Preprint: Selection of high-trait emotivity affects the volume of sensory and emotional-related brain regions in male Japanese quails
Bibliographic record
Abstract
Abstract Japanese quails (Coturnix japonica) divergently selected based on their behavior during a tonic immobility test are an excellent model to study the link between brain morphology and behavior expression. The LTI (Long Tonic Immobility) and STI (Short Tonic Immobility) quail lines differ in their level of emotivity, with LTI quails being selected for their high-trait emotivity. Here, comparing the brain regions of the LTI and STI lines of male Japanese quails, we test the hypothesis that this divergent selection could have influenced brain anatomy, in particular, those regions involved in sensory and emotional processing. The heads of twenty, 10 weeks old male Japanese quails (10 STI and 10 LTI) were imaged ex-vivo using ultra high-resolution (11.7 Tesla) magnetic resonance imaging. The resulting images were used to create a population-averaged quail brain template and manually segmented 3D whole-brain atlas (openly available: https://doi.org/10.5281/zenodo.4700522). The atlas is composed of 191 brain regions, the ventricular system, pineal and pituitary glands. Thanks to this atlas, an exploratory analysis was conducted to compare brain regions between the two lines: the relative volumes of 33 regions were impacted (with 24 larger relative volumes being found in STI). This demonstrates for the first time in male Japanese quail that genetic selection for a specific emotional behavior (tonic immobility) modifies the anatomy of brain regions involved in sensory and emotional processing.
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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) | 0.004 | 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".