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Record W2537263927 · doi:10.1371/journal.pone.0165141

Test Expectation Enhances Memory Consolidation across Both Sleep and Wake

2016· article· en· W2537263927 on OpenAlexaff
Erin J. Wamsley, Kelly Hamilton, Yvette M. Graveline, Stephanie Manceor, Elaine Parr

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental HealthFundação Bial
KeywordsMemory consolidationConsolidation (business)WakefulnessSleep (system call)PsychologyCognitive psychologyMemory testAudiologyNeuroscienceMedicineCognitionComputer scienceElectroencephalographyHippocampus

Abstract

fetched live from OpenAlex

Memory consolidation benefits from post-training sleep. However, recent studies suggest that sleep does not uniformly benefit all memory, but instead prioritizes information that is important to the individual. Here, we examined the effect of test expectation on memory consolidation across sleep and wakefulness. Following reports that information with strong "future relevance" is preferentially consolidated during sleep, we hypothesized that test expectation would enhance memory consolidation across a period of sleep, but not across wakefulness. To the contrary, we found that expectation of a future test enhanced memory for both spatial and motor learning, but that this effect was equivalent across both wake and sleep retention intervals. These observations differ from those of least two prior studies, and fail to support the hypothesis that the "future relevance" of learned material moderates its consolidation selectively during sleep.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.241

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.304
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations31
Published2016
Admission routes1
Has abstractyes

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