Acute exercise and motor memory consolidation: Does exercise type play a role?
Bibliographic record
Abstract
A single bout of high-intensity exercise can augment off-line gains in skills acquired during motor practice. It is currently unknown if the type of physical exercise influences the effect on motor skill consolidation. This study investigated the effect of three types of high-intensity exercise following visuomotor skill acquisition on the retention of motor memory in 40 young (25.3 ±3.6 years), able-bodied male participants randomly assigned to one of four groups either performing strength training (STR), circuit training (CT), indoor hockey (HOC) or rest (CON). Retention tests of the motor skill were performed 1 (R1h) and 24 h (R1d) post acquisition. For all exercise groups, mean motor performance scores decreased at R1h compared to post acquisition (POST) level; STR (P = 0.018), CT (P = 0.02), HOC (P = 0.014) and performance scores decreased for CT compared to CON (P = 0.049). Mean performance scores increased from POST to R1d for all exercise groups; STR (P = 0.010), CT (P = 0.020), HOC (P = 0.007) while performance scores for CON decreased (P = 0.043). Changes in motor performance were thus greater for STR (P = 0.006), CT (P < 0.001) and HOC (P < 0.001) compared to CON from POST to R1d. The results demonstrate that high-intensity, acute exercise can lead to a decrease in motor performance assessed shortly after motor skill practice (R1h), but enhances offline effects promoting long-term retention (R1d). Given that different exercise modalities produced similar positive off-line effects on motor memory, we conclude that exercise-induced effects beneficial to consolidation appear to depend primarily on the physiological stimulus rather than type of exercise and movements employed.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".