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Soumiya H, Mori S, Kageyama K, Kawakami M, Nara A, Furukawa S, Fukumitsu H. Distinct contributions of BDNF/MEK/ERK1/2 signaling pathway components to whisker-dependent tactile learning and memory. Brain Res 2025; 1848:149404. [PMID: 39694169 DOI: 10.1016/j.brainres.2024.149404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 11/24/2024] [Accepted: 12/14/2024] [Indexed: 12/20/2024]
Abstract
Whisker-mediated tactile perception is essential for rodent navigation, food acquisition, and social interactions. However, the molecular mechanisms underlying tactile information processing, learning, and memory have not been studied to the same extent as for other modalities. Using immunohistochemical staining, we investigated changes in regional c-Fos expression as an index of neuronal activity and phosphorylated (p)ERK1/2 as an index of ERK1/2 activity in mice trained on a tactile-cued 8-arm radial maze task. Over 12 trials, mice learned to selectively explore four baited arms covered with wire as the tactile cue while avoiding un-baited uncovered arms. The density of c-Fos+ cells was significantly higher in somatosensory cortex but not frontal cortex or amygdala of mice exposed to tactile cue - bait pairing compared to mice exposed to the same maze with all arms baited with or without tactile cues (unpaired conditions). The density of pERK1/2+ cells was also increased after paired trials 7 and 12 but not after paired trials 1 and 3 in frontal cortex, amygdala, and somatosensory cortex compared to mice exposed to the unpaired condition. The MEK1/2 inhibitor SL327 reduced c-Fos expression in frontal cortex and amygdala when applied during early trials, but impaired working memory when applied before later trials without affecting c-Fos expression. Heterozygous BDNF knockout mice exhibited impaired task learning and reduced pERK1/2 expression in frontal cortex and amygdala but not somatosensory cortex. These findings suggest that the BDNF/MEK/ERK1/2 pathway selectively promotes memory trace formation in frontal cortex and amygdala but not encoding in somatosensory cortex.
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Affiliation(s)
- Hitomi Soumiya
- Laboratory of Molecular Biology, Department of Biofunctional Analysis, Gifu Pharmaceutical University, Daigakunishi 1-25-4, Gifu 501-1196, Japan
| | - Shingo Mori
- Laboratory of Molecular Biology, Department of Biofunctional Analysis, Gifu Pharmaceutical University, Daigakunishi 1-25-4, Gifu 501-1196, Japan
| | - Kohta Kageyama
- Laboratory of Molecular Biology, Department of Biofunctional Analysis, Gifu Pharmaceutical University, Daigakunishi 1-25-4, Gifu 501-1196, Japan
| | - Masateru Kawakami
- Laboratory of Molecular Biology, Department of Biofunctional Analysis, Gifu Pharmaceutical University, Daigakunishi 1-25-4, Gifu 501-1196, Japan
| | - Aoi Nara
- Laboratory of Molecular Biology, Department of Biofunctional Analysis, Gifu Pharmaceutical University, Daigakunishi 1-25-4, Gifu 501-1196, Japan
| | - Shoei Furukawa
- Laboratory of Molecular Biology, Department of Biofunctional Analysis, Gifu Pharmaceutical University, Daigakunishi 1-25-4, Gifu 501-1196, Japan
| | - Hidefumi Fukumitsu
- Laboratory of Molecular Biology, Department of Biofunctional Analysis, Gifu Pharmaceutical University, Daigakunishi 1-25-4, Gifu 501-1196, Japan.
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2
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Mishra P, Narayanan R. The enigmatic HCN channels: A cellular neurophysiology perspective. Proteins 2025; 93:72-92. [PMID: 37982354 PMCID: PMC7616572 DOI: 10.1002/prot.26643] [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: 08/03/2023] [Revised: 10/24/2023] [Accepted: 11/09/2023] [Indexed: 11/21/2023]
Abstract
What physiological role does a slow hyperpolarization-activated ion channel with mixed cation selectivity play in the fast world of neuronal action potentials that are driven by depolarization? That puzzling question has piqued the curiosity of physiology enthusiasts about the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, which are widely expressed across the body and especially in neurons. In this review, we emphasize the need to assess HCN channels from the perspective of how they respond to time-varying signals, while also accounting for their interactions with other co-expressing channels and receptors. First, we illustrate how the unique structural and functional characteristics of HCN channels allow them to mediate a slow negative feedback loop in the neurons that they express in. We present the several physiological implications of this negative feedback loop to neuronal response characteristics including neuronal gain, voltage sag and rebound, temporal summation, membrane potential resonance, inductive phase lead, spike triggered average, and coincidence detection. Next, we argue that the overall impact of HCN channels on neuronal physiology critically relies on their interactions with other co-expressing channels and receptors. Interactions with other channels allow HCN channels to mediate intrinsic oscillations, earning them the "pacemaker channel" moniker, and to regulate spike frequency adaptation, plateau potentials, neurotransmitter release from presynaptic terminals, and spike initiation at the axonal initial segment. We also explore the impact of spatially non-homogeneous subcellular distributions of HCN channels in different neuronal subtypes and their interactions with other channels and receptors. Finally, we discuss how plasticity in HCN channels is widely prevalent and can mediate different encoding, homeostatic, and neuroprotective functions in a neuron. In summary, we argue that HCN channels form an important class of channels that mediate a diversity of neuronal functions owing to their unique gating kinetics that made them a puzzle in the first place.
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Affiliation(s)
- Poonam Mishra
- Department of Neuroscience, Yale School of MedicineYale UniversityNew HavenConnecticutUSA
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics UnitIndian Institute of ScienceBangaloreIndia
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3
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Northoff G, Hirjak D. Is depression a global brain disorder with topographic dynamic reorganization? Transl Psychiatry 2024; 14:278. [PMID: 38969642 PMCID: PMC11226458 DOI: 10.1038/s41398-024-02995-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 06/20/2024] [Accepted: 06/27/2024] [Indexed: 07/07/2024] Open
Abstract
Major depressive disorder (MDD) is characterized by a multitude of psychopathological symptoms including affective, cognitive, perceptual, sensorimotor, and social. The neuronal mechanisms underlying such co-occurrence of psychopathological symptoms remain yet unclear. Rather than linking and localizing single psychopathological symptoms to specific regions or networks, this perspective proposes a more global and dynamic topographic approach. We first review recent findings on global brain activity changes during both rest and task states in MDD showing topographic reorganization with a shift from unimodal to transmodal regions. Next, we single out two candidate mechanisms that may underlie and mediate such abnormal uni-/transmodal topography, namely dynamic shifts from shorter to longer timescales and abnormalities in the excitation-inhibition balance. Finally, we show how such topographic shift from unimodal to transmodal regions relates to the various psychopathological symptoms in MDD including their co-occurrence. This amounts to what we describe as 'Topographic dynamic reorganization' which extends our earlier 'Resting state hypothesis of depression' and complements other models of MDD.
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Affiliation(s)
- Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada.
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
- German Centre for Mental Health (DZPG), Partner Site Mannheim, Mannheim, Germany.
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4
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Federman N, Romano SA, Amigo-Duran M, Salomon L, Marin-Burgin A. Acquisition of non-olfactory encoding improves odour discrimination in olfactory cortex. Nat Commun 2024; 15:5572. [PMID: 38956072 PMCID: PMC11220071 DOI: 10.1038/s41467-024-49897-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 06/20/2024] [Indexed: 07/04/2024] Open
Abstract
Olfaction is influenced by contextual factors, past experiences, and the animal's internal state. Whether this information is integrated at the initial stages of cortical odour processing is not known, nor how these signals may influence odour encoding. Here we revealed multiple and diverse non-olfactory responses in the primary olfactory (piriform) cortex (PCx), which dynamically enhance PCx odour discrimination according to behavioural demands. We performed recordings of PCx neurons from mice trained in a virtual reality task to associate odours with visual contexts to obtain a reward. We found that learning shifts PCx activity from encoding solely odours to a regime in which positional, contextual, and associative responses emerge on odour-responsive neurons that become mixed-selective. The modulation of PCx activity by these non-olfactory signals was dynamic, improving odour decoding during task engagement and in rewarded contexts. This improvement relied on the acquired mixed-selectivity, demonstrating how integrating extra-sensory inputs in sensory cortices can enhance sensory processing while encoding the behavioural relevance of stimuli.
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Grants
- 108878 Canadian International Development Agency (Agence Canadienne de Développement International)
- PICT2018-0880 Ministry of Science, Technology and Productive Innovation, Argentina | National Agency for Science and Technology, Argentina | Fondo para la Investigación Científica y Tecnológica (Fund for Scientific and Technological Research)
- PICT2020-0360 Ministry of Science, Technology and Productive Innovation, Argentina | National Agency for Science and Technology, Argentina | Fondo para la Investigación Científica y Tecnológica (Fund for Scientific and Technological Research)
- PICT2020-1536 Ministry of Science, Technology and Productive Innovation, Argentina | National Agency for Science and Technology, Argentina | Fondo para la Investigación Científica y Tecnológica (Fund for Scientific and Technological Research)
- PICT2016-2758 Ministry of Science, Technology and Productive Innovation, Argentina | National Agency for Science and Technology, Argentina | Fondo para la Investigación Científica y Tecnológica (Fund for Scientific and Technological Research)
- PICT2017-4023 Ministry of Science, Technology and Productive Innovation, Argentina | National Agency for Science and Technology, Argentina | Fondo para la Investigación Científica y Tecnológica (Fund for Scientific and Technological Research)
- PIP2787 Ministerio de Ciencia, Tecnología e Innovación Productiva (Ministry of Science, Technology and Productive Innovation, Argentina)
- SPIRIT 216044 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
- Fondo para la convergencia estructural del Mercosur–FOCEM grant cOF 03/11
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Affiliation(s)
- Noel Federman
- Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA)-CONICET-Partner Institute of the Max Planck Society, Godoy Cruz 2390, C1425FQD, Buenos Aires, Argentina.
| | - Sebastián A Romano
- Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA)-CONICET-Partner Institute of the Max Planck Society, Godoy Cruz 2390, C1425FQD, Buenos Aires, Argentina.
| | - Macarena Amigo-Duran
- Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA)-CONICET-Partner Institute of the Max Planck Society, Godoy Cruz 2390, C1425FQD, Buenos Aires, Argentina
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, PhD Program, Buenos Aires, Argentina
| | - Lucca Salomon
- Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA)-CONICET-Partner Institute of the Max Planck Society, Godoy Cruz 2390, C1425FQD, Buenos Aires, Argentina
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, PhD Program, Buenos Aires, Argentina
| | - Antonia Marin-Burgin
- Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA)-CONICET-Partner Institute of the Max Planck Society, Godoy Cruz 2390, C1425FQD, Buenos Aires, Argentina.
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5
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Manley J, Lu S, Barber K, Demas J, Kim H, Meyer D, Traub FM, Vaziri A. Simultaneous, cortex-wide dynamics of up to 1 million neurons reveal unbounded scaling of dimensionality with neuron number. Neuron 2024; 112:1694-1709.e5. [PMID: 38452763 PMCID: PMC11098699 DOI: 10.1016/j.neuron.2024.02.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 05/18/2023] [Accepted: 02/14/2024] [Indexed: 03/09/2024]
Abstract
The brain's remarkable properties arise from the collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, can such low-dimensional representations truly explain the vast range of brain activity, and if not, what is the appropriate resolution and scale of recording to capture them? Imaging neural activity at cellular resolution and near-simultaneously across the mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number in populations up to 1 million neurons. Although half of the neural variance is contained within sixteen dimensions correlated with behavior, our discovered scaling of dimensionality corresponds to an ever-increasing number of neuronal ensembles without immediate behavioral or sensory correlates. The activity patterns underlying these higher dimensions are fine grained and cortex wide, highlighting that large-scale, cellular-resolution recording is required to uncover the full substrates of neuronal computations.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Sihao Lu
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Kevin Barber
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Jeffrey Demas
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - David Meyer
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Francisca Martínez Traub
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA.
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6
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Suárez-Grimalt R, Grunwald Kadow IC, Scheunemann L. An integrative sensor of body states: how the mushroom body modulates behavior depending on physiological context. Learn Mem 2024; 31:a053918. [PMID: 38876486 PMCID: PMC11199956 DOI: 10.1101/lm.053918.124] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 04/08/2024] [Indexed: 06/16/2024]
Abstract
The brain constantly compares past and present experiences to predict the future, thereby enabling instantaneous and future behavioral adjustments. Integration of external information with the animal's current internal needs and behavioral state represents a key challenge of the nervous system. Recent advancements in dissecting the function of the Drosophila mushroom body (MB) at the single-cell level have uncovered its three-layered logic and parallel systems conveying positive and negative values during associative learning. This review explores a lesser-known role of the MB in detecting and integrating body states such as hunger, thirst, and sleep, ultimately modulating motivation and sensory-driven decisions based on the physiological state of the fly. State-dependent signals predominantly affect the activity of modulatory MB input neurons (dopaminergic, serotoninergic, and octopaminergic), but also induce plastic changes directly at the level of the MB intrinsic and output neurons. Thus, the MB emerges as a tightly regulated relay station in the insect brain, orchestrating neuroadaptations due to current internal and behavioral states leading to short- but also long-lasting changes in behavior. While these adaptations are crucial to ensure fitness and survival, recent findings also underscore how circuit motifs in the MB may reflect fundamental design principles that contribute to maladaptive behaviors such as addiction or depression-like symptoms.
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Affiliation(s)
- Raquel Suárez-Grimalt
- Institute for Biology/Genetics, Freie Universität Berlin, 14195 Berlin, Germany
- Institut für Neurophysiologie and NeuroCure Cluster of Excellence, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
| | | | - Lisa Scheunemann
- Institute for Biology/Genetics, Freie Universität Berlin, 14195 Berlin, Germany
- Institut für Neurophysiologie and NeuroCure Cluster of Excellence, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
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7
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El Hady A, Takahashi D, Sun R, Akinwale O, Boyd-Meredith T, Zhang Y, Charles AS, Brody CD. Chronic brain functional ultrasound imaging in freely moving rodents performing cognitive tasks. J Neurosci Methods 2024; 403:110033. [PMID: 38056633 PMCID: PMC10872377 DOI: 10.1016/j.jneumeth.2023.110033] [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: 08/01/2023] [Revised: 11/06/2023] [Accepted: 12/01/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Functional ultrasound imaging (fUS) is an emerging imaging technique that indirectly measures neural activity via changes in blood volume. Chronic fUS imaging during cognitive tasks in freely moving animals faces multiple exceptional challenges: performing large durable craniotomies with chronic implants, designing behavioral experiments matching the hemodynamic timescale, stabilizing the ultrasound probe during freely moving behavior, accurately assessing motion artifacts, and validating that the animal can perform cognitive tasks while tethered. NEW METHOD We provide validated solutions for those technical challenges. In addition, we present standardized step-by-step reproducible protocols, procedures, and data processing pipelines. Finally, we present proof-of-concept analysis of brain dynamics during a decision making task. RESULTS We obtain stable recordings from which we can robustly decode task variables from fUS data over multiple months. Moreover, we find that brain wide imaging through hemodynamic response is nonlinearly related to cognitive variables, such as task difficulty, as compared to sensory responses previously explored. COMPARISON WITH EXISTING METHODS Computational pipelines in fUS are nascent and we present an initial development of a full processing pathway to correct and segment fUS data. CONCLUSIONS Our methods provide stable imaging and analysis of behavior with fUS that will enable new experimental paradigms in understanding brain-wide dynamics in naturalistic behaviors.
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Affiliation(s)
- Ahmed El Hady
- Princeton Neuroscience Institute, Princeton University, Princeton, United States; Center for advanced study of collective behavior, University of Konstanz, Germany; Max Planck Institute of Animal Behavior, Konstanz, Germany
| | - Daniel Takahashi
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Ruolan Sun
- Department of Biomedical Engineering, John Hopkins University, Baltimore, United States
| | - Oluwateniola Akinwale
- Department of Biomedical Engineering, John Hopkins University, Baltimore, United States
| | - Tyler Boyd-Meredith
- Princeton Neuroscience Institute, Princeton University, Princeton, United States
| | - Yisi Zhang
- Princeton Neuroscience Institute, Princeton University, Princeton, United States
| | - Adam S Charles
- Department of Biomedical Engineering, John Hopkins University, Baltimore, United States; Mathematical Institute for Data Science, Kavli Neuroscience Discovery Institute & Center for Imaging Science, John Hopkins University, Baltimore, United States.
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, United States; Howard Hughes Medical Institute, Princeton University, Princeton, United States; Department of Molecular Biology, Princeton University, Princeton, United States.
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8
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Brezovec BE, Berger AB, Hao YA, Chen F, Druckmann S, Clandinin TR. Mapping the neural dynamics of locomotion across the Drosophila brain. Curr Biol 2024; 34:710-726.e4. [PMID: 38242122 DOI: 10.1016/j.cub.2023.12.063] [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] [Revised: 11/13/2023] [Accepted: 12/20/2023] [Indexed: 01/21/2024]
Abstract
Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.
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Affiliation(s)
- Bella E Brezovec
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Andrew B Berger
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Yukun A Hao
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Feng Chen
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Shaul Druckmann
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Thomas R Clandinin
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA.
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9
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Chai Y, Qi K, Wu Y, Li D, Tan G, Guo Y, Chu J, Mu Y, Shen C, Wen Q. All-optical interrogation of brain-wide activity in freely swimming larval zebrafish. iScience 2024; 27:108385. [PMID: 38205255 PMCID: PMC10776927 DOI: 10.1016/j.isci.2023.108385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/22/2023] [Accepted: 10/30/2023] [Indexed: 01/12/2024] Open
Abstract
We introduce an all-optical technique that enables volumetric imaging of brain-wide calcium activity and targeted optogenetic stimulation of specific brain regions in unrestrained larval zebrafish. The system consists of three main components: a 3D tracking module, a dual-color fluorescence imaging module, and a real-time activity manipulation module. Our approach uses a sensitive genetically encoded calcium indicator in combination with a long Stokes shift red fluorescence protein as a reference channel, allowing the extraction of Ca2+ activity from signals contaminated by motion artifacts. The method also incorporates rapid 3D image reconstruction and registration, facilitating real-time selective optogenetic stimulation of different regions of the brain. By demonstrating that selective light activation of the midbrain regions in larval zebrafish could reliably trigger biased turning behavior and changes of brain-wide neural activity, we present a valuable tool for investigating the causal relationship between distributed neural circuit dynamics and naturalistic behavior.
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Affiliation(s)
- Yuming Chai
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Kexin Qi
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Yubin Wu
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Daguang Li
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Guodong Tan
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Yuqi Guo
- Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology and Center for Biomedical Optics and Molecular Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jun Chu
- Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology and Center for Biomedical Optics and Molecular Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yu Mu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Chen Shen
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Quan Wen
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
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10
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Manley J, Demas J, Kim H, Traub FM, Vaziri A. Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.15.575721. [PMID: 38293036 PMCID: PMC10827059 DOI: 10.1101/2024.01.15.575721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Jeffrey Demas
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Francisca Martínez Traub
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
- Lead Contact
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11
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Raut RV, Rosenthal ZP, Wang X, Miao H, Zhang Z, Lee JM, Raichle ME, Bauer AQ, Brunton SL, Brunton BW, Kutz JN. Arousal as a universal embedding for spatiotemporal brain dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.06.565918. [PMID: 38187528 PMCID: PMC10769245 DOI: 10.1101/2023.11.06.565918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Neural activity in awake organisms shows widespread and spatiotemporally diverse correlations with behavioral and physiological measurements. We propose that this covariation reflects in part the dynamics of a unified, arousal-related process that regulates brain-wide physiology on the timescale of seconds. Taken together with theoretical foundations in dynamical systems, this interpretation leads us to a surprising prediction: that a single, scalar measurement of arousal (e.g., pupil diameter) should suffice to reconstruct the continuous evolution of multimodal, spatiotemporal measurements of large-scale brain physiology. To test this hypothesis, we perform multimodal, cortex-wide optical imaging and behavioral monitoring in awake mice. We demonstrate that spatiotemporal measurements of neuronal calcium, metabolism, and blood-oxygen can be accurately and parsimoniously modeled from a low-dimensional state-space reconstructed from the time history of pupil diameter. Extending this framework to behavioral and electrophysiological measurements from the Allen Brain Observatory, we demonstrate the ability to integrate diverse experimental data into a unified generative model via mappings from an intrinsic arousal manifold. Our results support the hypothesis that spontaneous, spatially structured fluctuations in brain-wide physiology-widely interpreted to reflect regionally-specific neural communication-are in large part reflections of an arousal-related process. This enriched view of arousal dynamics has broad implications for interpreting observations of brain, body, and behavior as measured across modalities, contexts, and scales.
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Affiliation(s)
- Ryan V. Raut
- Allen Institute, Seattle, WA, USA
- Department of Physiology & Biophysics, University of Washington, Seattle, WA, USA
| | - Zachary P. Rosenthal
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Xiaodan Wang
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Hanyang Miao
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Zhanqi Zhang
- Department of Computer Science & Engineering, University of California San Diego, La Jolla, CA, USA
| | - Jin-Moo Lee
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Marcus E. Raichle
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Adam Q. Bauer
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Steven L. Brunton
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | | | - J. Nathan Kutz
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
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12
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Baruchin LJ, Alleman M, Schröder S. Reward Modulates Visual Responses in the Superficial Superior Colliculus of Mice. J Neurosci 2023; 43:8663-8680. [PMID: 37879894 PMCID: PMC7615379 DOI: 10.1523/jneurosci.0089-23.2023] [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: 01/09/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 10/27/2023] Open
Abstract
The processing of sensory input is constantly adapting to behavioral demands and internal states. The drive to obtain reward, e.g., searching for water when thirsty, is a strong behavioral demand and associating the reward with its source, a certain environment or action, is paramount for survival. Here, we show that water reward increases subsequent visual activity in the superficial layers of the superior colliculus (SC), which receive direct input from the retina and belong to the earliest stages of visual processing. We trained mice of either sex to perform a visual decision task and recorded the activity of neurons in the SC using two-photon calcium imaging and high-density electrophysiological recordings. Responses to visual stimuli in around 20% of visually responsive neurons in the superficial SC were affected by reward delivered in the previous trial. Reward mostly increased visual responses independent from modulations due to pupil size changes. The modulation of visual responses by reward could not be explained by movements like licking. It was specific to responses to the following visual stimulus, independent of slow fluctuations in neural activity and independent of how often the stimulus was previously rewarded. Electrophysiological recordings confirmed these results and revealed that reward affected the early phase of the visual response around 80 ms after stimulus onset. Modulation of visual responses by reward, but not pupil size, significantly improved the performance of a population decoder to detect visual stimuli, indicating the relevance of reward modulation for the visual performance of the animal.SIGNIFICANCE STATEMENT To learn which actions lead to food, water, or safety, it is necessary to integrate the receiving of reward with sensory stimuli related to the reward. Cortical stages of sensory processing have been shown to represent stimulus-reward associations. Here, we show, however, that reward influences neurons at a much earlier stage of sensory processing, the superior colliculus (SC), receiving direct input from the retina. Visual responses were increased shortly after the animal received the water reward, which led to an improved stimulus signal in the population of these visual neurons. Reward modulation of early visual responses may thus improve perception of visual environments predictive of reward.
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Affiliation(s)
- Liad J Baruchin
- School of Life Sciences, University of Sussex, Brighton BN1 9QG, United Kingdom
| | - Matteo Alleman
- Institute of Ophthalmology, University College London, London WC1E 6BT, United Kingdom
| | - Sylvia Schröder
- School of Life Sciences, University of Sussex, Brighton BN1 9QG, United Kingdom
- Institute of Ophthalmology, University College London, London WC1E 6BT, United Kingdom
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13
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Pennartz CMA, Oude Lohuis MN, Olcese U. How 'visual' is the visual cortex? The interactions between the visual cortex and other sensory, motivational and motor systems as enabling factors for visual perception. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220336. [PMID: 37545313 PMCID: PMC10404929 DOI: 10.1098/rstb.2022.0336] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/13/2023] [Indexed: 08/08/2023] Open
Abstract
The definition of the visual cortex is primarily based on the evidence that lesions of this area impair visual perception. However, this does not exclude that the visual cortex may process more information than of retinal origin alone, or that other brain structures contribute to vision. Indeed, research across the past decades has shown that non-visual information, such as neural activity related to reward expectation and value, locomotion, working memory and other sensory modalities, can modulate primary visual cortical responses to retinal inputs. Nevertheless, the function of this non-visual information is poorly understood. Here we review recent evidence, coming primarily from studies in rodents, arguing that non-visual and motor effects in visual cortex play a role in visual processing itself, for instance disentangling direct auditory effects on visual cortex from effects of sound-evoked orofacial movement. These findings are placed in a broader framework casting vision in terms of predictive processing under control of frontal, reward- and motor-related systems. In contrast to the prevalent notion that vision is exclusively constructed by the visual cortical system, we propose that visual percepts are generated by a larger network-the extended visual system-spanning other sensory cortices, supramodal areas and frontal systems. This article is part of the theme issue 'Decision and control processes in multisensory perception'.
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Affiliation(s)
- Cyriel M. A. Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
| | - Matthijs N. Oude Lohuis
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Champalimaud Research, Champalimaud Foundation, 1400-038 Lisbon, Portugal
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
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14
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Schaffer ES, Mishra N, Whiteway MR, Li W, Vancura MB, Freedman J, Patel KB, Voleti V, Paninski L, Hillman EMC, Abbott LF, Axel R. The spatial and temporal structure of neural activity across the fly brain. Nat Commun 2023; 14:5572. [PMID: 37696814 PMCID: PMC10495430 DOI: 10.1038/s41467-023-41261-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 08/29/2023] [Indexed: 09/13/2023] Open
Abstract
What are the spatial and temporal scales of brainwide neuronal activity? We used swept, confocally-aligned planar excitation (SCAPE) microscopy to image all cells in a large volume of the brain of adult Drosophila with high spatiotemporal resolution while flies engaged in a variety of spontaneous behaviors. This revealed neural representations of behavior on multiple spatial and temporal scales. The activity of most neurons correlated (or anticorrelated) with running and flailing over timescales that ranged from seconds to a minute. Grooming elicited a weaker global response. Significant residual activity not directly correlated with behavior was high dimensional and reflected the activity of small clusters of spatially organized neurons that may correspond to genetically defined cell types. These clusters participate in the global dynamics, indicating that neural activity reflects a combination of local and broadly distributed components. This suggests that microcircuits with highly specified functions are provided with knowledge of the larger context in which they operate.
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Affiliation(s)
- Evan S Schaffer
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA.
| | - Neeli Mishra
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Matthew R Whiteway
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Statistics and the Grossman Center for the Statistics of Mind, Columbia University, New York, NY, 10027, USA
| | - Wenze Li
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Michelle B Vancura
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Jason Freedman
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Kripa B Patel
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Venkatakaushik Voleti
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Liam Paninski
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Statistics and the Grossman Center for the Statistics of Mind, Columbia University, New York, NY, 10027, USA
| | - Elizabeth M C Hillman
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
- Department of Radiology, Columbia University, New York, NY, 10027, USA
| | - L F Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Physiology and Cellular Biophysics, Columbia University, New York, NY, 10032, USA
| | - Richard Axel
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
- Howard Hughes Medical Institute, Columbia University, New York, NY, 10027, USA
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15
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Hoemann K, Wormwood JB, Barrett LF, Quigley KS. Multimodal, Idiographic Ambulatory Sensing Will Transform our Understanding of Emotion. AFFECTIVE SCIENCE 2023; 4:480-486. [PMID: 37744967 PMCID: PMC10513989 DOI: 10.1007/s42761-023-00206-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 07/17/2023] [Indexed: 09/26/2023]
Abstract
Emotions are inherently complex - situated inside the brain while being influenced by conditions inside the body and outside in the world - resulting in substantial variation in experience. Most studies, however, are not designed to sufficiently sample this variation. In this paper, we discuss what could be discovered if emotion were systematically studied within persons 'in the wild', using biologically-triggered experience sampling: a multimodal and deeply idiographic approach to ambulatory sensing that links body and mind across contexts and over time. We outline the rationale for this approach, discuss challenges to its implementation and widespread adoption, and set out opportunities for innovation afforded by emerging technologies. Implementing these innovations will enrich method and theory at the frontier of affective science, propelling the contextually situated study of emotion into the future.
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Affiliation(s)
- Katie Hoemann
- Department of Psychology, KU Leuven, Tiensestraat 102, Box 3727, 3000 Leuven, BE Belgium
| | - Jolie B. Wormwood
- Department of Psychology, University of New Hampshire, Durham, NH USA
| | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Cambridge, MA USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
| | - Karen S. Quigley
- Department of Psychology, Northeastern University, Boston, MA USA
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16
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Mimica B, Tombaz T, Battistin C, Fuglstad JG, Dunn BA, Whitlock JR. Behavioral decomposition reveals rich encoding structure employed across neocortex in rats. Nat Commun 2023; 14:3947. [PMID: 37402724 PMCID: PMC10319800 DOI: 10.1038/s41467-023-39520-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 06/16/2023] [Indexed: 07/06/2023] Open
Abstract
The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordings across four cortical regions (visual, auditory, somatosensory, motor) in relation to sensory modulation, posture, movement, and ethograms of freely foraging male rats. Momentary actions, such as rearing or turning, were represented ubiquitously and could be decoded from all sampled structures. However, more elementary and continuous features, such as pose and movement, followed region-specific organization, with neurons in visual and auditory cortices preferentially encoding mutually distinct head-orienting features in world-referenced coordinates, and somatosensory and motor cortices principally encoding the trunk and head in egocentric coordinates. The tuning properties of synaptically coupled cells also exhibited connection patterns suggestive of area-specific uses of pose and movement signals, particularly in visual and auditory regions. Together, our results indicate that ongoing behavior is encoded at multiple levels throughout the dorsal cortex, and that low-level features are differentially utilized by different regions to serve locally relevant computations.
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Affiliation(s)
- Bartul Mimica
- Princeton Neuroscience Institute, Princeton University, Washington Road, Princeton, 100190, NJ, USA.
| | - Tuçe Tombaz
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway
| | - Claudia Battistin
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway
- Department of Mathematical Sciences, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Jingyi Guo Fuglstad
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway
| | - Benjamin A Dunn
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway
- Department of Mathematical Sciences, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Jonathan R Whitlock
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway.
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17
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Aimon S, Cheng KY, Gjorgjieva J, Grunwald Kadow IC. Global change in brain state during spontaneous and forced walk in Drosophila is composed of combined activity patterns of different neuron classes. eLife 2023; 12:e85202. [PMID: 37067152 PMCID: PMC10168698 DOI: 10.7554/elife.85202] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 04/13/2023] [Indexed: 04/18/2023] Open
Abstract
Movement-correlated brain activity has been found across species and brain regions. Here, we used fast whole brain lightfield imaging in adult Drosophila to investigate the relationship between walk and brain-wide neuronal activity. We observed a global change in activity that tightly correlated with spontaneous bouts of walk. While imaging specific sets of excitatory, inhibitory, and neuromodulatory neurons highlighted their joint contribution, spatial heterogeneity in walk- and turning-induced activity allowed parsing unique responses from subregions and sometimes individual candidate neurons. For example, previously uncharacterized serotonergic neurons were inhibited during walk. While activity onset in some areas preceded walk onset exclusively in spontaneously walking animals, spontaneous and forced walk elicited similar activity in most brain regions. These data suggest a major contribution of walk and walk-related sensory or proprioceptive information to global activity of all major neuronal classes.
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Affiliation(s)
- Sophie Aimon
- School of Life Sciences, Technical University of MunichFreisingGermany
| | - Karen Y Cheng
- School of Life Sciences, Technical University of MunichFreisingGermany
- University of Bonn, Medical Faculty (UKB), Institute of Physiology IIBonnGermany
| | - Julijana Gjorgjieva
- School of Life Sciences, Technical University of MunichFreisingGermany
- Max Planck Institute for Brain Research, Computation in Neural CircuitsFrankfurtGermany
| | - Ilona C Grunwald Kadow
- School of Life Sciences, Technical University of MunichFreisingGermany
- University of Bonn, Medical Faculty (UKB), Institute of Physiology IIBonnGermany
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18
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Lin A, Qin S, Casademunt H, Wu M, Hung W, Cain G, Tan NZ, Valenzuela R, Lesanpezeshki L, Venkatachalam V, Pehlevan C, Zhen M, Samuel AD. Functional imaging and quantification of multineuronal olfactory responses in C. elegans. SCIENCE ADVANCES 2023; 9:eade1249. [PMID: 36857454 PMCID: PMC9977185 DOI: 10.1126/sciadv.ade1249] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/01/2023] [Indexed: 05/21/2023]
Abstract
Many animals perceive odorant molecules by collecting information from ensembles of olfactory neurons, where each neuron uses receptors that are tuned to recognize certain odorant molecules with different binding affinity. Olfactory systems are able, in principle, to detect and discriminate diverse odorants using combinatorial coding strategies. We have combined microfluidics and multineuronal imaging to study the ensemble-level olfactory representations at the sensory periphery of the nematode Caenorhabditis elegans. The collective activity of C. elegans chemosensory neurons reveals high-dimensional representations of olfactory information across a broad space of odorant molecules. We reveal diverse tuning properties and dose-response curves across chemosensory neurons and across odorants. We describe the unique contribution of each sensory neuron to an ensemble-level code for volatile odorants. We show that a natural stimuli, a set of nematode pheromones, are also encoded by the sensory ensemble. The integrated activity of the C. elegans chemosensory neurons contains sufficient information to robustly encode the intensity and identity of diverse chemical stimuli.
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Affiliation(s)
- Albert Lin
- Department of Physics, Harvard University, Cambridge, MA, USA
- Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Shanshan Qin
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Helena Casademunt
- Department of Physics, Harvard University, Cambridge, MA, USA
- Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Min Wu
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Wesley Hung
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Gregory Cain
- Department of Physics, Harvard University, Cambridge, MA, USA
| | - Nicolas Z. Tan
- Department of Physics, Northeastern University, Boston, MA, USA
| | | | - Leila Lesanpezeshki
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | | | - Cengiz Pehlevan
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Mei Zhen
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Aravinthan D.T. Samuel
- Department of Physics, Harvard University, Cambridge, MA, USA
- Center for Brain Science, Harvard University, Cambridge, MA, USA
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19
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Westlin C, Theriault JE, Katsumi Y, Nieto-Castanon A, Kucyi A, Ruf SF, Brown SM, Pavel M, Erdogmus D, Brooks DH, Quigley KS, Whitfield-Gabrieli S, Barrett LF. Improving the study of brain-behavior relationships by revisiting basic assumptions. Trends Cogn Sci 2023; 27:246-257. [PMID: 36739181 PMCID: PMC10012342 DOI: 10.1016/j.tics.2022.12.015] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/23/2022] [Accepted: 12/29/2022] [Indexed: 02/05/2023]
Abstract
Neuroimaging research has been at the forefront of concerns regarding the failure of experimental findings to replicate. In the study of brain-behavior relationships, past failures to find replicable and robust effects have been attributed to methodological shortcomings. Methodological rigor is important, but there are other overlooked possibilities: most published studies share three foundational assumptions, often implicitly, that may be faulty. In this paper, we consider the empirical evidence from human brain imaging and the study of non-human animals that calls each foundational assumption into question. We then consider the opportunities for a robust science of brain-behavior relationships that await if scientists ground their research efforts in revised assumptions supported by current empirical evidence.
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Affiliation(s)
| | - Jordan E Theriault
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alfonso Nieto-Castanon
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Aaron Kucyi
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, USA
| | - Sebastian F Ruf
- Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, USA
| | - Sarah M Brown
- Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI, USA
| | - Misha Pavel
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA; Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA
| | - Deniz Erdogmus
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
| | - Dana H Brooks
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
| | - Karen S Quigley
- Department of Psychology, Northeastern University, Boston, MA, USA
| | | | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, USA; A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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20
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Bijoch Ł, Klos J, Pawłowska M, Wiśniewska J, Legutko D, Szachowicz U, Kaczmarek L, Beroun A. Whole-brain tracking of cocaine and sugar rewards processing. Transl Psychiatry 2023; 13:20. [PMID: 36683039 PMCID: PMC9868126 DOI: 10.1038/s41398-023-02318-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 01/07/2023] [Accepted: 01/10/2023] [Indexed: 01/24/2023] Open
Abstract
Natural rewards, such as food, and sex are appetitive stimuli available for animals in their natural environment. Similarly, addictive rewards such as drugs of abuse possess strong, positive valence, but their action relies on their pharmacological properties. Nevertheless, it is believed that both of these kinds of rewards activate similar brain circuitry. The present study aimed to discover which parts of the brain process the experience of natural and addictive rewards. To holistically address this question, we used a single-cell whole-brain imaging approach to find patterns of activation for acute and prolonged sucrose and cocaine exposure. We analyzed almost 400 brain structures and created a brain-wide map of specific, c-Fos-positive neurons engaged by these rewards. Acute but not prolonged sucrose exposure triggered a massive c-Fos expression throughout the brain. Cocaine exposure on the other hand potentiated c-Fos expression with prolonged use, engaging more structures than sucrose treatment. The functional connectivity analysis unraveled an increase in brain modularity after the initial exposure to both types of rewards. This modularity was increased after repeated cocaine, but not sucrose, intake. To check whether discrepancies between the processing of both types of rewards can be found on a cellular level, we further studied the nucleus accumbens, one of the most strongly activated brain structures by both sucrose and cocaine experience. We found a high overlap between natural and addictive rewards on the level of c-Fos expression. Electrophysiological measurements of cellular correlates of synaptic plasticity revealed that natural and addictive rewards alike induce the accumulation of silent synapses. These results strengthen the hypothesis that in the nucleus accumbens drugs of abuse cause maladaptive neuronal plasticity in the circuitry that typically processes natural rewards.
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Affiliation(s)
- Łukasz Bijoch
- grid.419305.a0000 0001 1943 2944Laboratory of Neuronal Plasticity, Nencki-EMBL Center of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Joanna Klos
- grid.419305.a0000 0001 1943 2944Laboratory of Neuronal Plasticity, Nencki-EMBL Center of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Monika Pawłowska
- grid.419305.a0000 0001 1943 2944Laboratory of Neurobiology, Nencki-EMBL Center of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland ,grid.12847.380000 0004 1937 1290Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland
| | - Justyna Wiśniewska
- grid.419305.a0000 0001 1943 2944Laboratory of Neuronal Plasticity, Nencki-EMBL Center of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Diana Legutko
- grid.419305.a0000 0001 1943 2944Laboratory of Neurobiology, Nencki-EMBL Center of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Urszula Szachowicz
- grid.419305.a0000 0001 1943 2944Laboratory of Neuronal Plasticity, Nencki-EMBL Center of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Leszek Kaczmarek
- grid.419305.a0000 0001 1943 2944Laboratory of Neurobiology, Nencki-EMBL Center of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Anna Beroun
- Laboratory of Neuronal Plasticity, Nencki-EMBL Center of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland.
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21
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Baker B, Lansdell B, Kording KP. Three aspects of representation in neuroscience. Trends Cogn Sci 2022; 26:942-958. [PMID: 36175303 PMCID: PMC11749295 DOI: 10.1016/j.tics.2022.08.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 08/18/2022] [Accepted: 08/25/2022] [Indexed: 01/12/2023]
Abstract
Neuroscientists often describe neural activity as a representation of something, or claim to have found evidence for a neural representation, but there is considerable ambiguity about what such claims entail. Here we develop a thorough account of what 'representation' does and should do for neuroscientists in terms of three key aspects of representation. (i) Correlation: a neural representation correlates to its represented content; (ii) causal role: the representation has a characteristic effect on behavior; and (iii) teleology: a goal or purpose served by the behavior and thus the representation. We draw broadly on literature in both neuroscience and philosophy to show how these three aspects are rooted in common approaches to understanding the brain and mind. We first describe different contexts that 'representation' has been closely linked to in neuroscience, then discuss each of the three aspects in detail.
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Affiliation(s)
- Ben Baker
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA.
| | - Benjamin Lansdell
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Konrad P Kording
- Department of Neuroscience, Bioengineering, University of Pennsylvania, CIFAR, Philadelphia, PA, USA
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22
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Lipp HP, Wolfer DP. Behavior is movement only but how to interpret it? Problems and pitfalls in translational neuroscience-a 40-year experience. Front Behav Neurosci 2022; 16:958067. [PMID: 36330050 PMCID: PMC9623569 DOI: 10.3389/fnbeh.2022.958067] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 09/07/2022] [Indexed: 09/19/2023] Open
Abstract
Translational research in behavioral neuroscience seeks causes and remedies for human mental health problems in animals, following leads imposed by clinical research in psychiatry. This endeavor faces several problems because scientists must read and interpret animal movements to represent human perceptions, mood, and memory processes. Yet, it is still not known how mammalian brains bundle all these processes into a highly compressed motor output in the brain stem and spinal cord, but without that knowledge, translational research remains aimless. Based on some four decades of experience in the field, the article identifies sources of interpretation problems and illustrates typical translational pitfalls. (1) The sensory world of mice is different. Smell, hearing, and tactile whisker sensations dominate in rodents, while visual input is comparatively small. In humans, the relations are reversed. (2) Mouse and human brains are equated inappropriately: the association cortex makes up a large portion of the human neocortex, while it is relatively small in rodents. The predominant associative cortex in rodents is the hippocampus itself, orchestrating chiefly inputs from secondary sensorimotor areas and generating species-typical motor patterns that are not easily reconciled with putative human hippocampal functions. (3) Translational interpretation of studies of memory or emotionality often neglects the ecology of mice, an extremely small species surviving by freezing or flight reactions that do not need much cognitive processing. (4) Further misinterpretations arise from confounding neuronal properties with system properties, and from rigid mechanistic thinking unaware that many experimentally induced changes in the brain do partially reflect unpredictable compensatory plasticity. (5) Based on observing hippocampal lesion effects in mice indoors and outdoors, the article offers a simplistic general model of hippocampal functions in relation to hypothalamic input and output, placing hypothalamus and the supraspinal motor system at the top of a cerebral hierarchy. (6) Many translational problems could be avoided by inclusion of simple species-typical behaviors as end-points comparable to human cognitive or executive processing, and to rely more on artificial intelligence for recognizing patterns not classifiable by traditional psychological concepts.
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Affiliation(s)
- Hans-Peter Lipp
- Institute of Evolutionary Medicine, University of Zürich, Zürich, Switzerland
| | - David P. Wolfer
- Faculty of Medicine, Institute of Anatomy, University of Zürich, Zürich, Switzerland
- Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zürich, Zürich, Switzerland
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23
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Katsumi Y, Theriault JE, Quigley KS, Barrett LF. Allostasis as a core feature of hierarchical gradients in the human brain. Netw Neurosci 2022; 6:1010-1031. [PMID: 38800458 PMCID: PMC11117115 DOI: 10.1162/netn_a_00240] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/11/2022] [Indexed: 05/29/2024] Open
Abstract
This paper integrates emerging evidence from two broad streams of scientific literature into one common framework: (a) hierarchical gradients of functional connectivity that reflect the brain's large-scale structural architecture (e.g., a lamination gradient in the cerebral cortex); and (b) approaches to predictive processing and one of its specific instantiations called allostasis (i.e., the predictive regulation of energetic resources in the service of coordinating the body's internal systems). This synthesis begins to sketch a coherent, neurobiologically inspired framework suggesting that predictive energy regulation is at the core of human brain function, and by extension, psychological and behavioral phenomena, providing a shared vocabulary for theory building and knowledge accumulation.
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Affiliation(s)
- Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Karen S. Quigley
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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24
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Zhang YS, Takahashi DY, El Hady A, Liao DA, Ghazanfar AA. Active neural coordination of motor behaviors with internal states. Proc Natl Acad Sci U S A 2022; 119:e2201194119. [PMID: 36122243 PMCID: PMC9522379 DOI: 10.1073/pnas.2201194119] [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: 01/21/2022] [Accepted: 08/16/2022] [Indexed: 11/18/2022] Open
Abstract
The brain continuously coordinates skeletomuscular movements with internal physiological states like arousal, but how is this coordination achieved? One possibility is that the brain simply reacts to changes in external and/or internal signals. Another possibility is that it is actively coordinating both external and internal activities. We used functional ultrasound imaging to capture a large medial section of the brain, including multiple cortical and subcortical areas, in marmoset monkeys while monitoring their spontaneous movements and cardiac activity. By analyzing the causal ordering of these different time series, we found that information flowing from the brain to movements and heart-rate fluctuations were significantly greater than in the opposite direction. The brain areas involved in this external versus internal coordination were spatially distinct, but also extensively interconnected. Temporally, the brain alternated between network states for this regulation. These findings suggest that the brain's dynamics actively and efficiently coordinate motor behavior with internal physiology.
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Affiliation(s)
- Yisi S. Zhang
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544
| | - Daniel Y. Takahashi
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544
- Brain Institute, Federal University of Rio Grande do Norte, Natal 59076-550, Brazil
| | - Ahmed El Hady
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544
- Center for Advanced Study of Collective Behavior, University of Konstanz, Konstanz 78464, Germany
- Department of Collective Behavior, Max Planck Institute of Animal Behavior, Konstanz 78464, Germany
| | - Diana A. Liao
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544
| | - Asif A. Ghazanfar
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544
- Department of Psychology, Princeton University, Princeton, NJ 08544
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25
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Orlowska-Feuer P, Ebrahimi AS, Zippo AG, Petersen RS, Lucas RJ, Storchi R. Look-up and look-down neurons in the mouse visual thalamus during freely moving exploration. Curr Biol 2022; 32:3987-3999.e4. [PMID: 35973431 PMCID: PMC9616738 DOI: 10.1016/j.cub.2022.07.049] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/24/2022] [Accepted: 07/20/2022] [Indexed: 12/28/2022]
Abstract
Visual information reaches cortex via the thalamic dorsal lateral geniculate nucleus (dLGN). dLGN activity is modulated by global sleep/wake states and arousal, indicating that it is not simply a passive relay station. However, its potential for more specific visuomotor integration is largely unexplored. We addressed this question by developing robust 3D video reconstruction of mouse head and body during spontaneous exploration paired with simultaneous neuronal recordings from dLGN. Unbiased evaluation of a wide range of postures and movements revealed a widespread coupling between neuronal activity and few behavioral parameters. In particular, postures associated with the animal looking up/down correlated with activity in >50% neurons, and the extent of this effect was comparable with that induced by full-body movements (typically locomotion). By contrast, thalamic activity was minimally correlated with other postures or movements (e.g., left/right head and body torsions). Importantly, up/down postures and full-body movements were largely independent and jointly coupled to neuronal activity. Thus, although most units were excited during full-body movements, some expressed highest firing when the animal was looking up ("look-up" neurons), whereas others expressed highest firing when the animal was looking down ("look-down" neurons). These results were observed in the dark, thus representing a genuine behavioral modulation, and were amplified in a lit arena. Our results demonstrate that the primary visual thalamus, beyond global modulations by sleep/awake states, is potentially involved in specific visuomotor integration and reveal two distinct couplings between up/down postures and neuronal activity.
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Affiliation(s)
- Patrycja Orlowska-Feuer
- University of Manchester, Faculty of Biology, Medicine and Health, School of Biological Science, Division of Neuroscience and Experimental Psychology, Oxford Road, M139PL Manchester, UK
| | - Aghileh S Ebrahimi
- University of Manchester, Faculty of Biology, Medicine and Health, School of Biological Science, Division of Neuroscience and Experimental Psychology, Oxford Road, M139PL Manchester, UK
| | - Antonio G Zippo
- Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Via Raoul Follereau, 3, 20854 Vedano al Lambro, Italy
| | - Rasmus S Petersen
- University of Manchester, Faculty of Biology, Medicine and Health, School of Biological Science, Division of Neuroscience and Experimental Psychology, Oxford Road, M139PL Manchester, UK
| | - Robert J Lucas
- University of Manchester, Faculty of Biology, Medicine and Health, School of Biological Science, Division of Neuroscience and Experimental Psychology, Oxford Road, M139PL Manchester, UK
| | - Riccardo Storchi
- University of Manchester, Faculty of Biology, Medicine and Health, School of Biological Science, Division of Neuroscience and Experimental Psychology, Oxford Road, M139PL Manchester, UK.
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26
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Bonato J, Panzeri S. Neural coding: Looking up and down the visual thalamus. Curr Biol 2022; 32:R941-R943. [PMID: 36167039 DOI: 10.1016/j.cub.2022.08.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Integrating sensory and postural information is essential for perception and behavior. A new study shows that information about whether mice are looking up or down is combined with visual information in the primary visual thalamus, an early sensory stage of visual processing.
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Affiliation(s)
- Jacopo Bonato
- Department of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Istituto Italiano di Tecnologia, Genova, Italy; Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Stefano Panzeri
- Department of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Istituto Italiano di Tecnologia, Genova, Italy.
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27
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Sych Y, Fomins A, Novelli L, Helmchen F. Dynamic reorganization of the cortico-basal ganglia-thalamo-cortical network during task learning. Cell Rep 2022; 40:111394. [PMID: 36130513 PMCID: PMC9513804 DOI: 10.1016/j.celrep.2022.111394] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 05/31/2022] [Accepted: 08/29/2022] [Indexed: 11/19/2022] Open
Abstract
Adaptive behavior is coordinated by neuronal networks that are distributed across multiple brain regions such as in the cortico-basal ganglia-thalamo-cortical (CBGTC) network. Here, we ask how cross-regional interactions within such mesoscale circuits reorganize when an animal learns a new task. We apply multi-fiber photometry to chronically record simultaneous activity in 12 or 48 brain regions of mice trained in a tactile discrimination task. With improving task performance, most regions shift their peak activity from the time of reward-related action to the reward-predicting stimulus. By estimating cross-regional interactions using transfer entropy, we reveal that functional networks encompassing basal ganglia, thalamus, neocortex, and hippocampus grow and stabilize upon learning, especially at stimulus presentation time. The internal globus pallidus, ventromedial thalamus, and several regions in the frontal cortex emerge as salient hub regions. Our results highlight the learning-related dynamic reorganization that brain networks undergo when task-appropriate mesoscale network dynamics are established for goal-oriented behavior. Multi-fiber photometry reveals brain network adaptations during learning Activity in most regions temporally shifts from reward to predictive stimulus Cross-regional interactions in the CBGTC network increase and stabilize with learning Internal pallidum, VM thalamus, and prefrontal cortex regions emerge as hubs
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Affiliation(s)
- Yaroslav Sych
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland.
| | - Aleksejs Fomins
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland; Neuroscience Center Zurich, 8057 Zurich, Switzerland
| | - Leonardo Novelli
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland
| | - Fritjof Helmchen
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland; Neuroscience Center Zurich, 8057 Zurich, Switzerland.
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28
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Riedl J, Fieseler C, Zimmer M. Tyraminergic corollary discharge filters reafferent perception in a chemosensory neuron. Curr Biol 2022; 32:3048-3058.e6. [PMID: 35690069 DOI: 10.1016/j.cub.2022.05.051] [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: 04/20/2022] [Revised: 05/10/2022] [Accepted: 05/18/2022] [Indexed: 12/25/2022]
Abstract
Interpreting sensory information requires its integration with the current behavior of the animal. However, how motor-related circuits influence sensory information processing is incompletely understood. Here, we report that current locomotor state directly modulates the activity of BAG CO2 sensory neurons in Caenorhabditis elegans. By recording neuronal activity in animals freely navigating CO2 landscapes, we found that during reverse crawling states, BAG activity is suppressed by tyraminergic corollary discharge signaling. We provide genetic evidence that tyramine released from the RIM reversal interneurons extrasynaptically activates the inhibitory chloride channel LGC-55 in BAG. Disrupting this pathway genetically leads to excessive behavioral responses to CO2 stimuli. Moreover, we find that LGC-55 signaling cancels out perception of self-produced CO2 and O2 stimuli when animals reverse into their own gas plume in ethologically relevant aqueous environments. Our results show that sensorimotor integration involves corollary discharge signals directly modulating chemosensory neurons.
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Affiliation(s)
- Julia Riedl
- Department of Neuroscience and Developmental Biology, Vienna BioCenter (VBC), University of Vienna, Djerassiplatz 1, 1030 Vienna, Austria
| | - Charles Fieseler
- Department of Neuroscience and Developmental Biology, Vienna BioCenter (VBC), University of Vienna, Djerassiplatz 1, 1030 Vienna, Austria
| | - Manuel Zimmer
- Department of Neuroscience and Developmental Biology, Vienna BioCenter (VBC), University of Vienna, Djerassiplatz 1, 1030 Vienna, Austria; Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria.
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29
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Oude Lohuis MN, Pie JL, Marchesi P, Montijn JS, de Kock CPJ, Pennartz CMA, Olcese U. Multisensory task demands temporally extend the causal requirement for visual cortex in perception. Nat Commun 2022; 13:2864. [PMID: 35606448 PMCID: PMC9126973 DOI: 10.1038/s41467-022-30600-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 05/09/2022] [Indexed: 01/02/2023] Open
Abstract
Primary sensory areas constitute crucial nodes during perceptual decision making. However, it remains unclear to what extent they mainly constitute a feedforward processing step, or rather are continuously involved in a recurrent network together with higher-order areas. We found that the temporal window in which primary visual cortex is required for the detection of identical visual stimuli was extended when task demands were increased via an additional sensory modality that had to be monitored. Late-onset optogenetic inactivation preserved bottom-up, early-onset responses which faithfully encoded stimulus features, and was effective in impairing detection only if it preceded a late, report-related phase of the cortical response. Increasing task demands were marked by longer reaction times and the effect of late optogenetic inactivation scaled with reaction time. Thus, independently of visual stimulus complexity, multisensory task demands determine the temporal requirement for ongoing sensory-related activity in V1, which overlaps with report-related activity. How primary sensory cortices contribute to decision making remains poorly understood. Here the authors report that increasing task demands extend the temporal window in which the primary visual cortex is required for detecting identical stimuli.
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30
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Potter HD, Mitchell KJ. Naturalising Agent Causation. ENTROPY 2022; 24:e24040472. [PMID: 35455135 PMCID: PMC9030586 DOI: 10.3390/e24040472] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/10/2022] [Accepted: 03/23/2022] [Indexed: 11/16/2022]
Abstract
The idea of agent causation—that a system such as a living organism can be a cause of things in the world—is often seen as mysterious and deemed to be at odds with the physicalist thesis that is now commonly embraced in science and philosophy. Instead, the causal power of organisms is attributed to mechanistic components within the system or derived from the causal activity at the lowest level of physical description. In either case, the ‘agent’ itself (i.e., the system as a whole) is left out of the picture entirely, and agent causation is explained away. We argue that this is not the right way to think about causation in biology or in systems more generally. We present a framework of eight criteria that we argue, collectively, describe a system that overcomes the challenges concerning agent causality in an entirely naturalistic and non-mysterious way. They are: (1) thermodynamic autonomy, (2) persistence, (3) endogenous activity, (4) holistic integration, (5) low-level indeterminacy, (6) multiple realisability, (7) historicity, (8) agent-level normativity. Each criterion is taken to be dimensional rather than categorical, and thus we conclude with a short discussion on how researchers working on quantifying agency may use this multidimensional framework to situate and guide their research.
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Affiliation(s)
- Henry D. Potter
- Smurfit Institute of Genetics, Trinity College Dublin, D02 VF25 Dublin, Ireland;
- Institute of Neuroscience, Trinity College Dublin, D02 PN40 Dublin, Ireland
| | - Kevin J. Mitchell
- Smurfit Institute of Genetics, Trinity College Dublin, D02 VF25 Dublin, Ireland;
- Institute of Neuroscience, Trinity College Dublin, D02 PN40 Dublin, Ireland
- Correspondence:
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31
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Han Y, Huang K, Chen K, Pan H, Ju F, Long Y, Gao G, Wu R, Wang A, Wang L, Wei P. MouseVenue3D: A Markerless Three-Dimension Behavioral Tracking System for Matching Two-Photon Brain Imaging in Free-Moving Mice. Neurosci Bull 2022; 38:303-317. [PMID: 34637091 PMCID: PMC8975979 DOI: 10.1007/s12264-021-00778-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 06/23/2021] [Indexed: 10/20/2022] Open
Abstract
Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional (3-D) space. However, there is no available three-dimensional behavior capture system that focuses on rodents. Here, we present MouseVenue3D, an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents. We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module. Then, we validated this process in behavior recognition tasks, and showed that 3-D behavioral data achieved higher accuracy than 2-D data. Subsequently, MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse. Finally, we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice. Our findings reveal that subtle, spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.
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Affiliation(s)
- Yaning Han
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kang Huang
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ke Chen
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hongli Pan
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
| | - Furong Ju
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
| | - Yueyue Long
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
- University of Rochester, Rochester, NY, 14627, USA
| | - Gao Gao
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
- Honam University, Gwangju, 62399, South Korea
| | - Runlong Wu
- State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking University, Beijing, 100101, China
| | - Aimin Wang
- Department of Electronics, Peking University, Beijing, 100871, China
- State Key Laboratory of Advanced Optical Communication Systems and Networks, Peking University, Beijing, 100101, China
| | - Liping Wang
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Pengfei Wei
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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32
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Zatka-Haas P, Steinmetz NA, Carandini M, Harris KD. Sensory coding and the causal impact of mouse cortex in a visual decision. eLife 2021; 10:e63163. [PMID: 34328419 PMCID: PMC8324299 DOI: 10.7554/elife.63163] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 07/07/2021] [Indexed: 01/05/2023] Open
Abstract
Correlates of sensory stimuli and motor actions are found in multiple cortical areas, but such correlates do not indicate whether these areas are causally relevant to task performance. We trained mice to discriminate visual contrast and report their decision by steering a wheel. Widefield calcium imaging and Neuropixels recordings in cortex revealed stimulus-related activity in visual (VIS) and frontal (MOs) areas, and widespread movement-related activity across the whole dorsal cortex. Optogenetic inactivation biased choices only when targeted at VIS and MOs,proportionally to each site's encoding of the visual stimulus, and at times corresponding to peak stimulus decoding. A neurometric model based on summing and subtracting activity in VIS and MOs successfully described behavioral performance and predicted the effect of optogenetic inactivation. Thus, sensory signals localized in visual and frontal cortex play a causal role in task performance, while widespread dorsal cortical signals correlating with movement reflect processes that do not play a causal role.
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Affiliation(s)
- Peter Zatka-Haas
- UCL Queen Square Institute of Neurology, University College London, LondonLondonUnited Kingdom
- Department of Physiology, Anatomy & Genetics, University of OxfordOxfordUnited Kingdom
| | - Nicholas A Steinmetz
- UCL Queen Square Institute of Neurology, University College London, LondonLondonUnited Kingdom
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, LondonLondonUnited Kingdom
| | - Kenneth D Harris
- UCL Queen Square Institute of Neurology, University College London, LondonLondonUnited Kingdom
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33
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Xu L, Guan NN, Huang CX, Hua Y, Song J. A neuronal circuit that generates the temporal motor sequence for the defensive response in zebrafish larvae. Curr Biol 2021; 31:3343-3357.e4. [PMID: 34289386 DOI: 10.1016/j.cub.2021.06.054] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/06/2021] [Accepted: 06/21/2021] [Indexed: 01/11/2023]
Abstract
Animals use a precisely timed motor sequence to escape predators. This requires the nervous system to coordinate several motor behaviors and execute them in a temporal and smooth manner. We here describe a neuronal circuit that faithfully generates a defensive motor sequence in zebrafish larvae. The temporally specific defensive motor sequence consists of an initial escape and a subsequent swim behavior and can be initiated by unilateral stimulation of a single Mauthner cell (M-cell). The smooth transition from escape behavior to swim behavior is achieved by activating a neuronal chain circuit, which permits an M-cell to drive descending neurons in bilateral nucleus of medial longitudinal fascicle (nMLF) via activation of an intermediate excitatory circuit formed by interconnected hindbrain cranial relay neurons. The sequential activation of M-cells and neurons in bilateral nMLF via activation of hindbrain cranial relay neurons ensures the smooth execution of escape and swim behaviors in a timely manner. We propose an existence of a serial model that executes a temporal motor sequence involving three different brain regions that initiates the escape behavior and triggers a subsequent swim. This model has general implications regarding the neural control of complex motor sequences.
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Affiliation(s)
- Lulu Xu
- Motor Control Laboratory, Translational Research Institute of Brain and Brain-Like Intelligence, Department of Anatomy, Histology and Embryology, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Na N Guan
- Motor Control Laboratory, Translational Research Institute of Brain and Brain-Like Intelligence, Department of Anatomy, Histology and Embryology, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200092, China; Clinical Center for Brain and Spinal Cord Research, Tongji University, 200092 Shanghai, China
| | - Chun-Xiao Huang
- Motor Control Laboratory, Translational Research Institute of Brain and Brain-Like Intelligence, Department of Anatomy, Histology and Embryology, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Yunfeng Hua
- Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Jianren Song
- Motor Control Laboratory, Translational Research Institute of Brain and Brain-Like Intelligence, Department of Anatomy, Histology and Embryology, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200092, China; Clinical Center for Brain and Spinal Cord Research, Tongji University, 200092 Shanghai, China.
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34
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Emmons SW, Yemini E, Zimmer M. Methods for analyzing neuronal structure and activity in Caenorhabditis elegans. Genetics 2021; 218:6303616. [PMID: 34151952 DOI: 10.1093/genetics/iyab072] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 04/20/2021] [Indexed: 11/12/2022] Open
Abstract
The model research animal Caenorhabditis elegans has unique properties making it particularly advantageous for studies of the nervous system. The nervous system is composed of a stereotyped complement of neurons connected in a consistent manner. Here, we describe methods for studying nervous system structure and function. The transparency of the animal makes it possible to visualize and identify neurons in living animals with fluorescent probes. These methods have been recently enhanced for the efficient use of neuron-specific reporter genes. Because of its simple structure, for a number of years, C. elegans has been at the forefront of connectomic studies defining synaptic connectivity by electron microscopy. This field is burgeoning with new, more powerful techniques, and recommended up-to-date methods are here described that encourage the possibility of new work in C. elegans. Fluorescent probes for single synapses and synaptic connections have allowed verification of the EM reconstructions and for experimental approaches to synapse formation. Advances in microscopy and in fluorescent reporters sensitive to Ca2+ levels have opened the way to observing activity within single neurons across the entire nervous system.
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Affiliation(s)
- Scott W Emmons
- Department of Genetics and Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 1041, USA
| | - Eviatar Yemini
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia University, New York, NY 10027, USA
| | - Manuel Zimmer
- Department of Neuroscience and Developmental Biology, University of Vienna, Vienna 1090, Austria and.,Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna 1030, Austria
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35
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Hasani R, Ferrari G, Yamamoto H, Tanii T, Prati E. Role of Noise in Spontaneous Activity of Networks of Neurons on Patterned Silicon Emulated by Noise–activated CMOS Neural Nanoelectronic Circuits. NANO EXPRESS 2021. [DOI: 10.1088/2632-959x/abf2ae] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Abstract
Background noise in biological cortical microcircuits constitutes a powerful resource to assess their computational tasks, including, for instance, the synchronization of spiking activity, the enhancement of the speed of information transmission, and the minimization of the corruption of signals. We explore the correlation of spontaneous firing activity of ≈ 100 biological neurons adhering to engineered scaffolds by governing the number of functionalized patterned connection pathways among groups of neurons. We then emulate the biological system by a series of noise-activated silicon neural network simulations. We show that by suitably tuning both the amplitude of noise and the number of synapses between the silicon neurons, the same controlled correlation of the biological population is achieved. Our results extend to a realistic silicon nanoelectronics neuron design using noise injection to be exploited in artificial spiking neural networks such as liquid state machines and recurrent neural networks for stochastic computation.
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36
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Huang K, Han Y, Chen K, Pan H, Zhao G, Yi W, Li X, Liu S, Wei P, Wang L. A hierarchical 3D-motion learning framework for animal spontaneous behavior mapping. Nat Commun 2021; 12:2784. [PMID: 33986265 PMCID: PMC8119960 DOI: 10.1038/s41467-021-22970-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Accepted: 04/06/2021] [Indexed: 02/03/2023] Open
Abstract
Animal behavior usually has a hierarchical structure and dynamics. Therefore, to understand how the neural system coordinates with behaviors, neuroscientists need a quantitative description of the hierarchical dynamics of different behaviors. However, the recent end-to-end machine-learning-based methods for behavior analysis mostly focus on recognizing behavioral identities on a static timescale or based on limited observations. These approaches usually lose rich dynamic information on cross-scale behaviors. Here, inspired by the natural structure of animal behaviors, we address this challenge by proposing a parallel and multi-layered framework to learn the hierarchical dynamics and generate an objective metric to map the behavior into the feature space. In addition, we characterize the animal 3D kinematics with our low-cost and efficient multi-view 3D animal motion-capture system. Finally, we demonstrate that this framework can monitor spontaneous behavior and automatically identify the behavioral phenotypes of the transgenic animal disease model. The extensive experiment results suggest that our framework has a wide range of applications, including animal disease model phenotyping and the relationships modeling between the neural circuits and behavior.
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Grants
- This work was supported in part by Key Area R&D Program of Guangdong Province (2018B030338001 P.W., 2018B030331001 L.W.), National Key R&D Program of China (2018YFA0701403 P.W.), National Natural Science Foundation of China (NSFC 31500861 P.W., NSFC 31630031 L.W., NSFC 91732304 L.W., NSFC 31930047 L.W.), Chang Jiang Scholars Program (L.W.), the International Big Science Program Cultivating Project of CAS (172644KYS820170004 L.W.), the Strategic Priority Research Program of Chinese Academy of Science (XDB32030100, L.W.), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (2017413 P.W.), CAS Key Laboratory of Brain Connectome and Manipulation (2019DP173024), Shenzhen Government Basic Research Grants (JCYJ20170411140807570 P.W., JCYJ20170413164535041 L.W.), Science, Technology and Innovation Commission of Shenzhen Municipality (JCYJ20160429185235132 K.H.), Helmholtz-CAS joint research grant (GJHZ1508 L.W.), Guangdong Provincial Key Laboratory of Brain Connectome and Behavior (2017B030301017 L.W.), the Ten Thousand Talent Program (L.W.), the Guangdong Special Support Program (L.W.), Key Laboratory of SIAT (2019DP173024 L.W.), Shenzhen Key Science and Technology Infrastructure Planning Project (ZDKJ20190204002 L.W.).
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Affiliation(s)
- Kang Huang
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yaning Han
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ke Chen
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Hongli Pan
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Gaoyang Zhao
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wenling Yi
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoxi Li
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Siyuan Liu
- Pennsylvania State University, University Park, PA, USA
| | - Pengfei Wei
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
- University of Chinese Academy of Sciences, Beijing, China.
| | - Liping Wang
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
- University of Chinese Academy of Sciences, Beijing, China.
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Jékely G, Godfrey-Smith P, Keijzer F. Reafference and the origin of the self in early nervous system evolution. Philos Trans R Soc Lond B Biol Sci 2021; 376:20190764. [PMID: 33550954 PMCID: PMC7934971 DOI: 10.1098/rstb.2019.0764] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/07/2020] [Indexed: 12/20/2022] Open
Abstract
Discussions of the function of early nervous systems usually focus on a causal flow from sensors to effectors, by which an animal coordinates its actions with exogenous changes in its environment. We propose, instead, that much early sensing was reafferent; it was responsive to the consequences of the animal's own actions. We distinguish two general categories of reafference-translocational and deformational-and use these to survey the distribution of several often-neglected forms of sensing, including gravity sensing, flow sensing and proprioception. We discuss sensing of these kinds in sponges, ctenophores, placozoans, cnidarians and bilaterians. Reafference is ubiquitous, as ongoing action, especially whole-body motility, will almost inevitably influence the senses. Corollary discharge-a pathway or circuit by which an animal tracks its own actions and their reafferent consequences-is not a necessary feature of reafferent sensing but a later-evolving mechanism. We also argue for the importance of reafferent sensing to the evolution of the body-self, a form of organization that enables an animal to sense and act as a single unit. This article is part of the theme issue 'Basal cognition: multicellularity, neurons and the cognitive lens'.
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Affiliation(s)
- Gáspár Jékely
- Living Systems Institute, University of Exeter, Stocker Road, Exeter, EX4 4QD, UK
| | - Peter Godfrey-Smith
- School of History and Philosophy of Science, University of Sydney, New South Wales 2006, Australia
| | - Fred Keijzer
- Department of Theoretical Philosophy, University of Groningen, Groningen, The Netherlands
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38
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Flossmann T, Rochefort NL. Spatial navigation signals in rodent visual cortex. Curr Opin Neurobiol 2020; 67:163-173. [PMID: 33360769 DOI: 10.1016/j.conb.2020.11.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/04/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022]
Abstract
During navigation, animals integrate sensory information with body movements to guide actions. The impact of both navigational and movement-related signals on cortical visual information processing remains largely unknown. We review recent studies in awake rodents that have revealed navigation-related signals in the primary visual cortex (V1) including speed, distance travelled and head-orienting movements. Both cortical and subcortical inputs convey self-motion related information to V1 neurons: for example, top-down inputs from secondary motor and retrosplenial cortices convey information about head movements and spatial expectations. Within V1, subtypes of inhibitory neurons are critical for the integration of navigation-related and visual signals. We conclude with potential functional roles of navigation-related signals in V1 including gain control, motor error signals and predictive coding.
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Affiliation(s)
- Tom Flossmann
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom
| | - Nathalie L Rochefort
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom; Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom.
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39
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Feldman D, Scott K. Editorial overview: Systems neuroscience. Curr Opin Neurobiol 2020; 64:iii. [PMID: 33189188 DOI: 10.1016/j.conb.2020.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Dan Feldman
- University of California, Berkeley, United States.
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40
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A Primer on Motion Capture with Deep Learning: Principles, Pitfalls, and Perspectives. Neuron 2020; 108:44-65. [DOI: 10.1016/j.neuron.2020.09.017] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 09/02/2020] [Accepted: 09/10/2020] [Indexed: 11/21/2022]
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