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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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2
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Lemke SM, Celotto M, Maffulli R, Ganguly K, Panzeri S. Information flow between motor cortex and striatum reverses during skill learning. Curr Biol 2024; 34:1831-1843.e7. [PMID: 38604168 PMCID: PMC11078609 DOI: 10.1016/j.cub.2024.03.023] [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: 12/13/2023] [Revised: 02/22/2024] [Accepted: 03/14/2024] [Indexed: 04/13/2024]
Abstract
The coordination of neural activity across brain areas during a specific behavior is often interpreted as neural communication involved in controlling the behavior. However, whether information relevant to the behavior is actually transferred between areas is often untested. Here, we used information-theoretic tools to quantify how motor cortex and striatum encode and exchange behaviorally relevant information about specific reach-to-grasp movement features during skill learning in rats. We found a temporal shift in the encoding of behaviorally relevant information during skill learning, as well as a reversal in the primary direction of behaviorally relevant information flow, from cortex-to-striatum during naive movements to striatum-to-cortex during skilled movements. Standard analytical methods that quantify the evolution of overall neural activity during learning-such as changes in neural signal amplitude or the overall exchange of information between areas-failed to capture these behaviorally relevant information dynamics. Using these standard methods, we instead found a consistent coactivation of overall neural signals during movement production and a bidirectional increase in overall information propagation between areas during learning. Our results show that skill learning is achieved through a transformation in how behaviorally relevant information is routed across cortical and subcortical brain areas and that isolating the components of neural activity relevant to and informative about behavior is critical to uncover directional interactions within a coactive and coordinated network.
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Affiliation(s)
- Stefan M Lemke
- Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Corso Bettini 31, 38068 Rovereto, Italy; Neurology Service, San Francisco Veterans Affairs Medical Center, 4150 Clement Street, San Francisco, CA 94121, USA; Department of Neurology, University of California, San Francisco, 1700 Owens Street, San Francisco, CA 94158, USA; Neuroscience Center, University of North Carolina, Chapel Hill, 116 Manning Drive, Chapel Hill, NC 27599, USA.
| | - Marco Celotto
- Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Corso Bettini 31, 38068 Rovereto, Italy; Department of Pharmacy and Biotechnology, University of Bologna, Via Irnerio 48, 40126 Bologna, Italy; Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, 20251 Hamburg, Germany
| | - Roberto Maffulli
- Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Corso Bettini 31, 38068 Rovereto, Italy
| | - Karunesh Ganguly
- Neurology Service, San Francisco Veterans Affairs Medical Center, 4150 Clement Street, San Francisco, CA 94121, USA; Department of Neurology, University of California, San Francisco, 1700 Owens Street, San Francisco, CA 94158, USA
| | - Stefano Panzeri
- Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, 20251 Hamburg, Germany.
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3
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Kuzmina E, Kriukov D, Lebedev M. Neuronal travelling waves explain rotational dynamics in experimental datasets and modelling. Sci Rep 2024; 14:3566. [PMID: 38347042 PMCID: PMC10861525 DOI: 10.1038/s41598-024-53907-2] [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: 11/25/2023] [Accepted: 02/06/2024] [Indexed: 02/15/2024] Open
Abstract
Spatiotemporal properties of neuronal population activity in cortical motor areas have been subjects of experimental and theoretical investigations, generating numerous interpretations regarding mechanisms for preparing and executing limb movements. Two competing models, representational and dynamical, strive to explain the relationship between movement parameters and neuronal activity. A dynamical model uses the jPCA method that holistically characterizes oscillatory activity in neuron populations by maximizing the data rotational dynamics. Different rotational dynamics interpretations revealed by the jPCA approach have been proposed. Yet, the nature of such dynamics remains poorly understood. We comprehensively analyzed several neuronal-population datasets and found rotational dynamics consistently accounted for by a traveling wave pattern. For quantifying rotation strength, we developed a complex-valued measure, the gyration number. Additionally, we identified parameters influencing rotation extent in the data. Our findings suggest that rotational dynamics and traveling waves are typically the same phenomena, so reevaluation of the previous interpretations where they were considered separate entities is needed.
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Affiliation(s)
- Ekaterina Kuzmina
- Skolkovo Institute of Science and Technology, Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Moscow, Russia, 121205.
- Artificial Intelligence Research Institute (AIRI), Moscow, Russia.
| | - Dmitrii Kriukov
- Artificial Intelligence Research Institute (AIRI), Moscow, Russia
- Skolkovo Institute of Science and Technology, Center for Molecular and Cellular Biology, Moscow, Russia, 121205
| | - Mikhail Lebedev
- Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, Moscow, Russia, 119992
- Sechenov Institute of Evolutionary Physiology and Biochemistry of the Russian Academy of Sciences, Saint-Petersburg, Russia, 194223
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4
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Mizes KGC, Lindsey J, Escola GS, Ölveczky BP. Dissociating the contributions of sensorimotor striatum to automatic and visually guided motor sequences. Nat Neurosci 2023; 26:1791-1804. [PMID: 37667040 PMCID: PMC11187818 DOI: 10.1038/s41593-023-01431-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/14/2023] [Indexed: 09/06/2023]
Abstract
The ability to sequence movements in response to new task demands enables rich and adaptive behavior. However, such flexibility is computationally costly and can result in halting performances. Practicing the same motor sequence repeatedly can render its execution precise, fast and effortless, that is, 'automatic'. The basal ganglia are thought to underlie both types of sequence execution, yet whether and how their contributions differ is unclear. We parse this in rats trained to perform the same motor sequence instructed by cues and in a self-initiated overtrained, or 'automatic,' condition. Neural recordings in the sensorimotor striatum revealed a kinematic code independent of the execution mode. Although lesions reduced the movement speed and affected detailed kinematics similarly, they disrupted high-level sequence structure for automatic, but not visually guided, behaviors. These results suggest that the basal ganglia are essential for 'automatic' motor skills that are defined in terms of continuous kinematics, but can be dispensable for discrete motor sequences guided by sensory cues.
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Affiliation(s)
- Kevin G C Mizes
- Program in Biophysics, Harvard University, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Jack Lindsey
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York City, NY, USA
| | - G Sean Escola
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York City, NY, USA
- Department of Psychiatry, Columbia University, New York City, NY, USA
| | - Bence P Ölveczky
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
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Mizes KGC, Lindsey J, Escola GS, Ölveczky BP. Motor cortex is required for flexible but not automatic motor sequences. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.05.556348. [PMID: 37732225 PMCID: PMC10508748 DOI: 10.1101/2023.09.05.556348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
How motor cortex contributes to motor sequence execution is much debated, with studies supporting disparate views. Here we probe the degree to which motor cortex's engagement depends on task demands, specifically whether its role differs for highly practiced, or 'automatic', sequences versus flexible sequences informed by external events. To test this, we trained rats to generate three-element motor sequences either by overtraining them on a single sequence or by having them follow instructive visual cues. Lesioning motor cortex revealed that it is necessary for flexible cue-driven motor sequences but dispensable for single automatic behaviors trained in isolation. However, when an automatic motor sequence was practiced alongside the flexible task, it became motor cortex-dependent, suggesting that subcortical consolidation of an automatic motor sequence is delayed or prevented when the same sequence is produced also in a flexible context. A simple neural network model recapitulated these results and explained the underlying circuit mechanisms. Our results critically delineate the role of motor cortex in motor sequence execution, describing the condition under which it is engaged and the functions it fulfills, thus reconciling seemingly conflicting views about motor cortex's role in motor sequence generation.
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Affiliation(s)
- Kevin G. C. Mizes
- Program in Biophysics, Harvard University, Cambridge, MA 02138,
USA
- Department of Organismic and Evolutionary Biology and Center for
Brain Science, Harvard University, Cambridge, MA, USA
| | - Jack Lindsey
- Zuckerman Mind Brain and Behavior Institute, Columbia
University, New York, NY, 10027, USA
| | - G. Sean Escola
- Zuckerman Mind Brain and Behavior Institute, Columbia
University, New York, NY, 10027, USA
- Department of Psychiatry, Columbia University, New York, NY,
10032, USA
| | - Bence P. Ölveczky
- Department of Organismic and Evolutionary Biology and Center for
Brain Science, Harvard University, Cambridge, MA, USA
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6
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Bracco M, Mutanen TP, Veniero D, Thut G, Robertson EM. Distinct frequencies balance segregation with interaction between different memory types within a prefrontal circuit. Curr Biol 2023:S0960-9822(23)00622-X. [PMID: 37269827 DOI: 10.1016/j.cub.2023.05.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 03/29/2023] [Accepted: 05/12/2023] [Indexed: 06/05/2023]
Abstract
Once formed, the fate of memory is uncertain. Subsequent offline interactions between even different memory types (actions versus words) modify retention.1,2,3,4,5,6 These interactions may occur due to different oscillations functionally linking together different memory types within a circuit.7,8,9,10,11,12,13 With memory processing driving the circuit, it may become less susceptible to external influences.14 We tested this prediction by perturbing the human brain with single pulses of transcranial magnetic stimulation (TMS) and simultaneously measuring the brain activity changes with electroencephalography (EEG15,16,17). Stimulation was applied over brain areas that contribute to memory processing (dorsolateral prefrontal cortex, DLPFC; primary motor cortex, M1) at baseline and offline, after memory formation, when memory interactions are known to occur.1,4,6,10,18 The EEG response decreased offline (compared with baseline) within the alpha/beta frequency bands when stimulation was applied to the DLPFC, but not to M1. This decrease exclusively followed memory tasks that interact, revealing that it was due specifically to the interaction, not task performance. It remained even when the order of the memory tasks was changed and so was present, regardless of how the memory interaction was produced. Finally, the decrease within alpha power (but not beta) was correlated with impairment in motor memory, whereas the decrease in beta power (but not alpha) was correlated with impairment in word-list memory. Thus, different memory types are linked to different frequency bands within a DLPFC circuit, and the power of these bands shapes the balance between interaction and segregation between these memories.
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Affiliation(s)
- Martina Bracco
- Sorbonne Université, Institut du Cerveau, Paris Brain Institute, ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, 47 Bd de l'Hôpital, 75013 Paris, France
| | - Tuomas P Mutanen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O. box 12200, FI-00076 Aalto, Finland
| | - Domenica Veniero
- School of Psychology, University of Nottingham, Nottingham NG7 2RD, UK
| | - Gregor Thut
- Institute of Neuroscience and Psychology, Centre for Cognitive Neuroimaging, University of Glasgow, Glasgow G12 8QB, UK
| | - Edwin M Robertson
- Institute of Neuroscience and Psychology, Centre for Cognitive Neuroimaging, University of Glasgow, Glasgow G12 8QB, UK.
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7
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Fleischer P, Abbasi A, Fealy AW, Danielsen NP, Sandhu R, Raj PR, Gulati T. Emergent Low-Frequency Activity in Cortico-Cerebellar Networks with Motor Skill Learning. eNeuro 2023; 10:ENEURO.0011-23.2023. [PMID: 36750360 PMCID: PMC9946068 DOI: 10.1523/eneuro.0011-23.2023] [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: 01/11/2023] [Accepted: 01/24/2023] [Indexed: 02/09/2023] Open
Abstract
The motor cortex controls skilled arm movement by recruiting a variety of targets in the nervous system, and it is important to understand the emergent activity in these regions as refinement of a motor skill occurs. One fundamental projection of the motor cortex (M1) is to the cerebellum. However, the emergent activity in the motor cortex and the cerebellum that appears as a dexterous motor skill is consolidated is incompletely understood. Here, we report on low-frequency oscillatory (LFO) activity that emerges in cortico-cerebellar networks with learning the reach-to-grasp motor skill. We chronically recorded the motor and the cerebellar cortices in rats, which revealed the emergence of coordinated movement-related activity in the local-field potentials as the reaching skill consolidated. Interestingly, we found this emergent activity only in the rats that gained expertise in the task. We found that the local and cross-area spiking activity was coordinated with LFOs in proficient rats. Finally, we also found that these neural dynamics were more prominently expressed during accurate behavior in the M1. This work furthers our understanding on emergent dynamics in the cortico-cerebellar loop that underlie learning and execution of precise skilled movement.
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Affiliation(s)
- Pierson Fleischer
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048
| | - Aamir Abbasi
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048
| | - Andrew W Fealy
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048
| | - Nathan P Danielsen
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048
| | - Ramneet Sandhu
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048
| | - Philip R Raj
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048
| | - Tanuj Gulati
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California 90048
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90095
- Department of Bioengineering, Henry Samueli School of Engineering, University of California-Los Angeles, Los Angeles, California 92697
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8
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Ganguly K, Khanna P, Morecraft R, Lin DJ. Modulation of neural co-firing to enhance network transmission and improve motor function after stroke. Neuron 2022; 110:2363-2385. [PMID: 35926452 PMCID: PMC9366919 DOI: 10.1016/j.neuron.2022.06.024] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 05/15/2022] [Accepted: 06/28/2022] [Indexed: 01/28/2023]
Abstract
Stroke is a leading cause of disability. While neurotechnology has shown promise for improving upper limb recovery after stroke, efficacy in clinical trials has been variable. Our central thesis is that to improve clinical translation, we need to develop a common neurophysiological framework for understanding how neurotechnology alters network activity. Our perspective discusses principles for how motor networks, both healthy and those recovering from stroke, subserve reach-to-grasp movements. We focus on neural processing at the resolution of single movements, the timescale at which neurotechnologies are applied, and discuss how this activity might drive long-term plasticity. We propose that future studies should focus on cross-area communication and bridging our understanding of timescales ranging from single trials within a session to across multiple sessions. We hope that this perspective establishes a combined path forward for preclinical and clinical research with the goal of more robust clinical translation of neurotechnology.
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Affiliation(s)
- Karunesh Ganguly
- Department of Neurology, Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA,Neurology Service, SFVAHCS, San Francisco, CA, USA,
| | - Preeya Khanna
- Department of Neurology, Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA,Neurology Service, SFVAHCS, San Francisco, CA, USA
| | - Robert Morecraft
- Laboratory of Neurological Sciences, Division of Basic Biomedical Sciences, Sanford School of Medicine, The University of South Dakota, Vermillion, SD, 57069 USA
| | - David J. Lin
- Center for Neurotechnology and Neurorecovery, Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Massachusetts General Hospital, Boston, MA,Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI
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