Does Cardiorespiratory Fitness Protect Memory from Sleep Deprivation?
Bibliographic record
Abstract
INTRODUCTION: Animal studies have demonstrated that physical exercise can protect memory from the effects of sleep deprivation (SD). We examined whether having a high cardiorespiratory fitness (V̇O 2peak ) is associated with an enhanced capacity to encode episodic memory after one night of SD. METHODS: Twenty-nine healthy young participants were allocated into either an SD group ( n = 19) that underwent 30 h of uninterrupted wakefulness, or a sleep control (SC) group ( n = 10) that followed a regular sleep routine. Following either the SD or SC period, participants were asked to view 150 images as the encoding part of the episodic memory task. Ninety-six hours after viewing the images, participants returned to the laboratory to perform the recognition part of the episodic memory task, which required the visual discrimination of the 150 images previously presented from 75 new images introduced as distractors. Cardiorespiratory fitness (V̇O 2peak ) was assessed with a bike ergometer graded exercise test. Group differences in memory performance were assessed with independent t tests and associations between V̇O 2peak and memory with multiple linear regression. RESULTS: The SD group showed a significant increase in subjective fatigue (mean difference [MD] [standard error {SE}] = 38.94 [8.82]; P = 0.0001) and a worse capacity to identify the original 150 images (MD [SE] = -0.18 [0.06]; P = 0.005) and discriminate them from distractors (MD [SE] = -0.78 [0.21] P = 0.001). When adjusted for fatigue, higher V̇O 2peak was significantly associated with better memory scores in the SD (R 2 = 0.41; β [SE] = 0.03 [0.01]; P = 0.015) but not in the SC group ( R2 = 0.23; β [SE] = 0.02 [0.03]; P = 0.408). CONCLUSIONS: These results confirm that SD before encoding impairs the capacity to create robust episodic memories and provide preliminary support to the hypothesis that maintaining high levels of cardiorespiratory fitness could have a protective effect against the disruptive effects of sleep loss on memory.
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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 | 0.000 |
| 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) | 0.002 | 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".