Oxytocin neurons in the paraventricular nucleus and fear empathy among male mice
Bibliographic record
Abstract
Background: Recent studies have identified empathy deficit as a core impairment and diagnostic criterion for people with autism spectrum disorders; however, the improvement of empathy focuses primarily on behavioural interventions without the target regulation. We sought to compare brain regions associated with empathy-like behaviours of fear and pain, and to explore the role of the oxytocin–oxytocin receptor system in fear empathy. Methods: We used C57BL mice to establish 2 models of fear empathy and pain empathy. We employed immunofluorescence histochemical techniques to observe the expression of c-Fos throughout the entire brain and subsequently quantified the number of c-Fos–positive cells in different brain regions. Furthermore, we employed chemogenetic technology to selectively manipulate these neurons in Oxt-Cre−/+ mice to identify the role of oxytocin in this process. Results: The regions activated by fear empathy were the anterior cingulate cortex, basolateral amygdala, nucleus accumbens, paraventricular nucleus (PVN), lateral habenula, and ventral and dorsal hippocampus. The regions activated by pain empathy were the anterior cingulate cortex, basolateral amygdala, nucleus accumbens, and lateral habenula. We found that increasing the activity of oxytocin neurons in the PVN region enhanced the response to fear empathy. This enhancement may be mediated through oxytocin receptors. Limitations: This study included only male animals, which restricts the broader interpretation of the findings. Further investigations on circuit function need to be conducted. Conclusion: The brain regions implicated in the regulation of fear and pain empathy exhibit distinctions; the activity of PVN neurons was positively correlated with empathic behaviour in mice. These findings highlight the role of the PVN oxytocin pathway in regulating fear empathy and suggest the importance of oxytocin signalling in mediating empathetic responses.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".