64 (11B) Neurological processing is depressed following downhill mountain bike racing in youth
Bibliographic record
Abstract
Background There is growing concern regarding neurological impairment associated with accumulation of non-concussive head acceleration events in sport, particularly during periods of neurological vulnerability, such as adolescence. A season of collision-sport exposure reduces cognitive processing performance in uninjured adolescent hockey and football players, approximated by the N400 Event Related Potential (ERP), but these results have not been confirmed in other sports.Purpose To investigate the association between a downhill mountain bike racing competition and sensory (N100), attentional (P300), and cognitive/sematic (N400) processing in youth by examining pre- to post-competition ERPs.Methods This prospective cohort study recruited youth (age 15–24) competing in the 2024 Whistler Crankworx downhill mountain biking competition. Benchmark ERP neurological processing assessment was collected pre-competition and during serial measures collected following each day of racing (up to 5 days).Results Fifteen youth downhill mountain bikers (6 female, 9 male) contributed 37 observations at pre- and post-competition. Mean N400 amplitude was 3.41μV (95% CI:2.91,3.90). A conditional linear regression model demonstrated a mean marginal difference in N400 amplitude from pre- to post-event of 1.26μV (95% CI:-2.16,-0.36; p=0.006). N400 latency, P300 amplitude and latency, and N100 amplitude and latency were unchanged by downhill mountain biking (all p>0.26).Conclusion Consistent with studies in ice hockey and football, our results demonstrated acute impairment in N400 cognitive neurological processing following a downhill mountain biking event. Future research is needed to elucidate the acute effects of exercise and concentration which may confound the relationship between sport-related repetitive head acceleration events and event related potential outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".