CENTER FOR RESEARCH IN
COGNITION & NEUROSCIENCES/ConnexConnex

Join the defense via Teams: https://bit.ly/3W1G57k

Location: AX1.216 (Campus du Solbosch)

Jury members:
- Philippe Peigneux, PhD (ULB; Promotor)
- Alison Mary, PhD (ULB; Secretary)
- Wim Gevers, PhD (ULB ; President)
- Olivier Collignon, PhD (UCLouvain)
- Monika Schönauer, PhD (University of Freiburg, Germany)

Abstract:

Currently available data indicate that microstructural brain changes underlying motor sequence learning can be evidenced already in the very short term (i.e., less than one hour). Further evidence suggests that post-training sleep contributes to consolidate motor memories, potentially leading to enduring microstructural modifications. Moreover, strengthening a recent memory trace by triggering its (re)processing during sleep is feasible through Targeted Memory Reactivation (TMR), by cueing previously learned material during post-training sleep. Whether TMR leads to additional changes in the brain’s microstructure remains yet to be determined.

Ninety young, healthy adults underwent five Diffusion Weighted Imaging (DWI) sessions, participated in two sequential motor trainings, and experienced either a post-training night of total sleep deprivation (SD), regular sleep (RS), or sleep with TMR, spread over five days. We combined standard Diffusion Tensor Imaging (DTI) with Neurite Orientation Dispersion & Density Imaging (NODDI) to assess dendritic and axonal complexity more accurately in grey matter.

Significant learning-induced changes were observed across extensive occipitoparietal and temporal regions, as well as in the cerebellar cortex and motor-related subcortical areas such as the thalamus, putamen, and hippocampus. Notably, reductions in Mean Diffusivity (MD) within cortical areas corresponded with decreases in Free Water Fraction (FWF) and increases in Neurite Density Index (NDI). Subcortical regions also showed MD reductions, with FWF reductions observed in all areas except the putamen, which exhibited a marked NDI increase suggesting enhanced neurite density. On day 5, a limited persistence of these learning-induced modifications was noted. A subsequent retraining session elicited noticeable cortical changes, albeit less extensive than those observed during initial learning. At the subcortical level, modifications were detected in the putamen and the thalamus, as well as in the cerebellar cortex. Furthermore, the caudate nucleus exhibited structural variations throughout the procedure, with the timing of these changes differing among groups (SD/RS/TMR). Sleep-related consolidation (SD vs. RS) did not markedly influence diffusion parameters within the observed timeframe. However, differences were noted between the RS and TMR groups, suggesting that TMR during sleep may affect specific brain regions implicated in motor-sequence learning. Our findings underscore the rapid, learning-related reorganization that occur in specific cortical and subcortical areas, reflecting a shift from hippocampal engagement in the early stages of skill learning, to more striatal regions in later stages, mirroring prior functional studies showing a similar dynamic. It is noticeable, however, that this transition did not occur uniformly across all our participants, particularly in the caudate nucleus, possibly influenced by the strength of the memory trace formed by the end of learning, or the performance strategic mode (speed/accuracy) individuals decided to prioritize.

Furthermore, we explored the impact of a brief behavioral reactivation of the memory trace at wake following post-training sleep or sleep deprivation on delayed motor performance. Existing evidence on the long-term effects of motor memory reactivation at wake and its interplay with sleep-related consolidation is sparse, highlighting the need for further exploration into the mechanisms underpinning long-term performance enhancements post reactivation.

With this project, we aimed at deepening our understanding of the complex interconnections between learning, sleep, neuronal plasticity, and the efficacy of targeted reactivation approaches in enhancing motor memory consolidation. Here, we highlight the dynamics of structural plasticity processes inherent to learning and memory consolidation.