Cumulative soccer heading amplifies the effects of brain activity observed during concurrent moderate exercise and continuous performance task in female youth soccer players
Bibliographic record
Abstract
ObjectivesTo determine whether youth female soccer players demonstrate spectral changes in electroencephalogram activity during a continuous performance test, related to cumulative soccer heading at rest and during exercise. ParticipantsTwenty-four female youth soccer players (age: 13.1 ± 0.8 years, mass: 49.5 ± 8.6 kg, height: 1.6 ± 0.1 m). MethodsPlayers completed testing at four time points during the soccer season. The continuous performance test involved players responding to target stimuli or refraining from responding to non-target stimuli. Omission errors (player failed to respond to target stimuli) and commission errors (player responded to non-target stimuli) were assessed for each continuous performance test. Electroencephalogram frequency bandwidths were divided into Theta (4.0–7.9 Hz), Alpha1 (8.0–9.9 Hz), Alpha2 (10.0–12.9 Hz), Beta1 (13.0–17.9 Hz), and Beta2 (18.0–29.9 Hz). Linear mixed-effects modeling was performed on electroencephalogram power at electrode locations Fp1, Fp2, F3, F4, F7, F8, C3, and C4. Participants completed a continuous performance test during rest and moderate exercise. ResultsOmission errors significantly increased during exercise compared to rest at all time points (p < 0.05), but not commission errors. Linear mixed-effects models revealed that there was a statistically significant increase in electroencephalogram power during exercise across all frequency bands (p < 0.05); the number of cumulative headers amplified this difference for Alpha1, Alpha2, and Beta2 (p < 0.05). There were no statistically significant differences between cumulative number of headers and remaining electroencephalogram frequency bands (all p values > 0.05). ConclusionModerate exercise may help to elicit sub-clinical changes in youth female soccer players due to cumulative head impacts, which are not apparent at rest.
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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 | 0.000 | 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".