Oxytocin-mediated empathy internally facilitates cooperative behaviors in rats
Bibliographic record
Abstract
Reciprocity is considered one of the vital mechanisms that sustain the evolution of cooperative behavior. However, free-riding, where assistance is received but not reciprocated, poses a serious threat to reciprocity behavior, which relies on future payback. Previous theories proposed that third-party punishment plays a vital role in preventing free-riding behavior. However, this external mechanism has inherent limitations, particularly in situations where third parties are absent. Empathy, the ability to perceive and share the emotional states of others, has long been considered a driving force behind prosocial behavior, yet its role in cooperative behavior remains underexplored. In this study, we have designed a new reciprocity paradigm, and demonstrate that rats' reciprocity behavior can stably establish even in the absence of the external mechanisms. Additionally, reciprocity experiences can enhance the empathy of wild type rats, but not oxytocin-deficient rats, towards their partners. Furthermore, oxytocin-deficient rats exhibit more free-riding behaviors. Through fiber photometry recording of oxytocin probe, we found that oxytocin is remarkably released in the orbitofrontal cortex during the reciprocity task, significantly exceeding levels observed in both mutualism and individual tasks. Based on our results, we suggest that oxytocin-mediated empathy enhancement reduces rats' free-riding behavior towards their partners, thereby making reciprocity behavior more stable. This empathy-mediated internal driving force complements the previously proposed external mechanisms, providing new theories and perspectives for understanding the evolution of cooperative behavior.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".