Can transcranial direct current stimulation (tDCS) over the motor cortex increase endurance running performance? a randomized crossover-controlled trial
Bibliographic record
Abstract
Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, has been shown to increase exercise performance in strength and cycling studies but its effects on running endurance remain unclear. The objectives of this randomized sham-controlled crossover trial were to assess tDCS efficacy on submaximal treadmill running time to exhaustion (TTE). Forty-five healthy male runners aged between 18 and 32 years (mean maximal oxygen consumption: 46.6 mL/min/kg) performed two constant-load tests at 90% of their maximal aerobic speed preceded by 20 minutes of active or sham multichannel (5 anodes, 3 cathodes) tDCS applied over the bilateral motor cortex with a total intensity of 4 mA. Ratings of perceived exertion (RPE), blood lactate, VO2, and heart rate were monitored every five minutes until volitional exhaustion. The median [IQR] TTE was similar following active (12.2 [10.5, 16.1] minutes) or sham (12.5 [10.2, 15.1] minutes) tDCS (p = 0.96). Likewise, there were no significant differences between active and sham conditions for RPE, blood lactate, final VO2, and final heart rate (all p ≥0.05). No difference in TTE was found when stratifying groups according to their VO2max (i.e., VO2max ≥ 45 mL/min/Kg, p = 0.53; VO2max < 45 mL/min/Kg, p = 0.45) but there was a trend for a significant correlation between VO2max and change in TTE (p = 0.06). TDCS applied over the bilateral motor cortex did not improve endurance performance in a large sample of trained runners. Characterization of individual tDCS responsiveness deserves further consideration. In our experimental conditions, tDCS had no ergogenic effect on endurance running performance. Trial registration: Clinical trial registration: NCT04005846.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".