Development of Auditory Phase-Locked Activity for Music Sounds
Bibliographic record
Abstract
The auditory cortex undergoes functional and anatomical development that reflects specialization for learned sounds. In humans, auditory maturation is evident in transient auditory-evoked potentials (AEPs) elicited by speech or music. However, neural oscillations at specific frequencies are also known to play an important role in perceptual processing. We hypothesized that, if oscillatory activity in different frequency bands reflects different aspects of sound processing, the development of phase-locking to stimulus attributes at these frequencies may have different trajectories. We examined the development of phase-locking of oscillatory responses to music sounds and to pure tones matched to the fundamental frequency of the music sounds. Phase-locking for theta (4-8 Hz), alpha (8-14 Hz), lower-to-mid beta (14-25 Hz), and upper-beta and gamma (25-70 Hz) bands strengthened with age. Phase-locking in the upper-beta and gamma range matured later than in lower frequencies and was stronger for music sounds than for pure tones, likely reflecting the maturation of neural networks that code spectral complexity. Phase-locking for theta, alpha, and lower-to-mid beta was sensitive to temporal onset (rise time) sound characteristics. The data were also consistent with phase-locked oscillatory effects of acoustic (spectrotemporal) complexity and timbre familiarity. Future studies are called for to evaluate developmental trajectories for oscillatory activity, using stimuli selected to address hypotheses related to familiarity and spectral and temporal encoding suggested by the current findings.
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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 | 0.000 | 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".