Does Sleep Promote Motor Learning? Implications for Physical Rehabilitation
Bibliographic record
Abstract
Sleep following motor skill practice has repeatedly been demonstrated to enhance motor skill learning off-line (continued overnight improvements in motor skill that are not associated with additional physical practice) for young people who are healthy. Mounting evidence suggests that older people who are healthy fail to demonstrate sleep-dependent off-line motor learning. However, little is known regarding the influence of sleep on motor skill enhancement following damage to the brain. Emerging evidence suggests that individuals with brain damage, particularly following stroke, do benefit from sleep to promote off-line motor skill learning. Because rehabilitation following stroke requires learning new, and re-learning old, motor skills, awareness that individuals with stroke benefit from a period of sleep following motor skill practice to enhance skill learning could affect physical therapist practice. The objective of this article is to present the evidence demonstrating sleep-dependent off-line motor learning in young people who are healthy and the variables that may influence this beneficial sleep-dependent skill enhancement. In young people who are healthy, these variables include the stages of memory formation, the type of memory, the type of instruction provided (implicit versus explicit learning), and the task utilized. The neural mechanisms thought to be associated with sleep-dependent off-line motor learning also are considered. Research examining whether older adults who are healthy show the same benefits of sleep as do younger adults is discussed. The data suggest that older adults who are healthy do not benefit from sleep to promote off-line skill enhancement. A possible explanation for the apparent lack of sleep-dependent off-line motor learning by older adults who are healthy is presented. Last, emerging evidence showing that individuals with chronic stroke demonstrate sleep-dependent off-line motor skill learning and some of the possible mechanisms for this effect are considered.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".