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Frostig H, Monasterio A, Xia H, Mishra U, Britton B, Giblin JT, Mertz J, Scott BB. Three-photon population imaging of subcortical brain regions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.21.644611. [PMID: 40166349 PMCID: PMC11957121 DOI: 10.1101/2025.03.21.644611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
Recording activity from large cell populations in deep neural circuits is essential for understanding brain function. Three-photon (3P) imaging is an emerging technology that allows for imaging of structure and function in subcortical brain structures. However, increased tissue heating, as well as the low repetition rate sources inherent to 3P imaging, have limited the fields of view (FOV) to areas of ≤0.3 mm 2 . Here we present a Large Imaging Field of view Three-photon (LIFT) microscope with a FOV of >3 mm 2 . LIFT combines high numerical aperture (NA) optimized sampling, using a custom scanning module, with deep learning-based denoising, to enable population imaging in deep brain regions. We demonstrate non-invasive calcium imaging in the mouse brain from >1500 cells across CA1, the surrounding white matter, and adjacent deep layers of the cortex, and show population imaging with high signal-to-noise in the rat cortex at a depth of 1.2 mm. The LIFT microscope was built with all off-the-shelf components and allows for a flexible choice of imaging scale and rate.
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Affiliation(s)
- Hadas Frostig
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Amy Monasterio
- Graduate Program for Neuroscience, Boston University, Boston, Massachusetts, USA
| | - Hongjie Xia
- Department of Biology, Boston University, Boston, Massachusetts, USA
| | - Urvi Mishra
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | | | - John T. Giblin
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Benjamin B. Scott
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
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2
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Schottdorf M, Rich PD, Diamanti EM, Lin A, Tafazoli S, Nieh EH, Thiberge SY. TWINKLE: An open-source two-photon microscope for teaching and research. PLoS One 2025; 20:e0318924. [PMID: 39946384 PMCID: PMC11824991 DOI: 10.1371/journal.pone.0318924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2024] [Accepted: 01/23/2025] [Indexed: 02/16/2025] Open
Abstract
Many laboratories use two-photon microscopy through commercial suppliers, or homemade designs of considerable complexity. The integrated nature of these systems complicates customization, troubleshooting, and training on the principles of two-photon microscopy. Here, we present "Twinkle": a microscope for Two-photon Imaging in Neuroscience, and Kit for Learning and Education. It is a fully open, high performing and easy-to-set-up microscope that can effectively be used for both education and research. The instrument features a >1 mm field of view, using a modern objective with 3 mm working distance and 2 inch diameter optics combined with GaAsP photomultiplier tubes to maximize the fluorescence signal. We document our experiences using this system as a teaching tool in several two week long workshops, exemplify scientific use cases, and conclude with a broader note on the place of our work in the growing space of open scientific instrumentation.
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Affiliation(s)
- Manuel Schottdorf
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States of America
- Psychological and Brain Sciences, University of Delaware, Newark, DE, United States of America
| | - P. Dylan Rich
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States of America
| | - E. Mika Diamanti
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States of America
| | - Albert Lin
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States of America
- Center for the Physics of Biological Function, Princeton University, Princeton, NJ, United States of America
| | - Sina Tafazoli
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States of America
| | - Edward H. Nieh
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States of America
- Department of Pharmacology, School of Medicine, University of Virginia, Charlottesville, VA, United States of America
| | - Stephan Y. Thiberge
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States of America
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, United States of America
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3
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McLachlan CA, Lee DG, Kwon O, Delgado KM, Manjrekar N, Yao Z, Zeng H, Tasic B, Chen JL. Transcriptional determinants of goal-directed learning and representational drift in the parahippocampal cortex. Cell Rep 2025; 44:115175. [PMID: 39792551 PMCID: PMC11920904 DOI: 10.1016/j.celrep.2024.115175] [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: 02/25/2024] [Revised: 10/21/2024] [Accepted: 12/17/2024] [Indexed: 01/12/2025] Open
Abstract
Task learning involves learning associations between stimuli and outcomes and storing these relationships in memory. While this information can be reliably decoded from population activity, individual neurons encoding this representation can drift over time. The circuit or molecular mechanisms underlying this drift and its role in learning are unclear. We performed two-photon calcium imaging in the perirhinal cortex during task training. Using post hoc spatial transcriptomics, we measured immediate-early gene (IEG) expression and assigned monitored neurons to excitatory or inhibitory subtypes. We discovered an IEG-defined network spanning multiple subtypes that form stimulus-outcome associations. Targeted deletion of brain-derived neurotrophic factor in the perirhinal cortex disrupted IEG expression and impaired task learning. Representational drift slowed with prolonged training. Pre-existing representations were strengthened while stimulus-reward associations failed to form. Our findings reveal the cell types and molecules regulating long-term network stability that is permissive for task learning and memory allocation.
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Affiliation(s)
- Caroline A McLachlan
- Department of Biology, Boston University, Boston, MA 02215, USA; Center for Neurophotonics, Boston University, Boston, MA 02215, USA
| | - David G Lee
- Center for Neurophotonics, Boston University, Boston, MA 02215, USA; Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Osung Kwon
- Department of Biology, Boston University, Boston, MA 02215, USA
| | - Kevin M Delgado
- Department of Biology, Boston University, Boston, MA 02215, USA
| | | | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jerry L Chen
- Department of Biology, Boston University, Boston, MA 02215, USA; Center for Neurophotonics, Boston University, Boston, MA 02215, USA; Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Center for Systems Neuroscience, Boston University, Boston MA 02215, USA.
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4
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Quirin S. Compact module for video-rate image mosaics in two-photon microscopy. OPTICS EXPRESS 2025; 33:1647-1659. [PMID: 39876333 PMCID: PMC12011383 DOI: 10.1364/oe.544906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2024] [Revised: 11/19/2024] [Accepted: 11/20/2024] [Indexed: 01/30/2025]
Abstract
Biological applications using multiphoton microscopy increasingly seek a larger field of view while maintaining sufficient temporal sampling to observe dynamic biological processes. Multiphoton imaging also requires high numerical aperture microscope objectives to realize efficient non-linear excitation and collection of fluorescence. This combination of low-magnification and high-numerical aperture poses a challenge for system design. To address this, the use of a liquid crystal polarization grating stack is proposed here to temporally sequence through multiple fields of view. This solution pans the native field of view with minimal latency and zero inertial movement of either the microscope or biological sample. Implemented as a simple add-on unit to existing multi-photon microscopes, this device increases the total field size by 4x, covering up to 7.6mm2. Performance constraints and functional demonstration of imaging neural activity are presented.
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Affiliation(s)
- Sean Quirin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
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5
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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: 1] [Impact Index Per Article: 1.0] [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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Wang J, Li Y, Qi L, Mamtilahun M, Liu C, Liu Z, Shi R, Wu S, Yang GY. Advanced rehabilitation in ischaemic stroke research. Stroke Vasc Neurol 2024; 9:328-343. [PMID: 37788912 PMCID: PMC11420926 DOI: 10.1136/svn-2022-002285] [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: 12/30/2022] [Accepted: 03/20/2023] [Indexed: 10/05/2023] Open
Abstract
At present, due to the rapid progress of treatment technology in the acute phase of ischaemic stroke, the mortality of patients has been greatly reduced but the number of disabled survivors is increasing, and most of them are elderly patients. Physicians and rehabilitation therapists pay attention to develop all kinds of therapist techniques including physical therapy techniques, robot-assisted technology and artificial intelligence technology, and study the molecular, cellular or synergistic mechanisms of rehabilitation therapies to promote the effect of rehabilitation therapy. Here, we discussed different animal and in vitro models of ischaemic stroke for rehabilitation studies; the compound concept and technology of neurological rehabilitation; all kinds of biological mechanisms of physical therapy; the significance, assessment and efficacy of neurological rehabilitation; the application of brain-computer interface, rehabilitation robotic and non-invasive brain stimulation technology in stroke rehabilitation.
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Affiliation(s)
- Jixian Wang
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medical, Shanghai, China
| | - Yongfang Li
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medical, Shanghai, China
| | - Lin Qi
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Muyassar Mamtilahun
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chang Liu
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ze Liu
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Rubing Shi
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Shengju Wu
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Guo-Yuan Yang
- Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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7
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Mo C, McKinnon C, Murray Sherman S. A transthalamic pathway crucial for perception. Nat Commun 2024; 15:6300. [PMID: 39060240 PMCID: PMC11282105 DOI: 10.1038/s41467-024-50163-w] [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: 03/21/2024] [Accepted: 06/28/2024] [Indexed: 07/28/2024] Open
Abstract
Perception is largely supported by cortical processing that involves communication among multiple areas, typically starting with primary sensory cortex and then involving higher order cortices. This communication is served in part by transthalamic (cortico-thalamo-cortical) pathways, which ubiquitously parallel direct corticocortical pathways, but their role in sensory processing has largely remained unexplored. Here, we suggest that transthalamic processing propagates task-relevant information required for correct sensory decisions. Using optogenetics, we specifically inhibited the pathway at its synapse in higher order somatosensory thalamus of mice performing a texture-based discrimination task. We concurrently monitored the cellular effects of inhibition in primary or secondary cortex using two-photon calcium imaging. Inhibition severely impaired performance despite intact direct corticocortical projections, thus challenging the purely corticocentric map of perception. Interestingly, the inhibition did not reduce overall cell responsiveness to texture stimulation in somatosensory cortex, but rather disrupted the texture selectivity of cells, a discriminability that develops over task learning. This discriminability was more disrupted in the secondary than primary somatosensory cortex, emphasizing the feedforward influence of the transthalamic route. Transthalamic pathways may therefore act to deliver performance-relevant information to higher order cortex and are underappreciated hierarchical pathways in perceptual decision-making.
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Affiliation(s)
- Christina Mo
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia.
- Department of Neurobiology, University of Chicago, Chicago, Illinois, USA.
| | - Claire McKinnon
- Department of Neurobiology, University of Chicago, Chicago, Illinois, USA
| | - S Murray Sherman
- Department of Neurobiology, University of Chicago, Chicago, Illinois, USA.
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8
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Lee DG, McLachlan CA, Nogueira R, Kwon O, Carey AE, House G, Lagani GD, LaMay D, Fusi S, Chen JL. Perirhinal cortex learns a predictive map of the task environment. Nat Commun 2024; 15:5544. [PMID: 38956015 PMCID: PMC11219840 DOI: 10.1038/s41467-024-47365-7] [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: 08/09/2023] [Accepted: 03/25/2024] [Indexed: 07/04/2024] Open
Abstract
Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
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Affiliation(s)
- David G Lee
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
| | - Caroline A McLachlan
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Ramon Nogueira
- Center for Theoretical Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Osung Kwon
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Alanna E Carey
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Garrett House
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Gavin D Lagani
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Danielle LaMay
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA.
- Department of Biology, Boston University, Boston, MA, 02215, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA.
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9
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Rupprecht P, Duss SN, Becker D, Lewis CM, Bohacek J, Helmchen F. Centripetal integration of past events in hippocampal astrocytes regulated by locus coeruleus. Nat Neurosci 2024; 27:927-939. [PMID: 38570661 PMCID: PMC11089000 DOI: 10.1038/s41593-024-01612-8] [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: 07/26/2022] [Accepted: 02/26/2024] [Indexed: 04/05/2024]
Abstract
An essential feature of neurons is their ability to centrally integrate information from their dendrites. The activity of astrocytes, in contrast, has been described as mostly uncoordinated across cellular compartments without clear central integration. Here we report conditional integration of calcium signals in astrocytic distal processes at their soma. In the hippocampus of adult mice of both sexes, we found that global astrocytic activity, as recorded with population calcium imaging, reflected past neuronal and behavioral events on a timescale of seconds. Salient past events, indicated by pupil dilations, facilitated the propagation of calcium signals from distal processes to the soma. Centripetal propagation to the soma was reproduced by optogenetic activation of the locus coeruleus, a key regulator of arousal, and reduced by pharmacological inhibition of α1-adrenergic receptors. Together, our results suggest that astrocytes are computational units of the brain that slowly and conditionally integrate calcium signals upon behaviorally relevant events.
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Affiliation(s)
- Peter Rupprecht
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zürich, Switzerland.
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zürich, Switzerland.
| | - Sian N Duss
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zürich, Switzerland
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
| | - Denise Becker
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zürich, Switzerland
| | - Christopher M Lewis
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zürich, Switzerland
| | - Johannes Bohacek
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zürich, Switzerland
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
| | - Fritjof Helmchen
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zürich, Switzerland.
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zürich, Switzerland.
- University Research Priority Program (URPP), Adaptive Brain Circuits in Development and Learning, University of Zurich, Zürich, Switzerland.
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10
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Liu C, Hao Y, Lei B, Zhong Y, Kong L. Removing crosstalk signals in neuron activity by time multiplexed excitations in a two-photon all-optical physiology system. BIOMEDICAL OPTICS EXPRESS 2024; 15:2708-2718. [PMID: 38633062 PMCID: PMC11019693 DOI: 10.1364/boe.521047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/11/2024] [Accepted: 03/11/2024] [Indexed: 04/19/2024]
Abstract
The two-photon all-optical physiology system has attracted great interest in deciphering neuronal circuits in vivo, benefiting from its advantages in recording and modulating neuronal activities at single neuron resolutions. However, the interference, or crosstalk, between the imaging and photostimulation beams introduces a significant challenge and may impede the future application of voltage indicators in two-photon all-optical physiology system. Here, we propose the time multiplexed excitation method to distinguish signals from neuronal activities and crosstalks from photostimulation. In our system, the laser pulses of the imaging beam and photostimulation beam are synchronized, and a time delay is introduced into these pulses to separate the fluorescence signal generated by these two beams. We demonstrate the efficacy of our system in eliminating crosstalk signals from photostimulation and evaluate its influence on both genetically encoded calcium indicators (GECIs) and genetically encoded voltage indicators (GEVIs) through in vivo experiments.
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Affiliation(s)
- Chi Liu
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Yuejun Hao
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
- School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Bo Lei
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
- Beijing Academy of Artificial Intelligence, Beijing 100084, China
| | - Yi Zhong
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
- School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Lingjie Kong
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
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11
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Han S, Helmchen F. Behavior-relevant top-down cross-modal predictions in mouse neocortex. Nat Neurosci 2024; 27:298-308. [PMID: 38177341 DOI: 10.1038/s41593-023-01534-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 11/27/2023] [Indexed: 01/06/2024]
Abstract
Animals adapt to a constantly changing world by predicting their environment and the consequences of their actions. The predictive coding hypothesis proposes that the brain generates predictions and continuously compares them with sensory inputs to guide behavior. However, how the brain reconciles conflicting top-down predictions and bottom-up sensory information remains unclear. To address this question, we simultaneously imaged neuronal populations in the mouse somatosensory barrel cortex and posterior parietal cortex during an auditory-cued texture discrimination task. In mice that had learned the task with fixed tone-texture matching, the presentation of mismatched pairing induced conflicts between tone-based texture predictions and actual texture inputs. When decisions were based on the predicted rather than the actual texture, top-down information flow was dominant and texture representations in both areas were modified, whereas dominant bottom-up information flow led to correct representations and behavioral choice. Our findings provide evidence for hierarchical predictive coding in the mouse neocortex.
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Affiliation(s)
- Shuting Han
- Brain Research Institute, University of Zurich, Zurich, Switzerland.
| | - Fritjof Helmchen
- Brain Research Institute, University of Zurich, Zurich, Switzerland.
- Neuroscience Center Zurich (ZNZ), University of Zurich, Zurich, Switzerland.
- University Research Priority Program (URPP), Adaptive Brain Circuits in Development and Learning, University of Zurich, Zurich, Switzerland.
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12
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Ledderose JMT, Zolnik TA, Toumazou M, Trimbuch T, Rosenmund C, Eickholt BJ, Jaeger D, Larkum ME, Sachdev RNS. Layer 1 of somatosensory cortex: an important site for input to a tiny cortical compartment. Cereb Cortex 2023; 33:11354-11372. [PMID: 37851709 PMCID: PMC10690867 DOI: 10.1093/cercor/bhad371] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 09/17/2023] [Indexed: 10/20/2023] Open
Abstract
Neocortical layer 1 has been proposed to be at the center for top-down and bottom-up integration. It is a locus for interactions between long-range inputs, layer 1 interneurons, and apical tuft dendrites of pyramidal neurons. While input to layer 1 has been studied intensively, the level and effect of input to this layer has still not been completely characterized. Here we examined the input to layer 1 of mouse somatosensory cortex with retrograde tracing and optogenetics. Our assays reveal that local input to layer 1 is predominantly from layers 2/3 and 5 pyramidal neurons and interneurons, and that subtypes of local layers 5 and 6b neurons project to layer 1 with different probabilities. Long-range input from sensory-motor cortices to layer 1 of somatosensory cortex arose predominantly from layers 2/3 neurons. Our optogenetic experiments showed that intra-telencephalic layer 5 pyramidal neurons drive layer 1 interneurons but have no effect locally on layer 5 apical tuft dendrites. Dual retrograde tracing revealed that a fraction of local and long-range neurons was both presynaptic to layer 5 neurons and projected to layer 1. Our work highlights the prominent role of local inputs to layer 1 and shows the potential for complex interactions between long-range and local inputs, which are both in position to modify the output of somatosensory cortex.
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Affiliation(s)
- Julia M T Ledderose
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
- Institute of Molecular Biology and Biochemistry, Charité—Universitätsmedizin Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Timothy A Zolnik
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
- Institute of Molecular Biology and Biochemistry, Charité—Universitätsmedizin Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Maria Toumazou
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Thorsten Trimbuch
- Institute of Neurophysiology, Charité—Universitätsmedizin Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Christian Rosenmund
- Institute of Neurophysiology, Charité—Universitätsmedizin Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
- Neurocure Centre for Excellence Charité—Universitätsmedizin Berlin Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | | | - Dieter Jaeger
- Department of Biology, Emory University, Atlanta, GA 30322, USA
| | - Matthew E Larkum
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
- Neurocure Centre for Excellence Charité—Universitätsmedizin Berlin Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Robert N S Sachdev
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
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13
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Platisa J, Ye X, Ahrens AM, Liu C, Chen IA, Davison IG, Tian L, Pieribone VA, Chen JL. High-speed low-light in vivo two-photon voltage imaging of large neuronal populations. Nat Methods 2023; 20:1095-1103. [PMID: 36973547 PMCID: PMC10894646 DOI: 10.1038/s41592-023-01820-3] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 02/16/2023] [Indexed: 03/29/2023]
Abstract
Monitoring spiking activity across large neuronal populations at behaviorally relevant timescales is critical for understanding neural circuit function. Unlike calcium imaging, voltage imaging requires kilohertz sampling rates that reduce fluorescence detection to near shot-noise levels. High-photon flux excitation can overcome photon-limited shot noise, but photobleaching and photodamage restrict the number and duration of simultaneously imaged neurons. We investigated an alternative approach aimed at low two-photon flux, which is voltage imaging below the shot-noise limit. This framework involved developing positive-going voltage indicators with improved spike detection (SpikeyGi and SpikeyGi2); a two-photon microscope ('SMURF') for kilohertz frame rate imaging across a 0.4 mm × 0.4 mm field of view; and a self-supervised denoising algorithm (DeepVID) for inferring fluorescence from shot-noise-limited signals. Through these combined advances, we achieved simultaneous high-speed deep-tissue imaging of more than 100 densely labeled neurons over 1 hour in awake behaving mice. This demonstrates a scalable approach for voltage imaging across increasing neuronal populations.
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Affiliation(s)
- Jelena Platisa
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT, USA
- The John B. Pierce Laboratory, New Haven, CT, USA
| | - Xin Ye
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | | | - Chang Liu
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | | | - Ian G Davison
- Neurophotonics Center, Boston University, Boston, MA, USA
- Department of Biology, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Lei Tian
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA
| | - Vincent A Pieribone
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT, USA.
- The John B. Pierce Laboratory, New Haven, CT, USA.
- Department of Neuroscience, Yale University, New Haven, CT, USA.
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
- Neurophotonics Center, Boston University, Boston, MA, USA.
- Department of Biology, Boston University, Boston, MA, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, USA.
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14
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Mo C, McKinnon C, Sherman SM. A transthalamic pathway crucial for perception. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.30.533323. [PMID: 37034798 PMCID: PMC10081228 DOI: 10.1101/2023.03.30.533323] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Perception arises from activity between cortical areas, first primary cortex and then higher order cortices. This communication is served in part by transthalamic (cortico-thalamo-cortical) pathways, which ubiquitously parallel direct corticocortical pathways, but their role in sensory processing has largely remained unexplored. Here, we show that the transthalamic pathway linking somatosensory cortices propagates task-relevant information required for correct sensory decisions. Using optogenetics, we specifically inhibited the pathway at its synapse in higher order somatosensory thalamus of mice performing a texture-based discrimination task. We concurrently monitored the cellular effects of inhibition in primary or secondary cortex using two-photon calcium imaging. Inhibition severely impaired performance despite intact direct corticocortical projections, thus challenging the purely corticocentric map of perception. Interestingly, the inhibition did not reduce overall cell responsiveness to texture stimulation in somatosensory cortex, but rather disrupted the texture selectivity of cells, a discriminability that develops over task learning. This discriminability was more disrupted in the secondary than primary somatosensory cortex, emphasizing the feedforward influence of the transthalamic route. Transthalamic pathways thus appear critical in delivering performance-relevant information to higher order cortex and are critical hierarchical pathways in perceptual decision-making.
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15
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Egashira T, Nakagawa-Tamagawa N, Abzhanova E, Kawae Y, Kohara A, Koitabashi R, Mizuno H, Mizuno H. In vivo two-photon calcium imaging of cortical neurons in neonatal mice. STAR Protoc 2023; 4:102245. [PMID: 37119143 PMCID: PMC10173855 DOI: 10.1016/j.xpro.2023.102245] [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: 11/22/2022] [Revised: 01/20/2023] [Accepted: 03/24/2023] [Indexed: 04/30/2023] Open
Abstract
In vivo calcium imaging is essential to elucidate unique synchronous activities observed in the developing brain. Here, we present a protocol to image and analyze activity patterns in neonatal mouse neocortex in a single-cell level. We describe steps for in utero electroporation, cranial window surgery, two-photon imaging, and activity correlation analysis. This protocol facilitates the understanding of neuronal activities and activity-dependent circuit formation during development. For complete details on the use and execution of this protocol, please refer to Mizuno et al. (2014),1 Mizuno et al. (2018a),2 and Mizuno et al. (2018b).3.
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Affiliation(s)
- Takamitsu Egashira
- Laboratory of Multi-Dimensional Imaging, International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan; Graduate School of Medical Sciences, Kumamoto University, Kumamoto 860-0811, Japan
| | - Nao Nakagawa-Tamagawa
- Department of Physiology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8544, Japan.
| | - Elvira Abzhanova
- Laboratory of Multi-Dimensional Imaging, International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan; Graduate School of Medical Sciences, Kumamoto University, Kumamoto 860-0811, Japan
| | - Yuzuki Kawae
- Laboratory of Multi-Dimensional Imaging, International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan
| | - Ayami Kohara
- Laboratory of Multi-Dimensional Imaging, International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan
| | - Ryoko Koitabashi
- Laboratory of Multi-Dimensional Imaging, International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan
| | - Hiromi Mizuno
- Laboratory of Multi-Dimensional Imaging, International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan
| | - Hidenobu Mizuno
- Laboratory of Multi-Dimensional Imaging, International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan; Graduate School of Medical Sciences, Kumamoto University, Kumamoto 860-0811, Japan.
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16
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Muller M, Pennartz CMA, Bosman CA, Olcese U. A novel task to investigate vibrotactile detection in mice. PLoS One 2023; 18:e0284735. [PMID: 37079581 PMCID: PMC10118142 DOI: 10.1371/journal.pone.0284735] [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: 12/02/2022] [Accepted: 04/06/2023] [Indexed: 04/21/2023] Open
Abstract
Throughout the last decades, understanding the neural mechanisms of sensory processing has been a key objective for neuroscientists. Many studies focused on uncovering the microcircuit-level architecture of somatosensation using the rodent whisker system as a model. Although these studies have significantly advanced our understanding of tactile processing, the question remains to what extent the whisker system can provide results translatable to the human somatosensory system. To address this, we developed a restrained vibrotactile detection task involving the limb system in mice. A vibrotactile stimulus was delivered to the hindlimb of head-fixed mice, who were trained to perform a Go/No-go detection task. Mice were able to learn this task with satisfactory performance and with reasonably short training times. In addition, the task we developed is versatile, as it can be combined with diverse neuroscience methods. Thus, this study introduces a novel task to study the neuron-level mechanisms of tactile processing in a system other than the more commonly studied whisker system.
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Affiliation(s)
- Mariel Muller
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M. A. Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Conrado A. Bosman
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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17
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Lee DG, McLachlan CA, Nogueira R, Kwon O, Carey AE, House G, Lagani GD, LaMay D, Fusi S, Chen JL. PERIRHINAL CORTEX LEARNS A PREDICTIVE MAP (INTERNAL MODEL) OF THE TASK ENVIRONMENT. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.532214. [PMID: 36993645 PMCID: PMC10055158 DOI: 10.1101/2023.03.17.532214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chemogenetic inactivation demonstrated that Prh is involved in task learning. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that expand in a retrospective manner and generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
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Affiliation(s)
- David G Lee
- Department of Biomedical Engineering, Boston University, Boston MA 02215, USA
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
| | - Caroline A McLachlan
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Ramon Nogueira
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Neuroscience, Columbia University, New York NY 10027, USA
| | - Osung Kwon
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Alanna E Carey
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Garrett House
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Gavin D Lagani
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Danielle LaMay
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Neuroscience, Columbia University, New York NY 10027, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston MA 02215, USA
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
- Center for Systems Neuroscience, Boston University, Boston MA 02215, USA
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18
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Koh TH, Bishop WE, Kawashima T, Jeon BB, Srinivasan R, Mu Y, Wei Z, Kuhlman SJ, Ahrens MB, Chase SM, Yu BM. Dimensionality reduction of calcium-imaged neuronal population activity. NATURE COMPUTATIONAL SCIENCE 2023; 3:71-85. [PMID: 37476302 PMCID: PMC10358781 DOI: 10.1038/s43588-022-00390-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 12/05/2022] [Indexed: 07/22/2023]
Abstract
Calcium imaging has been widely adopted for its ability to record from large neuronal populations. To summarize the time course of neural activity, dimensionality reduction methods, which have been applied extensively to population spiking activity, may be particularly useful. However, it is unclear if the dimensionality reduction methods applied to spiking activity are appropriate for calcium imaging. We thus carried out a systematic study of design choices based on standard dimensionality reduction methods. We also developed a method to perform deconvolution and dimensionality reduction simultaneously (Calcium Imaging Linear Dynamical System, CILDS). CILDS most accurately recovered the single-trial, low-dimensional time courses from simulated calcium imaging data. CILDS also outperformed the other methods on calcium imaging recordings from larval zebrafish and mice. More broadly, this study represents a foundation for summarizing calcium imaging recordings of large neuronal populations using dimensionality reduction in diverse experimental settings.
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Affiliation(s)
- Tze Hui Koh
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Center for the Neural Basis of Cognition, PA
| | - William E. Bishop
- Center for the Neural Basis of Cognition, PA
- Department of Machine Learning, Carnegie Mellon University, PA
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Takashi Kawashima
- Janelia Research Campus, Howard Hughes Medical Institute, VA
- Department of Brain Sciences, Weizmann Institute of Science, Israel
| | - Brian B. Jeon
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Center for the Neural Basis of Cognition, PA
| | - Ranjani Srinivasan
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Department of Electrical and Computer Engineering, Johns Hopkins University, MD
| | - Yu Mu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, China
| | - Ziqiang Wei
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Sandra J. Kuhlman
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
- Department of Biological Sciences, Carnegie Mellon University, PA
| | - Misha B. Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Steven M. Chase
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
| | - Byron M. Yu
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
- Department of Electrical and Computer Engineering, Carnegie Mellon University, PA
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19
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Wang Y, LeDue JM, Murphy TH. Multiscale imaging informs translational mouse modeling of neurological disease. Neuron 2022; 110:3688-3710. [PMID: 36198319 DOI: 10.1016/j.neuron.2022.09.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/26/2022] [Accepted: 09/06/2022] [Indexed: 11/05/2022]
Abstract
Multiscale neurophysiology reveals that simple motor actions are associated with changes in neuronal firing in virtually every brain region studied. Accordingly, the assessment of focal pathology such as stroke or progressive neurodegenerative diseases must also extend widely across brain areas. To derive mechanistic information through imaging, multiple resolution scales and multimodal factors must be included, such as the structure and function of specific neurons and glial cells and the dynamics of specific neurotransmitters. Emerging multiscale methods in preclinical animal studies that span micro- to macroscale examinations fill this gap, allowing a circuit-based understanding of pathophysiological mechanisms. Combined with high-performance computation and open-source data repositories, these emerging multiscale and large field-of-view techniques include live functional ultrasound, multi- and single-photon wide-scale light microscopy, video-based miniscopes, and tissue-penetrating fiber photometry, as well as variants of post-mortem expansion microscopy. We present these technologies and outline use cases and data pipelines to uncover new knowledge within animal models of stroke, Alzheimer's disease, and movement disorders.
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Affiliation(s)
- Yundi Wang
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
| | - Jeffrey M LeDue
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
| | - Timothy H Murphy
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada.
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20
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Machado TA, Kauvar IV, Deisseroth K. Multiregion neuronal activity: the forest and the trees. Nat Rev Neurosci 2022; 23:683-704. [PMID: 36192596 PMCID: PMC10327445 DOI: 10.1038/s41583-022-00634-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2022] [Indexed: 12/12/2022]
Abstract
The past decade has witnessed remarkable advances in the simultaneous measurement of neuronal activity across many brain regions, enabling fundamentally new explorations of the brain-spanning cellular dynamics that underlie sensation, cognition and action. These recently developed multiregion recording techniques have provided many experimental opportunities, but thoughtful consideration of methodological trade-offs is necessary, especially regarding field of view, temporal acquisition rate and ability to guarantee cellular resolution. When applied in concert with modern optogenetic and computational tools, multiregion recording has already made possible fundamental biological discoveries - in part via the unprecedented ability to perform unbiased neural activity screens for principles of brain function, spanning dozens of brain areas and from local to global scales.
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Affiliation(s)
- Timothy A Machado
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Isaac V Kauvar
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
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21
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Leisman G, Melillo R. Front and center: Maturational dysregulation of frontal lobe functional neuroanatomic connections in attention deficit hyperactivity disorder. Front Neuroanat 2022; 16:936025. [PMID: 36081853 PMCID: PMC9446472 DOI: 10.3389/fnana.2022.936025] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 07/29/2022] [Indexed: 12/21/2022] Open
Abstract
Frontal lobe function may not universally explain all forms of attention deficit hyperactivity disorder (ADHD) but the frontal lobe hypothesis described supports an internally consistent model for integrating the numerous behaviors associated with ADHD. The paper examines the developmental trajectories of frontal and prefrontal lobe development, framing ADHD as maturational dysregulation concluding that the cognitive, motor, and behavioral abilities of the presumptive majority of ADHD children may not primarily be disordered or dysfunctional but reflect maturational dysregulation that is inconsistent with the psychomotor and cognitive expectations for the child’s chronological and mental age. ADHD children demonstrate decreased activation of the right and middle prefrontal cortex. Prefrontal and frontal lobe regions have an exuberant network of shared pathways with the diencephalic region, also having a regulatory function in arousal as well as with the ascending reticular formation which has a capacity for response suppression to task-irrelevant stimuli. Prefrontal lesions oftentimes are associated with the regulatory breakdown of goal-directed activity and impulsivity. In conclusion, a presumptive majority of childhood ADHD may result from maturational dysregulation of the frontal lobes with effects on the direct, indirect and/or, hyperdirect pathways.
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Affiliation(s)
- Gerry Leisman
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel
- Department of Neurology, University of Medical Sciences of Havana, Havana, Cuba
- *Correspondence: Gerry Leisman,
| | - Robert Melillo
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel
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22
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Ebrahimi S, Lecoq J, Rumyantsev O, Tasci T, Zhang Y, Irimia C, Li J, Ganguli S, Schnitzer MJ. Emergent reliability in sensory cortical coding and inter-area communication. Nature 2022; 605:713-721. [PMID: 35589841 PMCID: PMC10985415 DOI: 10.1038/s41586-022-04724-y] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 04/04/2022] [Indexed: 12/16/2022]
Abstract
Reliable sensory discrimination must arise from high-fidelity neural representations and communication between brain areas. However, how neocortical sensory processing overcomes the substantial variability of neuronal sensory responses remains undetermined1-6. Here we imaged neuronal activity in eight neocortical areas concurrently and over five days in mice performing a visual discrimination task, yielding longitudinal recordings of more than 21,000 neurons. Analyses revealed a sequence of events across the neocortex starting from a resting state, to early stages of perception, and through the formation of a task response. At rest, the neocortex had one pattern of functional connections, identified through sets of areas that shared activity cofluctuations7,8. Within about 200 ms after the onset of the sensory stimulus, such connections rearranged, with different areas sharing cofluctuations and task-related information. During this short-lived state (approximately 300 ms duration), both inter-area sensory data transmission and the redundancy of sensory encoding peaked, reflecting a transient increase in correlated fluctuations among task-related neurons. By around 0.5 s after stimulus onset, the visual representation reached a more stable form, the structure of which was robust to the prominent, day-to-day variations in the responses of individual cells. About 1 s into stimulus presentation, a global fluctuation mode conveyed the upcoming response of the mouse to every area examined and was orthogonal to modes carrying sensory data. Overall, the neocortex supports sensory performance through brief elevations in sensory coding redundancy near the start of perception, neural population codes that are robust to cellular variability, and widespread inter-area fluctuation modes that transmit sensory data and task responses in non-interfering channels.
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Affiliation(s)
- Sadegh Ebrahimi
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA.
- CNC Program, Stanford University, Stanford, CA, USA.
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
| | - Jérôme Lecoq
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | - Oleg Rumyantsev
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Tugce Tasci
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Yanping Zhang
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Cristina Irimia
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Jane Li
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Surya Ganguli
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Mark J Schnitzer
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA.
- CNC Program, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
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23
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Feedforward and feedback interactions between visual cortical areas use different population activity patterns. Nat Commun 2022; 13:1099. [PMID: 35232956 PMCID: PMC8888615 DOI: 10.1038/s41467-022-28552-w] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 01/19/2022] [Indexed: 12/19/2022] Open
Abstract
Brain function relies on the coordination of activity across multiple, recurrently connected brain areas. For instance, sensory information encoded in early sensory areas is relayed to, and further processed by, higher cortical areas and then fed back. However, the way in which feedforward and feedback signaling interact with one another is incompletely understood. Here we investigate this question by leveraging simultaneous neuronal population recordings in early and midlevel visual areas (V1-V2 and V1-V4). Using a dimensionality reduction approach, we find that population interactions are feedforward-dominated shortly after stimulus onset and feedback-dominated during spontaneous activity. The population activity patterns most correlated across areas were distinct during feedforward- and feedback-dominated periods. These results suggest that feedforward and feedback signaling rely on separate "channels", which allows feedback signals to not directly affect activity that is fed forward.
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24
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Condylis C, Ghanbari A, Manjrekar N, Bistrong K, Yao S, Yao Z, Nguyen TN, Zeng H, Tasic B, Chen JL. Dense functional and molecular readout of a circuit hub in sensory cortex. Science 2022; 375:eabl5981. [PMID: 34990233 DOI: 10.1126/science.abl5981] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Although single-cell transcriptomics of the neocortex has uncovered more than 300 putative cell types, whether this molecular classification predicts distinct functional roles is unclear. We combined two-photon calcium imaging with spatial transcriptomics to functionally and molecularly investigate cortical circuits. We characterized behavior-related responses across major neuronal subclasses in layers 2 or 3 of the primary somatosensory cortex as mice performed a tactile working memory task. We identified an excitatory intratelencephalic cell type, Baz1a, that exhibits high tactile feature selectivity. Baz1a neurons homeostatically maintain stimulus responsiveness during altered experience and show persistent enrichment of subsets of immediately early genes. Functional and anatomical connectivity reveals that Baz1a neurons residing in upper portions of layers 2 or 3 preferentially innervate somatostatin-expressing inhibitory neurons. This motif defines a circuit hub that orchestrates local sensory processing in superficial layers of the neocortex.
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Affiliation(s)
- Cameron Condylis
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.,Center for Neurophotonics, Boston University, Boston, MA 02215, USA
| | - Abed Ghanbari
- Department of Biology, Boston University, Boston, MA 02215, USA
| | | | - Karina Bistrong
- Department of Biology, Boston University, Boston, MA 02215, USA
| | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.,Center for Neurophotonics, Boston University, Boston, MA 02215, USA.,Department of Biology, Boston University, Boston, MA 02215, USA.,Center for Systems Neuroscience, Boston University, Boston, MA 02215, USA
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25
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Yu CH, Stirman JN, Yu Y, Hira R, Smith SL. Diesel2p mesoscope with dual independent scan engines for flexible capture of dynamics in distributed neural circuitry. Nat Commun 2021; 12:6639. [PMID: 34789723 PMCID: PMC8599518 DOI: 10.1038/s41467-021-26736-4] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 10/05/2021] [Indexed: 11/09/2022] Open
Abstract
Imaging the activity of neurons that are widely distributed across brain regions deep in scattering tissue at high speed remains challenging. Here, we introduce an open-source system with Dual Independent Enhanced Scan Engines for Large field-of-view Two-Photon imaging (Diesel2p). Combining optical design, adaptive optics, and temporal multiplexing, the system offers subcellular resolution over a large field-of-view of ~25 mm2, encompassing distances up to 7 mm, with independent scan engines. We demonstrate the flexibility and various use cases of this system for calcium imaging of neurons in the living brain.
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Affiliation(s)
- Che-Hang Yu
- Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA
| | | | - Yiyi Yu
- Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA
| | - Riichiro Hira
- Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA
| | - Spencer L Smith
- Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA.
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26
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Clough M, Chen IA, Park SW, Ahrens AM, Stirman JN, Smith SL, Chen JL. Flexible simultaneous mesoscale two-photon imaging of neural activity at high speeds. Nat Commun 2021; 12:6638. [PMID: 34789730 PMCID: PMC8599611 DOI: 10.1038/s41467-021-26737-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 10/05/2021] [Indexed: 12/02/2022] Open
Abstract
Understanding brain function requires monitoring local and global brain dynamics. Two-photon imaging of the brain across mesoscopic scales has presented trade-offs between imaging area and acquisition speed. We describe a flexible cellular resolution two-photon microscope capable of simultaneous video rate acquisition of four independently targetable brain regions spanning an approximate five-millimeter field of view. With this system, we demonstrate the ability to measure calcium activity across mouse sensorimotor cortex at behaviorally relevant timescales.
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Affiliation(s)
- Mitchell Clough
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - Ichun Anderson Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
| | - Seong-Wook Park
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
| | - Allison M Ahrens
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Jeffrey N Stirman
- Neuroscience Center, University of North Carolina School of Medicine, Chapel Hill, NC, 27599, USA
| | - Spencer L Smith
- Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA.
- Department of Biology, Boston University, Boston, MA, 02215, USA.
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27
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Harrell ER, Renard A, Bathellier B. Fast cortical dynamics encode tactile grating orientation during active touch. SCIENCE ADVANCES 2021; 7:eabf7096. [PMID: 34516895 PMCID: PMC8442870 DOI: 10.1126/sciadv.abf7096] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Touch-based object recognition relies on perception of compositional tactile features like roughness, shape, and surface orientation. However, besides roughness, it remains unclear how these different tactile features are encoded by neural activity that is linked with perception. Here, we establish a cortex-dependent perceptual task in which mice discriminate tactile gratings on the basis of orientation using only their whiskers. Multielectrode recordings in the barrel cortex reveal weak orientation tuning in average firing rates (500-ms time scale) during grating exploration despite high levels of cortical activity. Just before decision, orientation information extracted from fast cortical dynamics (100-ms time scale) more closely resembles concurrent psychophysical measurements than single neuron orientation tuning curves. This temporal code conveys both stimulus and choice/action-related information, suggesting that fast cortical dynamics during exploration of a tactile object both reflect the physical stimulus and affect the decision.
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Affiliation(s)
- Evan R. Harrell
- Department for Integrative and Computational Neuroscience (ICN), Paris-Saclay Institute of Neuroscience (NeuroPSI), UMR9197 CNRS/University Paris Sud CNRS, Building 32/33, 1 Avenue de la Terrasse, 91190 Gif-sur-Yvette, France
- Institut Pasteur, INSERM, Institut de l’Audition, 63 rue de Charenton, F-75012 Paris, France
- Corresponding author. (E.R.H.); (B.B.)
| | - Anthony Renard
- Department for Integrative and Computational Neuroscience (ICN), Paris-Saclay Institute of Neuroscience (NeuroPSI), UMR9197 CNRS/University Paris Sud CNRS, Building 32/33, 1 Avenue de la Terrasse, 91190 Gif-sur-Yvette, France
- Institut Pasteur, INSERM, Institut de l’Audition, 63 rue de Charenton, F-75012 Paris, France
| | - Brice Bathellier
- Department for Integrative and Computational Neuroscience (ICN), Paris-Saclay Institute of Neuroscience (NeuroPSI), UMR9197 CNRS/University Paris Sud CNRS, Building 32/33, 1 Avenue de la Terrasse, 91190 Gif-sur-Yvette, France
- Institut Pasteur, INSERM, Institut de l’Audition, 63 rue de Charenton, F-75012 Paris, France
- Corresponding author. (E.R.H.); (B.B.)
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28
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Broussard GJ, Petreanu L. Eavesdropping wires: Recording activity in axons using genetically encoded calcium indicators. J Neurosci Methods 2021; 360:109251. [PMID: 34119572 PMCID: PMC8363211 DOI: 10.1016/j.jneumeth.2021.109251] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 05/31/2021] [Accepted: 06/05/2021] [Indexed: 12/23/2022]
Abstract
Neurons broadcast electrical signals to distal brain regions through extensive axonal arbors. Genetically encoded calcium sensors permit the direct observation of action potential activity at axonal terminals, providing unique insights on the organization and function of neural projections. Here, we consider what information can be gleaned from axonal recordings made at scales ranging from the summed activity extracted from multi-cell axon projections to single boutons. In particular, we discuss the application of different recently developed multi photon and fiber photometry methods for recording neural activity in axons of rodents. We define experimental difficulties associated with imaging approaches in the axonal compartment and highlight the latest methodological advances for addressing these issues. Finally, we reflect on ways in which new technologies can be used in conjunction with axon calcium imaging to address current questions in neurobiology.
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Affiliation(s)
| | - Leopoldo Petreanu
- Champalimaud Research, Champalimaud Center for the Unknown, Lisbon, Portugal.
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29
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Fast, cell-resolution, contiguous-wide two-photon imaging to reveal functional network architectures across multi-modal cortical areas. Neuron 2021; 109:1810-1824.e9. [PMID: 33878295 DOI: 10.1016/j.neuron.2021.03.032] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 02/11/2021] [Accepted: 03/25/2021] [Indexed: 02/07/2023]
Abstract
Fast and wide field-of-view imaging with single-cell resolution, high signal-to-noise ratio, and no optical aberrations have the potential to inspire new avenues of investigations in biology. However, such imaging is challenging because of the inevitable tradeoffs among these parameters. Here, we overcome these tradeoffs by combining a resonant scanning system, a large objective with low magnification and high numerical aperture, and highly sensitive large-aperture photodetectors. The result is a practically aberration-free, fast-scanning high optical invariant two-photon microscopy (FASHIO-2PM) that enables calcium imaging from a large network composed of ∼16,000 neurons at 7.5 Hz from a 9 mm2 contiguous image plane, including more than 10 sensory-motor and higher-order areas of the cerebral cortex in awake mice. Network analysis based on single-cell activities revealed that the brain exhibits small-world rather than scale-free behavior. The FASHIO-2PM is expected to enable studies on biological dynamics by simultaneously monitoring macroscopic activities and their compositional elements.
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30
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Burns TF, Rajan R. Sensing and processing whisker deflections in rodents. PeerJ 2021; 9:e10730. [PMID: 33665005 PMCID: PMC7906041 DOI: 10.7717/peerj.10730] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 12/17/2020] [Indexed: 11/20/2022] Open
Abstract
The classical view of sensory information mainly flowing into barrel cortex at layer IV, moving up for complex feature processing and lateral interactions in layers II and III, then down to layers V and VI for output and corticothalamic feedback is becoming increasingly undermined by new evidence. We review the neurophysiology of sensing and processing whisker deflections, emphasizing the general processing and organisational principles present along the entire sensory pathway—from the site of physical deflection at the whiskers to the encoding of deflections in the barrel cortex. Many of these principles support the classical view. However, we also highlight the growing number of exceptions to these general principles, which complexify the system and which investigators should be mindful of when interpreting their results. We identify gaps in the literature for experimentalists and theorists to investigate, not just to better understand whisker sensation but also to better understand sensory and cortical processing.
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Affiliation(s)
- Thomas F Burns
- Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia
| | - Ramesh Rajan
- Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia
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31
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Bale MR, Bitzidou M, Giusto E, Kinghorn P, Maravall M. Sequence Learning Induces Selectivity to Multiple Task Parameters in Mouse Somatosensory Cortex. Curr Biol 2021; 31:473-485.e5. [PMID: 33186553 PMCID: PMC7883307 DOI: 10.1016/j.cub.2020.10.059] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 09/01/2020] [Accepted: 10/20/2020] [Indexed: 11/20/2022]
Abstract
Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. To explore how cortical neuronal activity underpins sequence discrimination, we developed a task in which mice distinguished between tactile "word" sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Mice could respond to the earliest possible cues allowing discrimination, effectively solving the task as a "detection of change" problem, but enhanced their performance when responding later. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory "barrel" cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal's action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal's learned action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were found in naive mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf, sequence learning results in neurons whose activity reflects the learned association between target sequence and licking rather than a refined representation of sensory features.
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Affiliation(s)
- Michael R Bale
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Malamati Bitzidou
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Elena Giusto
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Paul Kinghorn
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Miguel Maravall
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK.
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32
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Cortical Localization of the Sensory-Motor Transformation in a Whisker Detection Task in Mice. eNeuro 2021; 8:ENEURO.0004-21.2021. [PMID: 33495240 PMCID: PMC7901152 DOI: 10.1523/eneuro.0004-21.2021] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 01/08/2021] [Indexed: 11/21/2022] Open
Abstract
Responding to a stimulus requires transforming an internal sensory representation into an internal motor representation. Where and how this sensory-motor transformation occurs is a matter of vigorous debate. Here, we trained male and female mice in a whisker detection go/no-go task in which they learned to respond (lick) following a transient whisker deflection. Using single unit recordings, we quantified sensory-related, motor-related, and choice-related activities in whisker primary somatosensory cortex (S1), whisker region of primary motor cortex (wMC), and anterior lateral motor cortex (ALM), three regions that have been proposed to be critical for the sensory-motor transformation in whisker detection. We observed strong sensory encoding in S1 and wMC, with enhanced encoding in wMC, and a lack of sensory encoding in ALM. We observed strong motor encoding in all three regions, yet largest in wMC and ALM. We observed the earliest choice probability in wMC, despite earliest sensory responses in S1. Based on the criteria of having both strong sensory and motor representations and early choice probability, we identify whisker motor cortex as the cortical region most directly related to the sensory-motor transformation. Our data support a model of sensory encoding originating in S1, sensory amplification and sensory-motor transformation occurring within wMC, and motor signals emerging in ALM after the sensory-motor transformation.
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33
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Whitesell JD, Liska A, Coletta L, Hirokawa KE, Bohn P, Williford A, Groblewski PA, Graddis N, Kuan L, Knox JE, Ho A, Wakeman W, Nicovich PR, Nguyen TN, van Velthoven CTJ, Garren E, Fong O, Naeemi M, Henry AM, Dee N, Smith KA, Levi B, Feng D, Ng L, Tasic B, Zeng H, Mihalas S, Gozzi A, Harris JA. Regional, Layer, and Cell-Type-Specific Connectivity of the Mouse Default Mode Network. Neuron 2020; 109:545-559.e8. [PMID: 33290731 PMCID: PMC8150331 DOI: 10.1016/j.neuron.2020.11.011] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 10/08/2020] [Accepted: 11/13/2020] [Indexed: 12/28/2022]
Abstract
The evolutionarily conserved default mode network (DMN) is a distributed set of brain regions coactivated during resting states that is vulnerable to brain disorders. How disease affects the DMN is unknown, but detailed anatomical descriptions could provide clues. Mice offer an opportunity to investigate structural connectivity of the DMN across spatial scales with cell-type resolution. We co-registered maps from functional magnetic resonance imaging and axonal tracing experiments into the 3D Allen mouse brain reference atlas. We find that the mouse DMN consists of preferentially interconnected cortical regions. As a population, DMN layer 2/3 (L2/3) neurons project almost exclusively to other DMN regions, whereas L5 neurons project in and out of the DMN. In the retrosplenial cortex, a core DMN region, we identify two L5 projection types differentiated by in- or out-DMN targets, laminar position, and gene expression. These results provide a multi-scale description of the anatomical correlates of the mouse DMN. Mouse resting-state default mode network anatomy described at high resolution in 3D Systematic axon tracing shows cortical DMN regions are preferentially interconnected Layer 2/3 DMN neurons project mostly in the DMN; layer 5 neurons project in and out Retrosplenial cortex contains distinct types of in- and out-DMN projection neurons
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Affiliation(s)
| | - Adam Liska
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto, Italy; DeepMind, London EC4A 3TW, UK
| | - Ludovico Coletta
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto, Italy; Center for Mind/Brain Sciences (CIMeC), University of Trento, 38068 Rovereto, Italy
| | | | - Phillip Bohn
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Ali Williford
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Nile Graddis
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Leonard Kuan
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Joseph E Knox
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Anh Ho
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Wayne Wakeman
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | - Emma Garren
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Olivia Fong
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Maitham Naeemi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Alex M Henry
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Boaz Levi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - David Feng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Stefan Mihalas
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto, Italy
| | - Julie A Harris
- Allen Institute for Brain Science, Seattle, WA 98109, USA.
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34
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Semedo JD, Gokcen E, Machens CK, Kohn A, Yu BM. Statistical methods for dissecting interactions between brain areas. Curr Opin Neurobiol 2020; 65:59-69. [PMID: 33142111 PMCID: PMC7935404 DOI: 10.1016/j.conb.2020.09.009] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 09/23/2020] [Accepted: 09/24/2020] [Indexed: 12/12/2022]
Abstract
The brain is composed of many functionally distinct areas. This organization supports distributed processing, and requires the coordination of signals across areas. Our understanding of how populations of neurons in different areas interact with each other is still in its infancy. As the availability of recordings from large populations of neurons across multiple brain areas increases, so does the need for statistical methods that are well suited for dissecting and interrogating these recordings. Here we review multivariate statistical methods that have been, or could be, applied to this class of recordings. By leveraging population responses, these methods can provide a rich description of inter-areal interactions. At the same time, these methods can introduce interpretational challenges. We thus conclude by discussing how to interpret the outputs of these methods to further our understanding of inter-areal interactions.
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Affiliation(s)
- João D Semedo
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Evren Gokcen
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Christian K Machens
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Adam Kohn
- Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Byron M Yu
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
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35
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Gallero-Salas Y, Han S, Sych Y, Voigt FF, Laurenczy B, Gilad A, Helmchen F. Sensory and Behavioral Components of Neocortical Signal Flow in Discrimination Tasks with Short-Term Memory. Neuron 2020; 109:135-148.e6. [PMID: 33159842 DOI: 10.1016/j.neuron.2020.10.017] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 09/13/2020] [Accepted: 10/12/2020] [Indexed: 12/30/2022]
Abstract
In the neocortex, each sensory modality engages distinct sensory areas that route information to association areas. Where signal flow converges for maintaining information in short-term memory and how behavior may influence signal routing remain open questions. Using wide-field calcium imaging, we compared cortex-wide neuronal activity in layer 2/3 for mice trained in auditory and tactile tasks with delayed response. In both tasks, mice were either active or passive during stimulus presentation, moving their body or sitting quietly. Irrespective of behavioral strategy, auditory and tactile stimulation activated distinct subdivisions of the posterior parietal cortex, anterior area A and rostrolateral area RL, which held stimulus-related information necessary for the respective tasks. In the delay period, in contrast, behavioral strategy rather than sensory modality determined short-term memory location, with activity converging frontomedially in active trials and posterolaterally in passive trials. Our results suggest behavior-dependent routing of sensory-driven cortical signals flow from modality-specific posterior parietal cortex (PPC) subdivisions to higher association areas.
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Affiliation(s)
- Yasir Gallero-Salas
- Brain Research Institute, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, Zurich, Switzerland
| | - Shuting Han
- Brain Research Institute, University of Zurich, Zurich, Switzerland
| | - Yaroslav Sych
- Brain Research Institute, University of Zurich, Zurich, Switzerland
| | - Fabian F Voigt
- Brain Research Institute, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, Zurich, Switzerland
| | - Balazs Laurenczy
- Brain Research Institute, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, Zurich, Switzerland
| | - Ariel Gilad
- Brain Research Institute, University of Zurich, Zurich, Switzerland; Department of Medical Neurobiology, Institute for Medical Research Israel Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Fritjof Helmchen
- Brain Research Institute, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, Zurich, Switzerland.
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36
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Kim J, Erskine A, Cheung JA, Hires SA. Behavioral and Neural Bases of Tactile Shape Discrimination Learning in Head-Fixed Mice. Neuron 2020; 108:953-967.e8. [PMID: 33002411 DOI: 10.1016/j.neuron.2020.09.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 07/31/2020] [Accepted: 09/08/2020] [Indexed: 11/29/2022]
Abstract
Tactile shape recognition requires the perception of object surface angles. We investigate how neural representations of object angles are constructed from sensory input and how they reorganize across learning. Head-fixed mice learned to discriminate object angles by active exploration with one whisker. Calcium imaging of layers 2-4 of the barrel cortex revealed maps of object-angle tuning before and after learning. Three-dimensional whisker tracking demonstrated that the sensory input components that best discriminate angles (vertical bending and slide distance) also have the greatest influence on object-angle tuning. Despite the high turnover in active ensemble membership across learning, the population distribution of object-angle tuning preferences remained stable. Angle tuning sharpened, but only in neurons that preferred trained angles. This was correlated with a selective increase in the influence of the most task-relevant sensory component on object-angle tuning. These results show how discrimination training enhances stimulus selectivity in the primary somatosensory cortex while maintaining perceptual stability.
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Affiliation(s)
- Jinho Kim
- Department of Biological Sciences, Section of Neurobiology, University of Southern California, Los Angeles, CA 90089, USA
| | - Andrew Erskine
- Department of Biological Sciences, Section of Neurobiology, University of Southern California, Los Angeles, CA 90089, USA
| | - Jonathan Andrew Cheung
- Department of Biological Sciences, Section of Neurobiology, University of Southern California, Los Angeles, CA 90089, USA
| | - Samuel Andrew Hires
- Department of Biological Sciences, Section of Neurobiology, University of Southern California, Los Angeles, CA 90089, USA.
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37
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Milosevic MM, Jang J, McKimm EJ, Zhu MH, Antic SD. In Vitro Testing of Voltage Indicators: Archon1, ArcLightD, ASAP1, ASAP2s, ASAP3b, Bongwoori-Pos6, BeRST1, FlicR1, and Chi-VSFP-Butterfly. eNeuro 2020; 7:ENEURO.0060-20.2020. [PMID: 32817120 PMCID: PMC7540930 DOI: 10.1523/eneuro.0060-20.2020] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 08/03/2020] [Accepted: 08/09/2020] [Indexed: 01/04/2023] Open
Abstract
Genetically encoded voltage indicators (GEVIs) could potentially be used for mapping neural circuits at the plane of synaptic potentials and plateau potentials-two blind spots of GCaMP-based imaging. In the last year alone, several laboratories reported significant breakthroughs in the quality of GEVIs and the efficacy of the voltage imaging equipment. One major obstacle of using well performing GEVIs in the pursuit of interesting biological data is the process of transferring GEVIs between laboratories, as their reported qualities (e.g., membrane targeting, brightness, sensitivity, optical signal quality) are often difficult to reproduce outside of the laboratory of the GEVI origin. We have tested eight available GEVIs (Archon1, ArcLightD, ASAP1, ASAP2s, ASAP3b, Bongwoori-Pos6, FlicR1, and chi-VSFP-Butterfly) and two voltage-sensitive dyes (BeRST1 and di-4-ANEPPS). We used the same microscope, lens, and optical detector, while the light sources were interchanged. GEVI voltage imaging was attempted in the following three preparations: (1) cultured neurons, (2) HEK293 cells, and (3) mouse brain slices. Systematic measurements were successful only in HEK293 cells and brain slices. Despite the significant differences in brightness and dynamic response (ON rate), all tested indicators produced reasonable optical signals in brain slices and solid in vitro quality properties, in the range initially reported by the creator laboratories. Side-by-side comparisons between GEVIs and organic dyes obtained in HEK293 cells and brain slices by a "third party" (current data) will be useful for determining the right voltage indicator for a given research application.
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Affiliation(s)
- Milena M Milosevic
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
- Center for Laser Microscopy, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Jinyoung Jang
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
| | - Eric J McKimm
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
| | - Mei Hong Zhu
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
| | - Srdjan D Antic
- Institute for Systems Genomics, Department of Neuroscience, UConn School of Medicine, Farmington, Connecticut 06030
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38
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Kohn A, Jasper AI, Semedo JD, Gokcen E, Machens CK, Yu BM. Principles of Corticocortical Communication: Proposed Schemes and Design Considerations. Trends Neurosci 2020; 43:725-737. [PMID: 32771224 PMCID: PMC7484382 DOI: 10.1016/j.tins.2020.07.001] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 07/01/2020] [Accepted: 07/05/2020] [Indexed: 12/22/2022]
Abstract
Nearly all brain functions involve routing neural activity among a distributed network of areas. Understanding this routing requires more than a description of interareal anatomical connectivity: it requires understanding what controls the flow of signals through interareal circuitry and how this communication might be modulated to allow flexible behavior. Here we review proposals of how communication, particularly between visual cortical areas, is instantiated and modulated, highlighting recent work that offers new perspectives. We suggest transitioning from a focus on assessing changes in the strength of interareal interactions, as often seen in studies of interareal communication, to a broader consideration of how different signaling schemes might contribute to computation. To this end, we discuss a set of features that might be desirable for a communication scheme.
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Affiliation(s)
- Adam Kohn
- Dominik Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, NY, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, New York, NY, USA; Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, NY, USA.
| | - Anna I Jasper
- Dominik Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, NY, USA
| | - João D Semedo
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Evren Gokcen
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Christian K Machens
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Byron M Yu
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
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39
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Staiger JF, Petersen CCH. Neuronal Circuits in Barrel Cortex for Whisker Sensory Perception. Physiol Rev 2020; 101:353-415. [PMID: 32816652 DOI: 10.1152/physrev.00019.2019] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The array of whiskers on the snout provides rodents with tactile sensory information relating to the size, shape and texture of objects in their immediate environment. Rodents can use their whiskers to detect stimuli, distinguish textures, locate objects and navigate. Important aspects of whisker sensation are thought to result from neuronal computations in the whisker somatosensory cortex (wS1). Each whisker is individually represented in the somatotopic map of wS1 by an anatomical unit named a 'barrel' (hence also called barrel cortex). This allows precise investigation of sensory processing in the context of a well-defined map. Here, we first review the signaling pathways from the whiskers to wS1, and then discuss current understanding of the various types of excitatory and inhibitory neurons present within wS1. Different classes of cells can be defined according to anatomical, electrophysiological and molecular features. The synaptic connectivity of neurons within local wS1 microcircuits, as well as their long-range interactions and the impact of neuromodulators, are beginning to be understood. Recent technological progress has allowed cell-type-specific connectivity to be related to cell-type-specific activity during whisker-related behaviors. An important goal for future research is to obtain a causal and mechanistic understanding of how selected aspects of tactile sensory information are processed by specific types of neurons in the synaptically connected neuronal networks of wS1 and signaled to downstream brain areas, thus contributing to sensory-guided decision-making.
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Affiliation(s)
- Jochen F Staiger
- University Medical Center Göttingen, Institute for Neuroanatomy, Göttingen, Germany; and Laboratory of Sensory Processing, Faculty of Life Sciences, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Carl C H Petersen
- University Medical Center Göttingen, Institute for Neuroanatomy, Göttingen, Germany; and Laboratory of Sensory Processing, Faculty of Life Sciences, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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40
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Vavladeli A, Daigle T, Zeng H, Crochet S, Petersen CCH. Projection-specific Activity of Layer 2/3 Neurons Imaged in Mouse Primary Somatosensory Barrel Cortex During a Whisker Detection Task. FUNCTION (OXFORD, ENGLAND) 2020; 1:zqaa008. [PMID: 35330741 PMCID: PMC8788860 DOI: 10.1093/function/zqaa008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 06/27/2020] [Accepted: 06/29/2020] [Indexed: 01/06/2023]
Abstract
The brain processes sensory information in a context- and learning-dependent manner for adaptive behavior. Through reward-based learning, relevant sensory stimuli can become linked to execution of specific actions associated with positive outcomes. The neuronal circuits involved in such goal-directed sensory-to-motor transformations remain to be precisely determined. Studying simple learned sensorimotor transformations in head-restrained mice offers the opportunity for detailed measurements of cellular activity during task performance. Here, we trained mice to lick a reward spout in response to a whisker deflection and an auditory tone. Through two-photon calcium imaging of retrogradely labeled neurons, we found that neurons located in primary whisker somatosensory barrel cortex projecting to secondary whisker somatosensory cortex had larger calcium signals than neighboring neurons projecting to primary whisker motor cortex in response to whisker deflection and auditory stimulation, as well as before spontaneous licking. Longitudinal imaging of the same neurons revealed that these projection-specific responses were relatively stable across 3 days. In addition, the activity of neurons projecting to secondary whisker somatosensory cortex was more highly correlated than for neurons projecting to primary whisker motor cortex. The large and correlated activity of neurons projecting to secondary whisker somatosensory cortex might enhance the pathway-specific signaling of important sensory information contributing to task execution. Our data support the hypothesis that communication between primary and secondary somatosensory cortex might be an early critical step in whisker sensory perception. More generally, our data suggest the importance of investigating projection-specific neuronal activity in distinct populations of intermingled excitatory neocortical neurons during task performance.
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Affiliation(s)
- Angeliki Vavladeli
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tanya Daigle
- Allen Institute for Brain Science, Seattle, Washington, DC, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, Washington, DC, USA
| | - Sylvain Crochet
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Carl C H Petersen
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Corresponding author. E-mail:
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41
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Mohr MA, Bushey D, Aggarwal A, Marvin JS, Kim JJ, Marquez EJ, Liang Y, Patel R, Macklin JJ, Lee CY, Tsang A, Tsegaye G, Ahrens AM, Chen JL, Kim DS, Wong AM, Looger LL, Schreiter ER, Podgorski K. jYCaMP: an optimized calcium indicator for two-photon imaging at fiber laser wavelengths. Nat Methods 2020; 17:694-697. [PMID: 32451475 PMCID: PMC7335340 DOI: 10.1038/s41592-020-0835-7] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 04/14/2020] [Indexed: 11/09/2022]
Abstract
Femtosecond lasers at fixed wavelengths above 1,000 nm are powerful, stable and inexpensive, making them promising sources for two-photon microscopy. Biosensors optimized for these wavelengths are needed for both next-generation microscopes and affordable turn-key systems. Here we report jYCaMP1, a yellow variant of the calcium indicator jGCaMP7 that outperforms its parent in mice and flies at excitation wavelengths above 1,000 nm and enables improved two-color calcium imaging with red fluorescent protein-based indicators.
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Affiliation(s)
- Manuel Alexander Mohr
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule Zurich, Basel, Switzerland
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Daniel Bushey
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Abhi Aggarwal
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Department of Chemistry, University of Alberta, Edmonton, Alberta, Canada
| | - Jonathan S Marvin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jeong Jun Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Emiliano Jimenez Marquez
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Universidad Nacional Autonoma de Mexico, Mexico, Mexico
| | - Yajie Liang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- GENIE Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Ronak Patel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - John J Macklin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Chi-Yu Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Arthur Tsang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- GENIE Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Getahun Tsegaye
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- GENIE Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Jerry L Chen
- Department of Biology, Boston University, Boston, MA, USA
| | - Douglas S Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- GENIE Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Allan M Wong
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- GENIE Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Loren L Looger
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- GENIE Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Eric R Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- GENIE Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kaspar Podgorski
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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42
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Fundamental bounds on the fidelity of sensory cortical coding. Nature 2020; 580:100-105. [PMID: 32238928 DOI: 10.1038/s41586-020-2130-2] [Citation(s) in RCA: 111] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Accepted: 01/21/2020] [Indexed: 12/13/2022]
Abstract
How the brain processes information accurately despite stochastic neural activity is a longstanding question1. For instance, perception is fundamentally limited by the information that the brain can extract from the noisy dynamics of sensory neurons. Seminal experiments2,3 suggest that correlated noise in sensory cortical neural ensembles is what limits their coding accuracy4-6, although how correlated noise affects neural codes remains debated7-11. Recent theoretical work proposes that how a neural ensemble's sensory tuning properties relate statistically to its correlated noise patterns is a greater determinant of coding accuracy than is absolute noise strength12-14. However, without simultaneous recordings from thousands of cortical neurons with shared sensory inputs, it is unknown whether correlated noise limits coding fidelity. Here we present a 16-beam, two-photon microscope to monitor activity across the mouse primary visual cortex, along with analyses to quantify the information conveyed by large neural ensembles. We found that, in the visual cortex, correlated noise constrained signalling for ensembles with 800-1,300 neurons. Several noise components of the ensemble dynamics grew proportionally to the ensemble size and the encoded visual signals, revealing the predicted information-limiting correlations12-14. Notably, visual signals were perpendicular to the largest noise mode, which therefore did not limit coding fidelity. The information-limiting noise modes were approximately ten times smaller and concordant with mouse visual acuity15. Therefore, cortical design principles appear to enhance coding accuracy by restricting around 90% of noise fluctuations to modes that do not limit signalling fidelity, whereas much weaker correlated noise modes inherently bound sensory discrimination.
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43
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Condylis C, Lowet E, Ni J, Bistrong K, Ouellette T, Josephs N, Chen JL. Context-Dependent Sensory Processing across Primary and Secondary Somatosensory Cortex. Neuron 2020; 106:515-525.e5. [PMID: 32164873 DOI: 10.1016/j.neuron.2020.02.004] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 11/11/2019] [Accepted: 02/06/2020] [Indexed: 12/16/2022]
Abstract
To interpret the environment, our brain must evaluate external stimuli against internal representations from past experiences. How primary (S1) and secondary (S2) somatosensory cortices process stimuli depending on recent experiences is unclear. Using simultaneous multi-area population imaging of projection neurons and focal optogenetic inactivation, we studied mice performing a whisker-based working memory task. We find that activity reflecting a current stimulus, the recollection of a previous stimulus (cued recall), and the stimulus category are distributed across S1 and S2. Despite this overlapping representation, S2 is important for processing cued recall responses and transmitting these responses to S1. S2 network properties differ from S1, wherein S2 persistently encodes cued recall and the stimulus category under passive conditions. Although both areas encode the stimulus category, only information in S1 is important for task performance through pathways that do not necessarily include S2. These findings reveal both distributed and segregated roles for S1 and S2 in context-dependent sensory processing.
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Affiliation(s)
- Cameron Condylis
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Eric Lowet
- Department of Biology, Boston University, Boston, MA 02215, USA; Center for Systems Neuroscience, Boston University, Boston, MA 02215, USA
| | - Jianguang Ni
- Department of Biology, Boston University, Boston, MA 02215, USA; Center for Systems Neuroscience, Boston University, Boston, MA 02215, USA
| | - Karina Bistrong
- Department of Biology, Boston University, Boston, MA 02215, USA
| | | | - Nathaniel Josephs
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Department of Biology, Boston University, Boston, MA 02215, USA; Center for Systems Neuroscience, Boston University, Boston, MA 02215, USA.
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44
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Simultaneous multiplane imaging with reverberation two-photon microscopy. Nat Methods 2020; 17:283-286. [PMID: 32042186 DOI: 10.1038/s41592-019-0728-9] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2019] [Accepted: 12/19/2019] [Indexed: 11/08/2022]
Abstract
Multiphoton microscopy has gained enormous popularity because of its unique capacity to provide high-resolution images from deep within scattering tissue. Here, we demonstrate video-rate multiplane imaging with two-photon microscopy by performing near-instantaneous axial scanning while maintaining three-dimensional micrometer-scale resolution. Our technique, termed reverberation microscopy, enables the monitoring of neuronal populations over large depth ranges and can be implemented as a simple add-on to a conventional design.
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45
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Lee CR, Najafizadeh L, Margolis DJ. Investigating learning-related neural circuitry with chronic in vivo optical imaging. Brain Struct Funct 2020; 225:467-480. [PMID: 32006147 DOI: 10.1007/s00429-019-02001-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 12/05/2019] [Indexed: 10/25/2022]
Abstract
Fundamental aspects of brain function, including development, plasticity, learning, and memory, can take place over time scales of days to years. Chronic in vivo imaging of neural activity with cellular resolution is a powerful method for tracking the long-term activity of neural circuits. We review recent advances in our understanding of neural circuit function from diverse brain regions that have been enabled by chronic in vivo cellular imaging. Insight into the neural basis of learning and decision-making, in particular, benefit from the ability to acquire longitudinal data from genetically identified neuronal populations, deep brain areas, and subcellular structures. We propose that combining chronic imaging with further experimental and computational innovations will advance our understanding of the neural circuit mechanisms of brain function.
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Affiliation(s)
- Christian R Lee
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA
| | - Laleh Najafizadeh
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA
| | - David J Margolis
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
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46
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47
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Yang M, Zhou Z, Zhang J, Jia S, Li T, Guan J, Liao X, Leng B, Lyu J, Zhang K, Li M, Gong Y, Zhu Z, Yan J, Zhou Y, Liu JK, Varga Z, Konnerth A, Tang Y, Gao J, Chen X, Jia H. MATRIEX imaging: multiarea two-photon real-time in vivo explorer. LIGHT, SCIENCE & APPLICATIONS 2019; 8:109. [PMID: 31798848 PMCID: PMC6881438 DOI: 10.1038/s41377-019-0219-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 10/31/2019] [Accepted: 11/05/2019] [Indexed: 06/01/2023]
Abstract
Two-photon laser scanning microscopy has been extensively applied to study in vivo neuronal activity at cellular and subcellular resolutions in mammalian brains. However, the extent of such studies is typically confined to a single functional region of the brain. Here, we demonstrate a novel technique, termed the multiarea two-photon real-time in vivo explorer (MATRIEX), that allows the user to target multiple functional brain regions distributed within a zone of up to 12 mm in diameter, each with a field of view (FOV) of ~200 μm in diameter, thus performing two-photon Ca2+ imaging with single-cell resolution in all of the regions simultaneously. For example, we demonstrate real-time functional imaging of single-neuron activities in the primary visual cortex, primary motor cortex and hippocampal CA1 region of mice in both anesthetized and awake states. A unique advantage of the MATRIEX technique is the configuration of multiple microscopic FOVs that are distributed in three-dimensional space over macroscopic distances (>1 mm) both laterally and axially but that are imaged by a single conventional laser scanning device. In particular, the MATRIEX technique can be effectively implemented as an add-on optical module for an existing conventional single-beam-scanning two-photon microscope without requiring any modification to the microscope itself. Thus, the MATRIEX technique can be readily applied to substantially facilitate the exploration of multiarea neuronal activity in vivo for studies of brain-wide neural circuit function with single-cell resolution.
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Affiliation(s)
- Mengke Yang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, 130033 China
- Graduate School, University of the Chinese Academy of Sciences, Beijing, 100039 China
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Zhenqiao Zhou
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Jianxiong Zhang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Shanshan Jia
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Tong Li
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Jiangheng Guan
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Xiang Liao
- Center for Neurointelligence, Chongqing University, Chongqing, 401331 China
| | - Bing Leng
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Jing Lyu
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Kuan Zhang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Min Li
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Yan Gong
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Zhiming Zhu
- Center for Hypertension and Metabolic Diseases, Daping Hospital, Chongqing, 400042 China
| | - Junan Yan
- Advanced Institute of Brain and Intelligence, Guangxi University, Nanning, 530005 China
| | - Yi Zhou
- Advanced Institute of Brain and Intelligence, Guangxi University, Nanning, 530005 China
| | - Jian K Liu
- Centre for Systems Neuroscience, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
| | - Zsuzsanna Varga
- Institute of Neuroscience, Technical University Munich, 80802 Munich, Germany
| | - Arthur Konnerth
- Institute of Neuroscience, Technical University Munich, 80802 Munich, Germany
| | - Yuguo Tang
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
| | - Jinsong Gao
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, 130033 China
| | - Xiaowei Chen
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038 China
| | - Hongbo Jia
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 China
- Institute of Neuroscience, Technical University Munich, 80802 Munich, Germany
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48
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Clough M, Chen JL. CELLULAR RESOLUTION IMAGING OF NEURONAL ACTIVITY ACROSS SPACE AND TIME IN THE MAMMALIAN BRAIN. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2019; 12:95-101. [PMID: 32104747 DOI: 10.1016/j.cobme.2019.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
While the action potential has long been understood to be the fundamental bit of information in brain, how these spikes encode representations of stimuli and drive behavior remains unclear. Large-scale neuronal recordings with cellular and spike-time resolution spanning multiple brain regions are needed to capture relevant network dynamics that can be sparse and distributed across the population. This review focuses on recent advancements in optical methods that have pushed the boundaries for simultaneous population recordings at increasing volumes, distances, depths, and speeds. The integration of these technologies will be critical for overcoming fundamental limits in the pursuit of whole brain imaging in mammalian species.
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Affiliation(s)
- Mitchell Clough
- Department of Biomedical Engineering, Boston University, Boston, USA.,Department of Biology, Boston University, Boston, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, USA.,Department of Biology, Boston University, Boston, USA.,Center for Neurophotonics, Boston University, Boston, USA
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49
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A Non-canonical Feedback Circuit for Rapid Interactions between Somatosensory Cortices. Cell Rep 2019; 23:2718-2731.e6. [PMID: 29847801 PMCID: PMC6004823 DOI: 10.1016/j.celrep.2018.04.115] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 03/20/2018] [Accepted: 04/26/2018] [Indexed: 12/17/2022] Open
Abstract
Sensory perception depends on interactions among cortical areas. These
interactions are mediated by canonical patterns of connectivity in which higher
areas send feedback projections to lower areas via neurons in superficial and
deep layers. Here, we probed the circuit basis of interactions among two areas
critical for touch perception in mice, whisker primary (wS1) and secondary (wS2)
somatosensory cortices. Neurons in layer 4 of wS2 (S2L4) formed a
major feedback pathway to wS1. Feedback from wS2 to wS1 was organized
somatotopically. Spikes evoked by whisker deflections occurred nearly as rapidly
in wS2 as in wS1, including among putative S2L4 → S1 feedback
neurons. Axons from S2L4 → S1 neurons sent stimulus
orientation-specific activity to wS1. Optogenetic excitation of S2L4
neurons modulated activity across both wS2 and wS1, while inhibition of
S2L4 reduced orientation tuning among wS1 neurons. Thus, a
non-canonical feedback circuit, originating in layer 4 of S2, rapidly modulates
early tactile processing.
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50
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Context-dependent limb movement encoding in neuronal populations of motor cortex. Nat Commun 2019; 10:4812. [PMID: 31645554 PMCID: PMC6811620 DOI: 10.1038/s41467-019-12670-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 09/23/2019] [Indexed: 12/24/2022] Open
Abstract
Neuronal networks of the mammalian motor cortex (M1) are important for dexterous control of limb joints. Yet it remains unclear how encoding of joint movement in M1 depends on varying environmental contexts. Using calcium imaging we measured neuronal activity in layer 2/3 of the M1 forelimb region while mice grasped regularly or irregularly spaced ladder rungs during locomotion. We found that population coding of forelimb joint movements is sparse and varies according to the flexibility demanded from individual joints in the regular and irregular context, even for equivalent grasping actions across conditions. This context-dependence of M1 encoding emerged during task learning, fostering higher precision of grasping actions, but broke apart upon silencing of projections from secondary motor cortex (M2). These findings suggest that M1 exploits information from M2 to adapt encoding of joint movements to the flexibility demands of distinct familiar contexts, thereby increasing the accuracy of motor output. Network activity in primary motor cortex (M1) controls dexterous limb movements. Here, the authors show that the M1 population code varies according to contextual motor demands that are conveyed via the secondary motor cortex (M2).
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