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Roshchupkina L, Wens V, Coquelet N, Urbain C, de Tiege X, Peigneux P. Motor learning- and consolidation-related resting state fast and slow brain dynamics across wake and sleep. Sci Rep 2024; 14:7531. [PMID: 38553500 PMCID: PMC10980824 DOI: 10.1038/s41598-024-58123-6] [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: 08/09/2023] [Accepted: 03/26/2024] [Indexed: 04/02/2024] Open
Abstract
Motor skills dynamically evolve during practice and after training. Using magnetoencephalography, we investigated the neural dynamics underpinning motor learning and its consolidation in relation to sleep during resting-state periods after the end of learning (boost window, within 30 min) and at delayed time scales (silent 4 h and next day 24 h windows) with intermediate daytime sleep or wakefulness. Resting-state neural dynamics were investigated at fast (sub-second) and slower (supra-second) timescales using Hidden Markov modelling (HMM) and functional connectivity (FC), respectively, and their relationship to motor performance. HMM results show that fast dynamic activities in a Temporal/Sensorimotor state network predict individual motor performance, suggesting a trait-like association between rapidly recurrent neural patterns and motor behaviour. Short, post-training task re-exposure modulated neural network characteristics during the boost but not the silent window. Re-exposure-related induction effects were observed on the next day, to a lesser extent than during the boost window. Daytime naps did not modulate memory consolidation at the behavioural and neural levels. These results emphasise the critical role of the transient boost window in motor learning and memory consolidation and provide further insights into the relationship between the multiscale neural dynamics of brain networks, motor learning, and consolidation.
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Affiliation(s)
- Liliia Roshchupkina
- UR2NF - Neuropsychology and Functional Neuroimaging Research Unit Affiliated at CRCN - Centre for Research in Cognition and Neurosciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.
- UNI - ULB Neuroscience Institute, Brussels, Belgium.
- LN2T - Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, ULB, Brussels, Belgium.
- Faculté des Sciences Psychologiques et de l'Éducation, Campus du Solbosch - CP 191, Avenue F.D. Roosevelt, 50, 1050, Brussels, Belgium.
| | - Vincent Wens
- UNI - ULB Neuroscience Institute, Brussels, Belgium
- LN2T - Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, ULB, Brussels, Belgium
- Department of Functional Neuroimaging, Service of Nuclear Medicine, HUB - Hôpital Universitaire de Bruxelles, Hospital Erasme, Brussels, Belgium
| | - Nicolas Coquelet
- UNI - ULB Neuroscience Institute, Brussels, Belgium
- LN2T - Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, ULB, Brussels, Belgium
- Department of Functional Neuroimaging, Service of Nuclear Medicine, HUB - Hôpital Universitaire de Bruxelles, Hospital Erasme, Brussels, Belgium
| | - Charline Urbain
- UR2NF - Neuropsychology and Functional Neuroimaging Research Unit Affiliated at CRCN - Centre for Research in Cognition and Neurosciences, Université Libre de Bruxelles (ULB), Brussels, Belgium
- UNI - ULB Neuroscience Institute, Brussels, Belgium
- LN2T - Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, ULB, Brussels, Belgium
| | - Xavier de Tiege
- UNI - ULB Neuroscience Institute, Brussels, Belgium
- LN2T - Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, ULB, Brussels, Belgium
- Department of Functional Neuroimaging, Service of Nuclear Medicine, HUB - Hôpital Universitaire de Bruxelles, Hospital Erasme, Brussels, Belgium
| | - Philippe Peigneux
- UR2NF - Neuropsychology and Functional Neuroimaging Research Unit Affiliated at CRCN - Centre for Research in Cognition and Neurosciences, Université Libre de Bruxelles (ULB), Brussels, Belgium
- UNI - ULB Neuroscience Institute, Brussels, Belgium
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Stee W, Legouhy A, Guerreri M, Villemonteix T, Zhang H, Peigneux P. Microstructural dynamics of motor learning and sleep-dependent consolidation: A diffusion imaging study. iScience 2023; 26:108426. [PMID: 38058306 PMCID: PMC10696465 DOI: 10.1016/j.isci.2023.108426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/20/2023] [Accepted: 11/08/2023] [Indexed: 12/08/2023] Open
Abstract
Memory consolidation can benefit from post-learning sleep, eventually leading to long-term microstructural brain modifications to accommodate new memory representations. Non-invasive diffusion-weighted magnetic resonance imaging (DWI) allows the observation of (micro)structural brain remodeling after time-limited motor learning. Here, we combine conventional diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) that allows modeling dendritic and axonal complexity in gray matter to investigate with improved specificity the microstructural brain mechanisms underlying time- and sleep-dependent motor memory consolidation dynamics. Sixty-one young healthy adults underwent four DWI sessions, two sequential motor trainings, and a night of total sleep deprivation or regular sleep distributed over five days. We observed rapid-motor-learning-related remodeling in occipitoparietal, temporal, and motor-related subcortical regions, reflecting temporary dynamics in learning-related neuronal brain plasticity processes. Sleep-related consolidation seems not to exert a detectable impact on diffusion parameters, at least on the timescale of a few days.
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Affiliation(s)
- Whitney Stee
- UR2NF-Neuropsychology and Functional Neuroimaging Research Unit affiliated at CRCN – Centre for Research in Cognition and Neurosciences and UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
- GIGA - Cyclotron Research Centre - In Vivo Imaging, University of Liège (ULiège), Liège, Belgium
| | - Antoine Legouhy
- Department of Computer Science & Centre for Medical Image Computing, University College London (UCL), London, UK
| | - Michele Guerreri
- Department of Computer Science & Centre for Medical Image Computing, University College London (UCL), London, UK
| | - Thomas Villemonteix
- UR2NF-Neuropsychology and Functional Neuroimaging Research Unit affiliated at CRCN – Centre for Research in Cognition and Neurosciences and UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
- Laboratoire Psychopathologie et Processus de Changement, Paris-Lumières University, Saint-Denis, France
| | - Hui Zhang
- Department of Computer Science & Centre for Medical Image Computing, University College London (UCL), London, UK
| | - Philippe Peigneux
- UR2NF-Neuropsychology and Functional Neuroimaging Research Unit affiliated at CRCN – Centre for Research in Cognition and Neurosciences and UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
- GIGA - Cyclotron Research Centre - In Vivo Imaging, University of Liège (ULiège), Liège, Belgium
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