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Rich PD, Thiberge SY, Scott BB, Guo C, Tervo DGR, Brody CD, Karpova AY, Daw ND, Tank DW. Magnetic voluntary head-fixation in transgenic rats enables lifespan imaging of hippocampal neurons. Nat Commun 2024; 15:4154. [PMID: 38755205 PMCID: PMC11099169 DOI: 10.1038/s41467-024-48505-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 05/01/2024] [Indexed: 05/18/2024] Open
Abstract
The precise neural mechanisms within the brain that contribute to the remarkable lifetime persistence of memory are not fully understood. Two-photon calcium imaging allows the activity of individual cells to be followed across long periods, but conventional approaches require head-fixation, which limits the type of behavior that can be studied. We present a magnetic voluntary head-fixation system that provides stable optical access to the brain during complex behavior. Compared to previous systems that used mechanical restraint, there are no moving parts and animals can engage and disengage entirely at will. This system is failsafe, easy for animals to use and reliable enough to allow long-term experiments to be routinely performed. Animals completed hundreds of trials per session of an odor discrimination task that required 2-4 s fixations. Together with a reflectance fluorescence collection scheme that increases two-photon signal and a transgenic Thy1-GCaMP6f rat line, we are able to reliably image the cellular activity in the hippocampus during behavior over long periods (median 6 months), allowing us track the same neurons over a large fraction of animals' lives (up to 19 months).
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Affiliation(s)
- P Dylan Rich
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
| | | | - Benjamin B Scott
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Caiying Guo
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - D Gowanlock R Tervo
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Howard Hughes Medical Institute, Princeton University, Princeton, NJ, USA
| | - Alla Y Karpova
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Nathaniel D Daw
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Psychology, Princeton University, Princeton, NJ, USA
| | - David W Tank
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, USA.
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA.
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2
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Bolaños F, Orlandi JG, Aoki R, Jagadeesh AV, Gardner JL, Benucci A. Efficient coding of natural images in the mouse visual cortex. Nat Commun 2024; 15:2466. [PMID: 38503746 PMCID: PMC10951403 DOI: 10.1038/s41467-024-45919-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 02/06/2024] [Indexed: 03/21/2024] Open
Abstract
How the activity of neurons gives rise to natural vision remains a matter of intense investigation. The mid-level visual areas along the ventral stream are selective to a common class of natural images-textures-but a circuit-level understanding of this selectivity and its link to perception remains unclear. We addressed these questions in mice, first showing that they can perceptually discriminate between textures and statistically simpler spectrally matched stimuli, and between texture types. Then, at the neural level, we found that the secondary visual area (LM) exhibited a higher degree of selectivity for textures compared to the primary visual area (V1). Furthermore, textures were represented in distinct neural activity subspaces whose relative distances were found to correlate with the statistical similarity of the images and the mice's ability to discriminate between them. Notably, these dependencies were more pronounced in LM, where the texture-related subspaces were smaller than in V1, resulting in superior stimulus decoding capabilities. Together, our results demonstrate texture vision in mice, finding a linking framework between stimulus statistics, neural representations, and perceptual sensitivity-a distinct hallmark of efficient coding computations.
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Affiliation(s)
- Federico Bolaños
- University of British Columbia, Neuroimaging and NeuroComputation Centre, Vancouver, BC, V6T, Canada
| | - Javier G Orlandi
- University of Calgary, Department of Physics and Astronomy, Calgary, AB, T2N 1N4, Canada.
| | - Ryo Aoki
- RIKEN Center for Brain Science, Laboratory for Neural Circuits and Behavior, Wakoshi, Japan
| | | | - Justin L Gardner
- Stanford University, Wu Tsai Neurosciences Institute, Stanford, CA, USA
| | - Andrea Benucci
- RIKEN Center for Brain Science, Laboratory for Neural Circuits and Behavior, Wakoshi, Japan.
- Queen Mary, University of London, School of Biological and Behavioral Science, London, E1 4NS, UK.
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3
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Zhou ZC, Gordon-Fennell A, Piantadosi SC, Ji N, Smith SL, Bruchas MR, Stuber GD. Deep-brain optical recording of neural dynamics during behavior. Neuron 2023; 111:3716-3738. [PMID: 37804833 PMCID: PMC10843303 DOI: 10.1016/j.neuron.2023.09.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/24/2023] [Accepted: 09/06/2023] [Indexed: 10/09/2023]
Abstract
In vivo fluorescence recording techniques have produced landmark discoveries in neuroscience, providing insight into how single cell and circuit-level computations mediate sensory processing and generate complex behaviors. While much attention has been given to recording from cortical brain regions, deep-brain fluorescence recording is more complex because it requires additional measures to gain optical access to harder to reach brain nuclei. Here we discuss detailed considerations and tradeoffs regarding deep-brain fluorescence recording techniques and provide a comprehensive guide for all major steps involved, from project planning to data analysis. The goal is to impart guidance for new and experienced investigators seeking to use in vivo deep fluorescence optical recordings in awake, behaving rodent models.
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Affiliation(s)
- Zhe Charles Zhou
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Adam Gordon-Fennell
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Sean C Piantadosi
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Na Ji
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Spencer LaVere Smith
- Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Michael R Bruchas
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA; Department of Pharmacology, University of Washington, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
| | - Garret D Stuber
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA; Department of Pharmacology, University of Washington, Seattle, WA 98195, USA.
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4
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Michelson NJ, Bolaños F, Bolaños LA, Balbi M, LeDue JM, Murphy TH. Meso-Py: Dual Brain Cortical Calcium Imaging in Mice during Head-Fixed Social Stimulus Presentation. eNeuro 2023; 10:ENEURO.0096-23.2023. [PMID: 38053472 PMCID: PMC10731520 DOI: 10.1523/eneuro.0096-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 11/06/2023] [Accepted: 11/14/2023] [Indexed: 12/07/2023] Open
Abstract
We present a cost-effective, compact foot-print, and open-source Raspberry Pi-based widefield imaging system. The compact nature allows the system to be used for close-proximity dual-brain cortical mesoscale functional-imaging to simultaneously observe activity in two head-fixed animals in a staged social touch-like interaction. We provide all schematics, code, and protocols for a rail system where head-fixed mice are brought together to a distance where the macrovibrissae of each mouse make contact. Cortical neuronal functional signals (GCaMP6s; genetically encoded Ca2+ sensor) were recorded from both mice simultaneously before, during, and after the social contact period. When the mice were together, we observed bouts of mutual whisking and cross-mouse correlated cortical activity across the cortex. Correlations were not observed in trial-shuffled mouse pairs, suggesting that correlated activity was specific to individual interactions. Whisking-related cortical signals were observed during the period where mice were together (closest contact). The effects of social stimulus presentation extend outside of regions associated with mutual touch and have global synchronizing effects on cortical activity.
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Affiliation(s)
- Nicholas J Michelson
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Federico Bolaños
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Luis A Bolaños
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Matilde Balbi
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Jeffrey M LeDue
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Timothy H Murphy
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
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5
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Kim SJ, Affan RO, Frostig H, Scott BB, Alexander AS. Advances in cellular resolution microscopy for brain imaging in rats. NEUROPHOTONICS 2023; 10:044304. [PMID: 38076724 PMCID: PMC10704261 DOI: 10.1117/1.nph.10.4.044304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 09/23/2023] [Accepted: 11/07/2023] [Indexed: 02/12/2024]
Abstract
Rats are used in neuroscience research because of their physiological similarities with humans and accessibility as model organisms, trainability, and behavioral repertoire. In particular, rats perform a wide range of sophisticated social, cognitive, motor, and learning behaviors within the contexts of both naturalistic and laboratory environments. Further progress in neuroscience can be facilitated by using advanced imaging methods to measure the complex neural and physiological processes during behavior in rats. However, compared with the mouse, the rat nervous system offers a set of challenges, such as larger brain size, decreased neuron density, and difficulty with head restraint. Here, we review recent advances in in vivo imaging techniques in rats with a special focus on open-source solutions for calcium imaging. Finally, we provide suggestions for both users and developers of in vivo imaging systems for rats.
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Affiliation(s)
- Su Jin Kim
- Johns Hopkins University, Department of Psychological and Brain Sciences, Baltimore, Maryland, United States
| | - Rifqi O. Affan
- Boston University, Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston, Massachusetts, United States
- Boston University, Graduate Program in Neuroscience, Boston, Massachusetts, United States
| | - Hadas Frostig
- Boston University, Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston, Massachusetts, United States
| | - Benjamin B. Scott
- Boston University, Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston, Massachusetts, United States
- Boston University, Neurophotonics Center and Photonics Center, Boston, Massachusetts, United States
| | - Andrew S. Alexander
- University of California Santa Barbara, Department of Psychological and Brain Sciences, Santa Barbara, California, United States
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6
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Orlandi JG, Abdolrahmani M, Aoki R, Lyamzin DR, Benucci A. Distributed context-dependent choice information in mouse posterior cortex. Nat Commun 2023; 14:192. [PMID: 36635318 PMCID: PMC9837177 DOI: 10.1038/s41467-023-35824-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 01/03/2023] [Indexed: 01/14/2023] Open
Abstract
Choice information appears in multi-area brain networks mixed with sensory, motor, and cognitive variables. In the posterior cortex-traditionally implicated in decision computations-the presence, strength, and area specificity of choice signals are highly variable, limiting a cohesive understanding of their computational significance. Examining the mesoscale activity in the mouse posterior cortex during a visual task, we found that choice signals defined a decision variable in a low-dimensional embedding space with a prominent contribution along the ventral visual stream. Their subspace was near-orthogonal to concurrently represented sensory and motor-related activations, with modulations by task difficulty and by the animals' attention state. A recurrent neural network trained with animals' choices revealed an equivalent decision variable whose context-dependent dynamics agreed with that of the neural data. Our results demonstrated an independent, multi-area decision variable in the posterior cortex, controlled by task features and cognitive demands, possibly linked to contextual inference computations in dynamic animal-environment interactions.
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Affiliation(s)
- Javier G Orlandi
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan.,Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
| | | | - Ryo Aoki
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan
| | - Dmitry R Lyamzin
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan
| | - Andrea Benucci
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan. .,University of Tokyo, Graduate School of Information Science and Technology, Department of Mathematical Informatics, 1-1-1 Yayoi, Bunkyo City, Tokyo, 113-0032, Japan.
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7
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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: 2.0] [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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8
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Barkus C, Bergmann C, Branco T, Carandini M, Chadderton PT, Galiñanes GL, Gilmour G, Huber D, Huxter JR, Khan AG, King AJ, Maravall M, O'Mahony T, Ragan CI, Robinson ESJ, Schaefer AT, Schultz SR, Sengpiel F, Prescott MJ. Refinements to rodent head fixation and fluid/food control for neuroscience. J Neurosci Methods 2022; 381:109705. [PMID: 36096238 DOI: 10.1016/j.jneumeth.2022.109705] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 09/01/2022] [Accepted: 09/03/2022] [Indexed: 12/14/2022]
Abstract
The use of head fixation in mice is increasingly common in research, its use having initially been restricted to the field of sensory neuroscience. Head restraint has often been combined with fluid control, rather than food restriction, to motivate behaviour, but this too is now in use for both restrained and non-restrained animals. Despite this, there is little guidance on how best to employ these techniques to optimise both scientific outcomes and animal welfare. This article summarises current practices and provides recommendations to improve animal wellbeing and data quality, based on a survey of the community, literature reviews, and the expert opinion and practical experience of an international working group convened by the UK's National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs). Topics covered include head fixation surgery and post-operative care, habituation to restraint, and the use of fluid/food control to motivate performance. We also discuss some recent developments that may offer alternative ways to collect data from large numbers of behavioural trials without the need for restraint. The aim is to provide support for researchers at all levels, animal care staff, and ethics committees to refine procedures and practices in line with the refinement principle of the 3Rs.
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Affiliation(s)
- Chris Barkus
- National Centre for Replacement, Refinement and Reduction of Animals in Research (NC3Rs), London, UK.
| | | | - Tiago Branco
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Matteo Carandini
- Institute of Ophthalmology, University College London, London, UK
| | - Paul T Chadderton
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | | | | | - Daniel Huber
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
| | | | - Adil G Khan
- Centre for Developmental Neurobiology, King's College London, London, UK
| | - Andrew J King
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Miguel Maravall
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, UK
| | - Tina O'Mahony
- Sainsbury Wellcome Centre, University College London, London, UK
| | - C Ian Ragan
- National Centre for Replacement, Refinement and Reduction of Animals in Research (NC3Rs), London, UK
| | - Emma S J Robinson
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Andreas T Schaefer
- Sensory Circuits and Neurotechnology Laboratory, The Francis Crick Institute, London, UK; Department of Neuroscience, Physiology & Pharmacology, University College London, London, UK
| | - Simon R Schultz
- Centre for Neurotechnology and Department of Bioengineering, Imperial College London, London, UK
| | | | - Mark J Prescott
- National Centre for Replacement, Refinement and Reduction of Animals in Research (NC3Rs), London, UK
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9
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Calapai A, Cabrera-Moreno J, Moser T, Jeschke M. Flexible auditory training, psychophysics, and enrichment of common marmosets with an automated, touchscreen-based system. Nat Commun 2022; 13:1648. [PMID: 35347139 PMCID: PMC8960775 DOI: 10.1038/s41467-022-29185-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 02/28/2022] [Indexed: 11/09/2022] Open
Abstract
Devising new and more efficient protocols to analyze the phenotypes of non-human primates, as well as their complex nervous systems, is rapidly becoming of paramount importance. This is because with genome-editing techniques, recently adopted to non-human primates, new animal models for fundamental and translational research have been established. One aspect in particular, namely cognitive hearing, has been difficult to assess compared to visual cognition. To address this, we devised autonomous, standardized, and unsupervised training and testing of auditory capabilities of common marmosets with a cage-based standalone, wireless system. All marmosets tested voluntarily operated the device on a daily basis and went from naïve to experienced at their own pace and with ease. Through a series of experiments, here we show, that animals autonomously learn to associate sounds with images; to flexibly discriminate sounds, and to detect sounds of varying loudness. The developed platform and training principles combine in-cage training of common marmosets for cognitive and psychoacoustic assessment with an enriched environment that does not rely on dietary restriction or social separation, in compliance with the 3Rs principle. The authors present a cage-based stand-alone platform for autonomous, standardized, and unsupervised training and testing of visuo-auditory-cued behaviours of common marmosets. The experiments do not require dietary restriction or social separation.
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Affiliation(s)
- A Calapai
- Cognitive Neuroscience Laboratory, German Primate Center - Leibniz-Institute for Primate Research, Göttingen, Germany.,Cognitive Hearing in Primates (CHiP) Group, Auditory Neuroscience and Optogenetics Laboratory, German Primate Center - Leibniz-Institute for Primate Research, Göttingen, Germany.,Auditory Neuroscience and Optogenetics Laboratory, German Primate Center - Leibniz-Institute for Primate Research, Göttingen, Germany.,Leibniz ScienceCampus "Primate Cognition", Göttingen, Germany
| | - J Cabrera-Moreno
- Cognitive Hearing in Primates (CHiP) Group, Auditory Neuroscience and Optogenetics Laboratory, German Primate Center - Leibniz-Institute for Primate Research, Göttingen, Germany.,Auditory Neuroscience and Optogenetics Laboratory, German Primate Center - Leibniz-Institute for Primate Research, Göttingen, Germany.,Institute for Auditory Neuroscience and InnerEarLab, University Medical Center Göttingen, 37075, Göttingen, Germany.,Göttingen Graduate School for Neurosciences, Biophysics and Molecular Biosciences, University of Göttingen, 37075, Göttingen, Germany
| | - T Moser
- Auditory Neuroscience and Optogenetics Laboratory, German Primate Center - Leibniz-Institute for Primate Research, Göttingen, Germany.,Institute for Auditory Neuroscience and InnerEarLab, University Medical Center Göttingen, 37075, Göttingen, Germany.,Göttingen Graduate School for Neurosciences, Biophysics and Molecular Biosciences, University of Göttingen, 37075, Göttingen, Germany.,Auditory Neuroscience Group and Synaptic Nanophysiology Group, Max Planck Institute for Multidisciplinary Sciences, 37077, Göttingen, Germany.,Cluster of Excellence "Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells" (MBExC), University of Göttingen, 37075, Göttingen, Germany
| | - M Jeschke
- Cognitive Hearing in Primates (CHiP) Group, Auditory Neuroscience and Optogenetics Laboratory, German Primate Center - Leibniz-Institute for Primate Research, Göttingen, Germany. .,Auditory Neuroscience and Optogenetics Laboratory, German Primate Center - Leibniz-Institute for Primate Research, Göttingen, Germany. .,Leibniz ScienceCampus "Primate Cognition", Göttingen, Germany. .,Institute for Auditory Neuroscience and InnerEarLab, University Medical Center Göttingen, 37075, Göttingen, Germany.
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10
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A miniature kinematic coupling device for mouse head fixation. J Neurosci Methods 2022; 372:109549. [DOI: 10.1016/j.jneumeth.2022.109549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/22/2022] [Accepted: 02/26/2022] [Indexed: 11/18/2022]
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11
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Samejima S, Ievins AM, Boissenin A, Tolley NM, Khorasani A, Mondello SE, Moritz CT. Automated lever task with minimum antigravity movement for rats with cervical spinal cord injury. J Neurosci Methods 2022; 366:109433. [PMID: 34863839 DOI: 10.1016/j.jneumeth.2021.109433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 10/31/2021] [Accepted: 11/28/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Although there is currently no cure for paralysis due to spinal cord injury (SCI), the highest treatment priority is restoring arm and hand function for people with cervical SCI. Preclinical animal models provide an opportunity to test innovative treatments, but severe cervical injury models require significant time and effort to assess responses to novel interventions. Moreover, there is no behavioral task that can assess forelimb movement in rats with severe cervical SCI unable to perform antigravity movements. NEW METHOD We developed a novel lever pressing task for rats with severe cervical SCI. We employed an automated adaptive algorithm to train animals using open-source software and commercially available hardware. We found that using the adaptive training required only 13.3 ± 2.5 training days to achieve behavioral proficiency. The lever press task could quantify immediate and long-term improvements in severely impaired forelimb function effectively. This behavior platform has potential to facilitate rehabilitative training and assess effects of therapeutic modalities following SCI. COMPARISON WITH EXISTING METHODS There is no existing assessment aiming to quantify forelimb extension movement in rodents without function against gravity. We found that the new lever press task in the antigravity position could assess the severity of cervical SCI as well as the compensatory movement in the proximal forelimb less affected by the injury. CONCLUSIONS This study demonstrates that the new behavioral task is capable of tracking the functional changes with various therapies in rats with severe forelimb impairments in a cost- and time-efficient manner.
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Affiliation(s)
- Soshi Samejima
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, United States; Department of Electrical & Computer Engineering, University of Washington, Seattle, WA, United States; UW Institute for Neural Engineering, University of Washington, Seattle, WA, United States; The Center for Neurotechnology, University of Washington, Seattle, WA, United States
| | - Aiva M Ievins
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, United States; Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States
| | - Adrien Boissenin
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, United States
| | - Nicholas M Tolley
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, United States
| | - Abed Khorasani
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, United States
| | - Sarah E Mondello
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, United States
| | - Chet T Moritz
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, United States; Department of Electrical & Computer Engineering, University of Washington, Seattle, WA, United States; Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States; UW Institute for Neural Engineering, University of Washington, Seattle, WA, United States; The Center for Neurotechnology, University of Washington, Seattle, WA, United States; Department of Physiology & Biophysics, University of Washington, Seattle, WA, United States.
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12
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Xiao D, Forys BJ, Vanni MP, Murphy TH. MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning. Nat Commun 2021; 12:5992. [PMID: 34645817 PMCID: PMC8514445 DOI: 10.1038/s41467-021-26255-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 09/23/2021] [Indexed: 01/17/2023] Open
Abstract
Understanding the basis of brain function requires knowledge of cortical operations over wide spatial scales and the quantitative analysis of brain activity in well-defined brain regions. Matching an anatomical atlas to brain functional data requires substantial labor and expertise. Here, we developed an automated machine learning-based registration and segmentation approach for quantitative analysis of mouse mesoscale cortical images. A deep learning model identifies nine cortical landmarks using only a single raw fluorescent image. Another fully convolutional network was adapted to delimit brain boundaries. This anatomical alignment approach was extended by adding three functional alignment approaches that use sensory maps or spatial-temporal activity motifs. We present this methodology as MesoNet, a robust and user-friendly analysis pipeline using pre-trained models to segment brain regions as defined in the Allen Mouse Brain Atlas. This Python-based toolbox can also be combined with existing methods to facilitate high-throughput data analysis.
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Affiliation(s)
- Dongsheng Xiao
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, V6T 1Z3, British Columbia, Canada
| | - Brandon J Forys
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, V6T 1Z3, British Columbia, Canada
- Department of Psychology, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Matthieu P Vanni
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, V6T 1Z3, British Columbia, Canada
- Université de Montréal, École d'Optométrie, 3744 Jean Brillant H3T 1P1, Montréal, Québec, Canada
| | - Timothy H Murphy
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, V6T 1Z3, British Columbia, Canada.
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13
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Hegedüs P, Velencei A, Belval CHD, Heckenast J, Hangya B. Training protocol for probabilistic Pavlovian conditioning in mice using an open-source head-fixed setup. STAR Protoc 2021; 2:100795. [PMID: 34522902 PMCID: PMC8424585 DOI: 10.1016/j.xpro.2021.100795] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
High throughput, temporally controlled, reproducible quantitative behavioral assays are important for understanding the neural mechanisms underlying behavior. Here, we provide a step-by-step training protocol for a probabilistic Pavlovian conditioning task, where two auditory cues predict probabilistic outcomes with different contingencies. This protocol allows us to study the differential behavioral and neuronal correlates of expected and surprising outcomes. It has been tested in combination with chronic in vivo electrophysiological recordings and optogenetic manipulations in ChAT-Cre and PV-Cre mouse lines. For complete details on the use and execution of this protocol, please refer to Hegedüs et al. (2021). We provide a training protocol for a probabilistic Pavlovian conditioning task in mice Two auditory cues predict probabilistic outcomes with different contingencies Possible to combine with chronic in vivo electrophysiology and optogenetics Ideal for testing behavioral and neural correlates of expected and surprising outcomes
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Affiliation(s)
- Panna Hegedüs
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary.,János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary
| | - Anna Velencei
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary
| | - Claire-Hélène de Belval
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary.,Interdisciplinary Masters' in Life Sciences, Ecole Normale Supérieure, Paris, France
| | - Julia Heckenast
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary
| | - Balázs Hangya
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary
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14
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Nomura H. [Autonomous mouse behavioral experiments]. Nihon Yakurigaku Zasshi 2021; 156:312. [PMID: 34470937 DOI: 10.1254/fpj.21048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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15
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Lyamzin DR, Aoki R, Abdolrahmani M, Benucci A. Probabilistic discrimination of relative stimulus features in mice. Proc Natl Acad Sci U S A 2021; 118:e2103952118. [PMID: 34301903 PMCID: PMC8325293 DOI: 10.1073/pnas.2103952118] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
During perceptual decision-making, the brain encodes the upcoming decision and the stimulus information in a mixed representation. Paradigms suitable for studying decision computations in isolation rely on stimulus comparisons, with choices depending on relative rather than absolute properties of the stimuli. The adoption of tasks requiring relative perceptual judgments in mice would be advantageous in view of the powerful tools available for the dissection of brain circuits. However, whether and how mice can perform a relative visual discrimination task has not yet been fully established. Here, we show that mice can solve a complex orientation discrimination task in which the choices are decoupled from the orientation of individual stimuli. Moreover, we demonstrate a typical discrimination acuity of 9°, challenging the common belief that mice are poor visual discriminators. We reached these conclusions by introducing a probabilistic choice model that explained behavioral strategies in 40 mice and demonstrated that the circularity of the stimulus space is an additional source of choice variability for trials with fixed difficulty. Furthermore, history biases in the model changed with task engagement, demonstrating behavioral sensitivity to the availability of cognitive resources. In conclusion, our results reveal that mice adopt a diverse set of strategies in a task that decouples decision-relevant information from stimulus-specific information, thus demonstrating their usefulness as an animal model for studying neural representations of relative categories in perceptual decision-making research.
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Affiliation(s)
- Dmitry R Lyamzin
- RIKEN Center for Brain Science, RIKEN, Wako-shi 351-0198, Japan;
| | - Ryo Aoki
- RIKEN Center for Brain Science, RIKEN, Wako-shi 351-0198, Japan
| | | | - Andrea Benucci
- RIKEN Center for Brain Science, RIKEN, Wako-shi 351-0198, Japan;
- Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo, Bunkyo City 113-0032, Japan
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16
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Abdolrahmani M, Lyamzin DR, Aoki R, Benucci A. Attention separates sensory and motor signals in the mouse visual cortex. Cell Rep 2021; 36:109377. [PMID: 34260937 DOI: 10.1016/j.celrep.2021.109377] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 03/23/2021] [Accepted: 06/18/2021] [Indexed: 11/18/2022] Open
Abstract
Visually guided behaviors depend on the activity of cortical networks receiving visual inputs and transforming these signals to guide appropriate actions. However, non-retinal inputs, carrying motor signals as well as cognitive and attentional modulatory signals, also activate these cortical regions. How these networks integrate coincident signals ensuring reliable visual behaviors is poorly understood. In this study, we observe neural responses in the dorsal-parietal cortex of mice during a visual discrimination task driven by visual stimuli and movements. We find that visual and motor signals interact according to two mechanisms: divisive normalization and separation of responses. Interactions are contextually modulated by the animal's state of sustained attention, which amplifies visual and motor signals and increases their discriminability in a low-dimensional space of neural activations. These findings reveal computational principles operating in dorsal-parietal networks that enable separation of incoming signals for reliable visually guided behaviors during interactions with the environment.
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Affiliation(s)
| | - Dmitry R Lyamzin
- RIKEN Center for Brain Science, Wako-shi, Saitama 351-0198, Japan
| | - Ryo Aoki
- RIKEN Center for Brain Science, Wako-shi, Saitama 351-0198, Japan
| | - Andrea Benucci
- RIKEN Center for Brain Science, Wako-shi, Saitama 351-0198, Japan; Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo, 1-1-1 Yayoi, Bunkyo City, Tokyo 113-0032, Japan.
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17
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Aguillon-Rodriguez V, Angelaki D, Bayer H, Bonacchi N, Carandini M, Cazettes F, Chapuis G, Churchland AK, Dan Y, Dewitt E, Faulkner M, Forrest H, Haetzel L, Häusser M, Hofer SB, Hu F, Khanal A, Krasniak C, Laranjeira I, Mainen ZF, Meijer G, Miska NJ, Mrsic-Flogel TD, Murakami M, Noel JP, Pan-Vazquez A, Rossant C, Sanders J, Socha K, Terry R, Urai AE, Vergara H, Wells M, Wilson CJ, Witten IB, Wool LE, Zador AM. Standardized and reproducible measurement of decision-making in mice. eLife 2021; 10:63711. [PMID: 34011433 DOI: 10.1101/2020.01.17.909838] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 04/08/2021] [Indexed: 05/25/2023] Open
Abstract
Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches.
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Affiliation(s)
| | - Dora Angelaki
- Center for Neural Science, New York University, New York, United States
| | - Hannah Bayer
- Zuckerman Institute, Columbia University, New York, United States
| | | | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London, United Kingdom
| | | | - Gaelle Chapuis
- Wolfson Institute for Biomedical Research, University College London, London, United Kingdom
| | | | - Yang Dan
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Eric Dewitt
- Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Mayo Faulkner
- Wolfson Institute for Biomedical Research, University College London, London, United Kingdom
| | - Hamish Forrest
- UCL Institute of Ophthalmology, University College London, London, United Kingdom
| | - Laura Haetzel
- Princeton Neuroscience Institute, Princeton University, Princeton, United States
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, United Kingdom
| | - Sonja B Hofer
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United Kingdom
| | - Fei Hu
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Anup Khanal
- Cold Spring Harbor Laboratory, New York, United States
| | - Christopher Krasniak
- Cold Spring Harbor Laboratory, New York, United States
- Watson School of Biological Sciences, New York, United States
| | | | | | - Guido Meijer
- Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Nathaniel J Miska
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United Kingdom
| | - Thomas D Mrsic-Flogel
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United Kingdom
| | | | - Jean-Paul Noel
- Center for Neural Science, New York University, New York, United States
| | | | - Cyrille Rossant
- UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | | | - Karolina Socha
- UCL Institute of Ophthalmology, University College London, London, United Kingdom
| | - Rebecca Terry
- UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Anne E Urai
- Cold Spring Harbor Laboratory, New York, United States
- Cognitive Psychology Unit, Leiden University, Leiden, Netherlands
| | - Hernando Vergara
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United Kingdom
| | - Miles Wells
- UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | | | - Ilana B Witten
- Princeton Neuroscience Institute, Princeton University, Princeton, United States
| | - Lauren E Wool
- UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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18
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Aguillon-Rodriguez V, Angelaki D, Bayer H, Bonacchi N, Carandini M, Cazettes F, Chapuis G, Churchland AK, Dan Y, Dewitt E, Faulkner M, Forrest H, Haetzel L, Häusser M, Hofer SB, Hu F, Khanal A, Krasniak C, Laranjeira I, Mainen ZF, Meijer G, Miska NJ, Mrsic-Flogel TD, Murakami M, Noel JP, Pan-Vazquez A, Rossant C, Sanders J, Socha K, Terry R, Urai AE, Vergara H, Wells M, Wilson CJ, Witten IB, Wool LE, Zador AM. Standardized and reproducible measurement of decision-making in mice. eLife 2021; 10:e63711. [PMID: 34011433 PMCID: PMC8137147 DOI: 10.7554/elife.63711] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 04/08/2021] [Indexed: 12/20/2022] Open
Abstract
Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches.
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Affiliation(s)
- The International Brain Laboratory
- Cold Spring Harbor LaboratoryNew YorkUnited States
- Center for Neural Science, New York UniversityNew YorkUnited States
- Zuckerman Institute, Columbia UniversityNew YorkUnited States
- Champalimaud Centre for the UnknownLisbonPortugal
- UCL Institute of Ophthalmology, University College LondonLondonUnited Kingdom
- Wolfson Institute for Biomedical Research, University College LondonLondonUnited Kingdom
- Department of Molecular and Cell Biology, University of California, BerkeleyBerkeleyUnited States
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College LondonLondonUnited Kingdom
- Watson School of Biological SciencesNew YorkUnited States
- UCL Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
- Sanworks LLCNew YorkUnited States
- Cognitive Psychology Unit, Leiden UniversityLeidenNetherlands
| | | | - Dora Angelaki
- Center for Neural Science, New York UniversityNew YorkUnited States
| | - Hannah Bayer
- Zuckerman Institute, Columbia UniversityNew YorkUnited States
| | | | - Matteo Carandini
- UCL Institute of Ophthalmology, University College LondonLondonUnited Kingdom
| | | | - Gaelle Chapuis
- Wolfson Institute for Biomedical Research, University College LondonLondonUnited Kingdom
| | | | - Yang Dan
- Department of Molecular and Cell Biology, University of California, BerkeleyBerkeleyUnited States
| | - Eric Dewitt
- Champalimaud Centre for the UnknownLisbonPortugal
| | - Mayo Faulkner
- Wolfson Institute for Biomedical Research, University College LondonLondonUnited Kingdom
| | - Hamish Forrest
- UCL Institute of Ophthalmology, University College LondonLondonUnited Kingdom
| | - Laura Haetzel
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College LondonLondonUnited Kingdom
| | - Sonja B Hofer
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College LondonLondonUnited Kingdom
| | - Fei Hu
- Department of Molecular and Cell Biology, University of California, BerkeleyBerkeleyUnited States
| | - Anup Khanal
- Cold Spring Harbor LaboratoryNew YorkUnited States
| | - Christopher Krasniak
- Cold Spring Harbor LaboratoryNew YorkUnited States
- Watson School of Biological SciencesNew YorkUnited States
| | | | | | - Guido Meijer
- Champalimaud Centre for the UnknownLisbonPortugal
| | - Nathaniel J Miska
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College LondonLondonUnited Kingdom
| | - Thomas D Mrsic-Flogel
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College LondonLondonUnited Kingdom
| | | | - Jean-Paul Noel
- Center for Neural Science, New York UniversityNew YorkUnited States
| | | | - Cyrille Rossant
- UCL Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | | | - Karolina Socha
- UCL Institute of Ophthalmology, University College LondonLondonUnited Kingdom
| | - Rebecca Terry
- UCL Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Anne E Urai
- Cold Spring Harbor LaboratoryNew YorkUnited States
- Cognitive Psychology Unit, Leiden UniversityLeidenNetherlands
| | - Hernando Vergara
- Sainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College LondonLondonUnited Kingdom
| | - Miles Wells
- UCL Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | | | - Ilana B Witten
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - Lauren E Wool
- UCL Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
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19
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Hao Y, Thomas AM, Li N. Fully autonomous mouse behavioral and optogenetic experiments in home-cage. eLife 2021; 10:e66112. [PMID: 33944781 PMCID: PMC8116056 DOI: 10.7554/elife.66112] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 05/02/2021] [Indexed: 01/19/2023] Open
Abstract
Goal-directed behaviors involve distributed brain networks. The small size of the mouse brain makes it amenable to manipulations of neural activity dispersed across brain areas, but existing optogenetic methods serially test a few brain regions at a time, which slows comprehensive mapping of distributed networks. Laborious operant conditioning training required for most experimental paradigms exacerbates this bottleneck. We present an autonomous workflow to survey the involvement of brain regions at scale during operant behaviors in mice. Naive mice living in a home-cage system learned voluntary head-fixation (>1 hr/day) and performed difficult decision-making tasks, including contingency reversals, for 2 months without human supervision. We incorporated an optogenetic approach to manipulate activity in deep brain regions through intact skull during home-cage behavior. To demonstrate the utility of this approach, we tested dozens of mice in parallel unsupervised optogenetic experiments, revealing multiple regions in cortex, striatum, and superior colliculus involved in tactile decision-making.
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Affiliation(s)
- Yaoyao Hao
- Department of Neuroscience, Baylor College of MedicineHoustonUnited States
| | | | - Nuo Li
- Department of Neuroscience, Baylor College of MedicineHoustonUnited States
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20
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Schnabel UH, Van der Bijl T, Roelfsema PR, Lorteije JAM. A Direct Comparison of Spatial Attention and Stimulus-Response Compatibility between Mice and Humans. J Cogn Neurosci 2021; 33:771-783. [PMID: 33544053 DOI: 10.1162/jocn_a_01681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Mice are becoming an increasingly popular model for investigating the neural substrates of visual processing and higher cognitive functions. To validate the translation of mouse visual attention and sensorimotor processing to humans, we compared their performance in the same visual task. Mice and human participants judged the orientation of a grating presented on either the right or left side in the visual field. To induce shifts of spatial attention, we varied the stimulus probability on each side. As expected, human participants showed faster RTs and a higher accuracy for the side with a higher probability, a well-established effect of visual attention. The attentional effect was only present in mice when their response was slow. Although the task demanded a judgment of grating orientation, the accuracy of the mice was strongly affected by whether the side of the stimulus corresponded to the side of the behavioral response. This stimulus-response compatibility (Simon) effect was much weaker in humans and only significant for their fastest responses. Both species exhibited a speed-accuracy trade-off in their responses, because slower responses were more accurate than faster responses. We found that mice typically respond very fast, which contributes to the stronger stimulus-response compatibility and weaker attentional effects, which were only apparent in the trials with slowest responses. Humans responded slower and had stronger attentional effects, combined with a weak influence of stimulus-response compatibility, which was only apparent in trials with fast responses. We conclude that spatial attention and stimulus-response compatibility influence the responses of humans and mice but that strategy differences between species determine the dominance of these effects.
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Affiliation(s)
| | | | - Pieter R Roelfsema
- Netherlands Institute for Neuroscience.,University of Amsterdam.,Vrije Universiteit, Amsterdam, The Netherlands
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21
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Efficient training of mice on the 5-choice serial reaction time task in an automated rodent training system. Sci Rep 2020; 10:22362. [PMID: 33349672 PMCID: PMC7752912 DOI: 10.1038/s41598-020-79290-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 12/07/2020] [Indexed: 11/24/2022] Open
Abstract
Experiments aiming to understand sensory-motor systems, cognition and behavior necessitate training animals to perform complex tasks. Traditional training protocols require lab personnel to move the animals between home cages and training chambers, to start and end training sessions, and in some cases, to hand-control each training trial. Human labor not only limits the amount of training per day, but also introduces several sources of variability and may increase animal stress. Here we present an automated training system for the 5-choice serial reaction time task (5CSRTT), a classic rodent task often used to test sensory detection, sustained attention and impulsivity. We found that full automation without human intervention allowed rapid, cost-efficient training, and decreased stress as measured by corticosterone levels. Training breaks introduced only a transient drop in performance, and mice readily generalized across training systems when transferred from automated to manual protocols. We further validated our automated training system with wireless optogenetics and pharmacology experiments, expanding the breadth of experimental needs our system may fulfill. Our automated 5CSRTT system can serve as a prototype for fully automated behavioral training, with methods and principles transferrable to a range of rodent tasks.
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22
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Bernhard SM, Lee J, Zhu M, Hsu A, Erskine A, Hires SA, Barth AL. An automated homecage system for multiwhisker detection and discrimination learning in mice. PLoS One 2020; 15:e0232916. [PMID: 33264281 PMCID: PMC7710058 DOI: 10.1371/journal.pone.0232916] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 11/16/2020] [Indexed: 12/19/2022] Open
Abstract
Automated, homecage behavioral training for rodents has many advantages: it is low stress, requires little interaction with the experimenter, and can be easily manipulated to adapt to different experimental conditions. We have developed an inexpensive, Arduino-based, homecage training apparatus for sensory association training in freely-moving mice using multiwhisker air current stimulation coupled to a water reward. Animals learn this task readily, within 1–2 days of training, and performance progressively improves with training. We examined the parameters that regulate task acquisition using different stimulus intensities, directions, and reward valence. Learning was assessed by comparing anticipatory licking for the stimulus compared to the no-stimulus (blank) trials. At high stimulus intensities (>9 psi), animals showed markedly less participation in the task. Conversely, very weak air current intensities (1–2 psi) were not sufficient to generate rapid learning behavior. At intermediate stimulus intensities (5–6 psi), a majority of mice learned that the multiwhisker stimulus predicted the water reward after 24–48 hrs of training. Both exposure to isoflurane and lack of whiskers decreased animals’ ability to learn the task. Following training at an intermediate stimulus intensity, mice were able to transfer learning behavior when exposed to a lower stimulus intensity, an indicator of perceptual learning. Mice learned to discriminate between two directions of stimulation rapidly and accurately, even when the angular distance between the stimuli was <15 degrees. Switching the reward to a more desirable reward, aspartame, had little effect on learning trajectory. Our results show that a tactile association task in an automated homecage environment can be monitored by anticipatory licking to reveal rapid and progressive behavioral change. These Arduino-based, automated mouse cages enable high-throughput training that facilitate analysis of large numbers of genetically modified mice with targeted manipulations of neural activity.
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Affiliation(s)
- Sarah M. Bernhard
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Jiseok Lee
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Mo Zhu
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Alex Hsu
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Andrew Erskine
- Department of Biological Sciences, Section of Neurobiology, University of Southern California, Los Angeles, California, United States of America
| | - Samuel A. Hires
- Department of Biological Sciences, Section of Neurobiology, University of Southern California, Los Angeles, California, United States of America
| | - Alison L. Barth
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- * E-mail:
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23
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Groblewski PA, Sullivan D, Lecoq J, de Vries SEJ, Caldejon S, L'Heureux Q, Keenan T, Roll K, Slaughterback C, Williford A, Farrell C. A standardized head-fixation system for performing large-scale, in vivo physiological recordings in mice. J Neurosci Methods 2020; 346:108922. [PMID: 32946912 DOI: 10.1016/j.jneumeth.2020.108922] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 08/24/2020] [Accepted: 08/24/2020] [Indexed: 11/25/2022]
Abstract
BACKGROUND The Allen Institute recently built a set of high-throughput experimental pipelines to collect comprehensive in vivo surveys of physiological activity in the visual cortex of awake, head-fixed mice. Developing these large-scale, industrial-like pipelines posed many scientific, operational, and engineering challenges. NEW METHOD Our strategies for creating a cross-platform reference space to which all pipeline datasets were mapped required development of 1) a robust headframe, 2) a reproducible clamping system, and 3) data-collection systems that are built, and maintained, around precise alignment with a reference artifact. RESULTS When paired with our pipeline clamping system, our headframe exceeded deflection and reproducibility requirements. By leveraging our headframe and clamping system we were able to create a cross-platform reference space to which multi-modal imaging datasets could be mapped. COMPARISON WITH EXISTING METHODS Together, the Allen Brain Observatory headframe, surgical tooling, clamping system, and system registration strategy create a unique system for collecting large amounts of standardized in vivo datasets over long periods of time. Moreover, the integrated approach to cross-platform registration allows for multi-modal datasets to be collected within a shared reference space. CONCLUSIONS Here we report the engineering strategies that we implemented when creating the Allen Brain Observatory physiology pipelines. All of the documentation related to headframe, surgical tooling, and clamp design has been made freely available and can be readily manufactured or procured. The engineering strategy, or components of the strategy, described in this report can be tailored and applied by external researchers to improve data standardization and stability.
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Affiliation(s)
- P A Groblewski
- Allen Institute for Brain Science, Seattle, WA, 98109, USA.
| | - D Sullivan
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - J Lecoq
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - S E J de Vries
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - S Caldejon
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - Q L'Heureux
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - T Keenan
- Amazon Logistics, Bellevue, WA, 98004, USA
| | - K Roll
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | | | - A Williford
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - C Farrell
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
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24
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Johnson NP, Gregorich SM, Passaglia CL. Spatiotemporal Contrast Sensitivity of Brown-Norway Rats under Scotopic and Photopic Illumination. Neuroscience 2020; 449:63-73. [PMID: 33035619 DOI: 10.1016/j.neuroscience.2020.09.056] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 09/03/2020] [Accepted: 09/28/2020] [Indexed: 11/24/2022]
Abstract
Rats are a popular animal model for vision research and for investigating disorders of the visual system. The study aimed to quantify the spatiotemporal contrast sensitivity function (CSF) of healthy adult Brown-Norway rats under scotopic and photopic illumination. Animals were trained to jump onto the one of two adjacent platforms behind which was displayed a sinewave grating pattern. Contrast thresholds of light- and dark-adapted rats were determined using a staircase method of adjustment for gratings that varied in spatial frequency (sf) and temporal frequency (tf) and ranged several log-units in mean luminance. Photopic CSFs showed strong bandpass spatial tuning, consistent with prior measurements, and weak bandpass temporal tuning. CSFs were parameterized by a truncated log-parabola model, yielding a peak contrast sensitivity of 52 ± 9, peak sf of 0.17 ± 0.05 cycles/degree, sf limit of 1.6 ± 0.3 cycles/degree, low sf attenuation of 85 ± 9%, peak tf of 1.7 ± 1.1 Hz, extrapolated tf limit of 166 ± 44 Hz, and low tf attenuation of 55 ± 12%. CSFs became more lowpass and decreased systematically in contrast sensitivity and spatiotemporal acuity as mean luminance was reduced. CSFs were also measured via the visual head-tracking reflex. Photopic contrast sensitivity, spatial acuity, and temporal acuity were all markedly below that of the grating detection task and optomotor findings for other rat strains. The CSF data provide a comprehensive and quantitative description of rat spatial and temporal vision and a benchmark for evaluating effects of ocular diseases on their ability to see.
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Affiliation(s)
- Nicholas P Johnson
- University of South Florida, Molecular Pharmacology & Physiology Department, 12901 Bruce B Downs Boulevard MDC 40, Tampa, FL 33612, United States
| | - Sarah M Gregorich
- University of South Florida, Medical Engineering Department, 4202 E Fowler Avenue, Tampa, FL 33620, United States
| | - Christopher L Passaglia
- University of South Florida, Molecular Pharmacology & Physiology Department, 12901 Bruce B Downs Boulevard MDC 40, Tampa, FL 33612, United States; University of South Florida, Medical Engineering Department, 4202 E Fowler Avenue, Tampa, FL 33620, United States; University of South Florida, Ophthalmology Department, 12901 Bruce B Downs Boulevard MDC21, Tampa, FL 33612, United States.
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25
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Black CJ, Allawala AB, Bloye K, Vanent KN, Edhi MM, Saab CY, Borton DA. Automated and rapid self-report of nociception in transgenic mice. Sci Rep 2020; 10:13215. [PMID: 32764714 PMCID: PMC7413385 DOI: 10.1038/s41598-020-70028-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 07/20/2020] [Indexed: 11/10/2022] Open
Abstract
There are currently no rapid, operant pain behaviors in rodents that use a self-report to directly engage higher-order brain circuitry. We have developed a pain detection assay consisting of a lick behavior in response to optogenetic activation of predominantly nociceptive peripheral afferent nerve fibers in head-restrained transgenic mice expressing ChR2 in TRPV1 containing neurons. TRPV1-ChR2-EYFP mice (n = 5) were trained to provide lick reports to the detection of light-evoked nociceptive stimulation to the hind paw. Using simultaneous video recording, we demonstrate that the learned lick behavior may prove more pertinent in investigating brain driven pain processes than the reflex behavior. Within sessions, the response bias of transgenic mice changed with respect to lick behavior but not reflex behavior. Furthermore, response similarity between the lick and reflex behaviors diverged near perceptual threshold. Our nociceptive lick-report detection assay will enable a host of investigations into the millisecond, single cell, neural dynamics underlying pain processing in the central nervous system of awake behaving animals.
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Affiliation(s)
| | | | - Kiernan Bloye
- Department of Neuroscience, Brown University, Providence, RI, 02912, USA
| | - Kevin N Vanent
- Department of Neuroscience, Brown University, Providence, RI, 02912, USA
| | - Muhammad M Edhi
- Department of Neurosurgery, Rhode Island Hospital, Providence, RI, 02903, USA
| | - Carl Y Saab
- Department of Neuroscience, Brown University, Providence, RI, 02912, USA.,Department of Neurosurgery, Rhode Island Hospital, Providence, RI, 02903, USA.,Carney Institute for Brain Science, Brown University, Providence, RI, 02912, USA
| | - David A Borton
- School of Engineering, Brown University, Providence, RI, 02912, USA. .,Carney Institute for Brain Science, Brown University, Providence, RI, 02912, USA. .,Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI, USA.
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26
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Broschard MB, Kim J, Love BC, Freeman JH. Category learning in rodents using touchscreen‐based tasks. GENES BRAIN AND BEHAVIOR 2020; 20:e12665. [DOI: 10.1111/gbb.12665] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 05/01/2020] [Accepted: 05/04/2020] [Indexed: 01/29/2023]
Affiliation(s)
- Matthew B. Broschard
- Department of Psychological and Brain Sciences University of Iowa Iowa City Iowa USA
| | - Jangjin Kim
- Department of Psychological and Brain Sciences University of Iowa Iowa City Iowa USA
| | - Bradley C. Love
- Department of Experimental Psychology and The Alan Turing Institute University College London London UK
| | - John H. Freeman
- Department of Psychological and Brain Sciences University of Iowa Iowa City Iowa USA
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27
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Campos P, Walker JJ, Mollard P. Diving into the brain: deep-brain imaging techniques in conscious animals. J Endocrinol 2020; 246:R33-R50. [PMID: 32380471 PMCID: PMC7354703 DOI: 10.1530/joe-20-0028] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 05/07/2020] [Indexed: 01/28/2023]
Abstract
In most species, survival relies on the hypothalamic control of endocrine axes that regulate critical functions such as reproduction, growth, and metabolism. For decades, the complexity and inaccessibility of the hypothalamic-pituitary axis has prevented researchers from elucidating the relationship between the activity of endocrine hypothalamic neurons and pituitary hormone secretion. Indeed, the study of central control of endocrine function has been largely dominated by 'traditional' techniques that consist of studying in vitro or ex vivo isolated cell types without taking into account the complexity of regulatory mechanisms at the level of the brain, pituitary and periphery. Nowadays, by exploiting modern neuronal transfection and imaging techniques, it is possible to study hypothalamic neuron activity in situ, in real time, and in conscious animals. Deep-brain imaging of calcium activity can be performed through gradient-index lenses that are chronically implanted and offer a 'window into the brain' to image multiple neurons at single-cell resolution. With this review, we aim to highlight deep-brain imaging techniques that enable the study of neuroendocrine neurons in awake animals whilst maintaining the integrity of regulatory loops between the brain, pituitary and peripheral glands. Furthermore, to assist researchers in setting up these techniques, we discuss the equipment required and include a practical step-by-step guide to performing these deep-brain imaging studies.
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Affiliation(s)
- Pauline Campos
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
- Correspondence should be addressed to P Campos:
| | - Jamie J Walker
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
- EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, UK
- Bristol Medical School, Translational Health Sciences, University of Bristol, Bristol, UK
| | - Patrice Mollard
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
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28
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Sato TK. Long-range connections enrich cortical computations. Neurosci Res 2020; 162:1-12. [PMID: 32470355 DOI: 10.1016/j.neures.2020.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 04/28/2020] [Accepted: 05/15/2020] [Indexed: 10/24/2022]
Abstract
The cerebral cortex can perform powerful computations, including those involved in higher cognitive functions. Cortical processing for such computations is executed by local circuits and is further enriched by long-range connectivity. This connectivity is activated under specific conditions and modulates local processing, providing flexibility in the computational performance of the cortex. For instance, long-range connectivity in the primary visual cortex exerts facilitatory impacts when the cortex is silent but suppressive impacts when the cortex is strongly sensory-stimulated. These dual impacts can be captured by a divisive gain control model. Recent methodological advances such as optogenetics, anatomical tracing, and two-photon microscopy have enabled neuroscientists to probe the circuit and synaptic bases of long-range connectivity in detail. Here, I review a series of evidence indicating essential roles of long-range connectivity in visual and hierarchical processing involving numerous cortical areas. I also describe an overview of the challenges encountered in investigating underlying synaptic mechanisms and highlight recent technical approaches that may overcome these difficulties and provide new insights into synaptic mechanisms for cortical processing involving long-range connectivity.
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Affiliation(s)
- Tatsuo K Sato
- Dept. of Physiology, Neuroscience Program, Biomedicine Discovery Inst., Monash University, Clayton, VIC 3800, Australia; PRESTO, Japan Science and Technology Agency, Saitama 332-0012, Japan.
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29
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Morales L, Tomàs DP, Dalmau J, de la Rocha J, Jercog PE. High-Throughput Task to Study Memory Recall During Spatial Navigation in Rodents. Front Behav Neurosci 2020; 14:64. [PMID: 32499683 PMCID: PMC7243682 DOI: 10.3389/fnbeh.2020.00064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 04/06/2020] [Indexed: 12/04/2022] Open
Abstract
Spatial navigation is one of the most frequently used behavioral paradigms to study memory formation in rodents. Commonly used tasks to study memory are labor-intensive, preventing the simultaneous testing of multiple animals with the tendency to yield a low number of trials, curtailing the statistical power. Moreover, they are not tailored to be combined with neurophysiology recordings because they are not based on overt stereotyped behavioral responses that can be precisely timed. Here we present a novel task to study long-term memory formation and recall during spatial navigation. The task consists of learning sessions during which mice need to find the rewarding port that changes from day to day. Hours after learning, there is a recall session during which mice search for the location of the memorized rewarding port. During the recall sessions, the animals repeatedly poke the remembered port over many trials (up to ∼20) without receiving a reward (i.e., no positive feedback) as a readout of memory. In this task, mice show memory of port locations learned on up to three previous days. This eight-port maze task requires minimal human intervention, allowing for simultaneous and unsupervised testing of several mice in parallel, yielding a high number of recall trials per session over many days, and compatible with recordings of neural activity.
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Affiliation(s)
- Lucia Morales
- Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - David P. Tomàs
- Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Josep Dalmau
- Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
- Neuroimmunology Program, IDIBAPS-Hospital Clinic, Universitat de Barcelona, Barcelona, Spain
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
- Catalan Institution for Research and Advanced Studies, Barcelona, Spain
| | - Jaime de la Rocha
- Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Pablo E. Jercog
- Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
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30
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Murphy TH, Michelson NJ, Boyd JD, Fong T, Bolanos LA, Bierbrauer D, Siu T, Balbi M, Bolanos F, Vanni M, LeDue JM. Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages. eLife 2020; 9:55964. [PMID: 32412409 PMCID: PMC7332290 DOI: 10.7554/elife.55964] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 05/07/2020] [Indexed: 12/12/2022] Open
Abstract
We report improved automated open-source methodology for head-fixed mesoscale cortical imaging and/or behavioral training of home cage mice using Raspberry Pi-based hardware. Staged partial and probabilistic restraint allows mice to adjust to self-initiated headfixation over 3 weeks' time with ~50% participation rate. We support a cue-based behavioral licking task monitored by a capacitive touch-sensor water spout. While automatically head-fixed, we acquire spontaneous, movement-triggered, or licking task-evoked GCaMP6 cortical signals. An analysis pipeline marked both behavioral events, as well as analyzed brain fluorescence signals as they relate to spontaneous and/or task-evoked behavioral activity. Mice were trained to suppress licking and wait for cues that marked the delivery of water. Correct rewarded go-trials were associated with widespread activation of midline and lateral barrel cortex areas following a vibration cue and delayed frontal and lateral motor cortex activation. Cortical GCaMP signals predicted trial success and correlated strongly with trial-outcome dependent body movements.
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Affiliation(s)
- Timothy H Murphy
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Nicholas J Michelson
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Jamie D Boyd
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Tony Fong
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Luis A Bolanos
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - David Bierbrauer
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Teri Siu
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Matilde Balbi
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Federico Bolanos
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Matthieu Vanni
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Jeff M LeDue
- Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, Canada.,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
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31
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Maor I, Shwartz-Ziv R, Feigin L, Elyada Y, Sompolinsky H, Mizrahi A. Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex. Front Neural Circuits 2020; 13:82. [PMID: 32047424 PMCID: PMC6997498 DOI: 10.3389/fncir.2019.00082] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 12/17/2019] [Indexed: 11/17/2022] Open
Abstract
Associative learning of pure tones is known to cause tonotopic map expansion in the auditory cortex (ACx), but the function this plasticity sub-serves is unclear. We developed an automated training platform called the “Educage,” which was used to train mice on a go/no-go auditory discrimination task to their perceptual limits, for difficult discriminations among pure tones or natural sounds. Spiking responses of excitatory and inhibitory parvalbumin (PV+) L2/3 neurons in mouse ACx revealed learning-induced overrepresentation of the learned frequencies, as expected from previous literature. The coordinated plasticity of excitatory and inhibitory neurons supports a role for PV+ neurons in homeostatic maintenance of excitation–inhibition balance within the circuit. Using a novel computational model to study auditory tuning curves, we show that overrepresentation of the learned tones does not necessarily improve discrimination performance of the network to these tones. In a separate set of experiments, we trained mice to discriminate among natural sounds. Perceptual learning of natural sounds induced “sparsening” and decorrelation of the neural response, consequently improving discrimination of these complex sounds. This signature of plasticity in A1 highlights its role in coding natural sounds.
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Affiliation(s)
- Ido Maor
- Department of Neurobiology, Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ravid Shwartz-Ziv
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Libi Feigin
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yishai Elyada
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Haim Sompolinsky
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.,The Racah Institute of Physics, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Adi Mizrahi
- Department of Neurobiology, Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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32
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Reinert JK, Schaefer AT, Kuner T. High-Throughput Automated Olfactory Phenotyping of Group-Housed Mice. Front Behav Neurosci 2019; 13:267. [PMID: 31920577 PMCID: PMC6927946 DOI: 10.3389/fnbeh.2019.00267] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 11/25/2019] [Indexed: 11/13/2022] Open
Abstract
Behavioral phenotyping of mice is often compromised by manual interventions of the experimenter and limited throughput. Here, we describe a fully automated behavior setup that allows for quantitative analysis of mouse olfaction with minimized experimenter involvement. Mice are group-housed and tagged with unique RFID chips. They can freely initiate trials and are automatically trained on a go/no-go task, learning to distinguish a rewarded from an unrewarded odor. Further, odor discrimination tasks and detailed training aspects can be set for each animal individually for automated execution without direct experimenter intervention. The procedure described here, from initial RFID implantation to discrimination of complex odor mixtures at high accuracy, can be completed within <2 months with cohorts of up to 25 male mice. Apart from the presentation of monomolecular odors, the setup can generate arbitrary mixtures and dilutions from any set of odors to create complex stimuli, enabling demanding behavioral analyses at high-throughput.
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Affiliation(s)
- Janine K. Reinert
- Institute of Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Andreas T. Schaefer
- Institute of Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
- Neurophysiology of Behaviour Laboratory, The Francis Crick Institute, London, United Kingdom
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom
| | - Thomas Kuner
- Institute of Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
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33
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Nakajima M, Schmitt LI. Understanding the circuit basis of cognitive functions using mouse models. Neurosci Res 2019; 152:44-58. [PMID: 31857115 DOI: 10.1016/j.neures.2019.12.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Revised: 12/01/2019] [Accepted: 12/09/2019] [Indexed: 01/13/2023]
Abstract
Understanding how cognitive functions arise from computations occurring in the brain requires the ability to measure and perturb neural activity while the relevant circuits are engaged for specific cognitive processes. Rapid technical advances have led to the development of new approaches to transiently activate and suppress neuronal activity as well as to record simultaneously from hundreds to thousands of neurons across multiple brain regions during behavior. To realize the full potential of these approaches for understanding cognition, however, it is critical that behavioral conditions and stimuli are effectively designed to engage the relevant brain networks. Here, we highlight recent innovations that enable this combined approach. In particular, we focus on how to design behavioral experiments that leverage the ever-growing arsenal of technologies for controlling and measuring neural activity in order to understand cognitive functions.
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Affiliation(s)
- Miho Nakajima
- McGovern Institute for Brain Research and the Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - L Ian Schmitt
- McGovern Institute for Brain Research and the Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA, United States; Center for Brain Science, RIKEN, Wako, Saitama, Japan.
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34
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Vanzella W, Grion N, Bertolini D, Perissinotto A, Gigante M, Zoccolan D. A passive, camera-based head-tracking system for real-time, three-dimensional estimation of head position and orientation in rodents. J Neurophysiol 2019; 122:2220-2242. [PMID: 31553687 DOI: 10.1152/jn.00301.2019] [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] [Indexed: 12/14/2022] Open
Abstract
Tracking head position and orientation in small mammals is crucial for many applications in the field of behavioral neurophysiology, from the study of spatial navigation to the investigation of active sensing and perceptual representations. Many approaches to head tracking exist, but most of them only estimate the 2D coordinates of the head over the plane where the animal navigates. Full reconstruction of the pose of the head in 3D is much more more challenging and has been achieved only in handful of studies, which employed headsets made of multiple LEDs or inertial units. However, these assemblies are rather bulky and need to be powered to operate, which prevents their application in wireless experiments and in the small enclosures often used in perceptual studies. Here we propose an alternative approach, based on passively imaging a lightweight, compact, 3D structure, painted with a pattern of black dots over a white background. By applying a cascade of feature extraction algorithms that progressively refine the detection of the dots and reconstruct their geometry, we developed a tracking method that is highly precise and accurate, as assessed through a battery of validation measurements. We show that this method can be used to study how a rat samples sensory stimuli during a perceptual discrimination task and how a hippocampal place cell represents head position over extremely small spatial scales. Given its minimal encumbrance and wireless nature, our method could be ideal for high-throughput applications, where tens of animals need to be simultaneously and continuously tracked.NEW & NOTEWORTHY Head tracking is crucial in many behavioral neurophysiology studies. Yet reconstruction of the head's pose in 3D is challenging and typically requires implanting bulky, electrically powered headsets that prevent wireless experiments and are hard to employ in operant boxes. Here we propose an alternative approach, based on passively imaging a compact, 3D dot pattern that, once implanted over the head of a rodent, allows estimating the pose of its head with high precision and accuracy.
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Affiliation(s)
- Walter Vanzella
- Visual Neuroscience Laboratory, International School for Advanced Studies (SISSA), Trieste, Italy.,Glance Vision Technologies, Trieste, Italy
| | - Natalia Grion
- Visual Neuroscience Laboratory, International School for Advanced Studies (SISSA), Trieste, Italy
| | - Daniele Bertolini
- Visual Neuroscience Laboratory, International School for Advanced Studies (SISSA), Trieste, Italy
| | - Andrea Perissinotto
- Visual Neuroscience Laboratory, International School for Advanced Studies (SISSA), Trieste, Italy.,Glance Vision Technologies, Trieste, Italy
| | - Marco Gigante
- Mechatronics Lab, International School for Advanced Studies (SISSA), Trieste, Italy
| | - Davide Zoccolan
- Visual Neuroscience Laboratory, International School for Advanced Studies (SISSA), Trieste, Italy
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35
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Singh S, Bermudez-Contreras E, Nazari M, Sutherland RJ, Mohajerani MH. Low-cost solution for rodent home-cage behaviour monitoring. PLoS One 2019; 14:e0220751. [PMID: 31374097 PMCID: PMC6677321 DOI: 10.1371/journal.pone.0220751] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 07/22/2019] [Indexed: 11/18/2022] Open
Abstract
In the current research on measuring complex behaviours/phenotyping in rodents, most of the experimental design requires the experimenter to remove the animal from its home-cage environment and place it in an unfamiliar apparatus (novel environment). This interaction may influence behaviour, general well-being, and the metabolism of the animal, affecting the phenotypic outcome even if the data collection method is automated. Most of the commercially available solutions for home-cage monitoring are expensive and usually lack the flexibility to be incorporated with existing home-cages. Here we present a low-cost solution for monitoring home-cage behaviour of rodents that can be easily incorporated to practically any available rodent home-cage. To demonstrate the use of our system, we reliably predict the sleep/wake state of mice in their home-cage using only video. We validate these results using hippocampal local field potential (LFP) and electromyography (EMG) data. Our approach provides a low-cost flexible methodology for high-throughput studies of sleep, circadian rhythm and rodent behaviour with minimal experimenter interference.
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Affiliation(s)
- Surjeet Singh
- Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, University of Lethbridge, Lethbridge, AB, Canada
| | - Edgar Bermudez-Contreras
- Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, University of Lethbridge, Lethbridge, AB, Canada
| | - Mojtaba Nazari
- Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, University of Lethbridge, Lethbridge, AB, Canada
| | - Robert J. Sutherland
- Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, University of Lethbridge, Lethbridge, AB, Canada
- * E-mail: (RJS); (MHM)
| | - Majid H. Mohajerani
- Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, University of Lethbridge, Lethbridge, AB, Canada
- * E-mail: (RJS); (MHM)
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36
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Erskine A, Bus T, Herb JT, Schaefer AT. AutonoMouse: High throughput operant conditioning reveals progressive impairment with graded olfactory bulb lesions. PLoS One 2019; 14:e0211571. [PMID: 30840676 PMCID: PMC6402634 DOI: 10.1371/journal.pone.0211571] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 01/16/2019] [Indexed: 11/18/2022] Open
Abstract
Operant conditioning is a crucial tool in neuroscience research for probing brain function. While molecular, anatomical and even physiological techniques have seen radical increases in throughput, efficiency, and reproducibility in recent years, behavioural tools have somewhat lagged behind. Here we present a fully automated, high-throughput system for self-initiated conditioning of up to 25 group-housed, radio-frequency identification (RFID) tagged mice over periods of several months and >106 trials. We validate this "AutonoMouse" system in a series of olfactory behavioural tasks and show that acquired data is comparable to previous semi-manual approaches. Furthermore, we use AutonoMouse to systematically probe the impact of graded olfactory bulb lesions on olfactory behaviour, demonstrating that while odour discrimination in general is robust to even most extensive disruptions, small olfactory bulb lesions already impair odour detection. Discrimination learning of similar mixtures as well as learning speed are in turn reliably impacted by medium lesion sizes. The modular nature and open-source design of AutonoMouse should allow for similar robust and systematic assessments across neuroscience research areas.
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Affiliation(s)
- Andrew Erskine
- The Francis Crick Institute, Neurophysiology of Behaviour Laboratory, London, United Kingdom
- Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom
| | - Thorsten Bus
- Behavioural Neurophysiology, Max-Planck-Institute for Medical Research, Heidelberg, Germany
| | - Jan T. Herb
- The Francis Crick Institute, Neurophysiology of Behaviour Laboratory, London, United Kingdom
- Behavioural Neurophysiology, Max-Planck-Institute for Medical Research, Heidelberg, Germany
- Department of Anatomy and Cell Biology, Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Andreas T. Schaefer
- The Francis Crick Institute, Neurophysiology of Behaviour Laboratory, London, United Kingdom
- Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom
- Behavioural Neurophysiology, Max-Planck-Institute for Medical Research, Heidelberg, Germany
- Department of Anatomy and Cell Biology, Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
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Nonlinear Processing of Shape Information in Rat Lateral Extrastriate Cortex. J Neurosci 2019; 39:1649-1670. [PMID: 30617210 DOI: 10.1523/jneurosci.1938-18.2018] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 11/28/2018] [Accepted: 12/02/2018] [Indexed: 11/21/2022] Open
Abstract
In rodents, the progression of extrastriate areas located laterally to primary visual cortex (V1) has been assigned to a putative object-processing pathway (homologous to the primate ventral stream), based on anatomical considerations. Recently, we found functional support for such attribution (Tafazoli et al., 2017), by showing that this cortical progression is specialized for coding object identity despite view changes, the hallmark property of a ventral-like pathway. Here, we sought to clarify what computations are at the base of such specialization. To this aim, we performed multielectrode recordings from V1 and laterolateral area LL (at the apex of the putative ventral-like hierarchy) of male adult rats, during the presentation of drifting gratings and noise movies. We found that the extent to which neuronal responses were entrained to the phase of the gratings sharply dropped from V1 to LL, along with the quality of the receptive fields inferred through reverse correlation. Concomitantly, the tendency of neurons to respond to different oriented gratings increased, whereas the sharpness of orientation tuning declined. Critically, these trends are consistent with the nonlinear summation of visual inputs that is expected to take place along the ventral stream, according to the predictions of hierarchical models of ventral computations and a meta-analysis of the monkey literature. This suggests an intriguing homology between the mechanisms responsible for building up shape selectivity and transformation tolerance in the visual cortex of primates and rodents, reasserting the potential of the latter as models to investigate ventral stream functions at the circuitry level.SIGNIFICANCE STATEMENT Despite the growing popularity of rodents as models of visual functions, it remains unclear whether their visual cortex contains specialized modules for processing shape information. To addresses this question, we compared how neuronal tuning evolves from rat primary visual cortex (V1) to a downstream visual cortical region (area LL) that previous work has implicated in shape processing. In our experiments, LL neurons displayed a stronger tendency to respond to drifting gratings with different orientations while maintaining a sustained response across the whole duration of the drift cycle. These trends match the increased complexity of pattern selectivity and the augmented tolerance to stimulus translation found in monkey visual temporal cortex, thus revealing a homology between shape processing in rodents and primates.
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Najafi F, Churchland AK. Perceptual Decision-Making: A Field in the Midst of a Transformation. Neuron 2018; 100:453-462. [PMID: 30359608 PMCID: PMC6427923 DOI: 10.1016/j.neuron.2018.10.017] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 10/03/2018] [Accepted: 10/08/2018] [Indexed: 12/30/2022]
Abstract
Major changes are underway in the field of perceptual decision-making. Single-neuron studies have given way to population recordings with identified cell types, traditional analyses have been extended to accommodate these large and diverse collections of neurons, and novel methods of neural disruption have provided insights about causal circuits. Further, the field has expanded to include multiple new species: rodents and invertebrates, for example, have been instrumental in demonstrating the importance of internal state on neural responses. Finally, a renewed interest in ethological stimuli prompted development of new behaviors, frequently analyzed by new, automated movement tracking methods. Taken together, these advances constitute a seismic shift in both our approach and understanding of how incoming sensory signals are used to guide decisions.
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Pakan JM, Francioni V, Rochefort NL. Action and learning shape the activity of neuronal circuits in the visual cortex. Curr Opin Neurobiol 2018; 52:88-97. [PMID: 29727859 PMCID: PMC6562203 DOI: 10.1016/j.conb.2018.04.020] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 04/13/2018] [Indexed: 11/25/2022]
Abstract
Arousal and locomotion modulate neuronal activity in primary visual cortex. Neurons in primary visual cortex respond to visuomotor mismatch. Experience shapes neuronal responses to familiar stimuli, reward and object location. Neuronal representations of visual stimuli are modulated according to the behavioural relevance of the stimuli. Neuromodulatory, top-down and thalamocortical inputs convey arousal-related and motor-related signals to primary visual cortex.
Nonsensory variables strongly influence neuronal activity in the adult mouse primary visual cortex. Neuronal responses to visual stimuli are modulated by behavioural state, such as arousal and motor activity, and are shaped by experience. This dynamic process leads to neural representations in the visual cortex that reflect stimulus familiarity, expectations of reward and object location, and mismatch between self-motion and visual-flow. The recent development of genetic tools and recording techniques in awake behaving mice has enabled the investigation of the circuit mechanisms underlying state-dependent and experience-dependent neuronal representations in primary visual cortex. These neuronal circuits involve neuromodulatory, top-down cortico-cortical and thalamocortical pathways. The functions of nonsensory signals at this early stage of visual information processing are now beginning to be unravelled.
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Affiliation(s)
- Janelle Mp Pakan
- Center for Behavioral Brain Sciences, Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany; German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - Valerio Francioni
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, Edinburgh, United Kingdom
| | - Nathalie L Rochefort
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, Edinburgh, United Kingdom; Simons Initiative for the Developing Brain, Edinburgh, United Kingdom.
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Dylda E, Pakan JM, Rochefort NL. Chronic Two-Photon Calcium Imaging in the Visual Cortex of Awake Behaving Mice. ACTA ACUST UNITED AC 2018. [DOI: 10.1016/b978-0-12-812028-6.00013-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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