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Identification of memory reactivation during sleep by EEG classification

Belal, Suliman, Cousins, James, El-Deredy, Wael, Parkes, Laura, Schneider, Jules, Tsujimura, Hikaru, Zoumpoulaki, Alexia ORCID:, Perapoch, Marta, Santamaria, Lorena and Lewis, Penelope ORCID: 2018. Identification of memory reactivation during sleep by EEG classification. NeuroImage 176 , pp. 203-214. 10.1016/j.neuroimage.2018.04.029

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Memory reactivation during sleep is critical for consolidation, but also extremely difficult to measure as it is subtle, distributed and temporally unpredictable. This article reports a novel method for detecting such reactivation in standard sleep recordings. During learning, participants produced a complex sequence of finger presses, with each finger cued by a distinct audio-visual stimulus. Auditory cues were then re-played during subsequent sleep to trigger neural reactivation through a method known as targeted memory reactivation (TMR). Next, we used electroencephalography data from the learning session to train a machine learning classifier, and then applied this classifier to sleep data to determine how successfully each tone had elicited memory reactivation. Neural reactivation was classified above chance in all participants when TMR was applied in SWS, and in 5 of the 14 participants to whom TMR was applied in N2. Classification success reduced across numerous repetitions of the tone cue, suggesting either a gradually reducing responsiveness to such cues or a plasticity-related change in the neural signature as a result of cueing. We believe this method will be valuable for future investigations of memory consolidation.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Computer Science & Informatics
Cardiff University Brain Research Imaging Centre (CUBRIC)
Additional Information: This is an open access article under the CC BY license
Publisher: Elsevier
ISSN: 1053-8119
Date of First Compliant Deposit: 16 May 2018
Date of Acceptance: 12 April 2018
Last Modified: 04 May 2023 16:18

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