Changes in the density of stage 2 sleep spindles following motor learning in young and older adults
Bibliographic record
Abstract
The purpose of this study was to compare the changes that occur in sleep architecture following the acquisition of a simple motor learning task in young and older adults. Subjects included 14 young (range = 17-24 years) and 14 older (range = 62-79 years) adults, all of whom were in good health. Using in-home recording systems, sleep architecture (sleep stages and the density of Stage 2 sleep spindles) was examined before and after learning the pursuit rotor. To control for possible age differences in baseline motor performance and spindle density, both absolute and relative (percent change) measures were examined. Both groups improved significantly on the pursuit rotor task at Retest (1 week later); however, the magnitude of absolute improvement was larger in the young group than in the older group. There was no group difference when a relative measure of improvement (percent increase across sessions) was used. The density of Stage 2 sleep spindles increased significantly following task Acquisition in the young group but not in the older group. These age differences failed to reach significance when change was measured as a percentage of baseline level of spindle density. The increase in spindle density was correlated with performance level during acquisition in the young group but not the older group. The results of the present study are largely consistent with previous studies on sleep and memory in young adults and suggest that more detailed examination of this relationship in older adults is warranted.
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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 | 0.001 |
| 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) | 0.001 | 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".