The stressed brain: regional and stress‐related corticosterone and stress‐regulated gene expression in the adult zebra finch (<i>Taeniopygia guttata</i>)
Bibliographic record
Abstract
Glucocorticoids (CORT) are well-known as important regulators of behaviour and cognition at basal levels and under stress. However, the precise mechanisms governing CORT action and functional outcomes of this action in the brain remain unclear, particularly in model systems other than rodents. In the present study, we investigated the dynamics of CORT regulation in the zebra finch, an important model system for vocal learning, neuroplasticity and cognition. We tested the hypothesis that CORT is locally regulated in the zebra finch brain by quantifying regional and stress-related variation in total CORT across brain regions. In addition, we used an ex vivo slice culture system to test whether CORT regulates target gene expression uniquely in discrete regions of the brain. We documented a robust increase in brain CORT across regions after 30 minutes of restraint stress but, interestingly, baseline and stress-induced CORT levels varied between regions. In addition, CORT treatment of brain slice cultures differentially affected expression of three CORT target genes: it up-regulated expression of FKBP5 in most regions and SGK1 in the hypothalamus only, whereas GILZ was unaffected by CORT treatment across all brain regions investigated. The specific mechanisms producing regional variation in CORT and CORT-dependent downstream gene expression remain unknown, although these data provide additional support for the hypothesis that the songbird brain employs regulatory mechanisms that result in precise control over the influence of CORT on glucocorticoid-sensitive neural circuits.
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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 | 0.001 |
| 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".