Evidence map›Paper›PMID 25331890›Full record

Trial reportProceedings of the National Academy of Sciences of the United States of America2014

Memory reactivation during rest supports upcoming learning of related content.

Margaret L Schlichting, Alison R Preston

Abstract readClinical Trial
In one paragraph

Trial report in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.

0numbers the graph read from it
0cells of the map it votes in
71citing 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

71 citing papers in PubMed.

  1. The hippocampus rapidly integrates sequence representations during novel multistep predictions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026
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  15. Repetition dynamically and rapidly increases cortical, but not hippocampal, offline reactivation.Proceedings of the National Academy of Sciences of the United States of America · 2024
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11 more citing papers are in PubMed but not listed here.

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

2 authors.

Margaret L SchlichtingDepartments of Psychology and Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712.
Alison R PrestonDepartments of Psychology and Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712 Neuroscience, and apreston@utexas.edu.

Funding

Hippocampal and prefrontal contributions to memory integrationR01MH100121 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI Alison R Preston · 2013 to 2026
$7.3M
NIMH NIH HHS R01 MH100121
6 · The paper itself

Abstract

Although a number of studies have highlighted the importance of offline processes for memory, how these mechanisms influence future learning remains unknown. Participants with established memories for a set of initial face-object associations were scanned during passive rest and during encoding of new related and unrelated pairs of objects. Spontaneous reactivation of established memories and enhanced hippocampal-neocortical functional connectivity during rest was related to better subsequent learning, specifically of related content. Moreover, the degree of functional coupling during rest was predictive of neural engagement during the new learning experience itself. These results suggest that through rest-phase reactivation and hippocampal-neocortical interactions, existing memories may come to facilitate encoding during subsequent related episodes.

Indexed as

AdultFemaleHippocampusHumansLearningMaleMemoryNeocortexepisodic memoryhippocampusinferenceinterferencememory integration

Identifiers

PMID25331890
PMCPMC4226095

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.