Sleep spindles track cortical learning patterns for memory consolidation
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Date
2022
Authors
Petzka, M.
Chatburn, A.
Charest, I.
Balanos, G.M.
Staresina, B.P.
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Journal article
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Current Biology, 2022; 32(11):2349.e4-2356.e4
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Abstract
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 behavioral 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.
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Data source: Supplemental information, https://doi.org/10.1016/j.cub.2022.04.045
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Copyright 2022 The author(s) This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)