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Record W2346477418 · doi:10.1111/jsr.12423

Sleep physiology predicts memory retention after reactivation

2016· article· en· W2346477418 on OpenAlexafffund
Kevin J. MacDonald, Kimberly A. Côté

Bibliographic record

VenueJournal of Sleep Research · 2016
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsBrock University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMemory consolidationEveningSleep (system call)PsychologyMorningConsolidation (business)AudiologyRelevance (law)Developmental psychologyCognitive psychologyNeuroscienceMedicineInternal medicineComputer science

Abstract

fetched live from OpenAlex

Both sleep and future relevance influence memory consolidation; however, limited research has investigated their role in memory reconsolidation. We manipulated the future relevance of both stable and labile memories in need of reconsolidation. Two groups learned two blocks of syllable pairs on one evening and were told they would be tested on one of the blocks later. On the second evening, one group (Labile) received reminders designed to return their memories of syllable pairs to a labile state, while a second group (Stable) received reminders designed to leave these memories in a stable state. No significant differences in memory retention were found between blocks or groups the following morning. Frontal delta (0.5-4 Hz) electroencephalographic power during Stage 2 sleep correlated positively with retention of future-relevant material exclusively in the Labile group. Central theta (4-8 Hz) electroencephalographic power during rapid eye movement (REM) sleep correlated positively with the extent to which the Labile group selectively retained future-relevant material. These relationships suggest that sleep-dependent processes are involved in an economical reprocessing of memories beyond the initial stages of consolidation.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.101
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.111
GPT teacher head0.364
Teacher spread0.254 · 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

Citations6
Published2016
Admission routes2
Has abstractyes

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