Social experiences shape song preference learning independent of developmental exposure to song
Bibliographic record
Abstract
Communication governs the formation and maintenance of social relationships. The interpretation of communication signals depends not only on the signal’s content, but also on a receiver’s individual experience. Experiences throughout life may interact to affect behavioral plasticity, such that a lack of developmental sensory exposure could constrain adult learning, while salient adult social experiences could remedy developmental deficits. We investigated how experiences impact the formation and direction of female auditory preferences in the zebra finch. Zebra finches form long-lasting pair bonds and females learn preferences for their mate’s vocalizations. We found that after two weeks of cohabitation with a male, females formed pair bonds and learned to prefer their partner’s song regardless of whether they were reared with (“normally-reared”) or without (“song-naïve”) developmental exposure to song. In contrast, females that heard but did not physically interact with a male did not prefer his song. In addition, previous work has found that song-naive females do not show species-typical preferences for courtship song. We found that cohabitation with a male ameliorated this difference in preference. Thus, courtship and pair bonding, but not acoustic-only interactions, strongly influence preference learning regardless of rearing experience, and may dynamically drive auditory plasticity for recognition and preference.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.040 |
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".