Fatigue-related impairments in oculomotor control are prevented by norepinephrine-dopamine reuptake inhibition
Bibliographic record
Abstract
Fatigue-induced reductions in saccade velocity have been reported following acute, prolonged exercise. Interestingly, the detrimental impact of fatigue on oculomotor control can be prevented by a moderate dose of caffeine. This effect may be related to central catecholamine upregulation via caffeine's action as an adenosine antagonist. To test this hypothesis, we compared the protective effect of caffeine on oculomotor control post-exercise to that of a norepinephrine-dopamine reuptake inhibitor. Within a placebo-controlled crossover design, 12 cyclists consumed placebo, caffeine or a norepinephrine-dopamine reuptake inhibitor (bupropion) during 180 minutes of stationary cycling. Saccades, smooth pursuit and optokinetic nystagmus were measured using infrared oculography. Exercise fatigue was associated with an 8 ± 11% reduction in the peak velocity of prosaccades, and a 10 ± 11% decrement in antisaccade peak velocity. Optokinetic nystagmus quick phases decreased in velocity by 15 ± 17%. These differences were statistically significant (p < 0.05). Norepinephrine-dopamine reuptake inhibition and caffeine prevented fatigue-related decrements in eye movement velocity. Pursuit eye movements and visual attention were unaffected. These findings show that norepinephrine-dopamine reuptake inhibition protects oculomotor function during exercise fatigue. Caffeine's fatigue-reversing effects on eye movements appear to be mediated, at least in part, via modulation of central catecholamines.
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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".