Effects of early song experience on song preferences and song control and auditory brain regions in female house finches (<i>Carpodacus mexicanus</i>)
Bibliographic record
Abstract
We examined the effects of song tutoring on adult song preferences, volume of song-control brain regions, and activity of auditory brain regions in female house finches (Carpodacus mexicanus). Hand-reared females were tutored with local songs, foreign songs, or no song. We then examined adult song preferences, determined the Nissl-defined volume of the song-control nuclei HVc, Area X, and RA, and compared the number of cells immunoreactive for Zenk protein in the auditory regions NCM and cmHV, following playback of songs heard early in life (Tutor/Playback Match) versus not heard (Tutor/Playback Nonmatch). All hand-reared birds exhibited preferences for locally recorded song over foreign or heterospecific song. We found no difference in the volume of song-control nuclei among the three groups. As well, we found no difference in the number of Zenk immunoreactive cells in NCM and cmHV between females in the Tutor/Playback Match group and females in the Tutor/Playback Nonmatch group. Isolate-reared birds showed greater Zenk immunoreactivity following song playback than either tutored group. Thus, early auditory experience may not play a role in adult geographic song preferences, suggesting that genetic factors can lead to preferences for songs of local dialects. Song tutoring did not influence the size of song-control regions nor Zenk induction levels following song playback, suggesting that early experience with particular songs does not influence Zenk expression. However, overall greater activation in isolate females in auditory areas suggests that exposure to song early in life may increase the selectivity of Zenk activation to song playback in auditory areas.
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 | 0.000 | 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) | 0.002 | 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".