Early auditory and adult mating experiences interact with singer identity to shape neural responses to song in female zebra finches
Bibliographic record
Abstract
ABSTRACT Social and sensory experiences across the lifespan can shape social interactions, however, experience-dependent plasticity is widely studied within discrete life stages. In the socially monogamous zebra finch, in which females use learned vocal signals to identify individuals and form long-lasting pair bonds, developmental exposure to song is key for females to show species-typical song perception and preferences. While adult mating experience can still lead to pair-bonding and song preference learning even in birds with limited previous song exposure (“song-naïve”), whether similarities in adult behavioral plasticity between normally-reared and song-naïve females reflect convergent patterns of neural activity is unknown. We investigated this using expression of a marker of neural activity and plasticity (phosphorylated S6) in mated normally-reared and song-naïve females in response to song from either their mate, a neighbor, or an unfamiliar male. We found that, in portions of a secondary auditory region (the caudomedial nidopallium NCM) and in dopaminergic neurons of the caudal ventral tegmental area, hearing the mate’s song significantly increased pS6 expression in females from both rearing conditions. In contrast, within other NCM subregions, song-identity drove different patterns of pS6 expression depending on the rearing condition. These data suggest that developmental experiences can have long-lasting impacts on the neural signatures of behaviors acquired in adulthood and that socially-driven behavioral plasticity in adults may arise through both shared and divergent neural circuits depending on an individual’s developmental experiences.
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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 | 0.000 |
| 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) | 0.001 | 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".