1
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Muir J, Iyer ES, Tse YC, Sorensen J, Wu S, Eid RS, Cvetkovska V, Wassef K, Gostlin S, Vitaro P, Spencer NJ, Bagot RC. Sex-biased neural encoding of threat discrimination in nucleus accumbens afferents drives suppression of reward behavior. Nat Neurosci 2024:10.1038/s41593-024-01748-7. [PMID: 39237654 DOI: 10.1038/s41593-024-01748-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 08/02/2024] [Indexed: 09/07/2024]
Abstract
Learning to predict threat is essential, but equally important-yet often overlooked-is learning about the absence of threat. Here, by recording neural activity in two nucleus accumbens (NAc) glutamatergic afferents during aversive and neutral cues, we reveal sex-biased encoding of threat cue discrimination. In male mice, NAc afferents from the ventral hippocampus are preferentially activated by threat cues. In female mice, these ventral hippocampus-NAc projections are activated by both threat and nonthreat cues, whereas NAc afferents from medial prefrontal cortex are more strongly recruited by footshock and reliably discriminate threat from nonthreat. Chemogenetic pathway-specific inhibition identifies a double dissociation between ventral hippocampus-NAc and medial prefrontal cortex-NAc projections in cue-mediated suppression of reward-motivated behavior in male and female mice, despite similar synaptic connectivity. We suggest that these sex biases may reflect sex differences in behavioral strategies that may have relevance for understanding sex differences in risk of psychiatric disorders.
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Affiliation(s)
- Jessie Muir
- Integrated Program in Neuroscience, McGill University, Montréal, Quebec, Canada
| | - Eshaan S Iyer
- Integrated Program in Neuroscience, McGill University, Montréal, Quebec, Canada
| | - Yiu-Chung Tse
- Department of Psychology, McGill University, Montréal, Quebec, Canada
| | - Julian Sorensen
- College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Bedford Park, South Australia, Australia
| | - Serena Wu
- Integrated Program in Neuroscience, McGill University, Montréal, Quebec, Canada
| | - Rand S Eid
- Department of Psychology, McGill University, Montréal, Quebec, Canada
| | | | - Karen Wassef
- Department of Psychology, McGill University, Montréal, Quebec, Canada
| | - Sarah Gostlin
- Department of Psychology, McGill University, Montréal, Quebec, Canada
| | - Peter Vitaro
- Department of Psychology, McGill University, Montréal, Quebec, Canada
| | - Nick J Spencer
- College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Bedford Park, South Australia, Australia
| | - Rosemary C Bagot
- Department of Psychology, McGill University, Montréal, Quebec, Canada.
- Ludmer Centre for Neuroinformatics and Mental Health, Montréal, Quebec, Canada.
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2
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Bonnavion P, Varin C, Fakhfouri G, Martinez Olondo P, De Groote A, Cornil A, Lorenzo Lopez R, Pozuelo Fernandez E, Isingrini E, Rainer Q, Xu K, Tzavara E, Vigneault E, Dumas S, de Kerchove d'Exaerde A, Giros B. Striatal projection neurons coexpressing dopamine D1 and D2 receptors modulate the motor function of D1- and D2-SPNs. Nat Neurosci 2024; 27:1783-1793. [PMID: 38965445 DOI: 10.1038/s41593-024-01694-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/28/2024] [Indexed: 07/06/2024]
Abstract
The role of the striatum in motor control is commonly assumed to be mediated by the two striatal efferent pathways characterized by striatal projection neurons (SPNs) expressing dopamine (DA) D1 receptors or D2 receptors (D1-SPNs and D2-SPNs, respectively), without regard to SPNs coexpressing both receptors (D1/D2-SPNs). Here we developed an approach to target these hybrid SPNs in mice and demonstrate that, although these SPNs are less abundant, they have a major role in guiding the motor function of the other two populations. D1/D2-SPNs project exclusively to the external globus pallidus and have specific electrophysiological features with distinctive integration of DA signals. Gain- and loss-of-function experiments indicate that D1/D2-SPNs potentiate the prokinetic and antikinetic functions of D1-SPNs and D2-SPNs, respectively, and restrain the integrated motor response to psychostimulants. Overall, our findings demonstrate the essential role of this population of D1/D2-coexpressing neurons in orchestrating the fine-tuning of DA regulation in thalamo-cortico-striatal loops.
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Affiliation(s)
- Patricia Bonnavion
- Neurophy Lab, ULB Neuroscience Institute, Université Libre Bruxelles (ULB), Brussels, Belgium
| | - Christophe Varin
- Neurophy Lab, ULB Neuroscience Institute, Université Libre Bruxelles (ULB), Brussels, Belgium
| | - Ghazal Fakhfouri
- Department of Psychiatry, Douglas Hospital, McGill University, Montreal, Quebec, Canada
| | - Pilar Martinez Olondo
- Neurophy Lab, ULB Neuroscience Institute, Université Libre Bruxelles (ULB), Brussels, Belgium
| | - Aurélie De Groote
- Neurophy Lab, ULB Neuroscience Institute, Université Libre Bruxelles (ULB), Brussels, Belgium
| | - Amandine Cornil
- Neurophy Lab, ULB Neuroscience Institute, Université Libre Bruxelles (ULB), Brussels, Belgium
| | - Ramiro Lorenzo Lopez
- Neurophy Lab, ULB Neuroscience Institute, Université Libre Bruxelles (ULB), Brussels, Belgium
| | - Elisa Pozuelo Fernandez
- Neurophy Lab, ULB Neuroscience Institute, Université Libre Bruxelles (ULB), Brussels, Belgium
| | - Elsa Isingrini
- Department of Psychiatry, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Université Paris Cité, INCC UMR 8002, CNRS, Paris, France
| | - Quentin Rainer
- Department of Psychiatry, Douglas Hospital, McGill University, Montreal, Quebec, Canada
| | - Kathleen Xu
- Department of Psychiatry, Douglas Hospital, McGill University, Montreal, Quebec, Canada
| | - Eleni Tzavara
- Université Paris Cité, INCC UMR 8002, CNRS, Paris, France
- AP-HM, Hôpital Sainte Marguerite, Pôle Psychiatrie Universitaire Solaris, Marseille, France
| | - Erika Vigneault
- Department of Psychiatry, Douglas Hospital, McGill University, Montreal, Quebec, Canada
| | | | - Alban de Kerchove d'Exaerde
- Neurophy Lab, ULB Neuroscience Institute, Université Libre Bruxelles (ULB), Brussels, Belgium.
- WELBIO, WEL Research Institute, Wavre, Belgium.
| | - Bruno Giros
- Department of Psychiatry, Douglas Hospital, McGill University, Montreal, Quebec, Canada.
- Université Paris Cité, INCC UMR 8002, CNRS, Paris, France.
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3
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Callahan JW, Morales JC, Atherton JF, Wang D, Kostic S, Bevan MD. Movement-related increases in subthalamic activity optimize locomotion. Cell Rep 2024; 43:114495. [PMID: 39068661 DOI: 10.1016/j.celrep.2024.114495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 05/27/2024] [Accepted: 06/27/2024] [Indexed: 07/30/2024] Open
Abstract
The subthalamic nucleus (STN) is traditionally thought to restrict movement. Lesion or prolonged STN inhibition increases movement vigor and propensity, while optogenetic excitation has opposing effects. However, STN neurons often exhibit movement-related increases in firing. To address this paradox, STN activity was recorded and manipulated in head-fixed mice at rest and during self-initiated and self-paced treadmill locomotion. We found that (1) most STN neurons (type 1) exhibit locomotion-dependent increases in activity, with half firing preferentially during the propulsive phase of the contralateral locomotor cycle; (2) a minority of STN neurons exhibit dips in activity or are uncorrelated with movement; (3) brief optogenetic inhibition of the lateral STN (where type 1 neurons are concentrated) slows and prematurely terminates locomotion; and (4) in Q175 Huntington's disease mice, abnormally brief, low-velocity locomotion is associated with type 1 hypoactivity. Together, these data argue that movement-related increases in STN activity contribute to optimal locomotor performance.
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Affiliation(s)
- Joshua W Callahan
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Juan Carlos Morales
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Jeremy F Atherton
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Dorothy Wang
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Selena Kostic
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Mark D Bevan
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
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4
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Kramer TS, Wan FK, Pugliese SM, Atanas AA, Hiser AW, Luo J, Bueno E, Flavell SW. Neural Sequences Underlying Directed Turning in C. elegans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.11.607076. [PMID: 39149398 PMCID: PMC11326294 DOI: 10.1101/2024.08.11.607076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Complex behaviors like navigation rely on sequenced motor outputs that combine to generate effective movement. The brain-wide organization of the circuits that integrate sensory signals to select and execute appropriate motor sequences is not well understood. Here, we characterize the architecture of neural circuits that control C. elegans olfactory navigation. We identify error-correcting turns during navigation and use whole-brain calcium imaging and cell-specific perturbations to determine their neural underpinnings. These turns occur as motor sequences accompanied by neural sequences, in which defined neurons activate in a stereotyped order during each turn. Distinct neurons in this sequence respond to sensory cues, anticipate upcoming turn directions, and drive movement, linking key features of this sensorimotor behavior across time. The neuromodulator tyramine coordinates these sequential brain dynamics. Our results illustrate how neuromodulation can act on a defined neural architecture to generate sequential patterns of activity that link sensory cues to motor actions.
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Affiliation(s)
- Talya S. Kramer
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- MIT Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Flossie K. Wan
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sarah M. Pugliese
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Adam A. Atanas
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alex W. Hiser
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jinyue Luo
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Bueno
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven W. Flavell
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
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5
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Stednitz SJ, Lesak A, Fecker AL, Painter P, Washbourne P, Mazzucato L, Scott EK. Probabilistic modeling reveals coordinated social interaction states and their multisensory bases. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.02.606104. [PMID: 39149367 PMCID: PMC11326195 DOI: 10.1101/2024.08.02.606104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Social behavior across animal species ranges from simple pairwise interactions to thousands of individuals coordinating goal-directed movements. Regardless of the scale, these interactions are governed by the interplay between multimodal sensory information and the internal state of each animal. Here, we investigate how animals use multiple sensory modalities to guide social behavior in the highly social zebrafish (Danio rerio) and uncover the complex features of pairwise interactions early in development. To identify distinct behaviors and understand how they vary over time, we developed a new hidden Markov model with constrained linear-model emissions to automatically classify states of coordinated interaction, using the movements of one animal to predict those of another. We discovered that social behaviors alternate between two interaction states within a single experimental session, distinguished by unique movements and timescales. Long-range interactions, akin to shoaling, rely on vision, while mechanosensation underlies rapid synchronized movements and parallel swimming, precursors of schooling. Altogether, we observe spontaneous interactions in pairs of fish, develop novel hidden Markov modeling to reveal two fundamental interaction modes, and identify the sensory systems involved in each. Our modeling approach to pairwise social interactions has broad applicability to a wide variety of naturalistic behaviors and species and solves the challenge of detecting transient couplings between quasi-periodic time series.
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Affiliation(s)
| | - Andrew Lesak
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | - Adeline L Fecker
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | | | - Phil Washbourne
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | - Luca Mazzucato
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | - Ethan K Scott
- Department of Anatomy & Physiology, University of Melbourne, Parkville, VIC, Australia
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
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6
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Josephine Stednitz S, Lesak A, Fecker AL, Painter P, Washbourne P, Mazzucato L, Scott EK. Probabilistic modeling reveals coordinated social interaction states and their multisensory bases. ARXIV 2024:arXiv:2408.01683v1. [PMID: 39130202 PMCID: PMC11312628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Social behavior across animal species ranges from simple pairwise interactions to thousands of individuals coordinating goal-directed movements. Regardless of the scale, these interactions are governed by the interplay between multimodal sensory information and the internal state of each animal. Here, we investigate how animals use multiple sensory modalities to guide social behavior in the highly social zebrafish (Danio rerio) and uncover the complex features of pairwise interactions early in development. To identify distinct behaviors and understand how they vary over time, we developed a new hidden Markov model with constrained linear-model emissions to automatically classify states of coordinated interaction, using the movements of one animal to predict those of another. We discovered that social behaviors alternate between two interaction states within a single experimental session, distinguished by unique movements and timescales. Long-range interactions, akin to shoaling, rely on vision, while mechanosensation underlies rapid synchronized movements and parallel swimming, precursors of schooling. Altogether, we observe spontaneous interactions in pairs of fish, develop novel hidden Markov modeling to reveal two fundamental interaction modes, and identify the sensory systems involved in each. Our modeling approach to pairwise social interactions has broad applicability to a wide variety of naturalistic behaviors and species and solves the challenge of detecting transient couplings between quasi-periodic time series.
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Affiliation(s)
| | - Andrew Lesak
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | - Adeline L Fecker
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | | | - Phil Washbourne
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | - Luca Mazzucato
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | - Ethan K Scott
- Department of Anatomy & Physiology, University of Melbourne, Parkville, VIC, Australia
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
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7
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Aldarondo D, Merel J, Marshall JD, Hasenclever L, Klibaite U, Gellis A, Tassa Y, Wayne G, Botvinick M, Ölveczky BP. A virtual rodent predicts the structure of neural activity across behaviours. Nature 2024; 632:594-602. [PMID: 38862024 DOI: 10.1038/s41586-024-07633-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 05/30/2024] [Indexed: 06/13/2024]
Abstract
Animals have exquisite control of their bodies, allowing them to perform a diverse range of behaviours. How such control is implemented by the brain, however, remains unclear. Advancing our understanding requires models that can relate principles of control to the structure of neural activity in behaving animals. Here, to facilitate this, we built a 'virtual rodent', in which an artificial neural network actuates a biomechanically realistic model of the rat1 in a physics simulator2. We used deep reinforcement learning3-5 to train the virtual agent to imitate the behaviour of freely moving rats, thus allowing us to compare neural activity recorded in real rats to the network activity of a virtual rodent mimicking their behaviour. We found that neural activity in the sensorimotor striatum and motor cortex was better predicted by the virtual rodent's network activity than by any features of the real rat's movements, consistent with both regions implementing inverse dynamics6. Furthermore, the network's latent variability predicted the structure of neural variability across behaviours and afforded robustness in a way consistent with the minimal intervention principle of optimal feedback control7. These results demonstrate how physical simulation of biomechanically realistic virtual animals can help interpret the structure of neural activity across behaviour and relate it to theoretical principles of motor control.
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Affiliation(s)
- Diego Aldarondo
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
- Fauna Robotics, New York, NY, USA.
| | - Josh Merel
- DeepMind, Google, London, UK
- Fauna Robotics, New York, NY, USA
| | - Jesse D Marshall
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
- Reality Labs, Meta, New York, NY, USA
| | | | - Ugne Klibaite
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Amanda Gellis
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | | | | | - Matthew Botvinick
- DeepMind, Google, London, UK
- Gatsby Computational Neuroscience Unit, University College London, London, UK
| | - Bence P Ölveczky
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
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8
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Lindsey J, Markowitz JE, Gillis WF, Datta SR, Litwin-Kumar A. Dynamics of striatal action selection and reinforcement learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.14.580408. [PMID: 38464083 PMCID: PMC10925202 DOI: 10.1101/2024.02.14.580408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Spiny projection neurons (SPNs) in dorsal striatum are often proposed as a locus of reinforcement learning in the basal ganglia. Here, we identify and resolve a fundamental inconsistency between striatal reinforcement learning models and known SPN synaptic plasticity rules. Direct-pathway (dSPN) and indirect-pathway (iSPN) neurons, which promote and suppress actions, respectively, exhibit synaptic plasticity that reinforces activity associated with elevated or suppressed dopamine release. We show that iSPN plasticity prevents successful learning, as it reinforces activity patterns associated with negative outcomes. However, this pathological behavior is reversed if functionally opponent dSPNs and iSPNs, which promote and suppress the current behavior, are simultaneously activated by efferent input following action selection. This prediction is supported by striatal recordings and contrasts with prior models of SPN representations. In our model, learning and action selection signals can be multiplexed without interference, enabling learning algorithms beyond those of standard temporal difference models.
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9
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Blau A, Schaffer ES, Mishra N, Miska NJ, Paninski L, Whiteway MR. A study of animal action segmentation algorithms across supervised, unsupervised, and semi-supervised learning paradigms. ARXIV 2024:arXiv:2407.16727v1. [PMID: 39108294 PMCID: PMC11302674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
Action segmentation of behavioral videos is the process of labeling each frame as belonging to one or more discrete classes, and is a crucial component of many studies that investigate animal behavior. A wide range of algorithms exist to automatically parse discrete animal behavior, encompassing supervised, unsupervised, and semi-supervised learning paradigms. These algorithms - which include tree-based models, deep neural networks, and graphical models - differ widely in their structure and assumptions on the data. Using four datasets spanning multiple species - fly, mouse, and human - we systematically study how the outputs of these various algorithms align with manually annotated behaviors of interest. Along the way, we introduce a semi-supervised action segmentation model that bridges the gap between supervised deep neural networks and unsupervised graphical models. We find that fully supervised temporal convolutional networks with the addition of temporal information in the observations perform the best on our supervised metrics across all datasets.
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Affiliation(s)
- Ari Blau
- Department of Statistics Columbia University
| | | | | | | | - Liam Paninski
- Department of Statistics Zuckerman Institute Columbia University
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10
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Sridhar S, Lowet E, Gritton HJ, Freire J, Zhou C, Liang F, Han X. Beta-frequency sensory stimulation enhances gait rhythmicity through strengthened coupling between striatal networks and stepping movement. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.07.602408. [PMID: 39026712 PMCID: PMC11257482 DOI: 10.1101/2024.07.07.602408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Stepping movement is delta (1-4 Hz) rhythmic and depends on sensory inputs. In addition to delta rhythms, beta (10-30 Hz) frequency dynamics are also prominent in the motor circuits and are coupled to neuronal delta rhythms both at the network and the cellular levels. Since beta rhythms are broadly supported by cortical and subcortical sensorimotor circuits, we explore how beta-frequency sensory stimulation influences delta-rhythmic stepping movement, and dorsal striatal circuit regulation of stepping. We delivered audiovisual stimulation at 10 Hz or 145 Hz to mice voluntarily locomoting, while simultaneously recording stepping movement, striatal cellular calcium dynamics and local field potentials (LFPs). We found that 10 Hz, but not 145 Hz stimulation prominently entrained striatal LFPs. Even though sensory stimulation at both frequencies promoted locomotion and desynchronized striatal network, only 10 Hz stimulation enhanced the delta rhythmicity of stepping movement and strengthened the coupling between stepping and striatal LFP delta and beta oscillations. These results demonstrate that higher frequency sensory stimulation can modulate lower frequency dorsal striatal neural dynamics and improve stepping rhythmicity, highlighting the translational potential of non-invasive beta-frequency sensory stimulation for improving gait.
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11
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Weinreb C, Pearl JE, Lin S, Osman MAM, Zhang L, Annapragada S, Conlin E, Hoffmann R, Makowska S, Gillis WF, Jay M, Ye S, Mathis A, Mathis MW, Pereira T, Linderman SW, Datta SR. Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics. Nat Methods 2024; 21:1329-1339. [PMID: 38997595 PMCID: PMC11245396 DOI: 10.1038/s41592-024-02318-2] [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: 04/05/2023] [Accepted: 05/22/2024] [Indexed: 07/14/2024]
Abstract
Keypoint tracking algorithms can flexibly quantify animal movement from videos obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into discrete actions. This challenge is particularly acute because keypoint data are susceptible to high-frequency jitter that clustering algorithms can mistake for transitions between actions. Here we present keypoint-MoSeq, a machine learning-based platform for identifying behavioral modules ('syllables') from keypoint data without human supervision. Keypoint-MoSeq uses a generative model to distinguish keypoint noise from behavior, enabling it to identify syllables whose boundaries correspond to natural sub-second discontinuities in pose dynamics. Keypoint-MoSeq outperforms commonly used alternative clustering methods at identifying these transitions, at capturing correlations between neural activity and behavior and at classifying either solitary or social behaviors in accordance with human annotations. Keypoint-MoSeq also works in multiple species and generalizes beyond the syllable timescale, identifying fast sniff-aligned movements in mice and a spectrum of oscillatory behaviors in fruit flies. Keypoint-MoSeq, therefore, renders accessible the modular structure of behavior through standard video recordings.
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Affiliation(s)
- Caleb Weinreb
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Jonah E Pearl
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Sherry Lin
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | | | - Libby Zhang
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | | | - Eli Conlin
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Red Hoffmann
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Sofia Makowska
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | | | - Maya Jay
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Shaokai Ye
- Brain Mind and Neuro-X Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Alexander Mathis
- Brain Mind and Neuro-X Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Mackenzie W Mathis
- Brain Mind and Neuro-X Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Talmo Pereira
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Scott W Linderman
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
- Department of Statistics, Stanford University, Stanford, CA, USA.
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12
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Song MR, Lee SW. Rethinking dopamine-guided action sequence learning. Eur J Neurosci 2024; 60:3447-3465. [PMID: 38798086 DOI: 10.1111/ejn.16426] [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: 08/17/2023] [Revised: 04/21/2024] [Accepted: 05/08/2024] [Indexed: 05/29/2024]
Abstract
As opposed to those requiring a single action for reward acquisition, tasks necessitating action sequences demand that animals learn action elements and their sequential order and sustain the behaviour until the sequence is completed. With repeated learning, animals not only exhibit precise execution of these sequences but also demonstrate enhanced smoothness and efficiency. Previous research has demonstrated that midbrain dopamine and its major projection target, the striatum, play crucial roles in these processes. Recent studies have shown that dopamine from the substantia nigra pars compacta (SNc) and the ventral tegmental area (VTA) serve distinct functions in action sequence learning. The distinct contributions of dopamine also depend on the striatal subregions, namely the ventral, dorsomedial and dorsolateral striatum. Here, we have reviewed recent findings on the role of striatal dopamine in action sequence learning, with a focus on recent rodent studies.
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Affiliation(s)
- Minryung R Song
- Department of Brain and Cognitive Sciences, KAIST, Daejeon, South Korea
| | - Sang Wan Lee
- Department of Brain and Cognitive Sciences, KAIST, Daejeon, South Korea
- Kim Jaechul Graduate School of AI, KAIST, Daejeon, South Korea
- KI for Health Science and Technology, KAIST, Daejeon, South Korea
- Center for Neuroscience-inspired AI, KAIST, Daejeon, South Korea
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13
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Dwivedi D, Dumontier D, Sherer M, Lin S, Mirow AMC, Qiu Y, Xu Q, Liebman SA, Joseph D, Datta SR, Fishell G, Pouchelon G. Metabotropic signaling within somatostatin interneurons controls transient thalamocortical inputs during development. Nat Commun 2024; 15:5421. [PMID: 38926335 PMCID: PMC11208423 DOI: 10.1038/s41467-024-49732-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 05/24/2024] [Indexed: 06/28/2024] Open
Abstract
During brain development, neural circuits undergo major activity-dependent restructuring. Circuit wiring mainly occurs through synaptic strengthening following the Hebbian "fire together, wire together" precept. However, select connections, essential for circuit development, are transient. They are effectively connected early in development, but strongly diminish during maturation. The mechanisms by which transient connectivity recedes are unknown. To investigate this process, we characterize transient thalamocortical inputs, which depress onto somatostatin inhibitory interneurons during development, by employing optogenetics, chemogenetics, transcriptomics and CRISPR-based strategies in mice. We demonstrate that in contrast to typical activity-dependent mechanisms, transient thalamocortical connectivity onto somatostatin interneurons is non-canonical and involves metabotropic signaling. Specifically, metabotropic-mediated transcription, of guidance molecules in particular, supports the elimination of this connectivity. Remarkably, we found that this process impacts the development of normal exploratory behaviors of adult mice.
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Affiliation(s)
- Deepanjali Dwivedi
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA
- Broad Institute, Stanley Center for Psychiatric Research, Cambridge, MA, USA
| | | | - Mia Sherer
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA
- Broad Institute, Stanley Center for Psychiatric Research, Cambridge, MA, USA
| | - Sherry Lin
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA
| | - Andrea M C Mirow
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA
- Broad Institute, Stanley Center for Psychiatric Research, Cambridge, MA, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, Harbor, NY, USA
| | - Yanjie Qiu
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA
- Broad Institute, Stanley Center for Psychiatric Research, Cambridge, MA, USA
| | - Qing Xu
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA
- Broad Institute, Stanley Center for Psychiatric Research, Cambridge, MA, USA
- Center for Genomics & Systems Biology, New York University Abu Dhabi, Abu Dhabi, UAE
| | - Samuel A Liebman
- Cold Spring Harbor Laboratory, Cold Spring Harbor, Harbor, NY, USA
| | - Djeckby Joseph
- Cold Spring Harbor Laboratory, Cold Spring Harbor, Harbor, NY, USA
| | - Sandeep R Datta
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA
| | - Gord Fishell
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA.
- Broad Institute, Stanley Center for Psychiatric Research, Cambridge, MA, USA.
| | - Gabrielle Pouchelon
- Harvard Medical School, Department of Neurobiology, Boston, MA, USA.
- Broad Institute, Stanley Center for Psychiatric Research, Cambridge, MA, USA.
- Cold Spring Harbor Laboratory, Cold Spring Harbor, Harbor, NY, USA.
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14
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Lin S, Gillis WF, Weinreb C, Zeine A, Jones SC, Robinson EM, Markowitz J, Datta SR. Characterizing the structure of mouse behavior using Motion Sequencing. Nat Protoc 2024:10.1038/s41596-024-01015-w. [PMID: 38926589 DOI: 10.1038/s41596-024-01015-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 04/12/2024] [Indexed: 06/28/2024]
Abstract
Spontaneous mouse behavior is composed from repeatedly used modules of movement (e.g., rearing, running or grooming) that are flexibly placed into sequences whose content evolves over time. By identifying behavioral modules and the order in which they are expressed, researchers can gain insight into the effect of drugs, genes, context, sensory stimuli and neural activity on natural behavior. Here we present a protocol for performing Motion Sequencing (MoSeq), an ethologically inspired method that uses three-dimensional machine vision and unsupervised machine learning to decompose spontaneous mouse behavior into a series of elemental modules called 'syllables'. This protocol is based upon a MoSeq pipeline that includes modules for depth video acquisition, data preprocessing and modeling, as well as a standardized set of visualization tools. Users are provided with instructions and code for building a MoSeq imaging rig and acquiring three-dimensional video of spontaneous mouse behavior for submission to the modeling framework; the outputs of this protocol include syllable labels for each frame of the video data as well as summary plots describing how often each syllable was used and how syllables transitioned from one to the other. In addition, we provide instructions for analyzing and visualizing the outputs of keypoint-MoSeq, a recently developed variant of MoSeq that can identify behavioral motifs from keypoints identified from standard (rather than depth) video. This protocol and the accompanying pipeline significantly lower the bar for users without extensive computational ethology experience to adopt this unsupervised, data-driven approach to characterize mouse behavior.
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Affiliation(s)
- Sherry Lin
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | | | - Caleb Weinreb
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Ayman Zeine
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Samuel C Jones
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Emma M Robinson
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Jeffrey Markowitz
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
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15
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Chen Y, Chien J, Dai B, Lin D, Chen ZS. Identifying behavioral links to neural dynamics of multifiber photometry recordings in a mouse social behavior network. J Neural Eng 2024; 21:10.1088/1741-2552/ad5702. [PMID: 38861996 PMCID: PMC11246699 DOI: 10.1088/1741-2552/ad5702] [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: 01/09/2024] [Accepted: 06/11/2024] [Indexed: 06/13/2024]
Abstract
Objective.Distributed hypothalamic-midbrain neural circuits help orchestrate complex behavioral responses during social interactions. Given rapid advances in optical imaging, it is a fundamental question how population-averaged neural activity measured by multi-fiber photometry (MFP) for calcium fluorescence signals correlates with social behaviors is a fundamental question. This paper aims to investigate the correspondence between MFP data and social behaviors.Approach:We propose a state-space analysis framework to characterize mouse MFP data based on dynamic latent variable models, which include a continuous-state linear dynamical system and a discrete-state hidden semi-Markov model. We validate these models on extensive MFP recordings during aggressive and mating behaviors in male-male and male-female interactions, respectively.Main results:Our results show that these models are capable of capturing both temporal behavioral structure and associated neural states, and produce interpretable latent states. Our approach is also validated in computer simulations in the presence of known ground truth.Significance:Overall, these analysis approaches provide a state-space framework to examine neural dynamics underlying social behaviors and reveals mechanistic insights into the relevant networks.
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Affiliation(s)
- Yibo Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Program in Artificial Intelligence, University of Science and Technology of China, Hefei, Anhui, China
- Equal contributions (Y.C. and J.C.)
| | - Jonathan Chien
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Equal contributions (Y.C. and J.C.)
| | - Bing Dai
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
| | - Dayu Lin
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Zhe Sage Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA
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16
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Cai H, Dong J, Wang L, Sullivan B, Sun L, Chang L, Smith VM, Ding J, Le W, Gerfen C. Patch and matrix striatonigral neurons differentially regulate locomotion. RESEARCH SQUARE 2024:rs.3.rs-4468830. [PMID: 38978598 PMCID: PMC11230471 DOI: 10.21203/rs.3.rs-4468830/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
The striatonigral neurons are known to promote locomotion1,2. These neurons reside in both the patch (also known as striosome) and matrix compartments of the dorsal striatum3-5. However, the specific contribution of patch and matrix striatonigral neurons to locomotion remain largely unexplored. Using molecular identifier Kringle-Containing Protein Marking the Eye and the Nose (Kremen1) and Calbidin (Calb1)6, we showed in mouse models that patch and matrix striatonigral neurons exert opposite influence on locomotion. While a reduction in neuronal activity in matrix striatonigral neurons precedes the cessation of locomotion, fiber photometry recording during self-paced movement revealed an unexpected increase of patch striatonigral neuron activity, indicating an inhibitory function. Indeed, optogenetic activation of patch striatonigral neurons suppressed locomotion, contrasting with the locomotion-promoting effect of matrix striatonigral neurons. Consistently, patch striatonigral neuron activation markedly inhibited dopamine release, whereas matrix striatonigral neuron activation initially promoted dopamine release. Moreover, the genetic deletion of inhibitory GABA-B receptor Gabbr1 in Aldehyde dehydrogenase 1A1-positive (ALDH1A1+) nigrostriatal dopaminergic neurons (DANs) completely abolished the locomotion-suppressing effect caused by activating patch striatonigral neurons. Together, our findings unravel a compartment-specific mechanism governing locomotion in the dorsal striatum, where patch striatonigral neurons suppress locomotion by inhibiting the activity of ALDH1A1+ nigrostriatal DANs.
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Affiliation(s)
| | | | | | | | - Lixin Sun
- National Institute on Aging, National Institutes of Health
| | - Lisa Chang
- National Institute on Aging, National Institutes of Health
| | | | - Jinhui Ding
- National Institute on Aging, National Institutes of Health
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17
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Dong J, Wang L, Sullivan BT, Sun L, Chang L, Martinez Smith VM, Ding J, Le W, Gerfen CR, Cai H. Patch and matrix striatonigral neurons differentially regulate locomotion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.12.598675. [PMID: 38915717 PMCID: PMC11195204 DOI: 10.1101/2024.06.12.598675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Striatonigral neurons, known to promote locomotion, reside in both the patch and matrix compartments of the dorsal striatum. However, their compartment-specific contributions to locomotion remain largely unexplored. Using molecular identifier Kremen1 and Calb1 , we showed in mouse models that patch and matrix striatonigral neurons exert opposite influences on locomotion. Matrix striatonigral neurons reduced their activity before the cessation of self-paced locomotion, while patch striatonigral neuronal activity increased, suggesting an inhibitory function. Indeed, optogenetic activation of patch striatonigral neurons suppressed ongoing locomotion with reduced striatal dopamine release, contrasting with the locomotion-promoting effect of matrix striatonigral neurons, which showed an initial increase in dopamine release. Furthermore, genetic deletion of the GABA-B receptor in Aldehyde dehydrogenase 1A1-positive (ALDH1A1 + ) nigrostriatal dopaminergic neurons completely abolished the locomotion-suppressing effect of patch striatonigral neurons. Our findings unravel a compartment-specific mechanism governing locomotion in the dorsal striatum, where patch striatonigral neurons suppress locomotion by inhibiting ALDH1A1 + nigrostriatal dopaminergic neurons.
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18
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Jáidar O, Albarran E, Albarran EN, Wu YW, Ding JB. Refinement of efficient encodings of movement in the dorsolateral striatum throughout learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.596654. [PMID: 38895486 PMCID: PMC11185645 DOI: 10.1101/2024.06.06.596654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
The striatum is required for normal action selection, movement, and sensorimotor learning. Although action-specific striatal ensembles have been well documented, it is not well understood how these ensembles are formed and how their dynamics may evolve throughout motor learning. Here we used longitudinal 2-photon Ca2+ imaging of dorsal striatal neurons in head-fixed mice as they learned to self-generate locomotion. We observed a significant activation of both direct- and indirect-pathway spiny projection neurons (dSPNs and iSPNs, respectively) during early locomotion bouts and sessions that gradually decreased over time. For dSPNs, onset- and offset-ensembles were gradually refined from active motion-nonspecific cells. iSPN ensembles emerged from neurons initially active during opponent actions before becoming onset- or offset-specific. Our results show that as striatal ensembles are progressively refined, the number of active nonspecific striatal neurons decrease and the overall efficiency of the striatum information encoding for learned actions increases.
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Affiliation(s)
- Omar Jáidar
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
| | - Eddy Albarran
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Current address: Columbia University
| | | | - Yu-Wei Wu
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Current address: Institute of Molecular Biology, Academia Sinica
| | - Jun B. Ding
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
- The Phil & Penny Knight Initiative for Brain Resilience at the Wu Tsai Neurosciences Institute, Stanford University
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19
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Cisek P, Green AM. Toward a neuroscience of natural behavior. Curr Opin Neurobiol 2024; 86:102859. [PMID: 38583263 DOI: 10.1016/j.conb.2024.102859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 03/04/2024] [Indexed: 04/09/2024]
Abstract
One of the most exciting new developments in systems neuroscience is the progress being made toward neurophysiological experiments that move beyond simplified laboratory settings and address the richness of natural behavior. This is enabled by technological advances such as wireless recording in freely moving animals, automated quantification of behavior, and new methods for analyzing large data sets. Beyond new empirical methods and data, however, there is also a need for new theories and concepts to interpret that data. Such theories need to address the particular challenges of natural behavior, which often differ significantly from the scenarios studied in traditional laboratory settings. Here, we discuss some strategies for developing such novel theories and concepts and some example hypotheses being proposed.
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Affiliation(s)
- Paul Cisek
- Department of Neuroscience, University of Montréal, Montréal, Québec, Canada.
| | - Andrea M Green
- Department of Neuroscience, University of Montréal, Montréal, Québec, Canada
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20
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Callahan JW, Morales JC, Atherton JF, Wang D, Kostic S, Bevan MD. Movement-related increases in subthalamic activity optimize locomotion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.07.570617. [PMID: 38105984 PMCID: PMC10723456 DOI: 10.1101/2023.12.07.570617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The subthalamic nucleus (STN) is traditionally thought to restrict movement. Lesion or prolonged STN inhibition increases movement vigor and propensity, while ontogenetic excitation typically has opposing effects. Subthalamic and motor activity are also inversely correlated in movement disorders. However, most STN neurons exhibit movement-related increases in firing. To address this paradox, STN activity was recorded and manipulated in head-fixed mice at rest and during self-initiated treadmill locomotion. The majority of STN neurons (type 1) exhibited locomotion-dependent increases in activity, with half encoding the locomotor cycle. A minority of neurons exhibited dips in activity or were uncorrelated with movement. Brief optogenetic inhibition of the dorsolateral STN (where type 1 neurons are concentrated) slowed and prematurely terminated locomotion. In Q175 Huntington's disease mice abnormally brief, low-velocity locomotion was specifically associated with type 1 hyperactivity. Together these data argue that movement-related increases in STN activity contribute to optimal locomotor performance.
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21
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Piantadosi SC, Manning EE, Chamberlain BL, Hyde J, LaPalombara Z, Bannon NM, Pierson JL, K Namboodiri VM, Ahmari SE. Hyperactivity of indirect pathway-projecting spiny projection neurons promotes compulsive behavior. Nat Commun 2024; 15:4434. [PMID: 38789416 PMCID: PMC11126597 DOI: 10.1038/s41467-024-48331-z] [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: 12/01/2023] [Accepted: 04/26/2024] [Indexed: 05/26/2024] Open
Abstract
Compulsive behaviors are a hallmark symptom of obsessive compulsive disorder (OCD). Striatal hyperactivity has been linked to compulsive behavior generation in correlative studies in humans and causal studies in rodents. However, the contribution of the two distinct striatal output populations to the generation and treatment of compulsive behavior is unknown. These populations of direct and indirect pathway-projecting spiny projection neurons (SPNs) have classically been thought to promote or suppress actions, respectively, leading to a long-held hypothesis that increased output of direct relative to indirect pathway promotes compulsive behavior. Contrary to this hypothesis, here we find that indirect pathway hyperactivity is associated with compulsive grooming in the Sapap3-knockout mouse model of OCD-relevant behavior. Furthermore, we show that suppression of indirect pathway activity using optogenetics or treatment with the first-line OCD pharmacotherapy fluoxetine is associated with reduced grooming in Sapap3-knockouts. Together, these findings highlight the striatal indirect pathway as a potential treatment target for compulsive behavior.
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Affiliation(s)
- Sean C Piantadosi
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
| | - Elizabeth E Manning
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia
| | - Brittany L Chamberlain
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - James Hyde
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biology, Southern Arkansas University, Magnolia, AK, USA
| | - Zoe LaPalombara
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicholas M Bannon
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jamie L Pierson
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Susanne E Ahmari
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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22
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Nasello C, Poppi LA, Wu J, Kowalski TF, Thackray JK, Wang R, Persaud A, Mahboob M, Lin S, Spaseska R, Johnson CK, Gordon D, Tissir F, Heiman GA, Tischfield JA, Bocarsly M, Tischfield MA. Human mutations in high-confidence Tourette disorder genes affect sensorimotor behavior, reward learning, and striatal dopamine in mice. Proc Natl Acad Sci U S A 2024; 121:e2307156121. [PMID: 38683996 PMCID: PMC11087812 DOI: 10.1073/pnas.2307156121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 02/13/2024] [Indexed: 05/02/2024] Open
Abstract
Tourette disorder (TD) is poorly understood, despite affecting 1/160 children. A lack of animal models possessing construct, face, and predictive validity hinders progress in the field. We used CRISPR/Cas9 genome editing to generate mice with mutations orthologous to human de novo variants in two high-confidence Tourette genes, CELSR3 and WWC1. Mice with human mutations in Celsr3 and Wwc1 exhibit cognitive and/or sensorimotor behavioral phenotypes consistent with TD. Sensorimotor gating deficits, as measured by acoustic prepulse inhibition, occur in both male and female Celsr3 TD models. Wwc1 mice show reduced prepulse inhibition only in females. Repetitive motor behaviors, common to Celsr3 mice and more pronounced in females, include vertical rearing and grooming. Sensorimotor gating deficits and rearing are attenuated by aripiprazole, a partial agonist at dopamine type II receptors. Unsupervised machine learning reveals numerous changes to spontaneous motor behavior and less predictable patterns of movement. Continuous fixed-ratio reinforcement shows that Celsr3 TD mice have enhanced motor responding and reward learning. Electrically evoked striatal dopamine release, tested in one model, is greater. Brain development is otherwise grossly normal without signs of striatal interneuron loss. Altogether, mice expressing human mutations in high-confidence TD genes exhibit face and predictive validity. Reduced prepulse inhibition and repetitive motor behaviors are core behavioral phenotypes and are responsive to aripiprazole. Enhanced reward learning and motor responding occur alongside greater evoked dopamine release. Phenotypes can also vary by sex and show stronger affection in females, an unexpected finding considering males are more frequently affected in TD.
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Affiliation(s)
- Cara Nasello
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ08854
| | - Lauren A. Poppi
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ08854
- Child Health Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ08901
| | - Junbing Wu
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ08854
- Child Health Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ08901
| | - Tess F. Kowalski
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ08854
- Child Health Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ08901
| | - Joshua K. Thackray
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ08854
| | - Riley Wang
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ08854
| | - Angelina Persaud
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ08854
- Child Health Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ08901
| | - Mariam Mahboob
- Department of Pharmacology, Physiology, and Neuroscience, Rutgers New Jersey Medical School and Rutgers Biomedical and Health Sciences, Newark, NJ07103
| | - Sherry Lin
- Department of Neurobiology, Harvard Medical School, Boston, MA02115
| | - Rodna Spaseska
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
| | - C. K. Johnson
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
| | - Derek Gordon
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
| | - Fadel Tissir
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha34110, Qatar
- Laboratory of Developmental Neurobiology, Institute of Neuroscience, Université Catholique de Louvain, Brussels1200, Belgium
| | - Gary A. Heiman
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
| | - Jay A. Tischfield
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ08854
| | - Miriam Bocarsly
- Department of Pharmacology, Physiology, and Neuroscience, Rutgers New Jersey Medical School and Rutgers Biomedical and Health Sciences, Newark, NJ07103
| | - Max A. Tischfield
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ08854
- Child Health Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ08901
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23
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Celii B, Papadopoulos S, Ding Z, Fahey PG, Wang E, Papadopoulos C, Kunin AB, Patel S, Bae JA, Bodor AL, Brittain D, Buchanan J, Bumbarger DJ, Castro MA, Cobos E, Dorkenwald S, Elabbady L, Halageri A, Jia Z, Jordan C, Kapner D, Kemnitz N, Kinn S, Lee K, Li K, Lu R, Macrina T, Mahalingam G, Mitchell E, Mondal SS, Mu S, Nehoran B, Popovych S, Schneider-Mizell CM, Silversmith W, Takeno M, Torres R, Turner NL, Wong W, Wu J, Yu SC, Yin W, Xenes D, Kitchell LM, Rivlin PK, Rose VA, Bishop CA, Wester B, Froudarakis E, Walker EY, Sinz F, Seung HS, Collman F, da Costa NM, Reid RC, Pitkow X, Tolias AS, Reimer J. NEURD: automated proofreading and feature extraction for connectomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.14.532674. [PMID: 36993282 PMCID: PMC10055177 DOI: 10.1101/2023.03.14.532674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods can now yield exceptionally accurate reconstructions of cells, but despite this accuracy, laborious post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons produced by these segmentations contain detailed morphological information, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting information about these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes each meshed neuron into a compact and extensively-annotated graph representation. With these feature-rich graphs, we implement workflows to automate a variety of tasks that would otherwise require extensive manual effort, such as state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and computation of other features. These features enable many downstream analyses of neural morphology and connectivity, making these new massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.
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24
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Fine JM, Yoo SBM, Hayden BY. Control over a mixture of policies determines change of mind topology during continuous choice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590154. [PMID: 38712284 PMCID: PMC11071291 DOI: 10.1101/2024.04.18.590154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Behavior is naturally organized into categorically distinct states with corresponding patterns of neural activity; how does the brain control those states? We propose that states are regulated by specific neural processes that implement meta-control that can blend simpler control processes. To test this hypothesis, we recorded from neurons in the dorsal anterior cingulate cortex (dACC) and dorsal premotor cortex (PMd) while macaques performed a continuous pursuit task with two moving prey that followed evasive strategies. We used a novel control theoretic approach to infer subjects' moment-to-moment latent control variables, which in turn dictated their blend of distinct identifiable control processes. We identified low-dimensional subspaces in neuronal responses that reflected the current strategy, the value of the pursued target, and the relative value of the two targets. The top two principal components of activity tracked changes of mind in abstract and change-type-specific formats, respectively. These results indicate that control of behavioral state reflects the interaction of brain processes found in dorsal prefrontal regions that implement a mixture over low-level control policies.
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25
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Dwivedi D, Dumontier D, Sherer M, Lin S, Mirow AM, Qiu Y, Xu Q, Liebman SA, Joseph D, Datta SR, Fishell G, Pouchelon G. Metabotropic signaling within somatostatin interneurons controls transient thalamocortical inputs during development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.21.558862. [PMID: 37790336 PMCID: PMC10542166 DOI: 10.1101/2023.09.21.558862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
During brain development, neural circuits undergo major activity-dependent restructuring. Circuit wiring mainly occurs through synaptic strengthening following the Hebbian "fire together, wire together" precept. However, select connections, essential for circuit development, are transient. They are effectively connected early in development, but strongly diminish during maturation. The mechanisms by which transient connectivity recedes are unknown. To investigate this process, we characterize transient thalamocortical inputs, which depress onto somatostatin inhibitory interneurons during development, by employing optogenetics, chemogenetics, transcriptomics and CRISPR-based strategies. We demonstrate that in contrast to typical activity-dependent mechanisms, transient thalamocortical connectivity onto somatostatin interneurons is non-canonical and involves metabotropic signaling. Specifically, metabotropic-mediated transcription, of guidance molecules in particular, supports the elimination of this connectivity. Remarkably, we found that this developmental process impacts the development of normal exploratory behaviors of adult mice.
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26
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Cregg JM, Sidhu SK, Leiras R, Kiehn O. Basal ganglia-spinal cord pathway that commands locomotor gait asymmetries in mice. Nat Neurosci 2024; 27:716-727. [PMID: 38347200 PMCID: PMC11001584 DOI: 10.1038/s41593-024-01569-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 01/05/2024] [Indexed: 04/10/2024]
Abstract
The basal ganglia are essential for executing motor actions. How the basal ganglia engage spinal motor networks has remained elusive. Medullary Chx10 gigantocellular (Gi) neurons are required for turning gait programs, suggesting that turning gaits organized by the basal ganglia are executed via this descending pathway. Performing deep brainstem recordings of Chx10 Gi Ca2+ activity in adult mice, we show that striatal projection neurons initiate turning gaits via a dominant crossed pathway to Chx10 Gi neurons on the contralateral side. Using intersectional viral tracing and cell-type-specific modulation, we uncover the principal basal ganglia-spinal cord pathway for locomotor asymmetries in mice: basal ganglia → pontine reticular nucleus, oral part (PnO) → Chx10 Gi → spinal cord. Modulating the restricted PnO → Chx10 Gi pathway restores turning competence upon striatal damage, suggesting that dysfunction of this pathway may contribute to debilitating turning deficits observed in Parkinson's disease. Our results reveal the stratified circuit architecture underlying a critical motor program.
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Affiliation(s)
- Jared M Cregg
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Simrandeep K Sidhu
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Roberto Leiras
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole Kiehn
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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27
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Kitchenham L, MacLellan A, Paletta P, Patel A, Choleris E, Mason G. Do housing-induced changes in brain activity cause stereotypic behaviours in laboratory mice? Behav Brain Res 2024; 462:114862. [PMID: 38216059 DOI: 10.1016/j.bbr.2024.114862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/30/2023] [Accepted: 01/06/2024] [Indexed: 01/14/2024]
Abstract
Abnormal repetitive stereotypic behaviours (SBs) (e.g. pacing, body-rocking) are common in animals with poor welfare (e.g. socially isolated/in barren housing). But how (or even whether) poor housing alters animals' brains to induce SBs remains uncertain. To date, there is little evidence for environmental effects on the brain that also correlate with individual SB performance. Using female mice from two strains (SB-prone DBA/2s; SB-resistant C57/BL/6s), displaying two forms of SB (route-tracing; bar-mouthing), we investigated how housing (conventional laboratory conditions vs. well-resourced 'enriched' cages) affects long-term neuronal activity as assessed via cytochrome oxidase histochemistry in 13 regions of interest (across cortex, striatum, basal ganglia and thalamus). Conventional housing reduced activity in the cortex and striatum. However, DBA mice had no cortical or striatal differences from C57 mice (just greater basal ganglia output activity, independent of housing). Neural correlates for individual levels of bar-mouthing (positive correlations in the substantia nigra and thalamus) were also independent of housing; while route-tracing levels had no clear neural correlates at all. Thus conventional laboratory housing can suppress cortico-striatal activity, but such changes are unrelated to SB (since not mirrored by congruent individual and strain differences). Furthermore, the neural correlates of SB at individual and strain levels seem to reflect underlying predispositions, not housing-mediated changes. To aid further work, hypothesis-generating model fit analyses highlighted this unexplained housing effect, and also suggested several regions of interest across cortex, striatum, thalamus and substantia nigra for future investigation (ideally with improved power to reduce risks of Type II error).
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Affiliation(s)
- Lindsey Kitchenham
- Campbell Centre for the Study of Animal Welfare/Dept. of Integrative Biology, University of Guelph, Ontario, Canada
| | - Aileen MacLellan
- Campbell Centre for the Study of Animal Welfare/Dept. of Integrative Biology, University of Guelph, Ontario, Canada; Canadian Council on Animal Care; Ottawa Hospital Research Institute; University of Ottawa, Dept. of Anesthesiology and Pain Medicine
| | - Pietro Paletta
- Dept. of Psychology, Neuroscience and Applied Cognitive Sciences, University of Guelph, Ontario, Canada
| | - Ashutosh Patel
- Dept. of Biomedical Sciences, University of Guelph, Ontario, Canada
| | - Elena Choleris
- Dept. of Psychology, Neuroscience and Applied Cognitive Sciences, University of Guelph, Ontario, Canada
| | - Georgia Mason
- Campbell Centre for the Study of Animal Welfare/Dept. of Integrative Biology, University of Guelph, Ontario, Canada.
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28
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Yang L, Singla D, Wu AK, Cross KA, Masmanidis SC. Dopamine lesions alter the striatal encoding of single-limb gait. eLife 2024; 12:RP92821. [PMID: 38526916 PMCID: PMC10963031 DOI: 10.7554/elife.92821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024] Open
Abstract
The striatum serves an important role in motor control, and neurons in this area encode the body's initiation, cessation, and speed of locomotion. However, it remains unclear whether the same neurons also encode the step-by-step rhythmic motor patterns of individual limbs that characterize gait. By combining high-speed video tracking, electrophysiology, and optogenetic tagging, we found that a sizable population of both D1 and D2 receptor expressing medium spiny projection neurons (MSNs) were phase-locked to the gait cycle of individual limbs in mice. Healthy animals showed balanced limb phase-locking between D1 and D2 MSNs, while dopamine depletion led to stronger phase-locking in D2 MSNs. These findings indicate that striatal neurons represent gait on a single-limb and step basis, and suggest that elevated limb phase-locking of D2 MSNs may underlie some of the gait impairments associated with dopamine loss.
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Affiliation(s)
- Long Yang
- Department of Neurobiology, University of California Los AngelesLos AngelesUnited States
| | - Deepak Singla
- Department of Bioengineering, University of California Los AngelesLos AngelesUnited States
| | - Alexander K Wu
- Department of Neurobiology, University of California Los AngelesLos AngelesUnited States
| | - Katy A Cross
- Department of Neurology, University of California Los AngelesLos AngelesUnited States
| | - Sotiris C Masmanidis
- Department of Neurobiology, University of California Los AngelesLos AngelesUnited States
- California Nanosystems Institute, University of California Los AngelesLos AngelesUnited States
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29
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Vu MAT, Brown EH, Wen MJ, Noggle CA, Zhang Z, Monk KJ, Bouabid S, Mroz L, Graham BM, Zhuo Y, Li Y, Otchy TM, Tian L, Davison IG, Boas DA, Howe MW. Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior. Neuron 2024; 112:909-923.e9. [PMID: 38242115 PMCID: PMC10957316 DOI: 10.1016/j.neuron.2023.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 11/11/2023] [Accepted: 12/15/2023] [Indexed: 01/21/2024]
Abstract
Neural population dynamics relevant to behavior vary over multiple spatial and temporal scales across three-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice, enabling the investigation of cell-type- and neurotransmitter-specific signals over arbitrary 3D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum, revealing distinct, modality-specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and the spatial localization of behavioral function across large circuits.
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Affiliation(s)
- Mai-Anh T Vu
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Eleanor H Brown
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
| | - Michelle J Wen
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Howard Hughes Medical Institute, Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Christian A Noggle
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Zicheng Zhang
- Department of Biology, Boston University, Boston, MA, USA
| | - Kevin J Monk
- Department of Biology, Boston University, Boston, MA, USA
| | - Safa Bouabid
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Lydia Mroz
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Northeastern University, Boston, MA, USA
| | - Benjamin M Graham
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
| | - Yizhou Zhuo
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China; PKU-IDG/McGovern Institute for Brain Research, Beijing, China; Peking-Tsinghua Center for Life Sciences, Beijing, China
| | - Yulong Li
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA; State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China; PKU-IDG/McGovern Institute for Brain Research, Beijing, China; Peking-Tsinghua Center for Life Sciences, Beijing, China
| | | | - Lin Tian
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA; Max Planck Florida Institute of Neuroscience, Jupiter, FL, USA
| | - Ian G Davison
- Department of Biology, Boston University, Boston, MA, USA
| | - David A Boas
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Mark W Howe
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
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30
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Simpson EH, Akam T, Patriarchi T, Blanco-Pozo M, Burgeno LM, Mohebi A, Cragg SJ, Walton ME. Lights, fiber, action! A primer on in vivo fiber photometry. Neuron 2024; 112:718-739. [PMID: 38103545 PMCID: PMC10939905 DOI: 10.1016/j.neuron.2023.11.016] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 10/16/2023] [Accepted: 11/15/2023] [Indexed: 12/19/2023]
Abstract
Fiber photometry is a key technique for characterizing brain-behavior relationships in vivo. Initially, it was primarily used to report calcium dynamics as a proxy for neural activity via genetically encoded indicators. This generated new insights into brain functions including movement, memory, and motivation at the level of defined circuits and cell types. Recently, the opportunity for discovery with fiber photometry has exploded with the development of an extensive range of fluorescent sensors for biomolecules including neuromodulators and peptides that were previously inaccessible in vivo. This critical advance, combined with the new availability of affordable "plug-and-play" recording systems, has made monitoring molecules with high spatiotemporal precision during behavior highly accessible. However, while opening exciting new avenues for research, the rapid expansion in fiber photometry applications has occurred without coordination or consensus on best practices. Here, we provide a comprehensive guide to help end-users execute, analyze, and suitably interpret fiber photometry studies.
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Affiliation(s)
- Eleanor H Simpson
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA.
| | - Thomas Akam
- Department of Experimental Psychology, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
| | - Tommaso Patriarchi
- Institute of Pharmacology and Toxicology, University of Zürich, Zürich, Switzerland; Neuroscience Center Zürich, University and ETH Zürich, Zürich, Switzerland.
| | - Marta Blanco-Pozo
- Department of Experimental Psychology, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Lauren M Burgeno
- Department of Experimental Psychology, University of Oxford, Oxford, UK; Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Ali Mohebi
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Stephanie J Cragg
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Mark E Walton
- Department of Experimental Psychology, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
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31
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Goldstein N, Maes A, Allen HN, Nelson TS, Kruger KA, Kindel M, Smith NK, Carty JRE, Villari RE, Cho E, Marble EL, Khanna R, Taylor BK, Kennedy A, Betley JN. A parabrachial hub for the prioritization of survival behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.26.582069. [PMID: 38464066 PMCID: PMC10925167 DOI: 10.1101/2024.02.26.582069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Long-term sustained pain in the absence of acute physical injury is a prominent feature of chronic pain conditions. While neurons responding to noxious stimuli have been identified, understanding the signals that persist without ongoing painful stimuli remains a challenge. Using an ethological approach based on the prioritization of adaptive survival behaviors, we determined that neuropeptide Y (NPY) signaling from multiple sources converges on parabrachial neurons expressing the NPY Y1 receptor to reduce sustained pain responses. Neural activity recordings and computational modeling demonstrate that activity in Y1R parabrachial neurons is elevated following injury, predicts functional coping behavior, and is inhibited by competing survival needs. Taken together, our findings suggest that parabrachial Y1 receptor-expressing neurons are a critical hub for endogenous analgesic pathways that suppress sustained pain states.
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32
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McDougle M, de Araujo A, Singh A, Yang M, Braga I, Paille V, Mendez-Hernandez R, Vergara M, Woodie LN, Gour A, Sharma A, Urs N, Warren B, de Lartigue G. Separate gut-brain circuits for fat and sugar reinforcement combine to promote overeating. Cell Metab 2024; 36:393-407.e7. [PMID: 38242133 DOI: 10.1016/j.cmet.2023.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 09/25/2023] [Accepted: 12/11/2023] [Indexed: 01/21/2024]
Abstract
Food is a powerful natural reinforcer that guides feeding decisions. The vagus nerve conveys internal sensory information from the gut to the brain about nutritional value; however, the cellular and molecular basis of macronutrient-specific reward circuits is poorly understood. Here, we monitor in vivo calcium dynamics to provide direct evidence of independent vagal sensing pathways for the detection of dietary fats and sugars. Using activity-dependent genetic capture of vagal neurons activated in response to gut infusions of nutrients, we demonstrate the existence of separate gut-brain circuits for fat and sugar sensing that are necessary and sufficient for nutrient-specific reinforcement. Even when controlling for calories, combined activation of fat and sugar circuits increases nigrostriatal dopamine release and overeating compared with fat or sugar alone. This work provides new insights into the complex sensory circuitry that mediates motivated behavior and suggests that a subconscious internal drive to consume obesogenic diets (e.g., those high in both fat and sugar) may impede conscious dieting efforts.
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Affiliation(s)
- Molly McDougle
- Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA; Center for Integrative Cardiovascular and Metabolic Disease, University of Florida, Gainesville, FL, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Alan de Araujo
- Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA; Center for Integrative Cardiovascular and Metabolic Disease, University of Florida, Gainesville, FL, USA
| | - Arashdeep Singh
- Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA; Center for Integrative Cardiovascular and Metabolic Disease, University of Florida, Gainesville, FL, USA; Monell Chemical Senses Center, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Mingxin Yang
- Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA; Center for Integrative Cardiovascular and Metabolic Disease, University of Florida, Gainesville, FL, USA; Monell Chemical Senses Center, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Isadora Braga
- Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA; Monell Chemical Senses Center, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Vincent Paille
- Monell Chemical Senses Center, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; UMR1280 Physiopathologie des adaptations nutritionnelles, INRAE, Institut des maladies de l'appareil digestif, Université de Nantes, Nantes, France
| | - Rebeca Mendez-Hernandez
- Monell Chemical Senses Center, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Macarena Vergara
- Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA; Center for Integrative Cardiovascular and Metabolic Disease, University of Florida, Gainesville, FL, USA
| | - Lauren N Woodie
- Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
| | - Abhishek Gour
- Department of Pharmaceutics, University of Florida, Gainesville, FL, USA
| | - Abhisheak Sharma
- Department of Pharmaceutics, University of Florida, Gainesville, FL, USA
| | - Nikhil Urs
- Department of Pharmacology, University of Florida, Gainesville, FL, USA
| | - Brandon Warren
- Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA
| | - Guillaume de Lartigue
- Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA; Center for Integrative Cardiovascular and Metabolic Disease, University of Florida, Gainesville, FL, USA; Monell Chemical Senses Center, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA.
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33
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Guilhemsang L, Mallet NP. Arkypallidal neurons in basal ganglia circuits: Unveiling novel pallidostriatal loops? Curr Opin Neurobiol 2024; 84:102814. [PMID: 38016260 DOI: 10.1016/j.conb.2023.102814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 11/30/2023]
Abstract
Just over a decade ago, a novel GABAergic input originating from a subpopulation of external globus pallidus neurons known as Arkypallidal and projecting exclusively to the striatum was unveiled. At the single-cell level, these pallidostriatal Arkypallidal projections represent one of the largest extrinsic sources of GABA known to innervate the dorsal striatum. This discovery has sparked new questions regarding their role in striatal information processing, the circuit that recruit these neurons, and their influence on behaviour, especially in the context of action selection vs. inhibition. In this review, we will present the different anatomo-functional organization of Arkypallidal neurons as compared to classic Prototypic neurons, including their unique molecular properties and what is known about their specific input/output synaptic organization. We will further describe recent findings that demonstrate one mode of action of Arkypallidal neurons, which is to convey feedback inhibition to the striatum, and how this mechanism is differentially modulated by both striatal projection pathways. Lastly, we will delve into speculations on their mechanistic contribution to striatal action execution or inhibition.
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Affiliation(s)
- Lise Guilhemsang
- Université de Bordeaux, CNRS, Institut des Maladies Neurodégénératives, F-33000 Bordeaux, France
| | - Nicolas P Mallet
- Université de Bordeaux, CNRS, Institut des Maladies Neurodégénératives, F-33000 Bordeaux, France.
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34
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Yang L, Singla D, Wu AK, Cross KA, Masmanidis SC. Dopamine lesions alter the striatal encoding of single-limb gait. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.06.561216. [PMID: 37873374 PMCID: PMC10592622 DOI: 10.1101/2023.10.06.561216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The striatum serves an important role in motor control, and neurons in this area encode the body's initiation, cessation, and speed of locomotion. However, it remains unclear whether the same neurons also encode the step-by-step rhythmic motor patterns of individual limbs that characterize gait. By combining high-speed video tracking, electrophysiology, and optogenetic tagging, we found that a sizable population of both D1 and D2 receptor expressing medium spiny projection neurons (MSNs) were phase-locked to the gait cycle of individual limbs in mice. Healthy animals showed balanced limb phase-locking between D1 and D2 MSNs, while dopamine depletion led to stronger phase-locking in D2 MSNs. These findings indicate that striatal neurons represent gait on a single-limb and step basis, and suggest that elevated limb phase-locking of D2 MSNs may underlie some of the gait impairments associated with dopamine loss.
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Affiliation(s)
- Long Yang
- Department of Neurobiology, University of California Los Angeles, Los Angeles, California 90095, USA
| | - Deepak Singla
- Department of Bioengineering, University of California Los Angeles, Los Angeles, California 90095, USA
| | - Alexander K. Wu
- Department of Neurobiology, University of California Los Angeles, Los Angeles, California 90095, USA
| | - Katy A. Cross
- Department of Neurology, University of California Los Angeles, Los Angeles, California 90095, USA
| | - Sotiris C. Masmanidis
- Department of Neurobiology, University of California Los Angeles, Los Angeles, California 90095, USA
- California Nanosystems Institute, University of California Los Angeles, Los Angeles, California 90095, USA
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35
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Chen Y, Chien J, Dai B, Lin D, Chen ZS. Identifying behavioral links to neural dynamics of multifiber photometry recordings in a mouse social behavior network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.25.573308. [PMID: 38234793 PMCID: PMC10793434 DOI: 10.1101/2023.12.25.573308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Distributed hypothalamic-midbrain neural circuits orchestrate complex behavioral responses during social interactions. How population-averaged neural activity measured by multi-fiber photometry (MFP) for calcium fluorescence signals correlates with social behaviors is a fundamental question. We propose a state-space analysis framework to characterize mouse MFP data based on dynamic latent variable models, which include continuous-state linear dynamical system (LDS) and discrete-state hidden semi-Markov model (HSMM). We validate these models on extensive MFP recordings during aggressive and mating behaviors in male-male and male-female interactions, respectively. Our results show that these models are capable of capturing both temporal behavioral structure and associated neural states. Overall, these analysis approaches provide an unbiased strategy to examine neural dynamics underlying social behaviors and reveals mechanistic insights into the relevant networks.
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Affiliation(s)
- Yibo Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Program in Artificial Intelligence, University of Science and Technology of China, Hefei, Anhui, China
| | - Jonathan Chien
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
| | - Bing Dai
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
| | - Dayu Lin
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Zhe Sage Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA
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36
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Lowet AS, Zheng Q, Meng M, Matias S, Drugowitsch J, Uchida N. An opponent striatal circuit for distributional reinforcement learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.02.573966. [PMID: 38260354 PMCID: PMC10802299 DOI: 10.1101/2024.01.02.573966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Machine learning research has achieved large performance gains on a wide range of tasks by expanding the learning target from mean rewards to entire probability distributions of rewards - an approach known as distributional reinforcement learning (RL)1. The mesolimbic dopamine system is thought to underlie RL in the mammalian brain by updating a representation of mean value in the striatum2,3, but little is known about whether, where, and how neurons in this circuit encode information about higher-order moments of reward distributions4. To fill this gap, we used high-density probes (Neuropixels) to acutely record striatal activity from well-trained, water-restricted mice performing a classical conditioning task in which reward mean, reward variance, and stimulus identity were independently manipulated. In contrast to traditional RL accounts, we found robust evidence for abstract encoding of variance in the striatum. Remarkably, chronic ablation of dopamine inputs disorganized these distributional representations in the striatum without interfering with mean value coding. Two-photon calcium imaging and optogenetics revealed that the two major classes of striatal medium spiny neurons - D1 and D2 MSNs - contributed to this code by preferentially encoding the right and left tails of the reward distribution, respectively. We synthesize these findings into a new model of the striatum and mesolimbic dopamine that harnesses the opponency between D1 and D2 MSNs5-15 to reap the computational benefits of distributional RL.
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Affiliation(s)
- Adam S Lowet
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
- Program in Neuroscience, Harvard University, Boston, MA, USA
| | - Qiao Zheng
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Melissa Meng
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Sara Matias
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Jan Drugowitsch
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Naoshige Uchida
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
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Lipp HP, Krackow S, Turkes E, Benner S, Endo T, Russig H. IntelliCage: the development and perspectives of a mouse- and user-friendly automated behavioral test system. Front Behav Neurosci 2024; 17:1270538. [PMID: 38235003 PMCID: PMC10793385 DOI: 10.3389/fnbeh.2023.1270538] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/18/2023] [Indexed: 01/19/2024] Open
Abstract
IntelliCage for mice is a rodent home-cage equipped with four corner structures harboring symmetrical double panels for operant conditioning at each of the two sides, either by reward (access to water) or by aversion (non-painful stimuli: air-puffs, LED lights). Corner visits, nose-pokes and actual licks at bottle-nipples are recorded individually using subcutaneously implanted transponders for RFID identification of up to 16 adult mice housed in the same home-cage. This allows for recording individual in-cage activity of mice and applying reward/punishment operant conditioning schemes in corners using workflows designed on a versatile graphic user interface. IntelliCage development had four roots: (i) dissatisfaction with standard approaches for analyzing mouse behavior, including standardization and reproducibility issues, (ii) response to handling and housing animal welfare issues, (iii) the increasing number of mouse models had produced a high work burden on classic manual behavioral phenotyping of single mice. and (iv), studies of transponder-chipped mice in outdoor settings revealed clear genetic behavioral differences in mouse models corresponding to those observed by classic testing in the laboratory. The latter observations were important for the development of home-cage testing in social groups, because they contradicted the traditional belief that animals must be tested under social isolation to prevent disturbance by other group members. The use of IntelliCages reduced indeed the amount of classic testing remarkably, while its flexibility was proved in a wide range of applications worldwide including transcontinental parallel testing. Essentially, two lines of testing emerged: sophisticated analysis of spontaneous behavior in the IntelliCage for screening of new genetic models, and hypothesis testing in many fields of behavioral neuroscience. Upcoming developments of the IntelliCage aim at improved stimulus presentation in the learning corners and videotracking of social interactions within the IntelliCage. Its main advantages are (i) that mice live in social context and are not stressfully handled for experiments, (ii) that studies are not restricted in time and can run in absence of humans, (iii) that it increases reproducibility of behavioral phenotyping worldwide, and (iv) that the industrial standardization of the cage permits retrospective data analysis with new statistical tools even after many years.
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Affiliation(s)
- Hans-Peter Lipp
- Faculty of Medicine, Institute of Evolutionary Medicine, University of Zürich, Zürich, Switzerland
| | - Sven Krackow
- Institute of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Emir Turkes
- Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Seico Benner
- Center for Health and Environmental Risk Research, National Institute for Environmental Studies, Ibaraki, Japan
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Weinreb C, Pearl J, Lin S, Osman MAM, Zhang L, Annapragada S, Conlin E, Hoffman R, Makowska S, Gillis WF, Jay M, Ye S, Mathis A, Mathis MW, Pereira T, Linderman SW, Datta SR. Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.532307. [PMID: 36993589 PMCID: PMC10055085 DOI: 10.1101/2023.03.16.532307] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Keypoint tracking algorithms have revolutionized the analysis of animal behavior, enabling investigators to flexibly quantify behavioral dynamics from conventional video recordings obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into the modules out of which behavior is organized. This challenge is particularly acute because keypoint data is susceptible to high frequency jitter that clustering algorithms can mistake for transitions between behavioral modules. Here we present keypoint-MoSeq, a machine learning-based platform for identifying behavioral modules ("syllables") from keypoint data without human supervision. Keypoint-MoSeq uses a generative model to distinguish keypoint noise from behavior, enabling it to effectively identify syllables whose boundaries correspond to natural sub-second discontinuities inherent to mouse behavior. Keypoint-MoSeq outperforms commonly used alternative clustering methods at identifying these transitions, at capturing correlations between neural activity and behavior, and at classifying either solitary or social behaviors in accordance with human annotations. Keypoint-MoSeq therefore renders behavioral syllables and grammar accessible to the many researchers who use standard video to capture animal behavior.
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Affiliation(s)
- Caleb Weinreb
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Jonah Pearl
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Sherry Lin
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | | | - Libby Zhang
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | | | - Eli Conlin
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Red Hoffman
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Sofia Makowska
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | | | - Maya Jay
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Shaokai Ye
- Brain Mind and Neuro-X Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Alexander Mathis
- Brain Mind and Neuro-X Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Mackenzie Weygandt Mathis
- Brain Mind and Neuro-X Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Talmo Pereira
- Salk Institute for Biological Studies, La Jolla, USA
| | - Scott W. Linderman
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
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Zhou ZC, Gordon-Fennell A, Piantadosi SC, Ji N, Smith SL, Bruchas MR, Stuber GD. Deep-brain optical recording of neural dynamics during behavior. Neuron 2023; 111:3716-3738. [PMID: 37804833 PMCID: PMC10843303 DOI: 10.1016/j.neuron.2023.09.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/24/2023] [Accepted: 09/06/2023] [Indexed: 10/09/2023]
Abstract
In vivo fluorescence recording techniques have produced landmark discoveries in neuroscience, providing insight into how single cell and circuit-level computations mediate sensory processing and generate complex behaviors. While much attention has been given to recording from cortical brain regions, deep-brain fluorescence recording is more complex because it requires additional measures to gain optical access to harder to reach brain nuclei. Here we discuss detailed considerations and tradeoffs regarding deep-brain fluorescence recording techniques and provide a comprehensive guide for all major steps involved, from project planning to data analysis. The goal is to impart guidance for new and experienced investigators seeking to use in vivo deep fluorescence optical recordings in awake, behaving rodent models.
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Affiliation(s)
- Zhe Charles Zhou
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Adam Gordon-Fennell
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Sean C Piantadosi
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA
| | - Na Ji
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Spencer LaVere Smith
- Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Michael R Bruchas
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA; Department of Pharmacology, University of Washington, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
| | - Garret D Stuber
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195, USA; Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA 98195, USA; Department of Pharmacology, University of Washington, Seattle, WA 98195, USA.
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40
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Baltz ET, Renteria R, Gremel CM. Chronic alcohol exposure differentially alters calcium activity of striatal cell populations during actions. ADDICTION NEUROSCIENCE 2023; 8:100128. [PMID: 37842013 PMCID: PMC10569208 DOI: 10.1016/j.addicn.2023.100128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
Alcohol Use Disorder (AUD) can induce long lasting alterations to executive function. This includes altered action control, which can manifest as dysfunctional goal-directed control. Cortical and striatal circuits mediate goal-directed control over behavior, and prior research has found chronic alcohol disrupts these circuits. In particular, prior in vivo and ex vivo work have identified alterations to function and activity of dorsal medial striatum (DMS), which is necessary for goal-directed control. However, unknown is whether these alterations manifest as altered activity of select DMS populations during behavior. Here we examine effects of prior chronic alcohol exposure on calcium activity modulation during action-related behaviors via fiber photometry of genetically-identified DMS populations including the direct and indirect output pathways, and fast-spiking interneurons. We find that prior chronic alcohol exposure leads to increased calcium modulation of the direct pathway during action related behavior. In contrast, prior chronic alcohol exposure led to decreased calcium activity modulation of the indirect pathway and the fast-spiking interneuron population around action-related events. Together, our findings suggest an imbalance in striatal activity during action control. This disruption may contribute to the altered goal-directed control previously reported.
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Affiliation(s)
- Emily T. Baltz
- The Neurosciences Graduate Program, University of California San Diego, La Jolla, CA 92093, USA
| | - Rafael Renteria
- Department of Psychology, University of California San Diego, La Jolla, CA 92093, USA
| | - Christina M. Gremel
- The Neurosciences Graduate Program, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychology, University of California San Diego, La Jolla, CA 92093, USA
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Nasello C, Poppi LA, Wu J, Kowalski TF, Thackray JK, Wang R, Persaud A, Mahboob M, Lin S, Spaseska R, Johnson CK, Gordon D, Tissir F, Heiman GA, Tischfield JA, Bocarsly M, Tischfield MA. Human mutations in high-confidence Tourette disorder genes affect sensorimotor behavior, reward learning, and striatal dopamine in mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.28.569034. [PMID: 38077033 PMCID: PMC10705456 DOI: 10.1101/2023.11.28.569034] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2024]
Abstract
Tourette disorder (TD) is poorly understood, despite affecting 1/160 children. A lack of animal models possessing construct, face, and predictive validity hinders progress in the field. We used CRISPR/Cas9 genome editing to generate mice with mutations orthologous to human de novo variants in two high-confidence Tourette genes, CELSR3 and WWC1 . Mice with human mutations in Celsr3 and Wwc1 exhibit cognitive and/or sensorimotor behavioral phenotypes consistent with TD. Sensorimotor gating deficits, as measured by acoustic prepulse inhibition, occur in both male and female Celsr3 TD models. Wwc1 mice show reduced prepulse inhibition only in females. Repetitive motor behaviors, common to Celsr3 mice and more pronounced in females, include vertical rearing and grooming. Sensorimotor gating deficits and rearing are attenuated by aripiprazole, a partial agonist at dopamine type II receptors. Unsupervised machine learning reveals numerous changes to spontaneous motor behavior and less predictable patterns of movement. Continuous fixed-ratio reinforcement shows Celsr3 TD mice have enhanced motor responding and reward learning. Electrically evoked striatal dopamine release, tested in one model, is greater. Brain development is otherwise grossly normal without signs of striatal interneuron loss. Altogether, mice expressing human mutations in high-confidence TD genes exhibit face and predictive validity. Reduced prepulse inhibition and repetitive motor behaviors are core behavioral phenotypes and are responsive to aripiprazole. Enhanced reward learning and motor responding occurs alongside greater evoked dopamine release. Phenotypes can also vary by sex and show stronger affection in females, an unexpected finding considering males are more frequently affected in TD. Significance Statement We generated mouse models that express mutations in high-confidence genes linked to Tourette disorder (TD). These models show sensorimotor and cognitive behavioral phenotypes resembling TD-like behaviors. Sensorimotor gating deficits and repetitive motor behaviors are attenuated by drugs that act on dopamine. Reward learning and striatal dopamine is enhanced. Brain development is grossly normal, including cortical layering and patterning of major axon tracts. Further, no signs of striatal interneuron loss are detected. Interestingly, behavioral phenotypes in affected females can be more pronounced than in males, despite male sex bias in the diagnosis of TD. These novel mouse models with construct, face, and predictive validity provide a new resource to study neural substrates that cause tics and related behavioral phenotypes in TD.
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42
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Knight A, Gschwind T, Galer P, Worrell GA, Litt B, Soltesz I, Beniczky S. Artificial intelligence in epilepsy phenotyping. Epilepsia 2023:10.1111/epi.17833. [PMID: 37983589 PMCID: PMC11102939 DOI: 10.1111/epi.17833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 11/17/2023] [Indexed: 11/22/2023]
Abstract
Artificial intelligence (AI) allows data analysis and integration at an unprecedented granularity and scale. Here we review the technological advances, challenges, and future perspectives of using AI for electro-clinical phenotyping of animal models and patients with epilepsy. In translational research, AI models accurately identify behavioral states in animal models of epilepsy, allowing identification of correlations between neural activity and interictal and ictal behavior. Clinical applications of AI-based automated and semi-automated analysis of audio and video recordings of people with epilepsy, allow significant data reduction and reliable detection and classification of major motor seizures. AI models can accurately identify electrographic biomarkers of epilepsy, such as spikes, high-frequency oscillations, and seizure patterns. Integrating AI analysis of electroencephalographic, clinical, and behavioral data will contribute to optimizing therapy for patients with epilepsy.
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Affiliation(s)
| | - Tilo Gschwind
- Department of Neurosurgery, Stanford University, Stanford, USA
| | - Peter Galer
- Center for Neuroengineering and Therapeutics; Department of Bioengineering; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, USA
| | | | - Brian Litt
- Center for Neuroengineering and Therapeutics; Department of Bioengineering; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, USA
| | - Ivan Soltesz
- Department of Neurosurgery, Stanford University, Stanford, USA
| | - Sándor Beniczky
- Danish Epilepsy Centre Filadelfia, Dianalund, Aarhus University Hospital and Aarhus University, Aarhus, Denmark
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43
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Calhoun AJ, El Hady A. Everyone knows what behavior is but they just don't agree on it. iScience 2023; 26:108210. [PMID: 37953955 PMCID: PMC10638025 DOI: 10.1016/j.isci.2023.108210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 03/08/2023] [Accepted: 10/11/2023] [Indexed: 11/14/2023] Open
Abstract
Studying "behavior" lies at the heart of many disciplines. Nevertheless, academics rarely provide an explicit definition of what "behavior" actually is. What range of definitions do people use, and how does that vary across disciplines? To answer these questions, we have developed a survey to probe what constitutes "behavior." We find that academics adopt different definitions of behavior according to their academic discipline, animal model that they work with, and level of academic seniority. Using hierarchical clustering, we identify at least six distinct types of "behavior" which are used in seven distinct operational archetypes of "behavior." Individual respondents have clear consistent definitions of behavior, but these definitions are not consistent across the population. Our study is a call for academics to clarify what they mean by "behavior" wherever they study it, with the hope that this will foster interdisciplinary studies that will improve our understanding of behavioral phenomena.
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Affiliation(s)
- Adam J. Calhoun
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Ahmed El Hady
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Cluster for Advanced Study of Collective Behavior, University of Konstanz, Konstanz, Germany
- Max Planck Institute of Animal Behavior, Konstanz, Germany
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Vu MAT, Brown EH, Wen MJ, Noggle CA, Zhang Z, Monk KJ, Bouabid S, Mroz L, Graham BM, Zhuo Y, Li Y, Otchy TM, Tian L, Davison IG, Boas DA, Howe MW. Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.17.567425. [PMID: 38014018 PMCID: PMC10680831 DOI: 10.1101/2023.11.17.567425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Neural population dynamics relevant for behavior vary over multiple spatial and temporal scales across 3-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array and imaging approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice. We developed a semi-automated micro-CT based strategy to precisely localize positions of each optical fiber. This highly-customizable approach enables investigation of multi-scale spatial and temporal patterns of cell-type and neurotransmitter specific signals over arbitrary 3-D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum volume which revealed distinct, modality specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics through our fiber arrays enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and spatial localization of behavioral function across large circuits.
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Affiliation(s)
- Mai-Anh T. Vu
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Eleanor H. Brown
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
| | - Michelle J. Wen
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
- Department of Neurobiology, Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Christian A. Noggle
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Zicheng Zhang
- Department of Biology, Boston University, Boston, MA, USA
| | - Kevin J. Monk
- Department of Biology, Boston University, Boston, MA, USA
| | - Safa Bouabid
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
| | - Lydia Mroz
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
- Northeastern University, Boston, MA, USA
| | - Benjamin M. Graham
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
| | - Yizhou Zhuo
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Beijing, China
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Beijing, China
| | | | - Lin Tian
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA
| | - Ian G. Davison
- Department of Biology, Boston University, Boston, MA, USA
| | - David A. Boas
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Mark W. Howe
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
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Hope J, Beckerle T, Cheng PH, Viavattine Z, Feldkamp M, Fausner S, Saxena K, Ko E, Hryb I, Carter R, Ebner T, Kodandaramaiah S. Brain-wide neural recordings in mice navigating physical spaces enabled by a cranial exoskeleton. RESEARCH SQUARE 2023:rs.3.rs-3491330. [PMID: 38014260 PMCID: PMC10680923 DOI: 10.21203/rs.3.rs-3491330/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Complex behaviors are mediated by neural computations occurring throughout the brain. In recent years, tremendous progress has been made in developing technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales. However, these technologies are primarily designed for studying the mammalian brain during head fixation - wherein the behavior of the animal is highly constrained. Miniaturized devices for studying neural activity in freely behaving animals are largely confined to recording from small brain regions owing to performance limitations. We present a cranial exoskeleton that assists mice in maneuvering neural recording headstages that are orders of magnitude larger and heavier than the mice, while they navigate physical behavioral environments. Force sensors embedded within the headstage are used to detect the mouse's milli-Newton scale cranial forces which then control the x, y, and yaw motion of the exoskeleton via an admittance controller. We discovered optimal controller tuning parameters that enable mice to locomote at physiologically realistic velocities and accelerations while maintaining natural walking gait. Mice maneuvering headstages weighing up to 1.5 kg can make turns, navigate 2D arenas, and perform a navigational decision-making task with the same performance as when freely behaving. We designed an imaging headstage and an electrophysiology headstage for the cranial exoskeleton to record brain-wide neural activity in mice navigating 2D arenas. The imaging headstage enabled recordings of Ca2+ activity of 1000s of neurons distributed across the dorsal cortex. The electrophysiology headstage supported independent control of up to 4 silicon probes, enabling simultaneous recordings from 100s of neurons across multiple brain regions and multiple days. Cranial exoskeletons provide flexible platforms for largescale neural recording during the exploration of physical spaces, a critical new paradigm for unraveling the brain-wide neural mechanisms that control complex behavior.
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Affiliation(s)
- James Hope
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Travis Beckerle
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Pin-Hao Cheng
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Zoey Viavattine
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Michael Feldkamp
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Skylar Fausner
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Kapil Saxena
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Eunsong Ko
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Ihor Hryb
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Neuroscience, University of Minnesota, Twin Cities
| | - Russell Carter
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - Timothy Ebner
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - Suhasa Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
- Department of Neuroscience, University of Minnesota, Twin Cities
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Barnett D, Bohmbach K, Grelot V, Charlet A, Dallérac G, Ju YH, Nagai J, Orr AG. Astrocytes as Drivers and Disruptors of Behavior: New Advances in Basic Mechanisms and Therapeutic Targeting. J Neurosci 2023; 43:7463-7471. [PMID: 37940585 PMCID: PMC10634555 DOI: 10.1523/jneurosci.1376-23.2023] [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: 07/19/2023] [Revised: 08/13/2023] [Accepted: 08/22/2023] [Indexed: 11/10/2023] Open
Abstract
Astrocytes are emerging as key regulators of cognitive function and behavior. This review highlights some of the latest advances in the understanding of astrocyte roles in different behavioral domains across lifespan and in disease. We address specific molecular and circuit mechanisms by which astrocytes modulate behavior, discuss their functional diversity and versatility, and highlight emerging astrocyte-targeted treatment strategies that might alleviate behavioral and cognitive dysfunction in pathologic conditions. Converging evidence across different model systems and manipulations is revealing that astrocytes regulate behavioral processes in a precise and context-dependent manner. Improved understanding of these astrocytic functions may generate new therapeutic strategies for various conditions with cognitive and behavioral impairments.
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Affiliation(s)
- Daniel Barnett
- Appel Alzheimer's Disease Research Institute, Weill Cornell Medicine, New York, New York 10021
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10021
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, New York 10021
| | - Kirsten Bohmbach
- Institute of Cellular Neurosciences, Medical Faculty, University of Bonn, 53127 Bonn, Germany
| | - Valentin Grelot
- Institute of Cellular and Integrative Neuroscience, Centre National de la Recherche Scientifique and University of Strasbourg, Strasbourg, 67000, France
| | - Alexandre Charlet
- Institute of Cellular and Integrative Neuroscience, Centre National de la Recherche Scientifique and University of Strasbourg, Strasbourg, 67000, France
| | - Glenn Dallérac
- Centre National de la Recherche Scientifique and Paris-Saclay University, Paris-Saclay Institute for Neurosciences, Paris, 91400, France
| | - Yeon Ha Ju
- Department of Psychiatry and Neuroscience, University of Texas-Austin Dell Medical School, Austin, Texas 78712
| | - Jun Nagai
- RIKEN Center for Brain Science, Laboratory for Glia-Neuron Circuit Dynamics, Saitama, 351-0198, Japan
| | - Anna G Orr
- Appel Alzheimer's Disease Research Institute, Weill Cornell Medicine, New York, New York 10021
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10021
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, New York 10021
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47
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Susoy V, Samuel ADT. Evolutionarily conserved behavioral plasticity enables context-dependent mating in C. elegans. Curr Biol 2023; 33:4532-4537.e3. [PMID: 37769659 PMCID: PMC10615801 DOI: 10.1016/j.cub.2023.09.003] [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: 04/26/2023] [Revised: 07/20/2023] [Accepted: 09/01/2023] [Indexed: 10/03/2023]
Abstract
Behavioral plasticity helps humans and animals to achieve their goals by adapting their behaviors to different environments.1,2 Although behavioral plasticity is ubiquitous, many innate species-specific behaviors, such as mating, are often assumed to be stereotyped and unaffected by plasticity or learning, especially in invertebrates. Here, we describe a novel case of behavioral plasticity in the nematode C. elegans. Under standard lab conditions (agar plates with bacterial food), the male performs parallel mating,3,4,5 a largely two-dimensional behavioral strategy where his body and tail remain flat on the surface and slide alongside the partner's body from initial contact to copulation. But when placed in liquid media, the male performs spiral mating, a distinctly three-dimensional behavioral strategy where he winds around the partner's body in a helical embrace. The performance of spiral mating does not require a long-term change in growing conditions, but it does improve with experience. This experience-dependent improvement appears to involve a critical period-a time window around the L4 larval stage to the early adult stage-which coincides with the development of most male-specific neurons. We tested several wild isolates of C. elegans and other Caenorhabditis species and found that most were capable of parallel mating on surfaces and spiral mating in liquids. We suggest that two- and three-dimensional mating strategies in Caenorhabditis are plastic, conditionally expressed phenotypes conserved across the genus, which can be genetically "fixed" in some species.
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Affiliation(s)
- Vladislav Susoy
- Department of Physics and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
| | - Aravinthan D T Samuel
- Department of Physics and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
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48
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Labouesse MA, Torres-Herraez A, Chohan MO, Villarin JM, Greenwald J, Sun X, Zahran M, Tang A, Lam S, Veenstra-VanderWeele J, Lacefield CO, Bonaventura J, Michaelides M, Chan CS, Yizhar O, Kellendonk C. A non-canonical striatopallidal Go pathway that supports motor control. Nat Commun 2023; 14:6712. [PMID: 37872145 PMCID: PMC10593790 DOI: 10.1038/s41467-023-42288-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 10/05/2023] [Indexed: 10/25/2023] Open
Abstract
In the classical model of the basal ganglia, direct pathway striatal projection neurons (dSPNs) send projections to the substantia nigra (SNr) and entopeduncular nucleus to regulate motor function. Recent studies have re-established that dSPNs also possess axon collaterals within the globus pallidus (GPe) (bridging collaterals), yet the significance of these collaterals for behavior is unknown. Here we use in vivo optical and chemogenetic tools combined with deep learning approaches in mice to dissect the roles of dSPN GPe collaterals in motor function. We find that dSPNs projecting to the SNr send synchronous motor-related information to the GPe via axon collaterals. Inhibition of native activity in dSPN GPe terminals impairs motor activity and function via regulation of Npas1 neurons. We propose a model by which dSPN GPe axon collaterals (striatopallidal Go pathway) act in concert with the canonical terminals in the SNr to support motor control by inhibiting Npas1 neurons.
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Affiliation(s)
- Marie A Labouesse
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA.
- Department of Health, Sciences and Technology, ETH Zurich, 8092, Zurich, Switzerland.
- Neuroscience Center Zurich, ETH Zurich and University of Zurich, 8057, Zurich, Switzerland.
| | - Arturo Torres-Herraez
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Muhammad O Chohan
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Joseph M Villarin
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Julia Greenwald
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Xiaoxiao Sun
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Mysarah Zahran
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
- Barnard College, Columbia University, New York, NY, 10027, USA
| | - Alice Tang
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
- Columbia College, Columbia University, New York, NY, 10027, USA
| | - Sherry Lam
- Biobehavioral Imaging and Molecular Neuropsychopharmacology Unit, National Institute on Drug Abuse Intramural Research Program, Baltimore, MD, 21224, USA
| | - Jeremy Veenstra-VanderWeele
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Clay O Lacefield
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Jordi Bonaventura
- Biobehavioral Imaging and Molecular Neuropsychopharmacology Unit, National Institute on Drug Abuse Intramural Research Program, Baltimore, MD, 21224, USA
- Departament de Patologia i Terapèutica Experimental, Institut de Neurociències, L'Hospitalet de Llobregat, Universitat de Barcelona, Barcelona, Spain
| | - Michael Michaelides
- Biobehavioral Imaging and Molecular Neuropsychopharmacology Unit, National Institute on Drug Abuse Intramural Research Program, Baltimore, MD, 21224, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - C Savio Chan
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Ofer Yizhar
- Departments of Brain Sciences and Molecular Neuroscience, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Christoph Kellendonk
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA.
- Department of Molecular Pharmacology & Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA.
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49
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García MT, Tran DN, Peterson RE, Stegmann SK, Hanson SM, Reid CM, Xie Y, Vu S, Harwell CC. A developmentally defined population of neurons in the lateral septum controls responses to aversive stimuli. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.24.559205. [PMID: 37873286 PMCID: PMC10592641 DOI: 10.1101/2023.09.24.559205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
When interacting with their environment, animals must balance exploratory and defensive behavior to evaluate and respond to potential threats. The lateral septum (LS) is a structure in the ventral forebrain that calibrates the magnitude of behavioral responses to stress-related external stimuli, including the regulation of threat avoidance. The complex connectivity between the LS and other parts of the brain, together with its largely unexplored neuronal diversity, makes it difficult to understand how defined LS circuits control specific behaviors. Here, we describe a mouse model in which a population of neurons with a common developmental origin (Nkx2.1-lineage neurons) are absent from the LS. Using a combination of circuit tracing and behavioral analyses, we found that these neurons receive inputs from the perifornical area of the anterior hypothalamus (PeFAH) and are specifically activated in stressful contexts. Mice lacking Nkx2.1-lineage LS neurons display increased exploratory behavior even under stressful conditions. Our study extends the current knowledge about how defined neuronal populations within the LS can evaluate contextual information to select appropriate behavioral responses. This is a necessary step towards understanding the crucial role that the LS plays in neuropsychiatric conditions where defensive behavior is dysregulated, such as anxiety and aggression disorders.
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Affiliation(s)
- Miguel Turrero García
- Department of Neurology, University of California, San Francisco; San Francisco, CA
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research; San Francisco, CA
| | - Diana N. Tran
- Department of Neurobiology, Harvard Medical School; Boston, MA
| | | | | | - Sarah M. Hanson
- Department of Neurology, University of California, San Francisco; San Francisco, CA
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research; San Francisco, CA
| | - Christopher M. Reid
- Department of Neurology, University of California, San Francisco; San Francisco, CA
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research; San Francisco, CA
- Ph.D. Program in Neuroscience, Harvard University; Boston, MA
| | - Yajun Xie
- Department of Neurology, University of California, San Francisco; San Francisco, CA
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research; San Francisco, CA
| | - Steve Vu
- Department of Neurobiology, Harvard Medical School; Boston, MA
| | - Corey C. Harwell
- Department of Neurology, University of California, San Francisco; San Francisco, CA
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research; San Francisco, CA
- Chan Zuckerberg Biohub San Francisco; San Francisco, CA
- Lead contact
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50
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Bech P, Crochet S, Dard R, Ghaderi P, Liu Y, Malekzadeh M, Petersen CCH, Pulin M, Renard A, Sourmpis C. Striatal Dopamine Signals and Reward Learning. FUNCTION 2023; 4:zqad056. [PMID: 37841525 PMCID: PMC10572094 DOI: 10.1093/function/zqad056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 10/17/2023] Open
Abstract
We are constantly bombarded by sensory information and constantly making decisions on how to act. In order to optimally adapt behavior, we must judge which sequences of sensory inputs and actions lead to successful outcomes in specific circumstances. Neuronal circuits of the basal ganglia have been strongly implicated in action selection, as well as the learning and execution of goal-directed behaviors, with accumulating evidence supporting the hypothesis that midbrain dopamine neurons might encode a reward signal useful for learning. Here, we review evidence suggesting that midbrain dopaminergic neurons signal reward prediction error, driving synaptic plasticity in the striatum underlying learning. We focus on phasic increases in action potential firing of midbrain dopamine neurons in response to unexpected rewards. These dopamine neurons prominently innervate the dorsal and ventral striatum. In the striatum, the released dopamine binds to dopamine receptors, where it regulates the plasticity of glutamatergic synapses. The increase of striatal dopamine accompanying an unexpected reward activates dopamine type 1 receptors (D1Rs) initiating a signaling cascade that promotes long-term potentiation of recently active glutamatergic input onto striatonigral neurons. Sensorimotor-evoked glutamatergic input, which is active immediately before reward delivery will thus be strengthened onto neurons in the striatum expressing D1Rs. In turn, these neurons cause disinhibition of brainstem motor centers and disinhibition of the motor thalamus, thus promoting motor output to reinforce rewarded stimulus-action outcomes. Although many details of the hypothesis need further investigation, altogether, it seems likely that dopamine signals in the striatum might underlie important aspects of goal-directed reward-based learning.
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Affiliation(s)
- Pol Bech
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Sylvain Crochet
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Robin Dard
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Parviz Ghaderi
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Yanqi Liu
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Meriam Malekzadeh
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Carl C H Petersen
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Mauro Pulin
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Anthony Renard
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Christos Sourmpis
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
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