Sleep Does not Help Relearning Declarative Memories in Older Adults
Bibliographic record
Abstract
How sleep affects memory in older adults is a critical topic,since age significantly impacts both sleep and memory. Fordeclarative memory, previous research reports contradictoryresults, with some studies showing sleep-dependent memoryconsolidation and some other not. We hypothesize that thisdiscrepancy may be due to the use of recall as the memorymeasure, a demanding task for older adults. The present paperfocuses on the effect of sleep on relearning, a measure thatproved useful to reveal subtle, implicit memory effects.Previous research in young adults showed that sleeping afterlearning was more beneficial to relearning the same Swahili-French word pairs 12 hours later, compared with the sameinterval spent awake. In particular, those words that could notbe recalled were relearned faster when participants previouslyslept. The effect of sleep was also beneficial for retention aftera one-week and a 6-month delay. The present study used thesame experimental design in older adults aged 71 on averagebut showed no significant effect of sleep on consolidation, onrelearning, or on long-term retention. Thus, even when usingrelearning speed as the memory measure, the consolidatingeffect of sleep in older adults was not demonstrated, inalignment with some previous findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".