Short-Term Longitudinal Changes In Event-Related Potentials In Youth And High School Football Players
Bibliographic record
Abstract
Tackle football is a contact-collision sport that predisposes players to brain injury. While concussion is a primary safety concern in tackle football, repetitive head impacts (RHI) are more pervasive and have poorly understood, and potentially deleterious, effects. RHI are often asymptomatic, making them difficult to detect; thus, there is a need for sensitive tests that can evaluate the impact of RHI on brain health. Electrophysiologic event-related potentials (ERPs) provide rapid, objective measures of specific brain responses, making them appealing brain health biomarkers. PURPOSE: Examine the amplitude and latency of three well-established ERPs in youth and high school football players. METHODS: ERPs of 29 tackle football players (14.7 ± 2.1 yr) were captured at baseline (pre-season), post-season, and six-months post-season using a g. Nautilus EEG cap (Gtec Medical Engineering, Austria) with three electrodes (Fz, Cz, and Pz) while subjects listened to an auditory stimulus (~6 min). ERPs corresponding to auditory sensation (N100), basic attention (P300), and cognitive processing (N400) were identified and processed (NeuroCatch, Surrey, BC, Canada). Mixed models were used to determine the effect of days since baseline on ERP amplitude and latency. Concussion history was a fixed effect, and subject ID was a random effect. All models were analyzed via ANOVA. RESULTS: Concussion history did not affect any ERP amplitude (N100: F1,44 = 2.37, p = 0.130; P300: F1,44 < 0.01, p = 0.976; N400: F1,44 = 0.05, p = 0.828) or latency (N100: F1,44 = 0.06, p = 0.801; P300: F1,44 < 0.01, p = 0.978; N400: F1,44 = 0.31, p = 0.580). N100 amplitude (F1,44 = 0.08, p = 0.776) and latency (F1,44 = 1.93, p = 0.172), P300 amplitude (F1,44 = 0.16, p = 0.688) and latency (F1,44 = 1.90, p = 0.175), and N400 latency (F1,44 = 1.97, p = 0.168) did not change over time. However, N400 amplitude (F1,44 = 5.38, p = 0.025) decreased as more days passed from baseline. CONCLUSION: Cognitive processing biomarker N400 amplitude decreased after a single season of youth and high school football, whereas other ERPs did not change over time. These findings indicate that youth and high school football players may experience subclinical changes in brain health with football participation, and that ERPs could serve as a useful biomarker for evaluating these changes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".