Development of Simultaneous Pitch Encoding: Infants Show a High Voice Superiority Effect
Bibliographic record
Abstract
Infants must learn to make sense of real-world auditory environments containing simultaneous and overlapping sounds. In adults, event-related potential studies have demonstrated the existence of separate preattentive memory traces for concurrent note sequences and revealed perceptual dominance for encoding of the voice with higher fundamental frequency of 2 simultaneous tones or melodies. Here, we presented 2 simultaneous streams of notes (15 semitones apart) to 7-month-old infants. On 50% of trials, either the higher or the lower note was modified by one semitone, up or down, leaving 50% standard trials. Infants showed mismatch negativity (MMN) to changes in both voices, indicating separate memory traces for each voice. Furthermore, MMN was earlier and larger for the higher voice as in adults. When in the context of a second voice, representation of the lower voice was decreased and that of the higher voice increased compared with when each voice was presented alone. Additionally, correlations between MMN amplitude and amount of weekly music listening suggest that experience affects the development of auditory memory. In sum, the ability to process simultaneous pitches and the dominance of the highest voice emerge early during infancy and are likely important for the perceptual organization of sound in realistic environments.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".