Personalized targeted memory reactivation enhances consolidation of challenging memories via slow wave and spindle dynamics
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912718495154176 |
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| author | Shin, Gi-Hwan Kweon, Young-Seok Oh, Seungwon Lee, Seong-Whan |
| author_facet | Shin, Gi-Hwan Kweon, Young-Seok Oh, Seungwon Lee, Seong-Whan |
| contents | Sleep is crucial for memory consolidation, underpinning effective learning. Targeted memory reactivation (TMR) can strengthen neural representations by re-engaging learning circuits during sleep. However, TMR protocols overlook individual differences in learning capacity and memory trace strength, limiting efficacy for difficult-to-recall memories. Here, we present a personalized TMR protocol that adjusts stimulation frequency based on individual retrieval performance and task difficulty during a word-pair memory task. In an experiment comparing personalized TMR, TMR, and control groups, the personalized protocol significantly reduced memory decay and improved error correction under challenging recall. Electroencephalogram (EEG) analyses revealed enhanced synchronization of slow waves and spindles, with a significant positive correlation between behavioral and EEG features for challenging memories. Multivariate classification identified distinct neural signatures linked to the personalized approach, highlighting its ability to target memory-specific circuits. These findings provide novel insights into sleep-dependent memory consolidation and support personalized TMR interventions to optimize learning outcomes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_15013 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Personalized targeted memory reactivation enhances consolidation of challenging memories via slow wave and spindle dynamics Shin, Gi-Hwan Kweon, Young-Seok Oh, Seungwon Lee, Seong-Whan Human-Computer Interaction Sleep is crucial for memory consolidation, underpinning effective learning. Targeted memory reactivation (TMR) can strengthen neural representations by re-engaging learning circuits during sleep. However, TMR protocols overlook individual differences in learning capacity and memory trace strength, limiting efficacy for difficult-to-recall memories. Here, we present a personalized TMR protocol that adjusts stimulation frequency based on individual retrieval performance and task difficulty during a word-pair memory task. In an experiment comparing personalized TMR, TMR, and control groups, the personalized protocol significantly reduced memory decay and improved error correction under challenging recall. Electroencephalogram (EEG) analyses revealed enhanced synchronization of slow waves and spindles, with a significant positive correlation between behavioral and EEG features for challenging memories. Multivariate classification identified distinct neural signatures linked to the personalized approach, highlighting its ability to target memory-specific circuits. These findings provide novel insights into sleep-dependent memory consolidation and support personalized TMR interventions to optimize learning outcomes. |
| title | Personalized targeted memory reactivation enhances consolidation of challenging memories via slow wave and spindle dynamics |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2511.15013 |