bioRxivNeurosciencePreprint
Visual training induced occipital fast sleep spindle clustering in humans revealed by full-night HD-EEG recordings
Patrícia GervániD, Gábor BocskaiiD, Andrea BerencsiiD, Ferenc GombosiD, Ilona KovácsiD
Abstract
This study investigates the impact of extensive visual procedural training on the temporal organisation of sleep spindles in healthy young adults. We selected 39 participants aged 16-20 and employed high-density electroencephalography to assess spindle characteristics during two full nights of sleep, with daytime practising in a contour integration task in between the two nights. We utilised linear mixed models to comprehensively analyse the effects of age and training on basic, clustering- and rhythmicity-related spindle parameters. Our findings indicate no significant age effects in this age-range, and no significant change between the two nights with respect to slow spindles. Fast spindles demonstrated a significant increase in density after training, and we observed significant changes in spindle clustering and rhythmicity parameters as well. Local spindle density, train density, and the ratio of clustered spindles have increased, and inter-train interval decreased by the second night. These results contribute to the growing literature on sleep-dependent memory consolidation by demonstrating that spindle reorganisation occurs not only in motor tasks but also in visual learning contexts. The absence of age-related differences further highlights the robustness of these mechanisms across developmental stages. Our study emphasises the importance of spindle dynamics in procedural learning and suggests promising possibilities for future research into the neurophysiological basis of memory consolidation. By revealing the relationship between training and sleep spindle characteristics, our findings provide valuable insights into how sleep supports learning and memory processes in young adults, potentially informing interventions aimed at enhancing memory performance through sleep-related strategies.
- organism: human
- assay: electronic health records
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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