Microelectrode recordings from the human cervical vagus nerve during maximal breath‐holds
Bibliographic record
Abstract
Voluntary breath-holds can be sustained for a long time following training, but ultimately, regardless of duration, the asphyxic break-point is reached and the apnoea terminated. The physiological changes occurring during the apnoea include a marked increase in sympathetically-mediated vasoconstriction in non-essential organs, such as skeletal muscle, spleen and kidney, while the brain is protected by a marked increase in perfusion. What is not understood is what happens to cardiac vagal activity. Here, we performed microelectrode recordings from the right cervical vagus nerve in healthy participants [both trained breath-hold divers (n = 10) and untrained controls (n = 10)] during tidal breathing, slow-deep breathing, an inspiratory-capacity apnoea and an end-expiratory apnoea. Using cross-correlation analysis of multi-unit neural activity, we tested the hypothesis that breath-hold divers would have greater cardiac modulation of vagal activity, which primarily reflects the discharge of cardiac afferents, particularly during a maximal apnoea. We showed that there were no differences in cardiac modulation of vagus nerve activity either during tidal breathing or during any of the respiratory manoeuvres, nor was there a difference in cardiac modulation during the static phase of a maximal apnoea or when involuntary breathing movements occurred before reaching the asphyxic break-point. We conclude that changes in vagal sensory inputs from the heart are not responsible for the marked tolerance to asphyxia shown by breath-hold divers.
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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) | 0.001 | 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".