Infants show enhanced neural responses to musical meter frequencies beyond low‐level features
Bibliographic record
Abstract
Music listening often entails spontaneous perception and body movement to a periodic pulse-like meter. There is increasing evidence that this cross-cultural ability relates to neural processes that selectively enhance metric periodicities, even when these periodicities are not prominent in the acoustic stimulus. However, whether these neural processes emerge early in development remains largely unknown. Here, we recorded the electroencephalogram (EEG) of 20 healthy 5- to 6-month-old infants, while they were exposed to two rhythms known to induce the perception of meter consistently across Western adults. One rhythm contained prominent acoustic periodicities corresponding to the meter, whereas the other rhythm did not. Infants showed significantly enhanced representations of meter periodicities in their EEG responses to both rhythms. This effect is unlikely to reflect the tracking of salient acoustic features in the stimulus, as it was observed irrespective of the prominence of meter periodicities in the audio signals. Moreover, as previously observed in adults, the neural enhancement of meter was greater when the rhythm was delivered by low-pitched sounds. Together, these findings indicate that the endogenous enhancement of metric periodicities beyond low-level acoustic features is a neural property that is already present soon after birth. These high-level neural processes could set the stage for internal representations of musical meter that are critical for human movement coordination during rhythmic musical behavior. RESEARCH HIGHLIGHTS: 5- to 6-month-old infants were presented with auditory rhythms that induce the perception of a periodic pulse-like meter in adults. Infants showed selective enhancement of EEG activity at meter-related frequencies irrespective of the prominence of these frequencies in the stimulus. Responses at meter-related frequencies were boosted when the rhythm was conveyed by bass sounds. High-level neural processes that transform rhythmic auditory stimuli into internal meter templates emerge early after birth.
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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) | 0.002 | 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".