis on rodent studies that monitor and manipulate the activity of specific circuits using modern systems neuroscience approaches. Social behavior is mediated by a distributed brain-wide network among major cortical (e.g., medial prefrontal cortex (mPFC), anterior cingulate cortex, and insular cortex (IC)) and subcortical (e.g., nucleus accumbens, basolateral amygdala (BLA), and ventral tegmental area) structures, influenced by multiple neuromodulatory systems (e.g., oxytocin, dopamine, and serotonin). We particularly draw special attention to IC as a unique cortical area that mediates multisensory integration, encoding of ongoing social interaction, social decision-making, emotion, and empathy. Additionally, a synthesis of studies investigating ASD mouse models demonstrates that dysfunctions in mPFC-BLA circuitry and neuromodulation are prominent. Pharmacological rescues by local or systemic (e.g., oral) administration of various drugs have provided valuable clues for developing new therapeutic agents for ASD. Future efforts and technological advances will push forward the next frontiers in this field, such as the elucidation of brain-wide network activity and inter-brain neural dynamics during real and virtual social interactions, and the establishment of circuit-based therapy for disorders affecting social functions.
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Affiliation(s)
- Masaaki Sato
- Department of Neuropharmacology, Hokkaido University Graduate School of Medicine, Kita, Sapporo, 060-8638, Japan
| | - Nobuhiro Nakai
- Department of Physiology and Cell Biology, Kobe University School of Medicine, Chuo, Kobe, 650-0017, Japan
| | - Shuhei Fujima
- Department of Physiology and Cell Biology, Kobe University School of Medicine, Chuo, Kobe, 650-0017, Japan
| | - Katrina Y Choe
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON, Canada
| | - Toru Takumi
- Department of Physiology and Cell Biology, Kobe University School of Medicine, Chuo, Kobe, 650-0017, Japan.
- RIKEN Center for Biosystems Dynamics Research, Chuo, Kobe, 650-0047, Japan.
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5
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Fişek M, Herrmann D, Egea-Weiss A, Cloves M, Bauer L, Lee TY, Russell LE, Häusser M. Cortico-cortical feedback engages active dendrites in visual cortex. Nature 2023; 617:769-776. [PMID: 37138089 DOI: 10.1038/s41586-023-06007-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 03/23/2023] [Indexed: 05/05/2023]
Abstract
Sensory processing in the neocortex requires both feedforward and feedback information flow between cortical areas1. In feedback processing, higher-level representations provide contextual information to lower levels, and facilitate perceptual functions such as contour integration and figure-ground segmentation2,3. However, we have limited understanding of the circuit and cellular mechanisms that mediate feedback influence. Here we use long-range all-optical connectivity mapping in mice to show that feedback influence from the lateromedial higher visual area (LM) to the primary visual cortex (V1) is spatially organized. When the source and target of feedback represent the same area of visual space, feedback is relatively suppressive. By contrast, when the source is offset from the target in visual space, feedback is relatively facilitating. Two-photon calcium imaging data show that this facilitating feedback is nonlinearly integrated in the apical tuft dendrites of V1 pyramidal neurons: retinotopically offset (surround) visual stimuli drive local dendritic calcium signals indicative of regenerative events, and two-photon optogenetic activation of LM neurons projecting to identified feedback-recipient spines in V1 can drive similar branch-specific local calcium signals. Our results show how neocortical feedback connectivity and nonlinear dendritic integration can together form a substrate to support both predictive and cooperative contextual interactions.
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Affiliation(s)
- Mehmet Fişek
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
| | - Dustin Herrmann
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Alexander Egea-Weiss
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Matilda Cloves
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Lisa Bauer
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Tai-Ying Lee
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Lloyd E Russell
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Michael Häusser
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
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6
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Moore JJ, Rashid SK, Johnson CD, Codrington N, Chklovskii DB, Basu J. Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3. RESEARCH SQUARE 2023:rs.3.rs-2733660. [PMID: 37131789 PMCID: PMC10153397 DOI: 10.21203/rs.3.rs-2733660/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Anatomically segregated apical and basal dendrites of pyramidal neurons receive functionally distinct inputs, but it is unknown if this results in compartment-level functional diversity during behavior. Here we imaged calcium signals from apical dendrites, soma, and basal dendrites of pyramidal neurons in area CA3 of mouse hippocampus during head-fixed navigation. To examine dendritic population activity, we developed computational tools to identify dendritic regions of interest and extract accurate fluorescence traces. We identified robust spatial tuning in apical and basal dendrites, similar to soma, though basal dendrites had reduced activity rates and place field widths. Across days, apical dendrites were more stable than soma or basal dendrites, resulting in better decoding of the animal's position. These population-level dendritic differences may reflect functionally distinct input streams leading to different dendritic computations in CA3. These tools will facilitate future studies of signal transformations between cellular compartments and their relation to behavior.
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Affiliation(s)
- Jason J Moore
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Center for Computational Neuroscience, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
| | - Shannon K Rashid
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Cara D. Johnson
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Naomi Codrington
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Dmitri B Chklovskii
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Center for Computational Neuroscience, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
| | - Jayeeta Basu
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
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7
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Zhao Z, Shen B, Li Y, Wang S, Hu R, Qu J, Lu Y, Liu L. Deep learning-based high-speed, large-field, and high-resolution multiphoton imaging. BIOMEDICAL OPTICS EXPRESS 2023; 14:65-80. [PMID: 36698678 PMCID: PMC9841989 DOI: 10.1364/boe.476737] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 06/17/2023]
Abstract
Multiphoton microscopy is a formidable tool for the pathological analysis of tumors. The physical limitations of imaging systems and the low efficiencies inherent in nonlinear processes have prevented the simultaneous achievement of high imaging speed and high resolution. We demonstrate a self-alignment dual-attention-guided residual-in-residual generative adversarial network trained with various multiphoton images. The network enhances image contrast and spatial resolution, suppresses noise, and scanning fringe artifacts, and eliminates the mutual exclusion between field of view, image quality, and imaging speed. The network may be integrated into commercial microscopes for large-scale, high-resolution, and low photobleaching studies of tumor environments.
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Affiliation(s)
- Zewei Zhao
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Binglin Shen
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Yanping Li
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Shiqi Wang
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Rui Hu
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Junle Qu
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Yuan Lu
- Department of Dermatology, Shenzhen Nanshan People's Hospital and The 6th Affiliated Hospital of Shenzhen University Health Science Center, and Hua Zhong University of Science and Technology Union Shenzhen Hospital, China
| | - Liwei Liu
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
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8
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Paulson B, Darian SB, Kim Y, Oh J, Ghasemi M, Lee K, Kim JK. Spectral Multiplexing of Fluorescent Endoscopy for Simultaneous Imaging with Multiple Fluorophores and Multiple Fields of View. BIOSENSORS 2022; 13:33. [PMID: 36671868 PMCID: PMC9855833 DOI: 10.3390/bios13010033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 12/22/2022] [Accepted: 12/22/2022] [Indexed: 06/17/2023]
Abstract
Complex clinical procedures and small-animal research procedures can benefit from dual-site imaging provided by multiple endoscopic devices. Here, an endoscopic system is proposed which enables multiple fluorescence microendoscopes to be spectrally multiplexed on a single microscope base, enabling light sources and optical relays to be shared between endoscopes. The presented system is characterized for resolution using USAF-1951 resolution test charts and for modulation transfer function using the slanted edge method. Imaging is demonstrated both directly and with microendoscopes attached. Imaging of phantoms was demonstrated by targeting USAF charts and fiber tissues dyed for FITC and Texas Red fluorescence. Afterwards, simultaneous liver and kidney imaging was demonstrated in mice expressing mitochondrial Dendra2 and injected with Texas Red-dextran. The results indicate that the system achieves high channel isolation and submicron and subcellular resolution, with resolution limited by the endoscopic probe and by physiological movement during endoscopic imaging. Multi-channel microendoscopy provides a potentially low-cost means of simultaneous multiple endoscopic imaging during biological experiments, resulting in reduced animal harm and potentially increasing insight into temporal connections between connected biological systems.
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Affiliation(s)
- Bjorn Paulson
- Biomedical Engineering Research Center, Asan Institute for Life Science, Asan Medical Center, Seoul 05505, Republic of Korea
| | - Saeed Bohlooli Darian
- Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
| | - Youngkyu Kim
- Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
| | - Jeongmin Oh
- Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
| | - Marjan Ghasemi
- Department of Physics, Yonsei University, Seoul 03722, Republic of Korea
| | - Kwanhee Lee
- Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
| | - Jun Ki Kim
- Biomedical Engineering Research Center, Asan Institute for Life Science, Asan Medical Center, Seoul 05505, Republic of Korea
- Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
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9
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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: 16] [Impact Index Per Article: 8.0] [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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10
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A Standardized Nonvisual Behavioral Event Is Broadcasted Homogeneously across Cortical Visual Areas without Modulating Visual Responses. eNeuro 2022; 9:ENEURO.0491-21.2022. [PMID: 36635937 PMCID: PMC9512619 DOI: 10.1523/eneuro.0491-21.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 06/10/2022] [Accepted: 08/23/2022] [Indexed: 02/02/2023] Open
Abstract
Multiple recent studies have shown that motor activity greatly impacts the activity of primary sensory areas like V1. Yet, the role of this motor related activity in sensory processing is still unclear. Here, we dissect how these behavior signals are broadcast to different layers and areas of the visual cortex. To do so, we leveraged a standardized and spontaneous behavioral fidget event in passively viewing mice. Importantly, this behavior event had no relevance to any ongoing task allowing us to compare its neuronal correlates with visually relevant behaviors (e.g., running). A large two-photon Ca2+ imaging database of neuronal responses uncovered four neural response types during fidgets that were consistent in their proportion and response patterns across all visual areas and layers of the visual cortex. Indeed, the layer and area identity could not be decoded above chance level based only on neuronal recordings. In contrast to running behavior, fidget evoked neural responses that were independent to visual processing. The broad availability of visually orthogonal standardized behavior signals could be a key component in how the cortex selects, learns and binds local sensory information with motor outputs. Contrary to behaviorally relevant motor outputs, irrelevant motor signals could project to separate local neural subspaces.
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11
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Ebrahimi S, Lecoq J, Rumyantsev O, Tasci T, Zhang Y, Irimia C, Li J, Ganguli S, Schnitzer MJ. Emergent reliability in sensory cortical coding and inter-area communication. Nature 2022; 605:713-721. [PMID: 35589841 PMCID: PMC10985415 DOI: 10.1038/s41586-022-04724-y] [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] [Received: 12/29/2020] [Accepted: 04/04/2022] [Indexed: 12/16/2022]
Abstract
Reliable sensory discrimination must arise from high-fidelity neural representations and communication between brain areas. However, how neocortical sensory processing overcomes the substantial variability of neuronal sensory responses remains undetermined1-6. Here we imaged neuronal activity in eight neocortical areas concurrently and over five days in mice performing a visual discrimination task, yielding longitudinal recordings of more than 21,000 neurons. Analyses revealed a sequence of events across the neocortex starting from a resting state, to early stages of perception, and through the formation of a task response. At rest, the neocortex had one pattern of functional connections, identified through sets of areas that shared activity cofluctuations7,8. Within about 200 ms after the onset of the sensory stimulus, such connections rearranged, with different areas sharing cofluctuations and task-related information. During this short-lived state (approximately 300 ms duration), both inter-area sensory data transmission and the redundancy of sensory encoding peaked, reflecting a transient increase in correlated fluctuations among task-related neurons. By around 0.5 s after stimulus onset, the visual representation reached a more stable form, the structure of which was robust to the prominent, day-to-day variations in the responses of individual cells. About 1 s into stimulus presentation, a global fluctuation mode conveyed the upcoming response of the mouse to every area examined and was orthogonal to modes carrying sensory data. Overall, the neocortex supports sensory performance through brief elevations in sensory coding redundancy near the start of perception, neural population codes that are robust to cellular variability, and widespread inter-area fluctuation modes that transmit sensory data and task responses in non-interfering channels.
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Affiliation(s)
- Sadegh Ebrahimi
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA.
- CNC Program, Stanford University, Stanford, CA, USA.
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
| | - Jérôme Lecoq
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | - Oleg Rumyantsev
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Tugce Tasci
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Yanping Zhang
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Cristina Irimia
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Jane Li
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Surya Ganguli
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Mark J Schnitzer
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA.
- CNC Program, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
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12
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Ota K, Uwamori H, Ode T, Murayama M. Breaking trade-offs: development of fast, high-resolution, wide-field two-photon microscopes to reveal the computational principles of the brain. Neurosci Res 2022; 179:3-14. [PMID: 35390357 DOI: 10.1016/j.neures.2022.03.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/26/2022] [Accepted: 03/07/2022] [Indexed: 11/29/2022]
Abstract
Information in the brain is represented by the collective and coordinated activity of single neurons. Activity is determined by a large amount of dynamic synaptic inputs from neurons in the same and/or distant brain regions. Therefore, the simultaneous recording of single neurons across several brain regions is critical for revealing the interactions among neurons that reflect the computational principles of the brain. Recently, several wide-field two-photon (2P) microscopes equipped with sizeable objective lenses have been reported. These microscopes enable large-scale in vivo calcium imaging and have the potential to make a significant contribution to the elucidation of information-processing mechanisms in the cerebral cortex. This review discusses recent reports on wide-field 2P microscopes and describes the trade-offs encountered in developing wide-field 2P microscopes. Large-scale imaging of neural activity allows us to test hypotheses proposed in theoretical neuroscience, and to identify rare but influential neurons that have potentially significant impacts on the whole-brain system.
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Affiliation(s)
- Keisuke Ota
- Department of Neurochemistry, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo113-0033, Japan; Center for Brain Science, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama351-0198, Japan.
| | - Hiroyuki Uwamori
- Center for Brain Science, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama351-0198, Japan
| | - Takahiro Ode
- Center for Brain Science, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama351-0198, Japan; FOV Corporation, 2-12-3 Taru-machi, Kouhoku-ku, Yokohama, Kanagawa222-0001, Japan
| | - Masanori Murayama
- Center for Brain Science, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama351-0198, Japan
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13
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Gauthier JL, Koay SA, Nieh EH, Tank DW, Pillow JW, Charles AS. Detecting and correcting false transients in calcium imaging. Nat Methods 2022; 19:470-478. [PMID: 35347320 PMCID: PMC10715860 DOI: 10.1038/s41592-022-01422-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 02/10/2022] [Indexed: 11/08/2022]
Abstract
Population recordings of calcium activity are a major source of insight into neural function. Large datasets require automated processing, but this can introduce errors that are difficult to detect. Here we show that popular time course-estimation algorithms often contain substantial misattribution errors affecting 10-20% of transients. Misattribution, in which fluorescence is ascribed to the wrong cell, arises when overlapping cells and processes are imperfectly defined or not identified. To diagnose misattribution, we develop metrics and visualization tools for evaluating large datasets. To correct time courses, we introduce a robust estimator that explicitly accounts for contaminating signals. In one hippocampal dataset, removing contamination reduced the number of place cells by 15%, and 19% of place fields shifted by over 10 cm. Our methods are compatible with other cell-finding techniques, empowering users to diagnose and correct a potentially widespread problem that could alter scientific conclusions.
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Affiliation(s)
| | - Sue Ann Koay
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Edward H Nieh
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - David W Tank
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, USA.
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA.
| | - Jonathan W Pillow
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Adam S Charles
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA.
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA.
- Mathematical Institute for Data Science, Johns Hopkins University, Baltimore, MD, USA.
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14
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Shen B, Liu S, Li Y, Pan Y, Lu Y, Hu R, Qu J, Liu L. Deep learning autofluorescence-harmonic microscopy. LIGHT, SCIENCE & APPLICATIONS 2022; 11:76. [PMID: 35351853 PMCID: PMC8964717 DOI: 10.1038/s41377-022-00768-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 03/05/2022] [Accepted: 03/10/2022] [Indexed: 05/28/2023]
Abstract
Laser scanning microscopy has inherent tradeoffs between imaging speed, field of view (FOV), and spatial resolution due to the limitations of sophisticated mechanical and optical setups, and deep learning networks have emerged to overcome these limitations without changing the system. Here, we demonstrate deep learning autofluorescence-harmonic microscopy (DLAM) based on self-alignment attention-guided residual-in-residual dense generative adversarial networks to close the gap between speed, FOV, and quality. Using the framework, we demonstrate label-free large-field multimodal imaging of clinicopathological tissues with enhanced spatial resolution and running time advantages. Statistical quality assessments show that the attention-guided residual dense connections minimize the persistent noise, distortions, and scanning fringes that degrade the autofluorescence-harmonic images and avoid reconstruction artifacts in the output images. With the advantages of high contrast, high fidelity, and high speed in image reconstruction, DLAM can act as a powerful tool for the noninvasive evaluation of diseases, neural activity, and embryogenesis.
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Affiliation(s)
- Binglin Shen
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, China
| | - Shaowen Liu
- Shenzhen Meitu Innovation Technology LTD, 518060, Shenzhen, China
| | - Yanping Li
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, China
| | - Ying Pan
- China-Japan Union Hospital of Jilin University, 130033, Changchun, China
| | - Yuan Lu
- The Sixth People's Hospital of Shenzhen, 518052, Shenzhen, China
| | - Rui Hu
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, China
| | - Junle Qu
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, China
| | - Liwei Liu
- Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, China.
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15
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Fluorescence imaging of large-scale neural ensemble dynamics. Cell 2022; 185:9-41. [PMID: 34995519 PMCID: PMC8849612 DOI: 10.1016/j.cell.2021.12.007] [Citation(s) in RCA: 57] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/14/2022]
Abstract
Recent progress in fluorescence imaging allows neuroscientists to observe the dynamics of thousands of individual neurons, identified genetically or by their connectivity, across multiple brain areas and for extended durations in awake behaving mammals. We discuss advances in fluorescent indicators of neural activity, viral and genetic methods to express these indicators, chronic animal preparations for long-term imaging studies, and microscopes to monitor and manipulate the activity of large neural ensembles. Ca2+ imaging studies of neural activity can track brain area interactions and distributed information processing at cellular resolution. Across smaller spatial scales, high-speed voltage imaging reveals the distinctive spiking patterns and coding properties of targeted neuron types. Collectively, these innovations will propel studies of brain function and dovetail with ongoing neuroscience initiatives to identify new neuron types and develop widely applicable, non-human primate models. The optical toolkit's growing sophistication also suggests that "brain observatory" facilities would be useful open resources for future brain-imaging studies.
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16
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Abdelfattah AS, Ahuja S, Akkin T, Allu SR, Brake J, Boas DA, Buckley EM, Campbell RE, Chen AI, Cheng X, Čižmár T, Costantini I, De Vittorio M, Devor A, Doran PR, El Khatib M, Emiliani V, Fomin-Thunemann N, Fainman Y, Fernandez-Alfonso T, Ferri CGL, Gilad A, Han X, Harris A, Hillman EMC, Hochgeschwender U, Holt MG, Ji N, Kılıç K, Lake EMR, Li L, Li T, Mächler P, Miller EW, Mesquita RC, Nadella KMNS, Nägerl UV, Nasu Y, Nimmerjahn A, Ondráčková P, Pavone FS, Perez Campos C, Peterka DS, Pisano F, Pisanello F, Puppo F, Sabatini BL, Sadegh S, Sakadzic S, Shoham S, Shroff SN, Silver RA, Sims RR, Smith SL, Srinivasan VJ, Thunemann M, Tian L, Tian L, Troxler T, Valera A, Vaziri A, Vinogradov SA, Vitale F, Wang LV, Uhlířová H, Xu C, Yang C, Yang MH, Yellen G, Yizhar O, Zhao Y. Neurophotonic tools for microscopic measurements and manipulation: status report. NEUROPHOTONICS 2022; 9:013001. [PMID: 35493335 PMCID: PMC9047450 DOI: 10.1117/1.nph.9.s1.013001] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Ahmed S. Abdelfattah
- Brown University, Department of Neuroscience, Providence, Rhode Island, United States
| | - Sapna Ahuja
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Taner Akkin
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, Minnesota, United States
| | - Srinivasa Rao Allu
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - David A. Boas
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Erin M. Buckley
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University, Department of Pediatrics, Atlanta, Georgia, United States
| | - Robert E. Campbell
- University of Tokyo, Department of Chemistry, Tokyo, Japan
- University of Alberta, Department of Chemistry, Edmonton, Alberta, Canada
| | - Anderson I. Chen
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Xiaojun Cheng
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Tomáš Čižmár
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Irene Costantini
- University of Florence, European Laboratory for Non-Linear Spectroscopy, Department of Biology, Florence, Italy
- National Institute of Optics, National Research Council, Rome, Italy
| | - Massimo De Vittorio
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Anna Devor
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Patrick R. Doran
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Mirna El Khatib
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | | | - Natalie Fomin-Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Yeshaiahu Fainman
- University of California San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
| | - Tomas Fernandez-Alfonso
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Christopher G. L. Ferri
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Ariel Gilad
- The Hebrew University of Jerusalem, Institute for Medical Research Israel–Canada, Department of Medical Neurobiology, Faculty of Medicine, Jerusalem, Israel
| | - Xue Han
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Andrew Harris
- Weizmann Institute of Science, Department of Brain Sciences, Rehovot, Israel
| | | | - Ute Hochgeschwender
- Central Michigan University, Department of Neuroscience, Mount Pleasant, Michigan, United States
| | - Matthew G. Holt
- University of Porto, Instituto de Investigação e Inovação em Saúde (i3S), Porto, Portugal
| | - Na Ji
- University of California Berkeley, Department of Physics, Berkeley, California, United States
| | - Kıvılcım Kılıç
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Evelyn M. R. Lake
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, Connecticut, United States
| | - Lei Li
- California Institute of Technology, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, Pasadena, California, United States
| | - Tianqi Li
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, Minnesota, United States
| | - Philipp Mächler
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Evan W. Miller
- University of California Berkeley, Departments of Chemistry and Molecular & Cell Biology and Helen Wills Neuroscience Institute, Berkeley, California, United States
| | | | | | - U. Valentin Nägerl
- Interdisciplinary Institute for Neuroscience University of Bordeaux & CNRS, Bordeaux, France
| | - Yusuke Nasu
- University of Tokyo, Department of Chemistry, Tokyo, Japan
| | - Axel Nimmerjahn
- Salk Institute for Biological Studies, Waitt Advanced Biophotonics Center, La Jolla, California, United States
| | - Petra Ondráčková
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Francesco S. Pavone
- National Institute of Optics, National Research Council, Rome, Italy
- University of Florence, European Laboratory for Non-Linear Spectroscopy, Department of Physics, Florence, Italy
| | - Citlali Perez Campos
- Columbia University, Zuckerman Mind Brain Behavior Institute, New York, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behavior Institute, New York, United States
| | - Filippo Pisano
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Ferruccio Pisanello
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Francesca Puppo
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Bernardo L. Sabatini
- Harvard Medical School, Howard Hughes Medical Institute, Department of Neurobiology, Boston, Massachusetts, United States
| | - Sanaz Sadegh
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Sava Sakadzic
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Shy Shoham
- New York University Grossman School of Medicine, Tech4Health and Neuroscience Institutes, New York, New York, United States
| | - Sanaya N. Shroff
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - R. Angus Silver
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Ruth R. Sims
- Sorbonne University, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Spencer L. Smith
- University of California Santa Barbara, Department of Electrical and Computer Engineering, Santa Barbara, California, United States
| | - Vivek J. Srinivasan
- New York University Langone Health, Departments of Ophthalmology and Radiology, New York, New York, United States
| | - Martin Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Lei Tian
- Boston University, Departments of Electrical Engineering and Biomedical Engineering, Boston, Massachusetts, United States
| | - Lin Tian
- University of California Davis, Department of Biochemistry and Molecular Medicine, Davis, California, United States
| | - Thomas Troxler
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Antoine Valera
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Alipasha Vaziri
- Rockefeller University, Laboratory of Neurotechnology and Biophysics, New York, New York, United States
- The Rockefeller University, The Kavli Neural Systems Institute, New York, New York, United States
| | - Sergei A. Vinogradov
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Flavia Vitale
- Center for Neuroengineering and Therapeutics, Departments of Neurology, Bioengineering, Physical Medicine and Rehabilitation, Philadelphia, Pennsylvania, United States
| | - Lihong V. Wang
- California Institute of Technology, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, Pasadena, California, United States
| | - Hana Uhlířová
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Chris Xu
- Cornell University, School of Applied and Engineering Physics, Ithaca, New York, United States
| | - Changhuei Yang
- California Institute of Technology, Departments of Electrical Engineering, Bioengineering and Medical Engineering, Pasadena, California, United States
| | - Mu-Han Yang
- University of California San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
| | - Gary Yellen
- Harvard Medical School, Department of Neurobiology, Boston, Massachusetts, United States
| | - Ofer Yizhar
- Weizmann Institute of Science, Department of Brain Sciences, Rehovot, Israel
| | - Yongxin Zhao
- Carnegie Mellon University, Department of Biological Sciences, Pittsburgh, Pennsylvania, United States
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17
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Chou N, Shin H, Kim K, Chae U, Jang M, Jeong U, Hwang K, Yi B, Lee SE, Woo J, Cho Y, Lee C, Baker BJ, Oh S, Nam M, Choi N, Cho I. A Multimodal Multi-Shank Fluorescence Neural Probe for Cell-Type-Specific Electrophysiology in Multiple Regions across a Neural Circuit. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2103564. [PMID: 34796701 PMCID: PMC8805556 DOI: 10.1002/advs.202103564] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 10/25/2021] [Indexed: 05/27/2023]
Abstract
Cell-type-specific, activity-dependent electrophysiology can allow in-depth analysis of functional connectivity inside complex neural circuits composed of various cell types. To date, optics-based fluorescence recording devices enable monitoring cell-type-specific activities. However, the monitoring is typically limited to a single brain region, and the temporal resolution is significantly low. Herein, a multimodal multi-shank fluorescence neural probe that allows cell-type-specific electrophysiology from multiple deep-brain regions at a high spatiotemporal resolution is presented. A photodiode and an electrode-array pair are monolithically integrated on each tip of a minimal-form-factor silicon device. Both fluorescence and electrical signals are successfully measured simultaneously in GCaMP6f expressing mice, and the cell type from sorted neural spikes is identified. The probe's capability of combined electro-optical recordings for cell-type-specific electrophysiology at multiple brain regions within a neural circuit is demonstrated. The new experimental paradigm to enable the precise investigation of functional connectivity inside and across complex neural circuits composed of various cell types is expected.
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Affiliation(s)
- Namsun Chou
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Hyogeun Shin
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Kanghwan Kim
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Uikyu Chae
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
- School of Electrical EngineeringKorea University145 Anam‐ro, Seongbuk‐guSeoul02841Republic of Korea
| | - Minsu Jang
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Ui‐Jin Jeong
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
- School of Electrical EngineeringKorea University145 Anam‐ro, Seongbuk‐guSeoul02841Republic of Korea
| | - Kyeong‐Seob Hwang
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
- School of Mechanical EngineeringYonsei University50 Yonsei‐ro, Seodaemun‐guSeoul03722Republic of Korea
| | - Bumjun Yi
- Center for Functional ConnectomicsBrain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Seung Eun Lee
- Virus Facility, Research Animal Resource CenterBrain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Jiwan Woo
- Center for Neuroscience, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Yakdol Cho
- Center for Neuroscience, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Changhyuk Lee
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Bradley J. Baker
- Center for Functional ConnectomicsBrain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Soo‐Jin Oh
- Center for Neuroscience, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Min‐Ho Nam
- Center for Neuroscience, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Nakwon Choi
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
- KU‐KIST Graduate School of Converging Science and TechnologyKorea University145 Anam‐ro, Seongbuk‐guSeoul02841Republic of Korea
- Division of Bio‐Medical Science and Technology, KIST SchoolKorea University of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
| | - Il‐Joo Cho
- Center for BioMicrosystems, Brain Science InstituteKorea Institute of Science and Technology5, Hwarang‐ro 14‐gil, Seongbuk‐guSeoul02792Republic of Korea
- School of Electrical and Electronics EngineeringYonsei University50 Yonsei‐ro, Seodaemun‐guSeoul03722Republic of Korea
- Yonsei‐KIST Convergence Research InstituteYonsei University50 Yonsei‐ro, Seodaemun‐guSeoul03722Republic of Korea
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18
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D'Souza JF, Price NSC, Hagan MA. Marmosets: a promising model for probing the neural mechanisms underlying complex visual networks such as the frontal-parietal network. Brain Struct Funct 2021; 226:3007-3022. [PMID: 34518902 PMCID: PMC8541938 DOI: 10.1007/s00429-021-02367-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 08/23/2021] [Indexed: 01/02/2023]
Abstract
The technology, methodology and models used by visual neuroscientists have provided great insights into the structure and function of individual brain areas. However, complex cognitive functions arise in the brain due to networks comprising multiple interacting cortical areas that are wired together with precise anatomical connections. A prime example of this phenomenon is the frontal–parietal network and two key regions within it: the frontal eye fields (FEF) and lateral intraparietal area (area LIP). Activity in these cortical areas has independently been tied to oculomotor control, motor preparation, visual attention and decision-making. Strong, bidirectional anatomical connections have also been traced between FEF and area LIP, suggesting that the aforementioned visual functions depend on these inter-area interactions. However, advancements in our knowledge about the interactions between area LIP and FEF are limited with the main animal model, the rhesus macaque, because these key regions are buried in the sulci of the brain. In this review, we propose that the common marmoset is the ideal model for investigating how anatomical connections give rise to functionally-complex cognitive visual behaviours, such as those modulated by the frontal–parietal network, because of the homology of their cortical networks with humans and macaques, amenability to transgenic technology, and rich behavioural repertoire. Furthermore, the lissencephalic structure of the marmoset brain enables application of powerful techniques, such as array-based electrophysiology and optogenetics, which are critical to bridge the gaps in our knowledge about structure and function in the brain.
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Affiliation(s)
- Joanita F D'Souza
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, VIC, 3800, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, 3800, Australia
| | - Nicholas S C Price
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, VIC, 3800, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, 3800, Australia
| | - Maureen A Hagan
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, VIC, 3800, Australia. .,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, 3800, Australia.
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19
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Visual stimulation with blue wavelength light drives V1 effectively eliminating stray light contamination during two-photon calcium imaging. J Neurosci Methods 2021; 362:109287. [PMID: 34256082 DOI: 10.1016/j.jneumeth.2021.109287] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 06/27/2021] [Accepted: 07/08/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Brain visual circuits are often studied in vivo by imaging Ca2+ indicators with green-shifted emission spectra. Polychromatic white visual stimuli have a spectrum that partially overlaps indicators´ emission spectra, resulting in significant contamination of calcium signals. NEW METHOD To overcome light contamination problems we choose blue visual stimuli, having a spectral composition not overlapping with Ca2+ indicator´s emission spectrum. To compare visual responsiveness to blue and white stimuli we used electrophysiology (visual evoked potentials -VEPs) and 3D acousto-optic two-photon (2P) population Ca2+ imaging in mouse primary visual cortex (V1). RESULTS VEPs in response to blue and white stimuli had comparable peak amplitudes and latencies. Ca2+ imaging in a Thy1 GP4.3 line revealed that the populations of neurons responding to blue and white stimuli were largely overlapping, that their responses had similar amplitudes, and that functional response properties such as orientation and direction selectivities were also comparable. COMPARISON WITH EXISTING METHODS Masking or shielding the microscope are often used to minimize the contamination of Ca2+ signal by white light, but they are time consuming, bulky and thus can limit experimental design, particularly in the more and more frequently used awake set-up. Blue stimuli not interfering with imaging allow to omit shielding. CONCLUSIONS Together, our results show that the selected blue light stimuli evoke responses comparable to those evoked by white stimuli in mouse V1. This will make complex designs of imaging experiments in behavioral set-ups easier, and facilitate the combination of Ca2+ imaging with electrophysiology and optogenetics.
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Mächler P, Broggini T, Mateo C, Thunemann M, Fomin-Thunemann N, Doran PR, Sencan I, Kilic K, Desjardins M, Uhlirova H, Yaseen MA, Boas DA, Linninger AA, Vergassola M, Yu X, Lewis LD, Polimeni JR, Rosen BR, Sakadžić S, Buxton RB, Lauritzen M, Kleinfeld D, Devor A. A Suite of Neurophotonic Tools to Underpin the Contribution of Internal Brain States in fMRI. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021; 18:100273. [PMID: 33959688 PMCID: PMC8095678 DOI: 10.1016/j.cobme.2021.100273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Recent developments in optical microscopy, applicable for large-scale and longitudinal imaging of cortical activity in behaving animals, open unprecedented opportunities to gain a deeper understanding of neurovascular and neurometabolic coupling during different brain states. Future studies will leverage these tools to deliver foundational knowledge about brain state-dependent regulation of cerebral blood flow and metabolism as well as regulation as a function of brain maturation and aging. This knowledge is of critical importance to interpret hemodynamic signals observed with functional magnetic resonance imaging (fMRI).
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Affiliation(s)
- Philipp Mächler
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
- Department of Physics, University of California San Diego, La Jolla, CA 92093, USA
| | - Thomas Broggini
- Department of Physics, University of California San Diego, La Jolla, CA 92093, USA
| | - Celine Mateo
- Department of Physics, University of California San Diego, La Jolla, CA 92093, USA
| | - Martin Thunemann
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | | | - Patrick R. Doran
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Ikbal Sencan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Kivilcim Kilic
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Michèle Desjardins
- Département de Physique, de Génie Physique et d’Optique, Université Laval, Québec, QC G1V 0A6, Canada
| | - Hana Uhlirova
- Institute of Scientific Instruments of the Czech Academy of Science, Brno, Czech Republic
| | - Mohammad A. Yaseen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Bioengineering, Northeastern University, Boston, MA 02115, USA
| | - David A. Boas
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Andreas A. Linninger
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Massimo Vergassola
- Department of Physics, University of California San Diego, La Jolla, CA 92093, USA
- Département de Physique de l’Ecole Normale Supérieure, 75005 Paris, France
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Laura D. Lewis
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Bruce R. Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Sava Sakadžić
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Richard B. Buxton
- Department of Radiology, University of California San Diego, La Jolla, CA 92037, USA
| | - Martin Lauritzen
- Department of Neuroscience and Pharmacology, University of Copenhagen, Copenhagen N 2200, Denmark
- Department of Clinical Neurophysiology, Glostrup Hospital, Glostrup 2600, Denmark
| | - David Kleinfeld
- Department of Physics, University of California San Diego, La Jolla, CA 92093, USA
- Section on Neurobiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Anna Devor
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
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21
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Laing BT, Siemian JN, Sarsfield S, Aponte Y. Fluorescence microendoscopy for in vivo deep-brain imaging of neuronal circuits. J Neurosci Methods 2021; 348:109015. [PMID: 33259847 PMCID: PMC8745022 DOI: 10.1016/j.jneumeth.2020.109015] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/24/2020] [Accepted: 11/26/2020] [Indexed: 11/16/2022]
Abstract
Imaging neuronal activity in awake, behaving animals has become a groundbreaking method in neuroscience that has rapidly enhanced our understanding of how the brain works. In vivo microendoscopic imaging has enabled researchers to see inside the brains of experimental animals and thus has emerged as a technology fit to answer many experimental questions. By combining microendoscopy with cutting edge targeting strategies and sophisticated analysis tools, neuronal activity patterns that underlie changes in behavior and physiology can be identified. However, new users may find it challenging to understand the techniques and to leverage this technology to best suit their needs. Here we present a background and overview of the necessary components for performing in vivo optical calcium imaging and offer some detailed guidance for current recommended approaches.
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Affiliation(s)
- Brenton T Laing
- Neuronal Circuits and Behavior Unit, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, MD, 21224-6823, USA
| | - Justin N Siemian
- Neuronal Circuits and Behavior Unit, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, MD, 21224-6823, USA
| | - Sarah Sarsfield
- Neuronal Circuits and Behavior Unit, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, MD, 21224-6823, USA
| | - Yeka Aponte
- Neuronal Circuits and Behavior Unit, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, MD, 21224-6823, USA; The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
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22
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Roth RH, Ding JB. From Neurons to Cognition: Technologies for Precise Recording of Neural Activity Underlying Behavior. BME FRONTIERS 2020; 2020:7190517. [PMID: 37849967 PMCID: PMC10521756 DOI: 10.34133/2020/7190517] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 10/27/2020] [Indexed: 10/19/2023] Open
Abstract
Understanding how brain activity encodes information and controls behavior is a long-standing question in neuroscience. This complex problem requires converging efforts from neuroscience and engineering, including technological solutions to perform high-precision and large-scale recordings of neuronal activity in vivo as well as unbiased methods to reliably measure and quantify behavior. Thanks to advances in genetics, molecular biology, engineering, and neuroscience, in recent decades, a variety of optical imaging and electrophysiological approaches for recording neuronal activity in awake animals have been developed and widely applied in the field. Moreover, sophisticated computer vision and machine learning algorithms have been developed to analyze animal behavior. In this review, we provide an overview of the current state of technology for neuronal recordings with a focus on optical and electrophysiological methods in rodents. In addition, we discuss areas that future technological development will need to cover in order to further our understanding of the neural activity underlying behavior.
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Affiliation(s)
- Richard H Roth
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
| | - Jun B Ding
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
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23
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Milosevic MM, Jang J, McKimm EJ, Zhu MH, Antic SD. In Vitro Testing of Voltage Indicators: Archon1, ArcLightD, ASAP1, ASAP2s, ASAP3b, Bongwoori-Pos6, BeRST1, FlicR1, and Chi-VSFP-Butterfly. eNeuro 2020; 7:ENEURO.0060-20.2020. [PMID: 32817120 PMCID: PMC7540930 DOI: 10.1523/eneuro.0060-20.2020] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 08/03/2020] [Accepted: 08/09/2020] [Indexed: 01/04/2023] Open
Abstract
Genetically encoded voltage indicators (GEVIs) could potentially be used for mapping neural circuits at the plane of synaptic potentials and plateau potentials-two blind spots of GCaMP-based imaging. In the last year alone, several laboratories reported significant breakthroughs in the quality of GEVIs and the efficacy of the voltage imaging equipment. One major obstacle of using well performing GEVIs in the pursuit of interesting biological data is the process of transferring GEVIs between laboratories, as their reported qualities (e.g., membrane targeting, brightness, sensitivity, optical signal quality) are often difficult to reproduce outside of the laboratory of the GEVI origin. We have tested eight available GEVIs (Archon1, ArcLightD, ASAP1, ASAP2s, ASAP3b, Bongwoori-Pos6, FlicR1, and chi-VSFP-Butterfly) and two voltage-sensitive dyes (BeRST1 and di-4-ANEPPS). We used the same microscope, lens, and optical detector, while the light sources were interchanged. GEVI voltage imaging was attempted in the following three preparations: (1) cultured neurons, (2) HEK293 cells, and (3) mouse brain slices. Systematic measurements were successful only in HEK293 cells and brain slices. Despite the significant differences in brightness and dynamic response (ON rate), all tested indicators produced reasonable optical signals in brain slices and solid in vitro quality properties, in the range initially reported by the creator laboratories. Side-by-side comparisons between GEVIs and organic dyes obtained in HEK293 cells and brain slices by a "third party" (current data) will be useful for determining the right voltage indicator for a given research application.
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Affiliation(s)
- Milena M Milosevic
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
- Center for Laser Microscopy, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Jinyoung Jang
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
| | - Eric J McKimm
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
| | - Mei Hong Zhu
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
| | - Srdjan D Antic
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
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24
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Qin Z, Chen C, He S, Wang Y, Tam KF, Ip NY, Qu JY. Adaptive optics two-photon endomicroscopy enables deep-brain imaging at synaptic resolution over large volumes. SCIENCE ADVANCES 2020; 6:6/40/eabc6521. [PMID: 32998883 PMCID: PMC7527232 DOI: 10.1126/sciadv.abc6521] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 08/11/2020] [Indexed: 05/02/2023]
Abstract
Optical deep-brain imaging in vivo at high resolution has remained a great challenge over the decades. Two-photon endomicroscopy provides a minimally invasive approach to image buried brain structures, once it is integrated with a gradient refractive index (GRIN) lens embedded in the brain. However, its imaging resolution and field of view are compromised by the intrinsic aberrations of the GRIN lens. Here, we develop a two-photon endomicroscopy by adding adaptive optics based on direct wavefront sensing, which enables recovery of diffraction-limited resolution in deep-brain imaging. A new precompensation strategy plays a critical role to correct aberrations over large volumes and achieve rapid random-access multiplane imaging. We investigate the neuronal plasticity in the hippocampus, a critical deep brain structure, and reveal the relationship between the somatic and dendritic activity of pyramidal neurons.
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Affiliation(s)
- Zhongya Qin
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
| | - Congping Chen
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
| | - Sicong He
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
| | - Ye Wang
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P.R. China
| | - Kam Fai Tam
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P.R. China
| | - Nancy Y Ip
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China.
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P.R. China
| | - Jianan Y Qu
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China.
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
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25
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Optical interrogation of multi-scale neuronal plasticity underlying behavioral learning. Curr Opin Neurobiol 2020; 67:8-15. [PMID: 32768886 DOI: 10.1016/j.conb.2020.07.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Revised: 07/14/2020] [Accepted: 07/17/2020] [Indexed: 01/16/2023]
Abstract
Behavioral learning is driven by adaptive changes in the activation of behaviorally relevant neuronal ensembles. This learning-specific reorganization of neuronal circuits is correlated with activity-dependent modifications of synaptic dynamics. However, a definitive causal link remains to be established. How is synaptic plasticity distributed among circuits to eventually shape behavioral learning? A multi-scale understanding of the progressive plasticity is hindered by the lack of techniques for monitoring and manipulating these events. The current rise of synaptic optogenetics, especially combined with brain-wide circuit imaging, opens an entirely new avenue for studying causality at multiple scales. In this review, we summarize these technical achievements and discuss challenges in linking the plasticity across levels to elucidate the multi-scale mechanisms of learning.
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26
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Campos P, Walker JJ, Mollard P. Diving into the brain: deep-brain imaging techniques in conscious animals. J Endocrinol 2020; 246:R33-R50. [PMID: 32380471 PMCID: PMC7354703 DOI: 10.1530/joe-20-0028] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 05/07/2020] [Indexed: 01/28/2023]
Abstract
In most species, survival relies on the hypothalamic control of endocrine axes that regulate critical functions such as reproduction, growth, and metabolism. For decades, the complexity and inaccessibility of the hypothalamic-pituitary axis has prevented researchers from elucidating the relationship between the activity of endocrine hypothalamic neurons and pituitary hormone secretion. Indeed, the study of central control of endocrine function has been largely dominated by 'traditional' techniques that consist of studying in vitro or ex vivo isolated cell types without taking into account the complexity of regulatory mechanisms at the level of the brain, pituitary and periphery. Nowadays, by exploiting modern neuronal transfection and imaging techniques, it is possible to study hypothalamic neuron activity in situ, in real time, and in conscious animals. Deep-brain imaging of calcium activity can be performed through gradient-index lenses that are chronically implanted and offer a 'window into the brain' to image multiple neurons at single-cell resolution. With this review, we aim to highlight deep-brain imaging techniques that enable the study of neuroendocrine neurons in awake animals whilst maintaining the integrity of regulatory loops between the brain, pituitary and peripheral glands. Furthermore, to assist researchers in setting up these techniques, we discuss the equipment required and include a practical step-by-step guide to performing these deep-brain imaging studies.
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Affiliation(s)
- Pauline Campos
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
- Correspondence should be addressed to P Campos:
| | - Jamie J Walker
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
- EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, UK
- Bristol Medical School, Translational Health Sciences, University of Bristol, Bristol, UK
| | - Patrice Mollard
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
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27
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Kauvar IV, Machado TA, Yuen E, Kochalka J, Choi M, Allen WE, Wetzstein G, Deisseroth K. Cortical Observation by Synchronous Multifocal Optical Sampling Reveals Widespread Population Encoding of Actions. Neuron 2020; 107:351-367.e19. [PMID: 32433908 PMCID: PMC7687350 DOI: 10.1016/j.neuron.2020.04.023] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 04/01/2020] [Accepted: 04/26/2020] [Indexed: 01/05/2023]
Abstract
To advance the measurement of distributed neuronal population representations of targeted motor actions on single trials, we developed an optical method (COSMOS) for tracking neural activity in a largely uncharacterized spatiotemporal regime. COSMOS allowed simultaneous recording of neural dynamics at ∼30 Hz from over a thousand near-cellular resolution neuronal sources spread across the entire dorsal neocortex of awake, behaving mice during a three-option lick-to-target task. We identified spatially distributed neuronal population representations spanning the dorsal cortex that precisely encoded ongoing motor actions on single trials. Neuronal correlations measured at video rate using unaveraged, whole-session data had localized spatial structure, whereas trial-averaged data exhibited widespread correlations. Separable modes of neural activity encoded history-guided motor plans, with similar population dynamics in individual areas throughout cortex. These initial experiments illustrate how COSMOS enables investigation of large-scale cortical dynamics and that information about motor actions is widely shared between areas, potentially underlying distributed computations.
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Affiliation(s)
- Isaac V Kauvar
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Timothy A Machado
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Elle Yuen
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - John Kochalka
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Neuroscience Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Minseung Choi
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Neuroscience Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - William E Allen
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Neuroscience Graduate Program, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Gordon Wetzstein
- Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Department of Psychiatry and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
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28
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Jiang J, Warren WS, Fischer MC. Crossed-beam pump-probe microscopy. OPTICS EXPRESS 2020; 28:11259-11266. [PMID: 32403640 DOI: 10.1364/oe.389004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 03/24/2020] [Indexed: 06/11/2023]
Abstract
We present a new imaging method for pump-probe microscopy that explores non-collinear excitation. This method (crossed-beam pump-probe microscopy, or CBPM) can significantly improve the axial resolution when imaging through low-NA lenses, providing an alternative way for depth-resolved, large field-of-view imaging. We performed a proof-of-concept demonstration, characterized CBPM's resolution using different imaging lenses, and measured an enhanced axial resolution for certain types of low-NA lenses.
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29
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Head-Mounted Display-Based Microscopic Imaging System with Customizable Field Size and Viewpoint. SENSORS 2020; 20:s20071967. [PMID: 32244620 PMCID: PMC7181164 DOI: 10.3390/s20071967] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/24/2020] [Accepted: 03/30/2020] [Indexed: 11/16/2022]
Abstract
In recent years, the use of microinjections has increased in life science and biotechnology fields; specific examples include artificial insemination and gene manipulation. Microinjections are mainly performed based on visual information; thus, the operator needs high-level skill because of the narrowness of the visual field. Additionally, microinjections are performed as the operator views a microscopic image on a display; the position of the display requires the operator to maintain an awkward posture throughout the procedure. In this study, we developed a microscopic image display apparatus for microinjections based on a view-expansive microscope. The prototype of the view-expansive microscope has problems related to the variations in brightness and focal blur that accompany changes in the optical path length and amount of reflected light. Therefore, we propose the use of a variable-focus device to expand the visual field and thus circumvent the above-mentioned problems. We evaluated the observable area of the system using this variable-focus device. We confirmed that the observable area is 261.4 and 13.9 times larger than that of a normal microscope and conventional view-expansive microscopic system, respectively. Finally, observations of mouse embryos were carried out by using the developed system. We confirmed that the microscopic images can be displayed on a head-mounted display in real time with the desired point and field sizes.
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Fundamental bounds on the fidelity of sensory cortical coding. Nature 2020; 580:100-105. [PMID: 32238928 DOI: 10.1038/s41586-020-2130-2] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Accepted: 01/21/2020] [Indexed: 12/13/2022]
Abstract
How the brain processes information accurately despite stochastic neural activity is a longstanding question1. For instance, perception is fundamentally limited by the information that the brain can extract from the noisy dynamics of sensory neurons. Seminal experiments2,3 suggest that correlated noise in sensory cortical neural ensembles is what limits their coding accuracy4-6, although how correlated noise affects neural codes remains debated7-11. Recent theoretical work proposes that how a neural ensemble's sensory tuning properties relate statistically to its correlated noise patterns is a greater determinant of coding accuracy than is absolute noise strength12-14. However, without simultaneous recordings from thousands of cortical neurons with shared sensory inputs, it is unknown whether correlated noise limits coding fidelity. Here we present a 16-beam, two-photon microscope to monitor activity across the mouse primary visual cortex, along with analyses to quantify the information conveyed by large neural ensembles. We found that, in the visual cortex, correlated noise constrained signalling for ensembles with 800-1,300 neurons. Several noise components of the ensemble dynamics grew proportionally to the ensemble size and the encoded visual signals, revealing the predicted information-limiting correlations12-14. Notably, visual signals were perpendicular to the largest noise mode, which therefore did not limit coding fidelity. The information-limiting noise modes were approximately ten times smaller and concordant with mouse visual acuity15. Therefore, cortical design principles appear to enhance coding accuracy by restricting around 90% of noise fluctuations to modes that do not limit signalling fidelity, whereas much weaker correlated noise modes inherently bound sensory discrimination.
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Soulet D, Lamontagne-Proulx J, Aubé B, Davalos D. Multiphoton intravital microscopy in small animals: motion artefact challenges and technical solutions. J Microsc 2020; 278:3-17. [PMID: 32072642 PMCID: PMC7187339 DOI: 10.1111/jmi.12880] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 02/06/2020] [Accepted: 02/14/2020] [Indexed: 12/28/2022]
Abstract
Since its invention 29 years ago, two‐photon laser‐scanning microscopy has evolved from a promising imaging technique, to an established widely available imaging modality used throughout the biomedical research community. The establishment of two‐photon microscopy as the preferred method for imaging fluorescently labelled cells and structures in living animals can be attributed to the biophysical mechanism by which the generation of fluorescence is accomplished. The use of powerful lasers capable of delivering infrared light pulses within femtosecond intervals, facilitates the nonlinear excitation of fluorescent molecules only at the focal plane and determines by objective lens position. This offers numerous benefits for studies of biological samples at high spatial and temporal resolutions with limited photo‐damage and superior tissue penetration. Indeed, these attributes have established two‐photon microscopy as the ideal method for live‐animal imaging in several areas of biology and have led to a whole new field of study dedicated to imaging biological phenomena in intact tissues and living organisms. However, despite its appealing features, two‐photon intravital microscopy is inherently limited by tissue motion from heartbeat, respiratory cycles, peristalsis, muscle/vascular tone and physiological functions that change tissue geometry. Because these movements impede temporal and spatial resolution, they must be properly addressed to harness the full potential of two‐photon intravital microscopy and enable accurate data analysis and interpretation. In addition, the sources and features of these motion artefacts are varied, sometimes unpredictable and unique to specific organs and multiple complex strategies have previously been devised to address them. This review will discuss these motion artefacts requirement and technical solutions for their correction and after intravital two‐photon microscopy.
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Affiliation(s)
- D Soulet
- Centre de recherche du CHUL, Department of Neurosciences, Quebec, Canada.,Faculty of Pharmacy, Université Laval, Quebec, Canada
| | - J Lamontagne-Proulx
- Centre de recherche du CHUL, Department of Neurosciences, Quebec, Canada.,Faculty of Pharmacy, Université Laval, Quebec, Canada
| | - B Aubé
- Centre de recherche du CHUL, Department of Neurosciences, Quebec, Canada
| | - D Davalos
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, U.S.A
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32
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Tang P, Li Y, Rakymzhan A, Xie Z, Wang RK. Measurement and visualization of stimulus-evoked tissue dynamics in mouse barrel cortex using phase-sensitive optical coherence tomography. BIOMEDICAL OPTICS EXPRESS 2020; 11:699-710. [PMID: 32206393 PMCID: PMC7041479 DOI: 10.1364/boe.381332] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 12/04/2019] [Accepted: 01/02/2020] [Indexed: 05/24/2023]
Abstract
We describe a method to measure tissue dynamics in mouse barrel cortex during functional activation via phase-sensitive optical coherence tomography (PhS-OCT). The method measures the phase changes in OCT signals, which are induced by the tissue volume change, upon which to localize the activated tissue region. Phase unwrapping, compensation and normalization are applied to increase the dynamic range of the OCT phase detection. To guide the OCT scanning, intrinsic optical signal imaging (IOSI) system equipped with a green light laser source (532 nm) is integrated with the PhS-OCT system to provide a full field time-lapsed images of the reflectance that is used to identify the transversal 2D localized tissue response in the mouse brain. The OCT results show a localized decrease in the OCT phase signal in the activated region of the mouse brain tissue. The decrease in the phase signal may be originated from the brain tissue compression caused by the vasodilatation in the activated region. The activated region revealed in the cross-sectional OCT image is consistent with that identified by the IOSI imaging, indicating the phase change in the OCT signals may associate with the changes in the corresponding hemodynamics. In vivo localized tissue dynamics in the barrel cortex at depth during whisker stimulation is observed and monitored in this study.
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33
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Lee CR, Najafizadeh L, Margolis DJ. Investigating learning-related neural circuitry with chronic in vivo optical imaging. Brain Struct Funct 2020; 225:467-480. [PMID: 32006147 DOI: 10.1007/s00429-019-02001-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 12/05/2019] [Indexed: 10/25/2022]
Abstract
Fundamental aspects of brain function, including development, plasticity, learning, and memory, can take place over time scales of days to years. Chronic in vivo imaging of neural activity with cellular resolution is a powerful method for tracking the long-term activity of neural circuits. We review recent advances in our understanding of neural circuit function from diverse brain regions that have been enabled by chronic in vivo cellular imaging. Insight into the neural basis of learning and decision-making, in particular, benefit from the ability to acquire longitudinal data from genetically identified neuronal populations, deep brain areas, and subcellular structures. We propose that combining chronic imaging with further experimental and computational innovations will advance our understanding of the neural circuit mechanisms of brain function.
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Affiliation(s)
- Christian R Lee
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA
| | - Laleh Najafizadeh
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA
| | - David J Margolis
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
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34
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Kondo T, Saito R, Otaka M, Yoshino-Saito K, Yamanaka A, Yamamori T, Watakabe A, Mizukami H, Schnitzer MJ, Tanaka KF, Ushiba J, Okano H. Calcium Transient Dynamics of Neural Ensembles in the Primary Motor Cortex of Naturally Behaving Monkeys. Cell Rep 2020; 24:2191-2195.e4. [PMID: 30134178 DOI: 10.1016/j.celrep.2018.07.057] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Revised: 04/05/2018] [Accepted: 07/16/2018] [Indexed: 11/26/2022] Open
Abstract
To understand brain circuits of cognitive behaviors under natural conditions, we developed techniques for imaging neuronal activities from large neuronal populations in the deep layer cortex of the naturally behaving common marmoset. Animals retrieved food pellets or climbed ladders as a miniature fluorescence microscope monitored hundreds of calcium indicator-expressing cortical neurons in the right primary motor cortex. This technique, which can be adapted to other brain regions, can deepen our understanding of brain circuits by facilitating longitudinal population analyses of neuronal representation associated with cognitive naturalistic behaviors and their pathophysiological processes.
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Affiliation(s)
- Takahiro Kondo
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan
| | - Risa Saito
- Graduate School of Science and Technology, Keio University, Kanagawa, Japan
| | - Masaki Otaka
- Graduate School of Science and Technology, Keio University, Kanagawa, Japan
| | - Kimika Yoshino-Saito
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan; Japan Society for the Promotion of Science, Tokyo, Japan
| | - Akihiro Yamanaka
- Research Institute of Environmental Medicine, Nagoya University, Nagoya, Japan
| | - Tetsuo Yamamori
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Saitama, Japan
| | - Akiya Watakabe
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Saitama, Japan
| | - Hiroaki Mizukami
- Division of Genetic Therapeutics, Center for Molecular Medicine, Jichi Medical University, Tochigi, Japan
| | - Mark J Schnitzer
- James H. Clark Center for Biomedical Engineering and Sciences, Stanford University, Stanford, CA, USA; CNC Program, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Kenji F Tanaka
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan; Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Kanagawa, Japan; Keio Institute of Pure and Applied Sciences (KiPAS), Kanagawa, Japan.
| | - Hideyuki Okano
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan.
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35
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Yang M, Zhou Z, Zhang J, Jia S, Li T, Guan J, Liao X, Leng B, Lyu J, Zhang K, Li M, Gong Y, Zhu Z, Yan J, Zhou Y, Liu JK, Varga Z, Konnerth A, Tang Y, Gao J, Chen X, Jia H. MATRIEX imaging: multiarea two-photon real-time in vivo explorer. LIGHT, SCIENCE & APPLICATIONS 2019; 8:109. [PMID: 31798848 PMCID: PMC6881438 DOI: 10.1038/s41377-019-0219-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 10/31/2019] [Accepted: 11/05/2019] [Indexed: 06/01/2023]
Abstract
Two-photon laser scanning microscopy has been extensively applied to study in vivo neuronal activity at cellular and subcellular resolutions in mammalian brains. However, the extent of such studies is typically confined to a single functional region of the brain. Here, we demonstrate a novel technique, termed the multiarea two-photon real-time in vivo explorer (MATRIEX), that allows the user to target multiple functional brain regions distributed within a zone of up to 12 mm in diameter, each with a field of view (FOV) of ~200 μm in diameter, thus performing two-photon Ca2+ imaging with single-cell resolution in all of the regions simultaneously. For example, we demonstrate real-time functional imaging of single-neuron activities in the primary visual cortex, primary motor cortex and hippocampal CA1 region of mice in both anesthetized and awake states. A unique advantage of the MATRIEX technique is the configuration of multiple microscopic FOVs that are distributed in three-dimensional space over macroscopic distances (>1 mm) both laterally and axially but that are imaged by a single conventional laser scanning device. In particular, the MATRIEX technique can be effectively implemented as an add-on optical module for an existing conventional single-beam-scanning two-photon microscope without requiring any modification to the microscope itself. Thus, the MATRIEX technique can be readily applied to substantially facilitate the exploration of multiarea neuronal activity in vivo for studies of brain-wide neural circuit function with single-cell resolution.
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Affiliation(s)
- Mengke Yang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, 130033 China
- Graduate School, University of the Chinese Academy of Sciences, Beijing, 100039 China
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Zhenqiao Zhou
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Jianxiong Zhang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Shanshan Jia
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Tong Li
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Jiangheng Guan
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Xiang Liao
- Center for Neurointelligence, Chongqing University, Chongqing, 401331 China
| | - Bing Leng
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Jing Lyu
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Kuan Zhang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Min Li
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Yan Gong
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Zhiming Zhu
- Center for Hypertension and Metabolic Diseases, Daping Hospital, Chongqing, 400042 China
| | - Junan Yan
- Advanced Institute of Brain and Intelligence, Guangxi University, Nanning, 530005 China
| | - Yi Zhou
- Advanced Institute of Brain and Intelligence, Guangxi University, Nanning, 530005 China
| | - Jian K Liu
- Centre for Systems Neuroscience, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
| | - Zsuzsanna Varga
- Institute of Neuroscience, Technical University Munich, 80802 Munich, Germany
| | - Arthur Konnerth
- Institute of Neuroscience, Technical University Munich, 80802 Munich, Germany
| | - Yuguo Tang
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Jinsong Gao
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, 130033 China
| | - Xiaowei Chen
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Hongbo Jia
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
- Institute of Neuroscience, Technical University Munich, 80802 Munich, Germany
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36
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Clough M, Chen JL. CELLULAR RESOLUTION IMAGING OF NEURONAL ACTIVITY ACROSS SPACE AND TIME IN THE MAMMALIAN BRAIN. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2019; 12:95-101. [PMID: 32104747 DOI: 10.1016/j.cobme.2019.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
While the action potential has long been understood to be the fundamental bit of information in brain, how these spikes encode representations of stimuli and drive behavior remains unclear. Large-scale neuronal recordings with cellular and spike-time resolution spanning multiple brain regions are needed to capture relevant network dynamics that can be sparse and distributed across the population. This review focuses on recent advancements in optical methods that have pushed the boundaries for simultaneous population recordings at increasing volumes, distances, depths, and speeds. The integration of these technologies will be critical for overcoming fundamental limits in the pursuit of whole brain imaging in mammalian species.
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Affiliation(s)
- Mitchell Clough
- Department of Biomedical Engineering, Boston University, Boston, USA.,Department of Biology, Boston University, Boston, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, USA.,Department of Biology, Boston University, Boston, USA.,Center for Neurophotonics, Boston University, Boston, USA
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37
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Lecoq J, Orlova N, Grewe BF. Wide. Fast. Deep: Recent Advances in Multiphoton Microscopy of In Vivo Neuronal Activity. J Neurosci 2019; 39:9042-9052. [PMID: 31578235 PMCID: PMC6855689 DOI: 10.1523/jneurosci.1527-18.2019] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Revised: 09/27/2019] [Accepted: 09/27/2019] [Indexed: 01/04/2023] Open
Abstract
Multiphoton microscopy (MPM) has emerged as one of the most powerful and widespread technologies to monitor the activity of neuronal networks in awake, behaving animals over long periods of time. MPM development spanned across decades and crucially depended on the concurrent improvement of calcium indicators that report neuronal activity as well as surgical protocols, head fixation approaches, and innovations in optics and microscopy technology. Here we review the last decade of MPM development and highlight how in vivo imaging has matured and diversified, making it now possible to concurrently monitor thousands of neurons across connected brain areas or, alternatively, small local networks with sampling rates in the kilohertz range. This review includes different laser scanning approaches, such as multibeam technologies as well as recent developments to image deeper into neuronal tissues using new, long-wavelength laser sources. As future development will critically depend on our ability to resolve and discriminate individual neuronal spikes, we will also describe a simple framework that allows performing quantitative comparisons between the reviewed MPM instruments. Finally, we provide our own opinion on how the most recent MPM developments can be leveraged at scale to enable the next generation of discoveries in brain function.
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Affiliation(s)
- Jérôme Lecoq
- Allen Institute for Brain Science, Seattle 98109, Washington,
| | - Natalia Orlova
- Allen Institute for Brain Science, Seattle 98109, Washington
| | - Benjamin F Grewe
- Institute of Neuroinformatics, UZH and ETH Zurich, Zurich 8057, Switzerland
- Department of Electrical Engineering and Information Technology, ETH Zurich, Zurich 8092, Switzerland, and
- Faculty of Sciences, University of Zurich, Zurich 8057, Switzerland
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38
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Barson D, Hamodi AS, Shen X, Lur G, Constable RT, Cardin JA, Crair MC, Higley MJ. Simultaneous mesoscopic and two-photon imaging of neuronal activity in cortical circuits. Nat Methods 2019; 17:107-113. [PMID: 31686040 PMCID: PMC6946863 DOI: 10.1038/s41592-019-0625-2] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 09/30/2019] [Indexed: 12/20/2022]
Abstract
Spontaneous and sensory-evoked activity propagates across varying spatial scales in the mammalian cortex, but technical challenges have limited conceptual links between the function of local neuronal circuits and brain-wide network dynamics. We present a method for simultaneous cellular-resolution two-photon calcium imaging of a local microcircuit and mesoscopic widefield calcium imaging of the entire cortical mantle in awake mice. Our multi-scale approach employs an orthogonal axis design where the mesoscopic objective is oriented above the brain and the two-photon objective is oriented horizontally, with imaging performed through a microprism. We also introduce a viral method for robust and widespread gene delivery in the mouse brain. These approaches allow us to identify the behavioral state-dependent functional connectivity of pyramidal neurons and vasoactive intestinal peptide (VIP)-expressing interneurons with long-range cortical networks. Our novel imaging system provides a powerful strategy for investigating cortical architecture across a wide range of spatial scales. Further information on research design is available in the Life Sciences Reporting Summary linked to this article.
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Affiliation(s)
- Daniel Barson
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.,Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA.,MD/PhD Program, Yale School of Medicine, New Haven, CT, USA
| | - Ali S Hamodi
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Gyorgy Lur
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.,Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA.,Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.,Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Jessica A Cardin
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Michael C Crair
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA. .,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA. .,Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, USA.
| | - Michael J Higley
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA. .,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA. .,Program in Cellular Neuroscience, Neurodegeneration and Repair, New Haven, CT, USA.
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39
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Zhang X, Coates K, Dacks A, Günay C, Lauritzen JS, Li F, Calle-Schuler SA, Bock D, Gaudry Q. Local synaptic inputs support opposing, network-specific odor representations in a widely projecting modulatory neuron. eLife 2019; 8:46839. [PMID: 31264962 PMCID: PMC6660217 DOI: 10.7554/elife.46839] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Accepted: 07/01/2019] [Indexed: 12/14/2022] Open
Abstract
Serotonin plays different roles across networks within the same sensory modality. Previously, we used whole-cell electrophysiology in Drosophila to show that serotonergic neurons innervating the first olfactory relay are inhibited by odorants (Zhang and Gaudry, 2016). Here we show that network-spanning serotonergic neurons segregate information about stimulus features, odor intensity and identity, by using opposing coding schemes in different olfactory neuropil. A pair of serotonergic neurons (the CSDns) innervate the antennal lobe and lateral horn, which are first and second order neuropils. CSDn processes in the antennal lobe are inhibited by odors in an identity independent manner. In the lateral horn, CSDn processes are excited in an odor identity dependent manner. Using functional imaging, modeling, and EM reconstruction, we demonstrate that antennal lobe derived inhibition arises from local GABAergic inputs and acts as a means of gain control on branch-specific inputs that the CSDns receive within the lateral horn.
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Affiliation(s)
- Xiaonan Zhang
- Department of Biology, University of Maryland, College Park, United States
| | - Kaylynn Coates
- Department of Biology, West Virginia University, Morgantown, United States
| | - Andrew Dacks
- Department of Biology, West Virginia University, Morgantown, United States
| | - Cengiz Günay
- School of Science and Technology, Georgia Gwinnett College, Lawrenceville, United States
| | - J Scott Lauritzen
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Feng Li
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | | | - Davi Bock
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, United States.,Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, United States
| | - Quentin Gaudry
- Department of Biology, University of Maryland, College Park, United States
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40
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Qin H, Lu J, Jin W, Chen X, Fu L. Multichannel fiber photometry for mapping axonal terminal activity in a restricted brain region in freely moving mice. NEUROPHOTONICS 2019; 6:035011. [PMID: 31528656 PMCID: PMC6739620 DOI: 10.1117/1.nph.6.3.035011] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 08/05/2019] [Indexed: 05/30/2023]
Abstract
Fiber photometry has been increasingly popular in neuroscience research in freely behaving animals. In combination with genetically encoded calcium indicators, it allows for real-time monitoring of neural activity in neuronal somata, dendrites, and axonal terminals. We developed a multichannel fiber photometry device to map the activity of axonal terminals in a restricted, 100 - μ m -wide brain region in freely moving mice. This device consists of four bundled multimode fibers, each with a 50 - μ m core diameter and a scientific complementary metal-oxide semiconductor camera to simultaneously acquire fluorescence. We achieved a sampling rate of 100 frames / s and sufficient sensitivity to acquire data from axonal terminals. To avoid interference with neighboring channels, the recording depth of each channel was restricted to < 250 μ m . Furthermore, the small-core-diameter fibers did not restrict mouse locomotion. Using the Ca 2 + indicator GCaMP5G, we validated the system by recording Ca 2 + signals in axonal terminals from the medial entorhinal cortex layer II to the hippocampal dentate gyrus (DG) in freely moving mice. We detected spatially separated Ca 2 + signals at four different sites in the DG. Therefore, our multichannel fiber photometry device provides a simple but powerful method to functionally map axonal terminals in spatially confined brain areas of freely moving animals.
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Affiliation(s)
- Han Qin
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan, China
| | - Jian Lu
- Third Military Medical University, Brain Research Center, State Key Laboratory of Trauma, Burns, and Combined Injury, Chongqing, China
| | - Wenjun Jin
- Third Military Medical University, Brain Research Center, State Key Laboratory of Trauma, Burns, and Combined Injury, Chongqing, China
| | - Xiaowei Chen
- Third Military Medical University, Brain Research Center, State Key Laboratory of Trauma, Burns, and Combined Injury, Chongqing, China
| | - Ling Fu
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan, China
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41
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Sych Y, Chernysheva M, Sumanovski LT, Helmchen F. High-density multi-fiber photometry for studying large-scale brain circuit dynamics. Nat Methods 2019; 16:553-560. [PMID: 31086339 DOI: 10.1038/s41592-019-0400-4] [Citation(s) in RCA: 113] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 03/28/2019] [Indexed: 11/09/2022]
Abstract
Animal behavior originates from neuronal activity distributed across brain-wide networks. However, techniques available to assess large-scale neural dynamics in behaving animals remain limited. Here we present compact, chronically implantable, high-density arrays of optical fibers that enable multi-fiber photometry and optogenetic perturbations across many regions in the mammalian brain. In mice engaged in a texture discrimination task, we achieved simultaneous photometric calcium recordings from networks of 12-48 brain regions, including striatal, thalamic, hippocampal and cortical areas. Furthermore, we optically perturbed subsets of regions in VGAT-ChR2 mice by targeting specific fiber channels with a spatial light modulator. Perturbation of ventral thalamic nuclei caused distributed network modulation and behavioral deficits. Finally, we demonstrate multi-fiber photometry in freely moving animals, including simultaneous recordings from two mice during social interaction. High-density multi-fiber arrays are versatile tools for the investigation of large-scale brain dynamics during behavior.
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Affiliation(s)
- Yaroslav Sych
- Brain Research Institute, University of Zurich, Zurich, Switzerland.
| | - Maria Chernysheva
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Neuroscience Center Zurich, Zurich, Switzerland
| | | | - Fritjof Helmchen
- Brain Research Institute, University of Zurich, Zurich, Switzerland. .,Neuroscience Center Zurich, Zurich, Switzerland.
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42
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Wagner MJ, Kim TH, Kadmon J, Nguyen ND, Ganguli S, Schnitzer MJ, Luo L. Shared Cortex-Cerebellum Dynamics in the Execution and Learning of a Motor Task. Cell 2019; 177:669-682.e24. [PMID: 30929904 PMCID: PMC6500577 DOI: 10.1016/j.cell.2019.02.019] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Revised: 01/08/2019] [Accepted: 02/12/2019] [Indexed: 01/09/2023]
Abstract
Throughout mammalian neocortex, layer 5 pyramidal (L5) cells project via the pons to a vast number of cerebellar granule cells (GrCs), forming a fundamental pathway. Yet, it is unknown how neuronal dynamics are transformed through the L5→GrC pathway. Here, by directly comparing premotor L5 and GrC activity during a forelimb movement task using dual-site two-photon Ca2+ imaging, we found that in expert mice, L5 and GrC dynamics were highly similar. L5 cells and GrCs shared a common set of task-encoding activity patterns, possessed similar diversity of responses, and exhibited high correlations comparable to local correlations among L5 cells. Chronic imaging revealed that these dynamics co-emerged in cortex and cerebellum over learning: as behavioral performance improved, initially dissimilar L5 cells and GrCs converged onto a shared, low-dimensional, task-encoding set of neural activity patterns. Thus, a key function of cortico-cerebellar communication is the propagation of shared dynamics that emerge during learning.
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Affiliation(s)
- Mark J Wagner
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
| | - Tony Hyun Kim
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Jonathan Kadmon
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Nghia D Nguyen
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Surya Ganguli
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Mark J Schnitzer
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA.
| | - Liqun Luo
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
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43
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Ghanbari L, Carter RE, Rynes ML, Dominguez J, Chen G, Naik A, Hu J, Sagar MAK, Haltom L, Mossazghi N, Gray MM, West SL, Eliceiri KW, Ebner TJ, Kodandaramaiah SB. Cortex-wide neural interfacing via transparent polymer skulls. Nat Commun 2019; 10:1500. [PMID: 30940809 PMCID: PMC6445105 DOI: 10.1038/s41467-019-09488-0] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 03/12/2019] [Indexed: 11/22/2022] Open
Abstract
Neural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating behaviors. Progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. We engineered ‘See-Shells’—digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (>300 days) optical access to 45 mm2 of the dorsal cerebral cortex in the mouse. We demonstrate the ability to perform mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm deep. See-Shells allow calcium imaging from multiple, non-contiguous regions across the cortex. Perforated See-Shells enable introducing penetrating neural probes to perturb or record neural activity simultaneously with whole cortex imaging. See-Shells are constructed using common desktop fabrication tools, providing a powerful tool for investigating brain structure and function. Imaging the mouse brain using glass cranial windows has limitations in terms of flexibility and long-term imaging. Here the authors engineer transparent polymer skulls that can fit various skull morphologies and can be implanted for over 300 days, enabling simultaneous high resolution brain imaging and electrophysiology across large cortical areas.
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Affiliation(s)
- Leila Ghanbari
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Mathew L Rynes
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Judith Dominguez
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Gang Chen
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Anant Naik
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Jia Hu
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA
| | | | - Lenora Haltom
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Nahom Mossazghi
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Madelyn M Gray
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Sarah L West
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Kevin W Eliceiri
- Department of Biomedical Engineering, University of Wisconsin, Madison, WI, USA
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA. .,Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA.
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44
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Tsyboulski D, Orlova N, Ledochowitsch P, Saggau P. Two-photon frequency division multiplexing for functional in vivo imaging: a feasibility study. OPTICS EXPRESS 2019; 27:4488-4503. [PMID: 30876067 DOI: 10.1364/oe.27.004488] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 01/19/2019] [Indexed: 06/09/2023]
Abstract
Recently, we presented a new approach to create high-speed amplitude modulation of femtosecond laser pulses and tag multiple excitation beams with specific modulation frequencies. In this work, we discuss the utility of this method to record calcium signals in brain tissue with two-photon frequency-division multiplexing (2P-FDM) microscopy. While frequency-multiplexed imaging appears slightly inferior in terms of image quality as compared to conventional two-photon laser scanning microscopy due to shot noise-induced cross-talk between frequency channels, applying this technique to record average signals from regions of interest (ROI) such as neuronal cell bodies was found to be promising. We use phase information associated with each pixel or waveform within a selected ROI to phase-align and recombine the signals into one extended amplitude-modulated waveform. This procedure narrows the frequency detection window, effectively decreasing noise contributions from other frequency channels. Using theoretical analysis, numerical simulations, and in vitro imaging, we demonstrate a reduction of cross-talk by more than an order of magnitude and predict the usefulness of 2P-FDM for functional studies of brain activity.
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45
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Ronzitti E, Emiliani V, Papagiakoumou E. Methods for Three-Dimensional All-Optical Manipulation of Neural Circuits. Front Cell Neurosci 2018; 12:469. [PMID: 30618626 PMCID: PMC6304748 DOI: 10.3389/fncel.2018.00469] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Accepted: 11/19/2018] [Indexed: 12/18/2022] Open
Abstract
Optical means for modulating and monitoring neuronal activity, have provided substantial insights to neurophysiology and toward our understanding of how the brain works. Optogenetic actuators, calcium or voltage imaging probes and other molecular tools, combined with advanced microscopies have allowed an "all-optical" readout and modulation of neural circuits. Completion of this remarkable work is evolving toward a three-dimensional (3D) manipulation of neural ensembles at a high spatiotemporal resolution. Recently, original optical methods have been proposed for both activating and monitoring neurons in a 3D space, mainly through optogenetic compounds. Here, we review these methods and anticipate possible combinations among them.
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Affiliation(s)
| | | | - Eirini Papagiakoumou
- Wavefront Engineering Microscopy Group, Photonics Department, Institut de la Vision, Sorbonne Université, Inserm S968, CNRS UMR7210, Paris, France
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46
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Super-wide-field two-photon imaging with a micro-optical device moving in post-objective space. Nat Commun 2018; 9:3550. [PMID: 30177699 PMCID: PMC6120955 DOI: 10.1038/s41467-018-06058-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 08/14/2018] [Indexed: 11/08/2022] Open
Abstract
Wide-field imaging of neural activity at a cellular resolution is a current challenge in neuroscience. To address this issue, wide-field two-photon microscopy has been developed; however, the field size is limited by the objective size. Here, we develop a micro-opto-mechanical device that rotates within the post-objective space between the objective and brain tissue. Two-photon microscopy with this device enables sub-second sequential calcium imaging of left and right mouse sensory forelimb areas 6 mm apart. When imaging the rostral and caudal motor forelimb areas (RFA and CFA) 2 mm apart, we found high pairwise correlations in spontaneous activity between RFA and CFA neurons and between an RFA neuron and its putative axons in CFA. While mice performed a sound-triggered forelimb-movement task, the population activity between RFA and CFA covaried across trials, although the field-averaged activity was similar across trials. The micro-opto-mechanical device in the post-objective space provides a novel and flexible design to clarify the correlation structure between distant brain areas at subcellular and population levels.
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47
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Abstract
Endocrine organs secrete a variety of hormones involved in the regulation of a multitude of body functions. Although pancreatic islets were discovered at the turn of the 19th century, other endocrine glands remained commonly described as diffuse endocrine systems. Over the last two decades, development of new imaging techniques and genetically-modified animals with cell-specific fluorescent tags or specific hormone deficiencies have enabled in vivo imaging of endocrine organs and revealed intricate endocrine cell network structures and plasticity. Overall, these new tools have revolutionized our understanding of endocrine function. The overarching aim of this Review is to describe the current mechanistic understanding that has emerged from imaging studies of endocrine cell network structure/function relationships in animal models, with a particular emphasis on the pituitary gland and the endocrine pancreas.
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Affiliation(s)
- Patrice Mollard
- Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, F-34094, Montpellier, France
| | - Marie Schaeffer
- Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, F-34094, Montpellier, France.
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48
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Yoshida E, Terada SI, Tanaka YH, Kobayashi K, Ohkura M, Nakai J, Matsuzaki M. In vivo wide-field calcium imaging of mouse thalamocortical synapses with an 8 K ultra-high-definition camera. Sci Rep 2018; 8:8324. [PMID: 29844612 PMCID: PMC5974322 DOI: 10.1038/s41598-018-26566-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 05/15/2018] [Indexed: 12/12/2022] Open
Abstract
In vivo wide-field imaging of neural activity with a high spatio-temporal resolution is a challenge in modern neuroscience. Although two-photon imaging is very powerful, high-speed imaging of the activity of individual synapses is mostly limited to a field of approximately 200 µm on a side. Wide-field one-photon epifluorescence imaging can reveal neuronal activity over a field of ≥1 mm2 at a high speed, but is not able to resolve a single synapse. Here, to achieve a high spatio-temporal resolution, we combine an 8 K ultra-high-definition camera with spinning-disk one-photon confocal microscopy. This combination allowed us to image a 1 mm2 field with a pixel resolution of 0.21 µm at 60 fps. When we imaged motor cortical layer 1 in a behaving head-restrained mouse, calcium transients were detected in presynaptic boutons of thalamocortical axons sparsely labeled with GCaMP6s, although their density was lower than when two-photon imaging was used. The effects of out-of-focus fluorescence changes on calcium transients in individual boutons appeared minimal. Axonal boutons with highly correlated activity were detected over the 1 mm2 field, and were probably distributed on multiple axonal arbors originating from the same thalamic neuron. This new microscopy with an 8 K ultra-high-definition camera should serve to clarify the activity and plasticity of widely distributed cortical synapses.
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Affiliation(s)
- Eriko Yoshida
- Department of Physiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Shin-Ichiro Terada
- Department of Physiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yasuyo H Tanaka
- Department of Physiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kenta Kobayashi
- Section of Viral Vector Development, National Institute for Physiological Sciences, Aichi, Japan
| | - Masamichi Ohkura
- Brain and Body System Science Institute, Saitama University, Saitama, Japan
| | - Junichi Nakai
- Brain and Body System Science Institute, Saitama University, Saitama, Japan
| | - Masanori Matsuzaki
- Department of Physiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study, Tokyo, 113-0033, Japan.
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State-of-the-Art Techniques to Causally Link Neural Plasticity to Functional Recovery in Experimental Stroke Research. Neural Plast 2018; 2018:3846593. [PMID: 29977279 PMCID: PMC5994266 DOI: 10.1155/2018/3846593] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 04/12/2018] [Accepted: 05/02/2018] [Indexed: 12/05/2022] Open
Abstract
Current experimental stroke research faces the same challenge as neuroscience: to transform correlative findings in causative ones. Research of recent years has shown the tremendous potential of the central nervous system to react to noxious stimuli such as a stroke: Increased plastic changes leading to reorganization in form of neuronal rewiring, neurogenesis, and synaptogenesis, accompanied by transcriptional and translational turnover in the affected cells, have been described both clinically and in experimental stroke research. However, only minor attempts have been made to connect distinct plastic remodeling processes as causative features for specific behavioral phenotypes. Here, we review current state-of the art techniques for the examination of cortical reorganization and for the manipulation of neuronal circuits as well as techniques which combine anatomical changes with molecular profiling. We provide the principles of the techniques together with studies in experimental stroke research which have already applied the described methodology. The tools discussed are useful to close the loop from our understanding of stroke pathology to the behavioral outcome and may allow discovering new targets for therapeutic approaches. The here presented methods open up new possibilities to assess the efficiency of rehabilitative strategies by understanding their external influence for intrinsic repair mechanisms on a neurobiological basis.
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50
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Diametric neural ensemble dynamics in parkinsonian and dyskinetic states. Nature 2018; 557:177-182. [PMID: 29720658 DOI: 10.1038/s41586-018-0090-6] [Citation(s) in RCA: 176] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Accepted: 03/27/2018] [Indexed: 01/02/2023]
Abstract
Loss of dopamine in Parkinson's disease is hypothesized to impede movement by inducing hypo- and hyperactivity in striatal spiny projection neurons (SPNs) of the direct (dSPNs) and indirect (iSPNs) pathways in the basal ganglia, respectively. The opposite imbalance might underlie hyperkinetic abnormalities, such as dyskinesia caused by treatment of Parkinson's disease with the dopamine precursor L-DOPA. Here we monitored thousands of SPNs in behaving mice, before and after dopamine depletion and during L-DOPA-induced dyskinesia. Normally, intermingled clusters of dSPNs and iSPNs coactivated before movement. Dopamine depletion unbalanced SPN activity rates and disrupted the movement-encoding iSPN clusters. Matching their clinical efficacy, L-DOPA or agonism of the D2 dopamine receptor reversed these abnormalities more effectively than agonism of the D1 dopamine receptor. The opposite pathophysiology arose in L-DOPA-induced dyskinesia, during which iSPNs showed hypoactivity and dSPNs showed unclustered hyperactivity. Therefore, both the spatiotemporal profiles and rates of SPN activity appear crucial to striatal function, and next-generation treatments for basal ganglia disorders should target both facets of striatal activity.
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