Athleticism and sex impact neural processing of sound
Bibliographic record
Abstract
Biology and experience both influence the auditory brain. Sex is one biological factor with pervasive effects on auditory processing. Females process sounds faster and more robustly than males. These differences are linked to hormone differences between the sexes. Athleticism is an experiential factor known to reduce ongoing neural noise, but whether it influences how sounds are processed by the brain is unknown. Furthermore, it is unknown whether sports participation influences auditory processing differently in males and females, given the well-documented sex differences in auditory processing seen in the general population. We hypothesized that athleticism enhances auditory processing and that these enhancements are greater in females. To test these hypotheses, we measured auditory processing in collegiate Division I male and female student-athletes and their non-athlete peers (total n = 1012) using the frequency-following response (FFR). The FFR is a neurophysiological response to sound that reflects the processing of discrete sound features. We measured across-trial consistency of the response in addition to fundamental frequency (F0) and harmonic encoding. We found that athletes had enhanced encoding of the harmonics, which was greatest in the female athletes, and that athletes had more consistent responses than non-athletes. In contrast, F0 encoding was reduced in athletes. The harmonic-encoding advantage in female athletes aligns with previous work linking harmonic encoding strength to female hormone levels and studies showing estrogen as mediating athlete sex differences in other sensory domains. Lastly, persistent deficits in auditory processing from previous concussive and repetitive subconcussive head trauma may underlie the reduced F0 encoding in athletes, as poor F0 encoding is a hallmark of concussion injury.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".