Stee, W;
Legouhy, A;
Guerreri, M;
Villemonteix, T;
Zhang, H;
Peigneux, P;
(2023)
Microstructural dynamics of motor learning and sleep-dependent consolidation: A diffusion imaging study.
iScience
, 26
(12)
, Article 108426. 10.1016/j.isci.2023.108426.
Preview |
Text
1-s2.0-S2589004223025038-main.pdf - Published Version Download (4MB) | Preview |
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.
Type: | Article |
---|---|
Title: | Microstructural dynamics of motor learning and sleep-dependent consolidation: A diffusion imaging study |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.isci.2023.108426 |
Publisher version: | https://doi.org/10.1016/j.isci.2023.108426 |
Language: | English |
Additional information: | © 2023 The Author(s). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10183852 |
Archive Staff Only
![]() |
View Item |