PreprintCited by 111Sleep and Wakefulness ResearchMemory and Neural MechanismsMemory Processes and Influences

Sleep enhances category learning.

Open access
Djonlagic, Ina, Rosenfeld, Andrew, Shohamy, Daphna, Myers, Catherine, Gluck, Mark, Stickgold, Robert·2009·Learning & Memory

Abstract

The ability to categorize objects and events in the world around us is a fundamental and critical aspect of human learning. We trained healthy adults on a probabilistic category-learning task in two different training modes. The aim of this study was to see whether either form of probabilistic category learning (feedback or observational) undergoes subsequent enhancement during sleep. Our results suggest that after training, a good night of sleep can lead to improved performance the following day on such tasks.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/lm.1634509

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Sleep not only quantitatively strengthens memory, but also qualitatively transforms past memory traces in a way that may help respond to similar events in the future.

    “Yet critically, sleep not only quantitatively strengthens memory, but also qualitatively transforms past memory traces in a way that may help us respond to similar events in the future.”

    From Constructive episodic simulation in dreams (2022) · cites this paper as [18]

    In the paper’s results (pp. 751–755), sleep was associated with improved category-task performance and more accurate estimates of the cards’ outcome probabilities, supporting both stronger performance and a change in how the learned relationships were represented. The second test used the same card combinations and trial sequence, however, so the paper does not establish that this change helps people respond to similar future events. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 40 · Cited by 111

Authors
Djonlagic, I., Rosenfeld, A., Shohamy, D., Myers, C., Gluck, M., & Stickgold, R.
Affiliations
  • Brigham and Women's Hospital (US)
  • Beth Israel Deaconess Medical Center (US)
  • Rutgers, The State University of New Jersey (US)
Venue
Learning & Memory
Published
2009-11-19
Volume
16
Issue
12
Pages
751-755
ISSN
  • 1072-0502 (ISSN-L)
  • 1549-5485
OpenAlex
W2136211925
Cited by
111
References
40
Citations by year
2026: 2 · 2025: 6 · 2024: 12 · 2023: 7 · 2022: 7 · 2021: 9 · 2020: 11 · 2019: 5 · 2018: 5 · 2017: 8 · 2016: 7 · 2015: 7 · 2014: 13 · 2013: 3 · 2012: 3
Type
posted content
Language
en
Open access
Locations
  • Learning & Memory (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (MH48,832)
  • National Heart, Lung, and Blood Institute (NIH-T32-HL07901-06, T32HL007901)
  • National Institute of Mental Health (MH-48832, R01MH048832)
  • National Center for Research Resources (M01RR001032)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
Keywords
sleep, category learning, probabilistic category learning, observational learning, feedback learning, memory consolidation, learning improvement
MeSH terms
Adolescent, Adult, Humans, Learning, Psychomotor Performance, Sleep, Sleep, REM, Models, Statistical, Polysomnography, Feedback, Psychological, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review