RT Journal Article
SR Electronic
T1 Sleep spindles track cortical learning patterns for memory consolidation
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.09.01.458569
DO 10.1101/2021.09.01.458569
A1 Marit Petzka
A1 Alex Chatburn
A1 Ian Charest
A1 George M. Balanos
A1 Bernhard P. Staresina
YR 2021
UL http://biorxiv.org/content/early/2021/09/03/2021.09.01.458569.abstract
AB Memory consolidation, the transformation of labile memory traces into stable long-term representations, is facilitated by post-learning sleep. Computational and biophysical models suggest that sleep spindles may play a key mechanistic role for consolidation, igniting structural changes at cortical sites involved in prior learning. Here we tested the resulting prediction that spindles are most pronounced over learning-related cortical areas and that the extent of this learning-spindle overlap predicts behavioural measures of memory consolidation. Using high-density scalp Electroencephalography (EEG) and Polysomnography (PSG) in healthy volunteers, we first identified cortical areas engaged during a temporospatial associative memory task (power decreases in the alpha/beta frequency range, 6-20 Hz). Critically, we found that participant-specific topographies (i.e., spatial distributions) of post-learning sleep spindle amplitude correlated with participant-specific learning topographies. Importantly, the extent to which spindles tracked learning patterns further predicted memory consolidation across participants. Our results provide empirical evidence for a role of post-learning sleep spindles in tracking learning networks, thereby facilitating memory consolidation.Competing Interest StatementThe authors have declared no competing interest.