Rest boosts the long-term retention of spatial associative and temporal order information
Bibliographic record
Abstract
People retain more new verbal episodic information for at least 7 days if they rest for a few minutes after learning than if they attend to new information. It is hypothesized that rest allows for superior consolidation of new memories. In rodents, rest periods promote hippocampal replay of a recently travelled route, and this replay is thought to be critical for memory consolidation and subsequent spatial navigation. If rest boosts human memory by promoting hippocampal replay/consolidation, then the beneficial effect of rest should extend to complex (hippocampal) memory tasks, for example, tasks probing associations and sequences. We investigated this question via a virtual reality route memory task. Healthy young participants learned two routes to a 100% criterion. One route was followed by a 10-min rest and the other by a 10-min spot the difference game. For each learned route, participants performed four delayed spatial memory tests probing: (i) associative (landmark-direction) memory, (ii) cognitive map formation, (iii) temporal (landmark) order memory, and (iv) route memory. Tests were repeated after 7 days to determine any long-term effects. No effect of rest was detected in the route memory or cognitive map tests, most likely due to ceiling and floor effects, respectively. Rest did, however, boost retention in the associative memory and temporal order memory tests, and this boost remained for at least 7 days. We therefore demonstrate that the benefit of rest extends to (spatial) associative and temporal order memory in humans. We hypothesise that rest allows superior consolidation/hippocampal replay of novel information pertaining to a recently learned route, thus boosting new memories over the long term.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".