Large-scale multi-site study shows no association between musical training and early auditory neural sound encoding
Bibliographic record
Abstract
Musical training has been reported to be associated with enhanced neural processing of sounds, as measured via the frequency following response (FFR), implying the potential for human subcortical neural plasticity. We conducted a large-scale multi-site preregistered study (n > 260) to replicate and extend the findings underpinning this important relationship. We failed to replicate any of the major findings selected for replication that were published previously in smaller studies. Musical training was not associated with enhanced neural encoding strength of a speech stimulus (/da/) in babble, whether measured via the spectral or temporal representations of the FFR. Similarly, the strength of neural tracking of a speech sound with a dynamic pitch trajectory was not related to either years of musical training or age of onset of musical training. Our findings provide no evidence for associations between early auditory neural responses and either musical training or musical ability. Widely cited studies have claimed that musical training is associated with enhanced neural encoding for sound at early stages of the auditory system. Results from this large-scale multisite study do not support this earlier claim.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".