Listening to the Brainstem: Musicianship Enhances Intelligibility of Subcortical Representations for Speech
Bibliographic record
Abstract
Auditory experiences including musicianship and bilingualism have been shown to enhance subcortical speech encoding operating below conscious awareness. Yet, the behavioral consequence of such enhanced subcortical auditory processing remains undetermined. Exploiting their remarkable fidelity, we examined the intelligibility of auditory playbacks (i.e., "sonifications") of brainstem potentials recorded in human listeners. We found naive listeners' behavioral classification of sonifications was faster and more categorical when evaluating brain responses recorded in individuals with extensive musical training versus those recorded in nonmusicians. These results reveal stronger behaviorally relevant speech cues in musicians' neural representations and demonstrate causal evidence that superior subcortical processing creates a more comprehensible speech signal (i.e., to naive listeners). We infer that neural sonifications of speech-evoked brainstem responses could be used in the early detection of speech-language impairments due to neurodegenerative disorders, or in objectively measuring individual differences in speech reception solely by listening to individuals' brain activity.
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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) | 0.004 | 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".