The effects of acute exercise and a nap on heart rate variability and memory in young sedentary adults
Bibliographic record
Abstract
Recent evidence suggests that the autonomic nervous system can contribute to memory consolidation during sleep. Whether fluctuations in cardiac autonomic activity during sleep following physical exercise contribute to the process of memory consolidation has not been studied. We assessed the effects of a non-rapid eye movement (NREM) nap following acute exercise on cardiac autonomic regulation assessed with heart rate variability (HRV) to examine if HRV influences memory processes. Fifty-six (59% female) healthy young adults (23.14 ± 3.74 years) were randomly allocated to either the exercise plus nap (ExNap, n = 27) or nap alone (NoExNap, n = 29) groups. The ExNap group performed a 40-minute moderate-intensity cycling, while the NoExNap group was sedentary prior to learning 45 neutral pictures for a later test. Subsequently, participants underwent a 60-minute NREM nap while measuring EKG, followed by a visual recognition test. Our results indicated that heart rate did not significantly differ between the groups (p = .243), whereas vagally mediated HRV indices were lower in the ExNap group compared to the NoExNap group (p < .05). There were no significant differences in sleep variables between the groups (p > .05). Recognition accuracy was significantly higher in the ExNap group than in the NoExNap group (p = .027). In addition, the recognition accuracy of the ExNap group was negatively associated with vagally mediated HRV (p < .05). Pre-nap acute exercise appears to attenuate parasympathetic activity and to alter the relationship between memory and cardiac autonomic activity.
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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".