Passive exercise increases cerebral blood flow velocity and supports a postexercise executive function benefit
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Executive function entails high‐level cognitive control supporting activities of daily living. Literature has shown that a single‐bout of exercise involving volitional muscle activation (i.e., active exercise) improves executive function and that an increase in cerebral blood flow (CBF) may contribute to this benefit. It is, however, unknown whether non‐volitional exercise (i.e., passive exercise) wherein an individual's limbs are moved via an external force elicits a similar executive function benefit. This is a salient question given that proprioceptive and feedforward drive from passive exercise increases CBF independent of the metabolic demands of active exercise. Here, in a procedural validation participants ( n = 2) used a cycle ergometer to complete separate 20‐min active and passive (via mechanically driven flywheel) exercise conditions and a non‐exercise control condition. Electromyography showed that passive exercise did not increase agonist muscle activation or increase ventilation or gas exchange variables (i.e., V̇O 2 and V̇CO 2 ). In a main experiment participants ( n = 28) completed the same exercise and control conditions and transcranial Doppler ultrasound showed that active and passive exercise (but not the control condition) increased CBF through the middle cerebral artery ( p s <.001); albeit the magnitude was less during passive exercise. Notably, antisaccade reaction times prior to and immediately after each condition showed that active ( p < .001) and passive ( p = .034) exercise improved an oculomotor‐based measure of executive function, whereas no benefit was observed in the control condition ( p = .85). Accordingly, results evince that passive exercise ‘boosts’ an oculomotor‐based measure of executive function and supports convergent evidence that increased CBF mediates this benefit.
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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 | 0.000 |
| 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) | 0.001 | 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 it