Evidence map›Paper›PMID 40691439›Full record

ArticleNPJ science of learning2025

Personalized targeted memory reactivation enhances consolidation of challenging memories via slow wave and spindle dynamics.

Gi-Hwan Shin, Young-Seok Kweon, Seungwon Oh, Seong-Whan Lee

Abstract read
In one paragraph

Article in NPJ science of learning, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Gi-Hwan ShinDepartment of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Young-Seok KweonDepartment of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Seungwon OhDepartment of Artificial Intelligence, Kongju National University, Cheonan, Republic of Korea.
Seong-Whan LeeDepartment of Artificial Intelligence, Korea University, Seoul, Republic of Korea. sw.lee@korea.ac.kr.

Funding

Institute of Information & Communications Technology Planning & Evaluation No. RS-2019-II190079National Research Foundation of Korea No. 2022-2-00975
6 · The paper itself

Abstract

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.

Identifiers

PMID40691439
PMCPMC12280145

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.