Plasticity after perceptual narrowing for voice perception: reinstating the ability to discriminate monkeys by their voices at 12 months of age
Bibliographic record
Abstract
Differentiating individuals by their voice is an important social skill for infants to acquire. In a previous study, we demonstrated that the ability to discriminate individuals by voice follows a pattern of perceptual narrowing (Friendly et al., 2013). Specifically, we found that the ability to discriminate between two foreign-species (rhesus monkey) voices decreased significantly between 6 and 12 months of age. Also during this period, there was a trend for the ability to discriminate human voices to increase. Here we investigate the extent to which plasticity remains at 12 months, after perceptual narrowing has occurred. We found that 12-month-olds who received 2 weeks of monkey-voice training were significantly better at discriminating between rhesus monkey voices than untrained 12-month-olds. Furthermore, discrimination was reinstated to a level slightly better than that of untrained 6-month-olds, suggesting that voice-processing abilities remain considerably plastic at the end of the first year.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".