A Role for Nonapeptides and Dopamine in Nest‐Building Behaviour
Bibliographic record
Abstract
During nest building in zebra finches (Taeniopygia guttata), several regions in the social behaviour network and the dopaminergic reward system, which are two neural circuits involved in social behaviour, appear to be active in male and female nest-building finches. Because the nonapeptides, mesotocin and vasotocin and the neurotransmitter, dopamine, play important roles in avian social behaviour, we tested the hypothesis that mesotocinergic-vasotocinergic and dopaminergic neuronal populations in the social behaviour network and dopaminergic reward system, respectively, are active during nest building. We combined immunohistochemistry for Fos (an indirect marker of neuronal activity) and vasotocin, mesotocin or tyrosine hydroxylase on brain tissue from nest-building and non-nest-building male and female zebra finches and compared Fos immunoreactivity in these neuronal populations with the variation in nest-building behaviour. Fos immunoreactivity in all three types of neuronal populations increased with some aspect of nest building: (i) higher immunoreactivity in a mesotocinergic neuronal population of nest-building finches compared to controls; (ii) increased immunoreactivity in the vasotocinergic neuronal populations in relation to the amount of material picked up by nest-building males and the length of time that a male spent in the nest with his mate; and (iii) increased immunoreactivity in a dopaminergic neuronal population in relation to the length of time that a male nest-building finch spent in the nest with his mate. Taken together, these findings provide evidence for a role of the mesotocinergic-vasotocinergic and dopaminergic systems in avian nest building.
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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".