Oxytocin neurons signal state-dependent transitions from rest to thermogenesis and behavioral arousal in social and non-social settings
Bibliographic record
Abstract
Abstract Core body temperature (Tb) is defended within narrow limits through thermoregulatory behaviors like huddling, nesting, and physical activity as well as autonomic responses like brown fat thermogenesis. While Tb displays regulated fluctuations across different behavioral states and rest/arousal cycles, the neural control of these transitions is poorly understood. Here, we investigate the relationship between oxytocin neurons of the paraventricular hypothalamus (PVN OT ) and behavioral and autonomic thermoeffector pathways across physiological states in mice. First, we show that PVN OT neurons are activated during social thermoregulation. We then demonstrate that in vivo PVN OT calcium dynamics align with transitions from rest to thermogenesis and behavioral arousal. Counter to our initial hypothesis, these dynamics were observed in both social and non-social contexts. Using a computer vision model to track thermoeffector pathways, we demonstrate that precisely timed stimulation of PVN OT neurons during low-Tb resting states increases thermogenesis followed by behavioral arousal. We therefore suggest a model in which PVN OT neurons facilitate homeostatic state-dependent transitions in thermo-behavioral states.
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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".