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Lewis CM, Hoffmann A, Helmchen F. Linking brain activity across scales with simultaneous opto- and electrophysiology. NEUROPHOTONICS 2024; 11:033403. [PMID: 37662552 PMCID: PMC10472193 DOI: 10.1117/1.nph.11.3.033403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/19/2023] [Accepted: 07/24/2023] [Indexed: 09/05/2023]
Abstract
The brain enables adaptive behavior via the dynamic coordination of diverse neuronal signals across spatial and temporal scales: from fast action potential patterns in microcircuits to slower patterns of distributed activity in brain-wide networks. Understanding principles of multiscale dynamics requires simultaneous monitoring of signals in multiple, distributed network nodes. Combining optical and electrical recordings of brain activity is promising for collecting data across multiple scales and can reveal aspects of coordinated dynamics invisible to standard, single-modality approaches. We review recent progress in combining opto- and electrophysiology, focusing on mouse studies that shed new light on the function of single neurons by embedding their activity in the context of brain-wide activity patterns. Optical and electrical readouts can be tailored to desired scales to tackle specific questions. For example, fast dynamics in single cells or local populations recorded with multi-electrode arrays can be related to simultaneously acquired optical signals that report activity in specified subpopulations of neurons, in non-neuronal cells, or in neuromodulatory pathways. Conversely, two-photon imaging can be used to densely monitor activity in local circuits while sampling electrical activity in distant brain areas at the same time. The refinement of combined approaches will continue to reveal previously inaccessible and under-appreciated aspects of coordinated brain activity.
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Affiliation(s)
| | - Adrian Hoffmann
- University of Zurich, Brain Research Institute, Zurich, Switzerland
- University of Zurich, Neuroscience Center Zurich, Zurich, Switzerland
| | - Fritjof Helmchen
- University of Zurich, Brain Research Institute, Zurich, Switzerland
- University of Zurich, Neuroscience Center Zurich, Zurich, Switzerland
- University of Zurich, University Research Priority Program, Adaptive Brain Circuits in Development and Learning, Zurich, Switzerland
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2
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Lorca-Cámara A, Blot FGC, Accanto N. Recent advances in light patterned optogenetic photostimulation in freely moving mice. NEUROPHOTONICS 2024; 11:S11508. [PMID: 38404422 PMCID: PMC10885521 DOI: 10.1117/1.nph.11.s1.s11508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/24/2024] [Accepted: 01/30/2024] [Indexed: 02/27/2024]
Abstract
Optogenetics opened the door to a new era of neuroscience. New optical developments are under way to enable high-resolution neuronal activity imaging and selective photostimulation of neuronal ensembles in freely moving animals. These advancements could allow researchers to interrogate, with cellular precision, functionally relevant neuronal circuits in the framework of naturalistic brain activity. We provide an overview of the current state-of-the-art of imaging and photostimulation in freely moving rodents and present a road map for future optical and engineering developments toward miniaturized microscopes that could reach beyond the currently existing systems.
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Affiliation(s)
| | - François G C Blot
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Nicolò Accanto
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
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3
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Du Y, Dylda E, Stibůrek M, Gomes AD, Turtaev S, Pakan JMP, Čižmár T. Advancing the path to in-vivo imaging in freely moving mice via multimode-multicore fiber based holographic endoscopy. NEUROPHOTONICS 2024; 11:S11506. [PMID: 38352728 PMCID: PMC10863504 DOI: 10.1117/1.nph.11.s1.s11506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/17/2024] [Accepted: 01/22/2024] [Indexed: 02/16/2024]
Abstract
Significance Hair-thin multimode optical fiber-based holographic endoscopes have gained considerable interest in modern neuroscience for their ability to achieve cellular and even subcellular resolution during in-vivo deep brain imaging. However, the application of multimode fibers in freely moving animals presents a persistent challenge as it is difficult to maintain optimal imaging performance while the fiber undergoes deformations. Aim We propose a fiber solution for challenging in-vivo applications with the capability of deep brain high spatial resolution imaging and neuronal activity monitoring in anesthetized as well as awake behaving mice. Approach We used our previously developed M 3 CF multimode-multicore fiber to record fluorescently labeled neurons in anesthetized mice. Our M 3 CF exhibits a cascaded refractive index structure, enabling two distinct regimes of light transport that imitate either a multimode or a multicore fiber. The M 3 CF has been specifically designed for use in the initial phase of an in-vivo experiment, allowing for the navigation of the endoscope's distal end toward the targeted brain structure. The multicore regime enables the transfer of light to and from each individual neuron within the field of view. For chronic experiments in awake behaving mice, it is crucial to allow for disconnecting the fiber and the animal between experiments. Therefore, we provide here an effective solution and establish a protocol for reconnection of two segments of M 3 CF with hexagonally arranged corelets. Results We successfully utilized the M 3 CF to image neurons in anaesthetized transgenic mice expressing enhanced green fluorescent protein. Additionally, we compared imaging results obtained with the M 3 CF with larger numerical aperture (NA) fibers in fixed whole-brain tissue. Conclusions This study focuses on addressing challenges and providing insights into the use of multimode-multicore fibers as imaging solutions for in-vivo applications. We suggest that the upcoming version of the M 3 CF increases the overall NA between the two cladding layers to allow for access to high resolution spatial imaging. As the NA increases in the multimode regime, the fiber diameter and ring structure must be reduced to minimize the computational burden and invasiveness.
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Affiliation(s)
- Yang Du
- University of Chinese Academy of Sciences, Hangzhou Institute for Advanced Study, Hangzhou, China
- Leibniz Institute of Photonic Technology, Jena, Germany
| | - Evelyn Dylda
- Otto-von-Guericke-University Magdeburg, Institute of Cognitive Neurology and Dementia Research, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | | | - André D Gomes
- Leibniz Institute of Photonic Technology, Jena, Germany
| | | | - Janelle M. P. Pakan
- Otto-von-Guericke-University Magdeburg, Institute of Cognitive Neurology and Dementia Research, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- German Centre for Neurodegenerative Diseases, Magdeburg, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Tomáš Čižmár
- Leibniz Institute of Photonic Technology, Jena, Germany
- Institute of Scientific Instruments of CAS, Brno, Czechia
- Friedrich Schiller University Jena, Institute of Applied Optics, Jena, Germany
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4
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Pisano F, Collard L, Zheng D, Kashif MF, Kazemzadeh M, Balena A, Piscopo L, Andriani MS, De Vittorio M, Pisanello F. Potential of plasmonics and nanoscale light-matter interactions for the next generation of optical neural interfaces. NEUROPHOTONICS 2024; 11:S11513. [PMID: 39119220 PMCID: PMC11309004 DOI: 10.1117/1.nph.11.s1.s11513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 07/02/2024] [Accepted: 07/15/2024] [Indexed: 08/10/2024]
Abstract
Within the realm of optical neural interfaces, the exploration of plasmonic resonances to interact with neural cells has captured increasing attention among the neuroscience community. The interplay of light with conduction electrons in nanometer-sized metallic nanostructures can induce plasmonic resonances, showcasing a versatile capability to both sense and trigger cellular events. We describe the perspective of generating propagating or localized surface plasmon polaritons on the tip of an optical neural implant, widening the possibility for neuroscience labs to explore the potential of plasmonic neural interfaces.
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Affiliation(s)
- Filippo Pisano
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
- University of Padua, Department of Physics and Astronomy “G. Galilei” Padua, Italy
| | - Liam Collard
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
- RAISE Ecosystem, Genova, Italy
| | - Di Zheng
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
| | - Muhammad Fayyaz Kashif
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
| | - Mohammadrahim Kazemzadeh
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
| | - Antonio Balena
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
| | - Linda Piscopo
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
- Università del Salento, Dipartimento di Ingegneria Dell’Innovazione, Lecce, Italy
| | - Maria Samuela Andriani
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
- Università del Salento, Dipartimento di Ingegneria Dell’Innovazione, Lecce, Italy
| | - Massimo De Vittorio
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
- RAISE Ecosystem, Genova, Italy
- Università del Salento, Dipartimento di Ingegneria Dell’Innovazione, Lecce, Italy
| | - Ferruccio Pisanello
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano (Lecce), Italy
- RAISE Ecosystem, Genova, Italy
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5
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Xia F, Rimoli CV, Akemann W, Ventalon C, Bourdieu L, Gigan S, de Aguiar HB. Neurophotonics beyond the surface: unmasking the brain's complexity exploiting optical scattering. NEUROPHOTONICS 2024; 11:S11510. [PMID: 38617592 PMCID: PMC11014413 DOI: 10.1117/1.nph.11.s1.s11510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 03/07/2024] [Accepted: 03/14/2024] [Indexed: 04/16/2024]
Abstract
The intricate nature of the brain necessitates the application of advanced probing techniques to comprehensively study and understand its working mechanisms. Neurophotonics offers minimally invasive methods to probe the brain using optics at cellular and even molecular levels. However, multiple challenges persist, especially concerning imaging depth, field of view, speed, and biocompatibility. A major hindrance to solving these challenges in optics is the scattering nature of the brain. This perspective highlights the potential of complex media optics, a specialized area of study focused on light propagation in materials with intricate heterogeneous optical properties, in advancing and improving neuronal readouts for structural imaging and optical recordings of neuronal activity. Key strategies include wavefront shaping techniques and computational imaging and sensing techniques that exploit scattering properties for enhanced performance. We discuss the potential merger of the two fields as well as potential challenges and perspectives toward longer term in vivo applications.
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Affiliation(s)
- Fei Xia
- Sorbonne Université, Collège de France, Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Paris, France
| | - Caio Vaz Rimoli
- Sorbonne Université, Collège de France, Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Paris, France
- Université PSL, Institut de Biologie de l’ENS, École Normale Supérieure, CNRS, INSERM, Paris, France
| | - Walther Akemann
- Université PSL, Institut de Biologie de l’ENS, École Normale Supérieure, CNRS, INSERM, Paris, France
| | - Cathie Ventalon
- Université PSL, Institut de Biologie de l’ENS, École Normale Supérieure, CNRS, INSERM, Paris, France
| | - Laurent Bourdieu
- Université PSL, Institut de Biologie de l’ENS, École Normale Supérieure, CNRS, INSERM, Paris, France
| | - Sylvain Gigan
- Sorbonne Université, Collège de France, Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Paris, France
| | - Hilton B. de Aguiar
- Sorbonne Université, Collège de France, Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Paris, France
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6
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Roth RH, Ding JB. Cortico-basal ganglia plasticity in motor learning. Neuron 2024; 112:2486-2502. [PMID: 39002543 PMCID: PMC11309896 DOI: 10.1016/j.neuron.2024.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 05/29/2024] [Accepted: 06/17/2024] [Indexed: 07/15/2024]
Abstract
One key function of the brain is to control our body's movements, allowing us to interact with the world around us. Yet, many motor behaviors are not innate but require learning through repeated practice. Among the brain's motor regions, the cortico-basal ganglia circuit is particularly crucial for acquiring and executing motor skills, and neuronal activity in these regions is directly linked to movement parameters. Cell-type-specific adaptations of activity patterns and synaptic connectivity support the learning of new motor skills. Functionally, neuronal activity sequences become structured and associated with learned movements. On the synaptic level, specific connections become potentiated during learning through mechanisms such as long-term synaptic plasticity and dendritic spine dynamics, which are thought to mediate functional circuit plasticity. These synaptic and circuit adaptations within the cortico-basal ganglia circuitry are thus critical for motor skill acquisition, and disruptions in this plasticity can contribute to movement disorders.
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Affiliation(s)
- Richard H Roth
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA.
| | - Jun B Ding
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA; Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA; The Phil & Penny Knight Initiative for Brain Resilience at the Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
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7
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Hu J, Cherkkil A, Surinach DA, Oladepo I, Hossain RF, Fausner S, Saxena K, Ko E, Peters R, Feldkamp M, Konda PC, Pathak V, Horstmeyer R, Kodandaramaiah SB. Pan-cortical cellular imaging in freely behaving mice using a miniaturized micro-camera array microscope (mini-MCAM). BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.04.601964. [PMID: 39005454 PMCID: PMC11245122 DOI: 10.1101/2024.07.04.601964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Understanding how circuits in the brain simultaneously coordinate their activity to mediate complex ethnologically relevant behaviors requires recording neural activities from distributed populations of neurons in freely behaving animals. Current miniaturized imaging microscopes are typically limited to imaging a relatively small field of view, precluding the measurement of neural activities across multiple brain regions. Here we present a miniaturized micro-camera array microscope (mini-MCAM) that consists of four fluorescence imaging micro-cameras, each capable of capturing neural activity across a 4.5 mm x 2.55 mm field of view (FOV). Cumulatively, the mini-MCAM images over 30 mm 2 area of sparsely expressed GCaMP6s neurons distributed throughout the dorsal cortex, in regions including the primary and secondary motor, somatosensory, visual, retrosplenial, and association cortices across both hemispheres. We demonstrate cortex-wide cellular resolution in vivo Calcium (Ca 2+ ) imaging using the mini-MCAM in both head-fixed and freely behaving mice.
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8
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Glaser A, Chandrashekar J, Vasquez S, Arshadi C, Ouellette N, Jiang X, Baka J, Kovacs G, Woodard M, Seshamani S, Cao K, Clack N, Recknagel A, Grim A, Balaram P, Turschak E, Hooper M, Liddell A, Rohde J, Hellevik A, Takasaki K, Erion Barner L, Logsdon M, Chronopoulos C, de Vries S, Ting J, Perlmutter S, Kalmbach B, Dembrow N, Tasic B, Reid RC, Feng D, Svoboda K. Expansion-assisted selective plane illumination microscopy for nanoscale imaging of centimeter-scale tissues. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.08.544277. [PMID: 37425699 PMCID: PMC10327101 DOI: 10.1101/2023.06.08.544277] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Recent advances in tissue processing, labeling, and fluorescence microscopy are providing unprecedented views of the structure of cells and tissues at sub-diffraction resolutions and near single molecule sensitivity, driving discoveries in diverse fields of biology, including neuroscience. Biological tissue is organized over scales of nanometers to centimeters. Harnessing molecular imaging across intact, three-dimensional samples on this scale requires new types of microscopes with larger fields of view and working distance, as well as higher throughput. We present a new expansion-assisted selective plane illumination microscope (ExA-SPIM) with aberration-free 1×1×3 μm optical resolution over a large field of view (10.6×8.0 mm 2 ) and working distance (35 mm) at speeds up to 946 megavoxels/sec. Combined with new tissue clearing and expansion methods, the microscope allows imaging centimeter-scale samples with 250×250×750 nm optical resolution (4× expansion), including entire mouse brains, with high contrast and without sectioning. We illustrate ExA-SPIM by reconstructing individual neurons across the mouse brain, imaging cortico-spinal neurons in the macaque motor cortex, and visualizing axons in human white matter.
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9
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Li D, Shi T, Xiao Y, Wu C. Sensorless adaptive optics in the second near-infrared window for deep vascular imaging in vivo. OPTICS LETTERS 2024; 49:4002-4005. [PMID: 39008762 DOI: 10.1364/ol.528634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 06/22/2024] [Indexed: 07/17/2024]
Abstract
We have experimentally validated the use of sensorless adaptive optics (AO) to enhance laser scanning confocal microscopy in the second near-infrared (NIR II) spectral range, termed as AO-NIR II confocal microscopy. This approach harnesses a NIR II fluorophore, excited by an 808 nm wavelength and emitting beyond 1000 nm, to visualize intricate structures in deep brain tissues with the intact skull. By leveraging the reduced scattering and aberrations in the NIR II spectrum, we successfully captured a three-dimensional (3D) vascular structure map extending 310 µm beneath the skull. AO typically boosts the fluorescence signal by approximately 2-3 times, leading to a superior contrast and diminished smearing effects. Consequently, small blood vessels at various depths can be clearly visualized, which might otherwise remain undetectable without AO corrections.
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10
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Turishcheva P, Fahey PG, Vystrčilová M, Hansel L, Froebe R, Ponder K, Qiu Y, Willeke KF, Bashiri M, Baikulov R, Zhu Y, Ma L, Yu S, Huang T, Li BM, Wulf WD, Kudryashova N, Hennig MH, Rochefort NL, Onken A, Wang E, Ding Z, Tolias AS, Sinz FH, Ecker AS. Retrospective for the Dynamic Sensorium Competition for predicting large-scale mouse primary visual cortex activity from videos. ARXIV 2024:arXiv:2407.09100v1. [PMID: 39040641 PMCID: PMC11261979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Understanding how biological visual systems process information is challenging because of the nonlinear relationship between visual input and neuronal responses. Artificial neural networks allow computational neuroscientists to create predictive models that connect biological and machine vision. Machine learning has benefited tremendously from benchmarks that compare different model on the same task under standardized conditions. However, there was no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we established the SENSORIUM 2023 Benchmark Competition with dynamic input, featuring a new large-scale dataset from the primary visual cortex of ten mice. This dataset includes responses from 78,853 neurons to 2 hours of dynamic stimuli per neuron, together with the behavioral measurements such as running speed, pupil dilation, and eye movements. The competition ranked models in two tracks based on predictive performance for neuronal responses on a held-out test set: one focusing on predicting in-domain natural stimuli and another on out-of-distribution (OOD) stimuli to assess model generalization. As part of the NeurIPS 2023 competition track, we received more than 160 model submissions from 22 teams. Several new architectures for predictive models were proposed, and the winning teams improved the previous state-of-the-art model by 50%. Access to the dataset as well as the benchmarking infrastructure will remain online at www.sensorium-competition.net.
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Affiliation(s)
- Polina Turishcheva
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
| | - Paul G. Fahey
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, USA
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
| | - Michaela Vystrčilová
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
| | - Laura Hansel
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
| | - Rachel Froebe
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, USA
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
| | - Kayla Ponder
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, USA
| | - Yongrong Qiu
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
| | - Konstantin F. Willeke
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- International Max Planck Research School for Intelligent Systems, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, Tübingen University, Germany
| | - Mohammad Bashiri
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- International Max Planck Research School for Intelligent Systems, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, Tübingen University, Germany
| | | | - Yu Zhu
- Institute of Automation, Chinese Academy of Sciences, China
- Beijing Academy of Artificial Intelligence, China
| | - Lei Ma
- Beijing Academy of Artificial Intelligence, China
| | - Shan Yu
- Institute of Automation, Chinese Academy of Sciences, China
| | - Tiejun Huang
- Beijing Academy of Artificial Intelligence, China
| | - Bryan M. Li
- The Alan Turing Institute, UK
- School of Informatics, University of Edinburgh, UK
| | - Wolf De Wulf
- School of Informatics, University of Edinburgh, UK
| | | | | | - Nathalie L. Rochefort
- Centre for Discovery Brain Sciences, University of Edinburgh, UK
- Simons Initiative for the Developing Brain, University of Edinburgh, UK
| | - Arno Onken
- School of Informatics, University of Edinburgh, UK
| | - Eric Wang
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, USA
| | - Zhiwei Ding
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, USA
| | - Andreas S. Tolias
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, USA
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
- Department of Electrical Engineering, Stanford University, Stanford, CA, US
| | - Fabian H. Sinz
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, USA
- International Max Planck Research School for Intelligent Systems, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, Tübingen University, Germany
| | - Alexander S Ecker
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
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11
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Turishcheva P, Fahey PG, Vystrčilová M, Hansel L, Froebe R, Ponder K, Qiu Y, Willeke KF, Bashiri M, Wang E, Ding Z, Tolias AS, Sinz FH, Ecker AS. The Dynamic Sensorium competition for predicting large-scale mouse visual cortex activity from videos. ARXIV 2024:arXiv:2305.19654v2. [PMID: 37396602 PMCID: PMC10312815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Understanding how biological visual systems process information is challenging due to the complex nonlinear relationship between neuronal responses and high-dimensional visual input. Artificial neural networks have already improved our understanding of this system by allowing computational neuroscientists to create predictive models and bridge biological and machine vision. During the Sensorium 2022 competition, we introduced benchmarks for vision models with static input (i.e. images). However, animals operate and excel in dynamic environments, making it crucial to study and understand how the brain functions under these conditions. Moreover, many biological theories, such as predictive coding, suggest that previous input is crucial for current input processing. Currently, there is no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we propose the Sensorium 2023 Benchmark Competition with dynamic input (https://www.sensorium-competition.net/). This competition includes the collection of a new large-scale dataset from the primary visual cortex of ten mice, containing responses from over 78,000 neurons to over 2 hours of dynamic stimuli per neuron. Participants in the main benchmark track will compete to identify the best predictive models of neuronal responses for dynamic input (i.e. video). We will also host a bonus track in which submission performance will be evaluated on out-of-domain input, using withheld neuronal responses to dynamic input stimuli whose statistics differ from the training set. Both tracks will offer behavioral data along with video stimuli. As before, we will provide code, tutorials, and strong pre-trained baseline models to encourage participation. We hope this competition will continue to strengthen the accompanying Sensorium benchmarks collection as a standard tool to measure progress in large-scale neural system identification models of the entire mouse visual hierarchy and beyond.
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Affiliation(s)
- Polina Turishcheva
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
| | - Paul G Fahey
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
| | - Michaela Vystrčilová
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
| | - Laura Hansel
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
| | - Rachel Froebe
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
| | - Kayla Ponder
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
| | - Yongrong Qiu
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
| | - Konstantin F Willeke
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
- International Max Planck Research School for Intelligent Systems, University of Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Germany
| | - Mohammad Bashiri
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- International Max Planck Research School for Intelligent Systems, University of Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Germany
| | - Eric Wang
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
| | - Zhiwei Ding
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
| | - Andreas S Tolias
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
- Department of Electrical Engineering, Stanford University, Stanford, CA, US
| | - Fabian H Sinz
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- International Max Planck Research School for Intelligent Systems, University of Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Germany
| | - Alexander S Ecker
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
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12
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Yang R, Xiao T, Cheng Y, Li A, Qu J, Liang R, Bao S, Wang X, Wang J, Suo J, Luo Q, Dai Q. Sharing massive biomedical data at magnitudes lower bandwidth using implicit neural function. Proc Natl Acad Sci U S A 2024; 121:e2320870121. [PMID: 38959033 PMCID: PMC11252806 DOI: 10.1073/pnas.2320870121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 05/21/2024] [Indexed: 07/04/2024] Open
Abstract
Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging deep learning-based methods demand huge training data and are difficult to generalize. Here, we propose to conduct Biomedical data compRession with Implicit nEural Function (BRIEF) by representing the target data with compact neural networks, which are data specific and thus have no generalization issues. Benefiting from the strong representation capability of implicit neural function, BRIEF achieves 2[Formula: see text]3 orders of magnitude compression on diverse biomedical data at significantly higher fidelity than existing techniques. Besides, BRIEF is of consistent performance across the whole data volume, and supports customized spatially varying fidelity. BRIEF's multifold advantageous features also serve reliable downstream tasks at low bandwidth. Our approach will facilitate low-bandwidth data sharing and promote collaboration and progress in the biomedical field.
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Affiliation(s)
- Runzhao Yang
- Department of Automation, Tsinghua University, Beijing100084, China
- Institute of Brain and Cognitive Sciences, Tsinghua University, Beijing100084, China
- Shanghai Artificial Intelligence Laboratory, Shanghai200232, China
| | - Tingxiong Xiao
- Department of Automation, Tsinghua University, Beijing100084, China
| | - Yuxiao Cheng
- Department of Automation, Tsinghua University, Beijing100084, China
| | - Anan Li
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan430074, China
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou215123, China
| | - Jinyuan Qu
- Department of Automation, Tsinghua University, Beijing100084, China
| | - Rui Liang
- School of Biomedical Engineering, Hainan University, Haikou570228, China
| | - Shengda Bao
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan430074, China
| | - Xiaofeng Wang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan430074, China
| | - Jue Wang
- Department of Automation, Tsinghua University, Beijing100084, China
| | - Jinli Suo
- Department of Automation, Tsinghua University, Beijing100084, China
- Institute of Brain and Cognitive Sciences, Tsinghua University, Beijing100084, China
- Shanghai Artificial Intelligence Laboratory, Shanghai200232, China
| | - Qingming Luo
- School of Biomedical Engineering, Hainan University, Haikou570228, China
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing100084, China
- Institute of Brain and Cognitive Sciences, Tsinghua University, Beijing100084, China
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13
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Bennett C, Ouellette B, Ramirez TK, Cahoon A, Cabasco H, Browning Y, Lakunina A, Lynch GF, McBride EG, Belski H, Gillis R, Grasso C, Howard R, Johnson T, Loeffler H, Smith H, Sullivan D, Williford A, Caldejon S, Durand S, Gale S, Guthrie A, Ha V, Han W, Hardcastle B, Mochizuki C, Sridhar A, Suarez L, Swapp J, Wilkes J, Siegle JH, Farrell C, Groblewski PA, Olsen SR. SHIELD: Skull-shaped hemispheric implants enabling large-scale electrophysiology datasets in the mouse brain. Neuron 2024:S0896-6273(24)00450-1. [PMID: 38996587 DOI: 10.1016/j.neuron.2024.06.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 05/02/2024] [Accepted: 06/18/2024] [Indexed: 07/14/2024]
Abstract
To understand the neural basis of behavior, it is essential to measure spiking dynamics across many interacting brain regions. Although new technologies, such as Neuropixels probes, facilitate multi-regional recordings, significant surgical and procedural hurdles remain for these experiments to achieve their full potential. Here, we describe skull-shaped hemispheric implants enabling large-scale electrophysiology datasets (SHIELD). These 3D-printed skull-replacement implants feature customizable insertion holes, allowing dozens of cortical and subcortical structures to be recorded in a single mouse using repeated multi-probe insertions over many days. We demonstrate the procedure's high success rate, biocompatibility, lack of adverse effects on behavior, and compatibility with imaging and optogenetics. To showcase SHIELD's scientific utility, we use multi-probe recordings to reveal novel insights into how alpha rhythms organize spiking activity across visual and sensorimotor networks. Overall, this method enables powerful, large-scale electrophysiological experiments for the study of distributed neural computation.
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Affiliation(s)
- Corbett Bennett
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA.
| | - Ben Ouellette
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | - Hannah Cabasco
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Yoni Browning
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Anna Lakunina
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Galen F Lynch
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | - Hannah Belski
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Ryan Gillis
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Conor Grasso
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Robert Howard
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Tye Johnson
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Henry Loeffler
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Heston Smith
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | | | | | - Samuel Gale
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Alan Guthrie
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Vivian Ha
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Warren Han
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Ben Hardcastle
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | - Arjun Sridhar
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Lucas Suarez
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Jackie Swapp
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Joshua Wilkes
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | | | - Shawn R Olsen
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA.
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14
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Hira R. Closed-loop experiments and brain machine interfaces with multiphoton microscopy. NEUROPHOTONICS 2024; 11:033405. [PMID: 38375331 PMCID: PMC10876015 DOI: 10.1117/1.nph.11.3.033405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 01/22/2024] [Accepted: 01/29/2024] [Indexed: 02/21/2024]
Abstract
In the field of neuroscience, the importance of constructing closed-loop experimental systems has increased in conjunction with technological advances in measuring and controlling neural activity in live animals. We provide an overview of recent technological advances in the field, focusing on closed-loop experimental systems where multiphoton microscopy-the only method capable of recording and controlling targeted population activity of neurons at a single-cell resolution in vivo-works through real-time feedback. Specifically, we present some examples of brain machine interfaces (BMIs) using in vivo two-photon calcium imaging and discuss applications of two-photon optogenetic stimulation and adaptive optics to real-time BMIs. We also consider conditions for realizing future optical BMIs at the synaptic level, and their possible roles in understanding the computational principles of the brain.
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Affiliation(s)
- Riichiro Hira
- Tokyo Medical and Dental University, Graduate School of Medical and Dental Sciences, Department of Physiology and Cell Biology, Tokyo, Japan
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15
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Mizuta K, Sato M. Multiphoton imaging of hippocampal neural circuits: techniques and biological insights into region-, cell-type-, and pathway-specific functions. NEUROPHOTONICS 2024; 11:033406. [PMID: 38464393 PMCID: PMC10923542 DOI: 10.1117/1.nph.11.3.033406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 03/12/2024]
Abstract
Significance The function of the hippocampus in behavior and cognition has long been studied primarily through electrophysiological recordings from freely moving rodents. However, the application of optical recording methods, particularly multiphoton fluorescence microscopy, in the last decade or two has dramatically advanced our understanding of hippocampal function. This article provides a comprehensive overview of techniques and biological findings obtained from multiphoton imaging of hippocampal neural circuits. Aim This review aims to summarize and discuss the recent technical advances in multiphoton imaging of hippocampal neural circuits and the accumulated biological knowledge gained through this technology. Approach First, we provide a brief overview of various techniques of multiphoton imaging of the hippocampus and discuss its advantages, drawbacks, and associated key innovations and practices. Then, we review a large body of findings obtained through multiphoton imaging by region (CA1 and dentate gyrus), cell type (pyramidal neurons, inhibitory interneurons, and glial cells), and cellular compartment (dendrite and axon). Results Multiphoton imaging of the hippocampus is primarily performed under head-fixed conditions and can reveal detailed mechanisms of circuit operation owing to its high spatial resolution and specificity. As the hippocampus lies deep below the cortex, its imaging requires elaborate methods. These include imaging cannula implantation, microendoscopy, and the use of long-wavelength light sources. Although many studies have focused on the dorsal CA1 pyramidal cells, studies of other local and inter-areal circuitry elements have also helped provide a more comprehensive picture of the information processing performed by the hippocampal circuits. Imaging of circuit function in mouse models of Alzheimer's disease and other brain disorders such as autism spectrum disorder has also contributed greatly to our understanding of their pathophysiology. Conclusions Multiphoton imaging has revealed much regarding region-, cell-type-, and pathway-specific mechanisms in hippocampal function and dysfunction in health and disease. Future technological advances will allow further illustration of the operating principle of the hippocampal circuits via the large-scale, high-resolution, multimodal, and minimally invasive imaging.
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Affiliation(s)
- Kotaro Mizuta
- RIKEN BDR, Kobe, Japan
- New York University Abu Dhabi, Department of Biology, Abu Dhabi, United Arab Emirates
| | - Masaaki Sato
- Hokkaido University Graduate School of Medicine, Department of Neuropharmacology, Sapporo, Japan
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16
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Liu G, Ahn SW, Kang JW, Bhagavatula S, Matthew D, Martin S, Marlin C, So PTC, Tearney GJ, Jonas O. Two-site microendoscopic imaging probe for simultaneous three-dimensional imaging at two anatomic locations in tissues. OPTICS LETTERS 2024; 49:3312-3315. [PMID: 38875608 PMCID: PMC11298057 DOI: 10.1364/ol.525945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 05/16/2024] [Indexed: 06/16/2024]
Abstract
Systems that can image in three dimensions at cellular resolution and across different locations within an organism may enable insights into complex biological processes, such as immune responses, for which a single location measurement may be insufficient. In this Letter, we describe an in vivo two-site imaging probe (TIP) that can simultaneously image two anatomic sites with a maximum separation of a few centimeters. The TIP consists of two identical bendable graded index (GRIN) lenses and is demonstrated by a two-photon two-color fluorescence imaging system. Each GRIN lens has a field of view of 162 × 162 × 170 µm3, a nominal numerical aperture of 0.5, a magnification of 0.7, and working distances of 0.2 mm in air for both ends. A blind linear unmixing algorithm is applied to suppress bleedthrough between channels. We use this system to successfully demonstrate two-site two-photon two-color imaging of two biomedically relevant samples, i.e., (1) a mixture of two autofluorescent anti-cancer drugs and (2) a live hybrid tumor consisting of two spectrally distinct fluorescent cell lines.
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Affiliation(s)
- Guigen Liu
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Sebastian W. Ahn
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Jeon Woong Kang
- Laser Biomedical Research Center, G. R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Sharath Bhagavatula
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Destiny Matthew
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Samantha Martin
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Courtney Marlin
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Peter T. C. So
- Laser Biomedical Research Center, G. R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Guillermo J. Tearney
- Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA
| | - Oliver Jonas
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
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17
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Sakamoto M, Yokoyama T. Probing neuronal activity with genetically encoded calcium and voltage fluorescent indicators. Neurosci Res 2024:S0168-0102(24)00076-2. [PMID: 38885881 DOI: 10.1016/j.neures.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/09/2024] [Accepted: 06/08/2024] [Indexed: 06/20/2024]
Abstract
Monitoring neural activity in individual neurons is crucial for understanding neural circuits and brain functions. The emergence of optical imaging technologies has dramatically transformed the field of neuroscience, enabling detailed observation of large-scale neuronal populations with both cellular and subcellular resolution. This transformation will be further accelerated by the integration of these imaging technologies and advanced big data analysis. Genetically encoded fluorescent indicators to detect neural activity with high signal-to-noise ratios are pivotal in this advancement. In recent years, these indicators have undergone significant developments, greatly enhancing the understanding of neural dynamics and networks. This review highlights the recent progress in genetically encoded calcium and voltage indicators and discusses the future direction of imaging techniques with big data analysis that deepens our understanding of the complexities of the brain.
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Affiliation(s)
- Masayuki Sakamoto
- Graduate School of Biostudies, Kyoto University, 53 Shogoin Kawara-cho, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Tatsushi Yokoyama
- Graduate School of Biostudies, Kyoto University, 53 Shogoin Kawara-cho, Sakyo-ku, Kyoto 606-8507, Japan
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18
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Saxena R, McNaughton BL. Bridging Neuroscience and AI: Environmental Enrichment as a Model for Forward Knowledge Transfer. ARXIV 2024:arXiv:2405.07295v2. [PMID: 38947919 PMCID: PMC11213130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Continual learning (CL) refers to an agent's capability to learn from a continuous stream of data and transfer knowledge without forgetting old information. One crucial aspect of CL is forward transfer, i.e., improved and faster learning on a new task by leveraging information from prior knowledge. While this ability comes naturally to biological brains, it poses a significant challenge for artificial intelligence (AI). Here, we suggest that environmental enrichment (EE) can be used as a biological model for studying forward transfer, inspiring human-like AI development. EE refers to animal studies that enhance cognitive, social, motor, and sensory stimulation and is a model for what, in humans, is referred to as 'cognitive reserve'. Enriched animals show significant improvement in learning speed and performance on new tasks, typically exhibiting forward transfer. We explore anatomical, molecular, and neuronal changes post-EE and discuss how artificial neural networks (ANNs) can be used to predict neural computation changes after enriched experiences. Finally, we provide a synergistic way of combining neuroscience and AI research that paves the path toward developing AI capable of rapid and efficient new task learning.
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Affiliation(s)
- Rajat Saxena
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA 92697, USA
| | - Bruce L McNaughton
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA 92697, USA
- Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, T1K 3M4 Canada
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19
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Mohammadi FS, Shabani H, Zarei M. Fast and robust feature-based stitching algorithm for microscopic images. Sci Rep 2024; 14:13304. [PMID: 38858367 PMCID: PMC11164998 DOI: 10.1038/s41598-024-61970-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 05/13/2024] [Indexed: 06/12/2024] Open
Abstract
The limited field of view of high-resolution microscopic images hinders the study of biological samples in a single shot. Stitching of microscope images (tiles) captured by the whole-slide imaging (WSI) technique solves this problem. However, stitching is challenging due to the repetitive textures of tissues, the non-informative background part of the slide, and the large number of tiles that impact performance and computational time. To address these challenges, we proposed the Fast and Robust Microscopic Image Stitching (FRMIS) algorithm, which relies on pairwise and global alignment. The speeded up robust features (SURF) were extracted and matched within a small part of the overlapping region to compute the transformation and align two neighboring tiles. In cases where the transformation could not be computed due to an insufficient number of matched features, features were extracted from the entire overlapping region. This enhances the efficiency of the algorithm since most of the computational load is related to pairwise registration and reduces misalignment that may occur by matching duplicated features in tiles with repetitive textures. Then, global alignment was achieved by constructing a weighted graph where the weight of each edge is determined by the normalized inverse of the number of matched features between two tiles. FRMIS has been evaluated on experimental and synthetic datasets from different modalities with different numbers of tiles and overlaps, demonstrating faster stitching time compared to existing algorithms such as the Microscopy Image Stitching Tool (MIST) toolbox. FRMIS outperforms MIST by 481% for bright-field, 259% for phase-contrast, and 282% for fluorescence modalities, while also being robust to uneven illumination.
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Affiliation(s)
| | - Hasti Shabani
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran.
| | - Mojtaba Zarei
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
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20
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Choi YK, Feng L, Jeong WK, Kim J. Connecto-informatics at the mesoscale: current advances in image processing and analysis for mapping the brain connectivity. Brain Inform 2024; 11:15. [PMID: 38833195 DOI: 10.1186/s40708-024-00228-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 05/08/2024] [Indexed: 06/06/2024] Open
Abstract
Mapping neural connections within the brain has been a fundamental goal in neuroscience to understand better its functions and changes that follow aging and diseases. Developments in imaging technology, such as microscopy and labeling tools, have allowed researchers to visualize this connectivity through high-resolution brain-wide imaging. With this, image processing and analysis have become more crucial. However, despite the wealth of neural images generated, access to an integrated image processing and analysis pipeline to process these data is challenging due to scattered information on available tools and methods. To map the neural connections, registration to atlases and feature extraction through segmentation and signal detection are necessary. In this review, our goal is to provide an updated overview of recent advances in these image-processing methods, with a particular focus on fluorescent images of the mouse brain. Our goal is to outline a pathway toward an integrated image-processing pipeline tailored for connecto-informatics. An integrated workflow of these image processing will facilitate researchers' approach to mapping brain connectivity to better understand complex brain networks and their underlying brain functions. By highlighting the image-processing tools available for fluroscent imaging of the mouse brain, this review will contribute to a deeper grasp of connecto-informatics, paving the way for better comprehension of brain connectivity and its implications.
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Affiliation(s)
- Yoon Kyoung Choi
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, South Korea
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea
| | | | - Won-Ki Jeong
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea
| | - Jinhyun Kim
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, South Korea.
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea.
- KIST-SKKU Brain Research Center, SKKU Institute for Convergence, Sungkyunkwan University, Suwon, South Korea.
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21
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Xie H, Han X, Xiao G, Xu H, Zhang Y, Zhang G, Li Q, He J, Zhu D, Yu X, Dai Q. Multifocal fluorescence video-rate imaging of centimetre-wide arbitrarily shaped brain surfaces at micrometric resolution. Nat Biomed Eng 2024; 8:740-753. [PMID: 38057428 PMCID: PMC11250366 DOI: 10.1038/s41551-023-01155-6] [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: 10/14/2022] [Accepted: 10/26/2023] [Indexed: 12/08/2023]
Abstract
Fluorescence microscopy allows for the high-throughput imaging of cellular activity across brain areas in mammals. However, capturing rapid cellular dynamics across the curved cortical surface is challenging, owing to trade-offs in image resolution, speed, field of view and depth of field. Here we report a technique for wide-field fluorescence imaging that leverages selective illumination and the integration of focal areas at different depths via a spinning disc with varying thickness to enable video-rate imaging of previously reconstructed centimetre-scale arbitrarily shaped surfaces at micrometre-scale resolution and at a depth of field of millimetres. By implementing the technique in a microscope capable of acquiring images at 1.68 billion pixels per second and resolving 16.8 billion voxels per second, we recorded neural activities and the trajectories of neutrophils in real time on curved cortical surfaces in live mice. The technique can be integrated into many microscopes and macroscopes, in both reflective and fluorescence modes, for the study of multiscale cellular interactions on arbitrarily shaped surfaces.
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Affiliation(s)
- Hao Xie
- Department of Automation, Tsinghua University, Beijing, China.
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China.
| | - Xiaofei Han
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Guihua Xiao
- Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China
| | - Hanyun Xu
- Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yuanlong Zhang
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Guoxun Zhang
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Qingwei Li
- School of Medicine, Tsinghua University, Beijing, China
| | - Jing He
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Dan Zhu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, China
| | - Xinguang Yu
- Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing, China.
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China.
- Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China.
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.
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22
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Sarafraz H, Nöbauer T, Kim H, Soldevila F, Gigan S, Vaziri A. Speckle-enabled in vivo demixing of neural activity in the mouse brain. BIOMEDICAL OPTICS EXPRESS 2024; 15:3586-3608. [PMID: 38867774 PMCID: PMC11166431 DOI: 10.1364/boe.524521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/11/2024] [Accepted: 04/14/2024] [Indexed: 06/14/2024]
Abstract
Functional imaging of neuronal activity in awake animals, using a combination of fluorescent reporters of neuronal activity and various types of microscopy modalities, has become an indispensable tool in neuroscience. While various imaging modalities based on one-photon (1P) excitation and parallel (camera-based) acquisition have been successfully used for imaging more transparent samples, when imaging mammalian brain tissue, due to their scattering properties, two-photon (2P) microscopy systems are necessary. In 2P microscopy, the longer excitation wavelengths reduce the amount of scattering while the diffraction-limited 3D localization of excitation largely eliminates out-of-focus fluorescence. However, this comes at the cost of time-consuming serial scanning of the excitation spot and more complex and expensive instrumentation. Thus, functional 1P imaging modalities that can be used beyond the most transparent specimen are highly desirable. Here, we transform light scattering from an obstacle into a tool. We use speckles with their unique patterns and contrast, formed when fluorescence from individual neurons propagates through rodent cortical tissue, to encode neuronal activity. Spatiotemporal demixing of these patterns then enables functional recording of neuronal activity from a group of discriminable sources. For the first time, we provide an experimental, in vivo characterization of speckle generation, speckle imaging and speckle-assisted demixing of neuronal activity signals in the scattering mammalian brain tissue. We found that despite an initial fast speckle decorrelation, substantial correlation was maintained over minute-long timescales that contributed to our ability to demix temporal activity traces in the mouse brain in vivo. Informed by in vivo quantifications of speckle patterns from single and multiple neurons excited using 2P scanning excitation, we recorded and demixed activity from several sources excited using 1P oblique illumination. In our proof-of-principle experiments, we demonstrate in vivo speckle-assisted demixing of functional signals from groups of sources in a depth range of 220-320 µm in mouse cortex, limited by available speckle contrast. Our results serve as a basis for designing an in vivo functional speckle imaging modality and for maximizing the key resource in any such modality, the speckle contrast. We anticipate that our results will provide critical quantitative guidance to the community for designing techniques that overcome light scattering as a fundamental limitation in bioimaging.
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Affiliation(s)
- Hossein Sarafraz
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
| | - Tobias Nöbauer
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
| | - Fernando Soldevila
- Laboratoire Kastler Brossel, ENS–Université PSL, CNRS, Sorbonne Université, College de France, 24 Rue Lhomond, F-75005 Paris, France
| | - Sylvain Gigan
- Laboratoire Kastler Brossel, ENS–Université PSL, CNRS, Sorbonne Université, College de France, 24 Rue Lhomond, F-75005 Paris, France
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY, USA
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23
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Ching-Roa VD, Huang CZ, Giacomelli MG. Suppression of Subpixel Jitter in Resonant Scanning Systems With Phase-locked Sampling. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2159-2168. [PMID: 38265914 PMCID: PMC11147734 DOI: 10.1109/tmi.2024.3358191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
Resonant scanning is critical to high speed and in vivo imaging in many applications of laser scanning microscopy. However, resonant scanning suffers from well-known image artifacts due to scanner jitter, limiting adoption of high-speed imaging technologies. Here, we introduce a real-time, inexpensive and all electrical method to suppress jitter more than an order of magnitude below the diffraction limit that can be applied to most existing microscope systems with no software changes. By phase-locking imaging to the resonant scanner period, we demonstrate an 86% reduction in pixel jitter, a 15% improvement in point spread function with resonant scanning and show that this approach enables two widely used models of resonant scanners to achieve comparable accuracy to galvanometer scanners running two orders of magnitude slower. Finally, we demonstrate the versatility of this method by retrofitting a commercial two photon microscope and show that this approach enables significant quantitative and qualitative improvements in biological imaging.
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24
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Zhang Y, Yuan L, Zhu Q, Wu J, Nöbauer T, Zhang R, Xiao G, Wang M, Xie H, Guo Z, Dai Q, Vaziri A. A miniaturized mesoscope for the large-scale single-neuron-resolved imaging of neuronal activity in freely behaving mice. Nat Biomed Eng 2024; 8:754-774. [PMID: 38902522 DOI: 10.1038/s41551-024-01226-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/03/2024] [Indexed: 06/22/2024]
Abstract
Exploring the relationship between neuronal dynamics and ethologically relevant behaviour involves recording neuronal-population activity using technologies that are compatible with unrestricted animal behaviour. However, head-mounted microscopes that accommodate weight limits to allow for free animal behaviour typically compromise field of view, resolution or depth range, and are susceptible to movement-induced artefacts. Here we report a miniaturized head-mounted fluorescent mesoscope that we systematically optimized for calcium imaging at single-neuron resolution, for increased fields of view and depth of field, and for robustness against motion-generated artefacts. Weighing less than 2.5 g, the mesoscope enabled recordings of neuronal-population activity at up to 16 Hz, with 4 μm resolution over 300 μm depth-of-field across a field of view of 3.6 × 3.6 mm2 in the cortex of freely moving mice. We used the mesoscope to record large-scale neuronal-population activity in socially interacting mice during free exploration and during fear-conditioning experiments, and to investigate neurovascular coupling across multiple cortical regions.
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Affiliation(s)
- Yuanlong Zhang
- Department of Automation, Tsinghua University, Beijing, China
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
| | - Lekang Yuan
- Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China
| | - Qiyu Zhu
- School of Medicine, Tsinghua University, Beijing, China
- Tsinghua-Peking Joint Center for Life Sciences, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
| | - Jiamin Wu
- Department of Automation, Tsinghua University, Beijing, China
| | - Tobias Nöbauer
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
| | - Rujin Zhang
- Department of Anesthesiology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Guihua Xiao
- Department of Automation, Tsinghua University, Beijing, China
| | - Mingrui Wang
- Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China
| | - Hao Xie
- Department of Automation, Tsinghua University, Beijing, China
| | - Zengcai Guo
- School of Medicine, Tsinghua University, Beijing, China
- Tsinghua-Peking Joint Center for Life Sciences, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing, China.
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA.
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY, USA.
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25
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Vickers ED, McCormick DA. Pan-cortical 2-photon mesoscopic imaging and neurobehavioral alignment in awake, behaving mice. eLife 2024; 13:RP94167. [PMID: 38808733 PMCID: PMC11136495 DOI: 10.7554/elife.94167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/30/2024] Open
Abstract
The flow of neural activity across the neocortex during active sensory discrimination is constrained by task-specific cognitive demands, movements, and internal states. During behavior, the brain appears to sample from a broad repertoire of activation motifs. Understanding how these patterns of local and global activity are selected in relation to both spontaneous and task-dependent behavior requires in-depth study of densely sampled activity at single neuron resolution across large regions of cortex. In a significant advance toward this goal, we developed procedures to record mesoscale 2-photon Ca2+ imaging data from two novel in vivo preparations that, between them, allow for simultaneous access to nearly all 0f the mouse dorsal and lateral neocortex. As a proof of principle, we aligned neural activity with both behavioral primitives and high-level motifs to reveal the existence of large populations of neurons that coordinated their activity across cortical areas with spontaneous changes in movement and/or arousal. The methods we detail here facilitate the identification and exploration of widespread, spatially heterogeneous neural ensembles whose activity is related to diverse aspects of behavior.
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Affiliation(s)
- Evan D Vickers
- Institute of Neuroscience, University of OregonEugeneUnited States
| | - David A McCormick
- Institute of Neuroscience, University of OregonEugeneUnited States
- Department of Biology, University of OregonEugeneUnited States
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26
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Franke K, Cai C, Ponder K, Fu J, Sokoloski S, Berens P, Tolias AS. Asymmetric distribution of color-opponent response types across mouse visual cortex supports superior color vision in the sky. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.01.543054. [PMID: 37333280 PMCID: PMC10274736 DOI: 10.1101/2023.06.01.543054] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Color is an important visual feature that informs behavior, and the retinal basis for color vision has been studied across various vertebrate species. While many studies have investigated how color information is processed in visual brain areas of primate species, we have limited understanding of how it is organized beyond the retina in other species, including most dichromatic mammals. In this study, we systematically characterized how color is represented in the primary visual cortex (V1) of mice. Using large-scale neuronal recordings and a luminance and color noise stimulus, we found that more than a third of neurons in mouse V1 are color-opponent in their receptive field center, while the receptive field surround predominantly captures luminance contrast. Furthermore, we found that color-opponency is especially pronounced in posterior V1 that encodes the sky, matching the statistics of natural scenes experienced by mice. Using unsupervised clustering, we demonstrate that the asymmetry in color representations across cortex can be explained by an uneven distribution of green-On/UV-Off color-opponent response types that are represented in the upper visual field. Finally, a simple model with natural scene-inspired parametric stimuli shows that green-On/UV-Off color-opponent response types may enhance the detection of "predatory"-like dark UV-objects in noisy daylight scenes. The results from this study highlight the relevance of color processing in the mouse visual system and contribute to our understanding of how color information is organized in the visual hierarchy across species.
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Affiliation(s)
- Katrin Franke
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
| | - Chenchen Cai
- Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany
- Graduate Training Center of Neuroscience, International Max Planck Research School, University of Tübingen, Tübingen, Germany
| | - Kayla Ponder
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
| | - Jiakun Fu
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
| | - Sacha Sokoloski
- Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany
- Hertie Institute for AI in Brain Health, University of Tübingen, Tübingen, Germany
| | - Philipp Berens
- Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany
- Hertie Institute for AI in Brain Health, University of Tübingen, Tübingen, Germany
| | - Andreas S Tolias
- Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, US
- Stanford Bio-X, Stanford University, Stanford, CA, US
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, US
- Department of Neuroscience & Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, US
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27
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Rich PD, Thiberge SY, Scott BB, Guo C, Tervo DGR, Brody CD, Karpova AY, Daw ND, Tank DW. Magnetic voluntary head-fixation in transgenic rats enables lifespan imaging of hippocampal neurons. Nat Commun 2024; 15:4154. [PMID: 38755205 PMCID: PMC11099169 DOI: 10.1038/s41467-024-48505-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 05/01/2024] [Indexed: 05/18/2024] Open
Abstract
The precise neural mechanisms within the brain that contribute to the remarkable lifetime persistence of memory are not fully understood. Two-photon calcium imaging allows the activity of individual cells to be followed across long periods, but conventional approaches require head-fixation, which limits the type of behavior that can be studied. We present a magnetic voluntary head-fixation system that provides stable optical access to the brain during complex behavior. Compared to previous systems that used mechanical restraint, there are no moving parts and animals can engage and disengage entirely at will. This system is failsafe, easy for animals to use and reliable enough to allow long-term experiments to be routinely performed. Animals completed hundreds of trials per session of an odor discrimination task that required 2-4 s fixations. Together with a reflectance fluorescence collection scheme that increases two-photon signal and a transgenic Thy1-GCaMP6f rat line, we are able to reliably image the cellular activity in the hippocampus during behavior over long periods (median 6 months), allowing us track the same neurons over a large fraction of animals' lives (up to 19 months).
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Affiliation(s)
- P Dylan Rich
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
| | | | - Benjamin B Scott
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Caiying Guo
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - D Gowanlock R Tervo
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Howard Hughes Medical Institute, Princeton University, Princeton, NJ, USA
| | - Alla Y Karpova
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Nathaniel D Daw
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Psychology, 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.
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28
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Manley J, Lu S, Barber K, Demas J, Kim H, Meyer D, Traub FM, Vaziri A. Simultaneous, cortex-wide dynamics of up to 1 million neurons reveal unbounded scaling of dimensionality with neuron number. Neuron 2024; 112:1694-1709.e5. [PMID: 38452763 PMCID: PMC11098699 DOI: 10.1016/j.neuron.2024.02.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 05/18/2023] [Accepted: 02/14/2024] [Indexed: 03/09/2024]
Abstract
The brain's remarkable properties arise from the collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, can such low-dimensional representations truly explain the vast range of brain activity, and if not, what is the appropriate resolution and scale of recording to capture them? Imaging neural activity at cellular resolution and near-simultaneously across the mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number in populations up to 1 million neurons. Although half of the neural variance is contained within sixteen dimensions correlated with behavior, our discovered scaling of dimensionality corresponds to an ever-increasing number of neuronal ensembles without immediate behavioral or sensory correlates. The activity patterns underlying these higher dimensions are fine grained and cortex wide, highlighting that large-scale, cellular-resolution recording is required to uncover the full substrates of neuronal computations.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Sihao Lu
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Kevin Barber
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Jeffrey Demas
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - David Meyer
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Francisca Martínez Traub
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA.
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29
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Fu J, Shrinivasan S, Baroni L, Ding Z, Fahey PG, Pierzchlewicz P, Ponder K, Froebe R, Ntanavara L, Muhammad T, Willeke KF, Wang E, Ding Z, Tran DT, Papadopoulos S, Patel S, Reimer J, Ecker AS, Pitkow X, Antolik J, Sinz FH, Haefner RM, Tolias AS, Franke K. Pattern completion and disruption characterize contextual modulation in the visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.13.532473. [PMID: 36993321 PMCID: PMC10054952 DOI: 10.1101/2023.03.13.532473] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Vision is fundamentally context-dependent, with neuronal responses influenced not just by local features but also by surrounding contextual information. In the visual cortex, studies using simple grating stimuli indicate that congruent stimuli - where the center and surround share the same orientation - are more inhibitory than when orientations are orthogonal, potentially serving redundancy reduction and predictive coding. Understanding these center-surround interactions in relation to natural image statistics is challenging due to the high dimensionality of the stimulus space, yet crucial for deciphering the neuronal code of real-world sensory processing. Utilizing large-scale recordings from mouse V1, we trained convolutional neural networks (CNNs) to predict and synthesize surround patterns that either optimally suppressed or enhanced responses to center stimuli, confirmed by in vivo experiments. Contrary to the notion that congruent stimuli are suppressive, we found that surrounds that completed patterns based on natural image statistics were facilitatory, while disruptive surrounds were suppressive. Applying our CNN image synthesis method in macaque V1, we discovered that pattern completion within the near surround occurred more frequently with excitatory than with inhibitory surrounds, suggesting that our results in mice are conserved in macaques. Further, experiments and model analyses confirmed previous studies reporting the opposite effect with grating stimuli in both species. Using the MICrONS functional connectomics dataset, we observed that neurons with similar feature selectivity formed excitatory connections regardless of their receptive field overlap, aligning with the pattern completion phenomenon observed for excitatory surrounds. Finally, our empirical results emerged in a normative model of perception implementing Bayesian inference, where neuronal responses are modulated by prior knowledge of natural scene statistics. In summary, our findings identify a novel relationship between contextual information and natural scene statistics and provide evidence for a role of contextual modulation in hierarchical inference.
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30
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Wu Y, Xu Z, Liang S, Wang L, Wang M, Jia H, Chen X, Zhao Z, Liao X. NeuroSeg-III: efficient neuron segmentation in two-photon Ca 2+ imaging data using self-supervised learning. BIOMEDICAL OPTICS EXPRESS 2024; 15:2910-2925. [PMID: 38855703 PMCID: PMC11161377 DOI: 10.1364/boe.521478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 03/28/2024] [Accepted: 03/30/2024] [Indexed: 06/11/2024]
Abstract
Two-photon Ca2+ imaging technology increasingly plays an essential role in neuroscience research. However, the requirement for extensive professional annotation poses a significant challenge to improving the performance of neuron segmentation models. Here, we present NeuroSeg-III, an innovative self-supervised learning approach specifically designed to achieve fast and precise segmentation of neurons in imaging data. This approach consists of two modules: a self-supervised pre-training network and a segmentation network. After pre-training the encoder of the segmentation network via a self-supervised learning method without any annotated data, we only need to fine-tune the segmentation network with a small amount of annotated data. The segmentation network is designed with YOLOv8s, FasterNet, efficient multi-scale attention mechanism (EMA), and bi-directional feature pyramid network (BiFPN), which enhanced the model's segmentation accuracy while reducing the computational cost and parameters. The generalization of our approach was validated across different Ca2+ indicators and scales of imaging data. Significantly, the proposed neuron segmentation approach exhibits exceptional speed and accuracy, surpassing the current state-of-the-art benchmarks when evaluated using a publicly available dataset. The results underscore the effectiveness of NeuroSeg-III, with employing an efficient training strategy tailored for two-photon Ca2+ imaging data and delivering remarkable precision in neuron segmentation.
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Affiliation(s)
- Yukun Wu
- Guangxi Key Laboratory of Special Biomedicine and Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning 530004, China
| | - Zhehao Xu
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing 400030, China
| | - Shanshan Liang
- Brain Research Center, State Key Laboratory of Trauma and Chemical Poisoning, Third Military Medical University, Chongqing 400038, China
| | - Lukang Wang
- Brain Research Center, State Key Laboratory of Trauma and Chemical Poisoning, Third Military Medical University, Chongqing 400038, China
| | - Meng Wang
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing 400030, China
| | - Hongbo Jia
- Guangxi Key Laboratory of Special Biomedicine and Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning 530004, China
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, Jiangsu, China
| | - Xiaowei Chen
- Guangxi Key Laboratory of Special Biomedicine and Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning 530004, China
- Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China
| | - Zhikai Zhao
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing 400030, China
| | - Xiang Liao
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing 400030, China
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31
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Ocklenburg S, Guo ZV. Cross-hemispheric communication: Insights on lateralized brain functions. Neuron 2024; 112:1222-1234. [PMID: 38458199 DOI: 10.1016/j.neuron.2024.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 12/13/2023] [Accepted: 02/12/2024] [Indexed: 03/10/2024]
Abstract
On the surface, the two hemispheres of vertebrate brains look almost perfectly symmetrical, but several motor, sensory, and cognitive systems show a deeply lateralized organization. Importantly, the two hemispheres are connected by various commissures, white matter tracts that cross the brain's midline and enable cross-hemispheric communication. Cross-hemispheric communication has been suggested to play an important role in the emergence of lateralized brain functions. Here, we review current advances in understanding cross-hemispheric communication that have been made using modern neuroscientific tools in rodents and other model species, such as genetic labeling, large-scale recordings of neuronal activity, spatiotemporally precise perturbation, and quantitative behavior analyses. These findings suggest that the emergence of lateralized brain functions cannot be fully explained by largely static factors such as genetic variation and differences in structural brain asymmetries. In addition, learning-dependent asymmetric interactions between the left and right hemispheres shape lateralized brain functions.
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Affiliation(s)
- Sebastian Ocklenburg
- Department of Psychology, MSH Medical School Hamburg, Hamburg, Germany; ICAN Institute for Cognitive and Affective Neuroscience, MSH Medical School Hamburg, Hamburg, Germany; Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany.
| | - Zengcai V Guo
- School of Medicine, Tsinghua University, Beijing 100084, China; Tsinghua-Peking Joint Center for Life Sciences, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China.
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32
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Mok AT, Wang T, Zhao S, Kolkman KE, Wu D, Ouzounov DG, Seo C, Wu C, Fetcho JR, Xu C. A Large Field-of-view, Single-cell-resolution Two- and Three-Photon Microscope for Deep Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.14.566970. [PMID: 38014101 PMCID: PMC10680773 DOI: 10.1101/2023.11.14.566970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
In vivo imaging of large-scale neuron activity plays a pivotal role in unraveling the function of the brain's network. Multiphoton microscopy, a powerful tool for deep-tissue imaging, has received sustained interest in advancing its speed, field of view and imaging depth. However, to avoid thermal damage in scattering biological tissue, field of view decreases exponentially as imaging depth increases. We present a suite of innovations to overcome constraints on the field of view in three-photon microscopy and to perform deep imaging that is inaccessible to two-photon microscopy. These innovations enable us to image neuronal activities in a ~3.5-mm diameter field-of-view at 4 Hz with single-cell resolution and in the deepest cortical layer of mouse brains. We further demonstrate simultaneous large field-of-view two-photon and three-photon imaging, subcortical imaging in the mouse brain, and whole-brain imaging in adult zebrafish. The demonstrated techniques can be integrated into any multiphoton microscope for large-field-of-view and system-level neural circuit research.
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Affiliation(s)
- Aaron T. Mok
- School of Applied Engineering Physics, Cornell University, NY, USA
- Meining School of Biomedical Engineering, Cornell University, NY, USA
| | - Tianyu Wang
- School of Applied Engineering Physics, Cornell University, NY, USA
| | - Shitong Zhao
- School of Applied Engineering Physics, Cornell University, NY, USA
| | | | - Danni Wu
- Department of Population Health, New York University, NY, USA
| | | | - Changwoo Seo
- Department of Neurobiology and Behavior, Cornell University, NY, USA
| | - Chunyan Wu
- College of Veterinary Medicine, Cornell University, NY, USA
| | - Joseph R. Fetcho
- Department of Neurobiology and Behavior, Cornell University, NY, USA
| | - Chris Xu
- School of Applied Engineering Physics, Cornell University, NY, USA
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33
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Latifi S, Carmichael ST. The emergence of multiscale connectomics-based approaches in stroke recovery. Trends Neurosci 2024; 47:303-318. [PMID: 38402008 DOI: 10.1016/j.tins.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/31/2023] [Accepted: 01/21/2024] [Indexed: 02/26/2024]
Abstract
Stroke is a leading cause of adult disability. Understanding stroke damage and recovery requires deciphering changes in complex brain networks across different spatiotemporal scales. While recent developments in brain readout technologies and progress in complex network modeling have revolutionized current understanding of the effects of stroke on brain networks at a macroscale, reorganization of smaller scale brain networks remains incompletely understood. In this review, we use a conceptual framework of graph theory to define brain networks from nano- to macroscales. Highlighting stroke-related brain connectivity studies at multiple scales, we argue that multiscale connectomics-based approaches may provide new routes to better evaluate brain structural and functional remapping after stroke and during recovery.
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Affiliation(s)
- Shahrzad Latifi
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA; Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA
| | - S Thomas Carmichael
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA.
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Seiler JL, Zhuang X, Nelson AB, Lerner TN. Dopamine across timescales and cell types: Relevance for phenotypes in Parkinson's disease progression. Exp Neurol 2024; 374:114693. [PMID: 38242300 DOI: 10.1016/j.expneurol.2024.114693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 01/21/2024]
Abstract
Dopamine neurons in the substantia nigra pars compacta (SNc) synthesize and release dopamine, a critical neurotransmitter for movement and learning. SNc dopamine neurons degenerate in Parkinson's Disease (PD), causing a host of motor and non-motor symptoms. Here, we review recent conceptual advances in our basic understanding of the dopamine system - including our rapidly advancing knowledge of dopamine neuron heterogeneity - with special attention to their importance for understanding PD. In PD patients, dopamine neuron degeneration progresses from lateral SNc to medial SNc, suggesting clinically relevant heterogeneity in dopamine neurons. With technical advances in dopamine system interrogation, we can understand the relevance of this heterogeneity for PD progression and harness it to develop new treatments.
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Affiliation(s)
- Jillian L Seiler
- Department of Neuroscience, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Xiaowen Zhuang
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Weill Institute for Neuroscience, University of California San Francisco, San Francisco, CA, USA; Kavli Institute for Fundamental Neuroscience, University of California San Francisco, San Francisco, CA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Alexandra B Nelson
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Neuroscience Graduate Program, University of California San Francisco, San Francisco, CA, USA; Weill Institute for Neuroscience, University of California San Francisco, San Francisco, CA, USA; Kavli Institute for Fundamental Neuroscience, University of California San Francisco, San Francisco, CA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
| | - Talia N Lerner
- Department of Neuroscience, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Northwestern University Interdepartmental Neuroscience Program (NUIN), Evanston, IL, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
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35
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Akbari N, Tatarsky RL, Kolkman KE, Fetcho JR, Xu C, Bass AH. Label-free, whole-brain in vivo mapping in an adult vertebrate with third harmonic generation microscopy. J Comp Neurol 2024; 532:e25614. [PMID: 38616537 PMCID: PMC11069316 DOI: 10.1002/cne.25614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 02/16/2024] [Accepted: 03/24/2024] [Indexed: 04/16/2024]
Abstract
Comprehensive understanding of interconnected networks within the brain requires access to high resolution information within large field of views and over time. Currently, methods that enable mapping structural changes of the entire brain in vivo are extremely limited. Third harmonic generation (THG) can resolve myelinated structures, blood vessels, and cell bodies throughout the brain without the need for any exogenous labeling. Together with deep penetration of long wavelengths, this enables in vivo brain-mapping of large fractions of the brain in small animals and over time. Here, we demonstrate that THG microscopy allows non-invasive label-free mapping of the entire brain of an adult vertebrate, Danionella dracula, which is a miniature species of cyprinid fish. We show this capability in multiple brain regions and in particular the identification of major commissural fiber bundles in the midbrain and the hindbrain. These features provide readily discernable landmarks for navigation and identification of regional-specific neuronal groups and even single neurons during in vivo experiments. We further show how this label-free technique can easily be coupled with fluorescence microscopy and used as a comparative tool for studies of other species with similar body features to Danionella, such as zebrafish (Danio rerio) and tetras (Trochilocharax ornatus). This new evidence, building on previous studies, demonstrates how small size and relative transparency, combined with the unique capabilities of THG microscopy, can enable label-free access to the entire adult vertebrate brain.
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Affiliation(s)
- Najva Akbari
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY USA 14850
- Present address: Department of Biology, Stanford University, Stanford, CA USA 94305
| | - Rose L. Tatarsky
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY USA 14850
| | - Kristine E. Kolkman
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY USA 14850
| | - Joseph R. Fetcho
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY USA 14850
| | - Chris Xu
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY USA 14850
| | - Andrew H. Bass
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY USA 14850
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Xia F, Rimoli CV, Akemann W, Ventalon C, Bourdieu L, Gigan S, de Aguiar HB. Neurophotonics beyond the Surface: Unmasking the Brain's Complexity Exploiting Optical Scattering. ARXIV 2024:arXiv:2403.14809v1. [PMID: 38562443 PMCID: PMC10984001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The intricate nature of the brain necessitates the application of advanced probing techniques to comprehensively study and understand its working mechanisms. Neurophotonics offers minimally invasive methods to probe the brain using optics at cellular and even molecular levels. However, multiple challenges persist, especially concerning imaging depth, field of view, speed, and biocompatibility. A major hindrance to solving these challenges in optics is the scattering nature of the brain. This perspective highlights the potential of complex media optics, a specialized area of study focused on light propagation in materials with intricate heterogeneous optical properties, in advancing and improving neuronal readouts for structural imaging and optical recordings of neuronal activity. Key strategies include wavefront shaping techniques and computational imaging and sensing techniques that exploit scattering properties for enhanced performance. We discuss the potential merger of the two fields as well as potential challenges and perspectives toward longer term in vivo applications.
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Affiliation(s)
- Fei Xia
- Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Sorbonne Université, Collège de France, 24 rue Lhomond, 75005 Paris, France
| | - Caio Vaz Rimoli
- Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Sorbonne Université, Collège de France, 24 rue Lhomond, 75005 Paris, France
- Institut de Biologie de l'ENS (IBENS), École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Walther Akemann
- Institut de Biologie de l'ENS (IBENS), École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Cathie Ventalon
- Institut de Biologie de l'ENS (IBENS), École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Laurent Bourdieu
- Institut de Biologie de l'ENS (IBENS), École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Sylvain Gigan
- Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Sorbonne Université, Collège de France, 24 rue Lhomond, 75005 Paris, France
| | - Hilton B de Aguiar
- Laboratoire Kastler Brossel, ENS-Université PSL, CNRS, Sorbonne Université, Collège de France, 24 rue Lhomond, 75005 Paris, France
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Vu MAT, Brown EH, Wen MJ, Noggle CA, Zhang Z, Monk KJ, Bouabid S, Mroz L, Graham BM, Zhuo Y, Li Y, Otchy TM, Tian L, Davison IG, Boas DA, Howe MW. Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior. Neuron 2024; 112:909-923.e9. [PMID: 38242115 PMCID: PMC10957316 DOI: 10.1016/j.neuron.2023.12.011] [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: 07/21/2023] [Revised: 11/11/2023] [Accepted: 12/15/2023] [Indexed: 01/21/2024]
Abstract
Neural population dynamics relevant to behavior vary over multiple spatial and temporal scales across three-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice, enabling the investigation of cell-type- and neurotransmitter-specific signals over arbitrary 3D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum, revealing distinct, modality-specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and the spatial localization of behavioral function across large circuits.
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Affiliation(s)
- Mai-Anh T Vu
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Eleanor H Brown
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
| | - Michelle J Wen
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Howard Hughes Medical Institute, Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Christian A Noggle
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Zicheng Zhang
- Department of Biology, Boston University, Boston, MA, USA
| | - Kevin J Monk
- Department of Biology, Boston University, Boston, MA, USA
| | - Safa Bouabid
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Lydia Mroz
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Northeastern University, Boston, MA, USA
| | - Benjamin M Graham
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
| | - Yizhou Zhuo
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China; PKU-IDG/McGovern Institute for Brain Research, Beijing, China; Peking-Tsinghua Center for Life Sciences, Beijing, China
| | - Yulong Li
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA; State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China; PKU-IDG/McGovern Institute for Brain Research, Beijing, China; Peking-Tsinghua Center for Life Sciences, Beijing, China
| | | | - Lin Tian
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA; Max Planck Florida Institute of Neuroscience, Jupiter, FL, USA
| | - Ian G Davison
- Department of Biology, Boston University, Boston, MA, USA
| | - David A Boas
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Mark W Howe
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
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Takahashi T, Zhang H, Agetsuma M, Nabekura J, Otomo K, Okamura Y, Nemoto T. Large-scale cranial window for in vivo mouse brain imaging utilizing fluoropolymer nanosheet and light-curable resin. Commun Biol 2024; 7:232. [PMID: 38438546 PMCID: PMC10912766 DOI: 10.1038/s42003-024-05865-8] [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: 03/19/2023] [Accepted: 01/26/2024] [Indexed: 03/06/2024] Open
Abstract
Two-photon microscopy enables in vivo imaging of neuronal activity in mammalian brains at high resolution. However, two-photon imaging tools for stable, long-term, and simultaneous study of multiple brain regions in same mice are lacking. Here, we propose a method to create large cranial windows covering such as the whole parietal cortex and cerebellum in mice using fluoropolymer nanosheets covered with light-curable resin (termed the 'Nanosheet Incorporated into light-curable REsin' or NIRE method). NIRE method can produce cranial windows conforming the curved cortical and cerebellar surfaces, without motion artifacts in awake mice, and maintain transparency for >5 months. In addition, we demonstrate that NIRE method can be used for in vivo two-photon imaging of neuronal ensembles, individual neurons and subcellular structures such as dendritic spines. The NIRE method can facilitate in vivo large-scale analysis of heretofore inaccessible neural processes, such as the neuroplastic changes associated with maturation, learning and neural pathogenesis.
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Affiliation(s)
- Taiga Takahashi
- Division of Biophotonics, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan
- Biophotonics Research Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan
- School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan
- Department of Medical and Robotic Engineering Design, Faculty of Advanced Engineering, Tokyo University of Science, 6-3-1 Niijuku, Katsushika, Tokyo, 125-8585, Japan
| | - Hong Zhang
- Micro/Nano Technology Center, Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan
- School of Chemical Engineering and Technology, Tianjin University, 135 Yaguan Road, Jinnan District, Tianjin, 300350, China
| | - Masakazu Agetsuma
- Division of Homeostatic Development, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, 444-8585, Japan
- Quantum Regenerative and Biomedical Engineering Team, Institute for Quantum Life Science, National Institutes for Quantum Science and Technology (QST), Anagawa 4-9-1, Chiba Inage-ku, Chiba, 263-8555, Japan
| | - Junichi Nabekura
- School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan
- Division of Homeostatic Development, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, 444-8585, Japan
| | - Kohei Otomo
- Division of Biophotonics, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan
- Biophotonics Research Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan
- School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan
- Department of Biochemistry and Systems Biomedicine, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Yosuke Okamura
- Micro/Nano Technology Center, Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan
- Department of Applied Chemistry, School of Engineering, Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan
- Course of Applied Science, Graduate School of Engineering, Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan
| | - Tomomi Nemoto
- Division of Biophotonics, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan.
- Biophotonics Research Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan.
- School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Higashiyama 5-1, Myodaiji, Okazaki, Aichi, 444-8787, Japan.
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Vickers ED, McCormick DA. Pan-cortical 2-photon mesoscopic imaging and neurobehavioral alignment in awake, behaving mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.19.563159. [PMID: 37961229 PMCID: PMC10634705 DOI: 10.1101/2023.10.19.563159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The flow of neural activity across the neocortex during active sensory discrimination is constrained by task-specific cognitive demands, movements, and internal states. During behavior, the brain appears to sample from a broad repertoire of activation motifs. Understanding how these patterns of local and global activity are selected in relation to both spontaneous and task-dependent behavior requires in-depth study of densely sampled activity at single neuron resolution across large regions of cortex. In a significant advance toward this goal, we developed procedures to record mesoscale 2-photon Ca2+ imaging data from two novel in vivo preparations that, between them, allow simultaneous access to nearly all of the mouse dorsal and lateral neocortex. As a proof of principle, we aligned neural activity with both behavioral primitives and high-level motifs to reveal the existence of large populations of neurons that coordinated their activity across cortical areas with spontaneous changes in movement and/or arousal. The methods we detail here facilitate the identification and exploration of widespread, spatially heterogeneous neural ensembles whose activity is related to diverse aspects of behavior.
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Affiliation(s)
- Evan D Vickers
- Institute of Neuroscience, University of Oregon, Eugene, OR
| | - David A McCormick
- Institute of Neuroscience, University of Oregon, Eugene, OR
- Department of Biology
- Institute of Neuroscience
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40
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Manley J, Demas J, Kim H, Traub FM, Vaziri A. Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.15.575721. [PMID: 38293036 PMCID: PMC10827059 DOI: 10.1101/2024.01.15.575721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Jeffrey Demas
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Francisca Martínez Traub
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
- Lead Contact
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41
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Bogatova D, Smirnakis SM, Palagina G. Tug-of-Peace: Visual Rivalry and Atypical Visual Motion Processing in MECP2 Duplication Syndrome of Autism. eNeuro 2024; 11:ENEURO.0102-23.2023. [PMID: 37940561 PMCID: PMC10792601 DOI: 10.1523/eneuro.0102-23.2023] [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: 03/23/2023] [Revised: 06/25/2023] [Accepted: 08/12/2023] [Indexed: 11/10/2023] Open
Abstract
Extracting common patterns of neural circuit computations in the autism spectrum and confirming them as a cause of specific core traits of autism is the first step toward identifying cell-level and circuit-level targets for effective clinical intervention. Studies in humans with autism have identified functional links and common anatomic substrates between core restricted behavioral repertoire, cognitive rigidity, and overstability of visual percepts during visual rivalry. To study these processes with single-cell precision and comprehensive neuronal population coverage, we developed the visual bistable perception paradigm for mice based on ambiguous moving plaid patterns consisting of two transparent gratings drifting at an angle of 120°. This results in spontaneous reversals of the perception between local component motion (plaid perceived as two separate moving grating components) and integrated global pattern motion (plaid perceived as a fused moving texture). This robust paradigm does not depend on the explicit report of the mouse, since the direction of the optokinetic nystagmus (OKN) is used to infer the dominant percept. Using this paradigm, we found that the rate of perceptual reversals between global and local motion interpretations is reduced in the methyl-CpG-binding protein 2 duplication syndrome (MECP2-ds) mouse model of autism. Moreover, the stability of local motion percepts is greatly increased in MECP2-ds mice at the expense of global motion percepts. Thus, our model reproduces a subclass of the core features in human autism (reduced rate of visual rivalry and atypical perception of visual motion). This further offers a well-controlled approach for dissecting neuronal circuits underlying these core features.
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Affiliation(s)
- Daria Bogatova
- Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115
- Department of Biology, Boston University, Boston, MA 02115
- Harvard Medical School, Boston, MA 02115
| | - Stelios M Smirnakis
- Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115
- Harvard Medical School, Boston, MA 02115
- Jamaica Plain Veterans Affairs Hospital, Boston, MA 02130
| | - Ganna Palagina
- Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115
- Harvard Medical School, Boston, MA 02115
- Jamaica Plain Veterans Affairs Hospital, Boston, MA 02130
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42
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Syeda A, Zhong L, Tung R, Long W, Pachitariu M, Stringer C. Facemap: a framework for modeling neural activity based on orofacial tracking. Nat Neurosci 2024; 27:187-195. [PMID: 37985801 PMCID: PMC10774130 DOI: 10.1038/s41593-023-01490-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 10/10/2023] [Indexed: 11/22/2023]
Abstract
Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relate them to neural activity. Here we developed Facemap, a framework consisting of a keypoint tracker and a deep neural network encoder for predicting neural activity. Our algorithm for tracking mouse orofacial behaviors was more accurate than existing pose estimation tools, while the processing speed was several times faster, making it a powerful tool for real-time experimental interventions. The Facemap tracker was easy to adapt to data from new labs, requiring as few as 10 annotated frames for near-optimal performance. We used the keypoints as inputs to a deep neural network which predicts the activity of ~50,000 simultaneously-recorded neurons and, in visual cortex, we doubled the amount of explained variance compared to previous methods. Using this model, we found that the neuronal activity clusters that were well predicted from behavior were more spatially spread out across cortex. We also found that the deep behavioral features from the model had stereotypical, sequential dynamics that were not reversible in time. In summary, Facemap provides a stepping stone toward understanding the function of the brain-wide neural signals and their relation to behavior.
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Affiliation(s)
- Atika Syeda
- HHMI Janelia Research Campus, Ashburn, VA, USA.
| | - Lin Zhong
- HHMI Janelia Research Campus, Ashburn, VA, USA
| | - Renee Tung
- HHMI Janelia Research Campus, Ashburn, VA, USA
| | - Will Long
- HHMI Janelia Research Campus, Ashburn, VA, USA
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Jose A, Cheung PY, Laouby Z, Vanholsbeeck F, Cheyne JE. Low-cost reversible tandem lens mesoscope for brain imaging in rodents. NEUROPHOTONICS 2024; 11:014306. [PMID: 38464865 PMCID: PMC10924044 DOI: 10.1117/1.nph.11.1.014306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 02/07/2024] [Accepted: 02/09/2024] [Indexed: 03/12/2024]
Abstract
Significance The development of imaging systems that are cost-efficient and modular is essential for modern neuroscience research. Aim In the current study, we designed, developed, and characterized a low-cost reversible tandem lens mesoscope for brain imaging in rodents. Approach Using readily available components, we assembled a robust imaging system that is highly efficient and cost-effective. We developed a mesoscope that offers high-resolution structural and functional imaging with cost-effective lenses and CMOS camera. Results The reversible tandem lens configuration of the mesoscope offers two fields of view (FOVs), which can be achieved by swapping the objective and imaging lenses. The large FOV configuration of 12.6 × 10.5 mm provides a spatial resolution up to 4.92 μ m , and the small FOV configuration of 6 × 5 mm provides a resolution of up to 2.46 μ m . We demonstrate the efficiency of our system for imaging neuronal calcium activity in both rat and mouse brains in vivo. Conclusions The careful selection of the mesoscope components ensured its compactness, portability, and versatility, meaning that different types of samples and sample holders can be easily accommodated, enabling a range of different experiments both in vivo and in vitro. The custom-built reversible FOV mesoscope is cost-effective and was developed for under US$10,000 with excellent performance.
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Affiliation(s)
- Ashly Jose
- University of Auckland, Department of Physics, Auckland, New Zealand
- Dodd-Walls Centre for Photonic and Quantum Technologies (DWC), Dunedin, New Zealand
| | - Pang Ying Cheung
- Dodd-Walls Centre for Photonic and Quantum Technologies (DWC), Dunedin, New Zealand
- University of Auckland, Department of Physiology, Auckland, New Zealand
| | - Zahra Laouby
- Dodd-Walls Centre for Photonic and Quantum Technologies (DWC), Dunedin, New Zealand
- University of Auckland, Department of Physiology, Auckland, New Zealand
| | - Frédérique Vanholsbeeck
- University of Auckland, Department of Physics, Auckland, New Zealand
- Dodd-Walls Centre for Photonic and Quantum Technologies (DWC), Dunedin, New Zealand
| | - Juliette E. Cheyne
- Dodd-Walls Centre for Photonic and Quantum Technologies (DWC), Dunedin, New Zealand
- University of Auckland, Department of Physiology, Auckland, New Zealand
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44
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Pinke D, Issa JB, Dara GA, Dobos G, Dombeck DA. Full field-of-view virtual reality goggles for mice. Neuron 2023; 111:3941-3952.e6. [PMID: 38070501 PMCID: PMC10841834 DOI: 10.1016/j.neuron.2023.11.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 10/03/2023] [Accepted: 11/15/2023] [Indexed: 12/23/2023]
Abstract
Visual virtual reality (VR) systems for head-fixed mice offer advantages over real-world studies for investigating the neural circuitry underlying behavior. However, current VR approaches do not fully cover the visual field of view of mice, do not stereoscopically illuminate the binocular zone, and leave the lab frame visible. To overcome these limitations, we developed iMRSIV (Miniature Rodent Stereo Illumination VR)-VR goggles for mice. Our system is compact, separately illuminates each eye for stereo vision, and provides each eye with an ∼180° field of view, thus excluding the lab frame while accommodating saccades. Mice using iMRSIV while navigating engaged in virtual behaviors more quickly than in a current monitor-based system and displayed freezing and fleeing reactions to overhead looming stimulation. Using iMRSIV with two-photon functional imaging, we found large populations of hippocampal place cells during virtual navigation, global remapping during environment changes, and unique responses of place cell ensembles to overhead looming stimulation.
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Affiliation(s)
- Domonkos Pinke
- Department of Neurobiology, Northwestern University, Evanston, IL 60208, USA
| | - John B Issa
- Department of Neurobiology, Northwestern University, Evanston, IL 60208, USA
| | - Gabriel A Dara
- Department of Neurobiology, Northwestern University, Evanston, IL 60208, USA
| | - Gergely Dobos
- 360world Ltd, Sümegvár köz 9, 1118 Budapest, Hungary
| | - Daniel A Dombeck
- Department of Neurobiology, Northwestern University, Evanston, IL 60208, USA.
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45
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Hoffmann M, Henninger J, Veith J, Richter L, Judkewitz B. Blazed oblique plane microscopy reveals scale-invariant inference of brain-wide population activity. Nat Commun 2023; 14:8019. [PMID: 38049412 PMCID: PMC10695970 DOI: 10.1038/s41467-023-43741-x] [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: 05/05/2023] [Accepted: 11/17/2023] [Indexed: 12/06/2023] Open
Abstract
Due to the size and opacity of vertebrate brains, it has until now been impossible to simultaneously record neuronal activity at cellular resolution across the entire adult brain. As a result, scientists are forced to choose between cellular-resolution microscopy over limited fields-of-view or whole-brain imaging at coarse-grained resolution. Bridging the gap between these spatial scales of understanding remains a major challenge in neuroscience. Here, we introduce blazed oblique plane microscopy to perform brain-wide recording of neuronal activity at cellular resolution in an adult vertebrate. Contrary to common belief, we find that inferences of neuronal population activity are near-independent of spatial scale: a set of randomly sampled neurons has a comparable predictive power as the same number of coarse-grained macrovoxels. Our work thus links cellular resolution with brain-wide scope, challenges the prevailing view that macroscale methods are generally inferior to microscale techniques and underscores the value of multiscale approaches to studying brain-wide activity.
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Affiliation(s)
- Maximilian Hoffmann
- Einstein Center for Neurosciences, NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Rockefeller University, New York, USA
| | - Jörg Henninger
- Einstein Center for Neurosciences, NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Johannes Veith
- Einstein Center for Neurosciences, NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Biology, Humboldt University Berlin, Berlin, Germany
| | - Lars Richter
- Department of Chemistry and Center for NanoScience, Ludwig Maximilians University, Munich, Germany
| | - Benjamin Judkewitz
- Einstein Center for Neurosciences, NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, Berlin, Germany.
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46
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Vu MAT, Brown EH, Wen MJ, Noggle CA, Zhang Z, Monk KJ, Bouabid S, Mroz L, Graham BM, Zhuo Y, Li Y, Otchy TM, Tian L, Davison IG, Boas DA, Howe MW. Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.17.567425. [PMID: 38014018 PMCID: PMC10680831 DOI: 10.1101/2023.11.17.567425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Neural population dynamics relevant for behavior vary over multiple spatial and temporal scales across 3-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array and imaging approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice. We developed a semi-automated micro-CT based strategy to precisely localize positions of each optical fiber. This highly-customizable approach enables investigation of multi-scale spatial and temporal patterns of cell-type and neurotransmitter specific signals over arbitrary 3-D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum volume which revealed distinct, modality specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics through our fiber arrays enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and spatial localization of behavioral function across large circuits.
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Affiliation(s)
- Mai-Anh T. Vu
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Eleanor H. Brown
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
| | - Michelle J. Wen
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
- Department of Neurobiology, Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Christian A. Noggle
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Zicheng Zhang
- Department of Biology, Boston University, Boston, MA, USA
| | - Kevin J. Monk
- Department of Biology, Boston University, Boston, MA, USA
| | - Safa Bouabid
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
| | - Lydia Mroz
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
- Northeastern University, Boston, MA, USA
| | - Benjamin M. Graham
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
| | - Yizhou Zhuo
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Beijing, China
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Beijing, China
| | | | - Lin Tian
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA
| | - Ian G. Davison
- Department of Biology, Boston University, Boston, MA, USA
| | - David A. Boas
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Mark W. Howe
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
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47
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Lee CH, Park YK, Lee K. Recent strategies for neural dynamics observation at a larger scale and wider scope. Biosens Bioelectron 2023; 240:115638. [PMID: 37647685 DOI: 10.1016/j.bios.2023.115638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/15/2023] [Accepted: 08/24/2023] [Indexed: 09/01/2023]
Abstract
The tremendous technical progress in neuroscience offers opportunities to observe a more minor or/and broader dynamic picture of the brain. Moreover, the large-scale neural activity of individual neurons enables the dissection of detailed mechanistic links between neural populations and behaviors. To measure neural activity in-vivo, multi-neuron recording, and neuroimaging techniques are employed and developed to acquire more neurons. The tools introduced concurrently recorded dozens to hundreds of neurons in the coordinated brain regions and elucidated the neuronal ensembles from a massive population perspective of diverse neurons at cellular resolution. In particular, the increasing spatiotemporal resolution of neuronal monitoring across the whole brain dramatically facilitates our understanding of additional nervous system functions in health and disease. Here, we will introduce state-of-the-art neuroscience tools involving large-scale neural population recording and the long-range connections spanning multiple brain regions. Their synergic effects provide to clarify the controversial circuitry underlying neuroscience. These challenging neural tools present a promising outlook for the fundamental dynamic interplay across levels of synaptic cellular, circuit organization, and brain-wide. Hence, more observations of neural dynamics will provide more clues to elucidate brain functions and push forward innovative technology at the intersection of neural engineering disciplines. We hope this review will provide insight into the use or development of recent neural techniques considering spatiotemporal scales of brain observation.
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Affiliation(s)
- Chang Hak Lee
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea
| | - Young Kwon Park
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea
| | - Kwang Lee
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea.
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48
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Hope J, Beckerle T, Cheng PH, Viavattine Z, Feldkamp M, Fausner S, Saxena K, Ko E, Hryb I, Carter R, Ebner T, Kodandaramaiah S. Brain-wide neural recordings in mice navigating physical spaces enabled by a cranial exoskeleton. RESEARCH SQUARE 2023:rs.3.rs-3491330. [PMID: 38014260 PMCID: PMC10680923 DOI: 10.21203/rs.3.rs-3491330/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Complex behaviors are mediated by neural computations occurring throughout the brain. In recent years, tremendous progress has been made in developing technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales. However, these technologies are primarily designed for studying the mammalian brain during head fixation - wherein the behavior of the animal is highly constrained. Miniaturized devices for studying neural activity in freely behaving animals are largely confined to recording from small brain regions owing to performance limitations. We present a cranial exoskeleton that assists mice in maneuvering neural recording headstages that are orders of magnitude larger and heavier than the mice, while they navigate physical behavioral environments. Force sensors embedded within the headstage are used to detect the mouse's milli-Newton scale cranial forces which then control the x, y, and yaw motion of the exoskeleton via an admittance controller. We discovered optimal controller tuning parameters that enable mice to locomote at physiologically realistic velocities and accelerations while maintaining natural walking gait. Mice maneuvering headstages weighing up to 1.5 kg can make turns, navigate 2D arenas, and perform a navigational decision-making task with the same performance as when freely behaving. We designed an imaging headstage and an electrophysiology headstage for the cranial exoskeleton to record brain-wide neural activity in mice navigating 2D arenas. The imaging headstage enabled recordings of Ca2+ activity of 1000s of neurons distributed across the dorsal cortex. The electrophysiology headstage supported independent control of up to 4 silicon probes, enabling simultaneous recordings from 100s of neurons across multiple brain regions and multiple days. Cranial exoskeletons provide flexible platforms for largescale neural recording during the exploration of physical spaces, a critical new paradigm for unraveling the brain-wide neural mechanisms that control complex behavior.
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Affiliation(s)
- James Hope
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Travis Beckerle
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Pin-Hao Cheng
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Zoey Viavattine
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Michael Feldkamp
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Skylar Fausner
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Kapil Saxena
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Eunsong Ko
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Ihor Hryb
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Neuroscience, University of Minnesota, Twin Cities
| | - Russell Carter
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - Timothy Ebner
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - Suhasa Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
- Department of Neuroscience, University of Minnesota, Twin Cities
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49
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Jin Z, Lakshmanan A, Zhang R, Tran TA, Rabut C, Dutka P, Duan M, Hurt RC, Malounda D, Yao Y, Shapiro MG. Ultrasonic reporters of calcium for deep tissue imaging of cellular signals. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.09.566364. [PMID: 37986929 PMCID: PMC10659314 DOI: 10.1101/2023.11.09.566364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Calcium imaging has enabled major biological discoveries. However, the scattering of light by tissue limits the use of standard fluorescent calcium indicators in living animals. To address this limitation, we introduce the first genetically encoded ultrasonic reporter of calcium (URoC). Based on a unique class of air-filled protein nanostructures called gas vesicles, we engineered URoC to produce elevated nonlinear ultrasound signal upon binding to calcium ions. With URoC expressed in mammalian cells, we demonstrate noninvasive ultrasound imaging of calcium signaling in vivo during drug-induced receptor activation. URoC brings the depth and resolution advantages of ultrasound to the in vivo imaging of dynamic cellular function and paves the way for acoustic biosensing of a broader variety of biological signals.
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50
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Gerasimov E, Mitenev A, Pchitskaya E, Chukanov V, Bezprozvanny I. NeuroActivityToolkit-Toolbox for Quantitative Analysis of Miniature Fluorescent Microscopy Data. J Imaging 2023; 9:243. [PMID: 37998090 PMCID: PMC10672520 DOI: 10.3390/jimaging9110243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 11/25/2023] Open
Abstract
The visualization of neuronal activity in vivo is an urgent task in modern neuroscience. It allows neurobiologists to obtain a large amount of information about neuronal network architecture and connections between neurons. The miniscope technique might help to determine changes that occurred in the network due to external stimuli and various conditions: processes of learning, stress, epileptic seizures and neurodegenerative diseases. Furthermore, using the miniscope method, functional changes in the early stages of such disorders could be detected. The miniscope has become a modern approach for recording hundreds to thousands of neurons simultaneously in a certain brain area of a freely behaving animal. Nevertheless, the analysis and interpretation of the large recorded data is still a nontrivial task. There are a few well-working algorithms for miniscope data preprocessing and calcium trace extraction. However, software for further high-level quantitative analysis of neuronal calcium signals is not publicly available. NeuroActivityToolkit is a toolbox that provides diverse statistical metrics calculation, reflecting the neuronal network properties such as the number of neuronal activations per minute, amount of simultaneously co-active neurons, etc. In addition, the module for analyzing neuronal pairwise correlations is implemented. Moreover, one can visualize and characterize neuronal network states and detect changes in 2D coordinates using PCA analysis. This toolbox, which is deposited in a public software repository, is accompanied by a detailed tutorial and is highly valuable for the statistical interpretation of miniscope data in a wide range of experimental tasks.
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Affiliation(s)
- Evgenii Gerasimov
- Laboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia
| | - Alexander Mitenev
- Laboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia
| | - Ekaterina Pchitskaya
- Laboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia
| | - Viacheslav Chukanov
- Laboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia
| | - Ilya Bezprozvanny
- Laboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia
- Department of Physiology, UT Southwestern Medical Center at Dallas, Dallas, TX 75390, USA
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