Oxytocin-Dopamine Interactions Mediate Variations in Maternal Behavior in the Rat
Bibliographic record
Abstract
Variations in maternal behavior among lactating rats associate with differences in estrogen-oxytocin interactions in the medial preoptic area (mPOA) and in dopamine levels in the nucleus accumbens (nAcc). Thus, stable, individual differences in pup licking/grooming (LG) are abolished by oxytocin receptor blockade or treatments that eliminate differences in the nAcc dopamine signal. We provide novel evidence for a direct effect of oxytocin at the level of the ventral tegmental area (VTA) in the regulation of nAcc dopamine levels. Mothers that exhibit consistently increased pup LG (i.e. high LG mothers) by comparison with low LG mothers show increased oxytocin expression in the mPOA and the paraventricular nucleus of the hypothalamus and increased projections of oxytocin-positive cells from both mPOA and paraventricular nucleus of the hypothalamus to the VTA. Direct infusion of oxytocin into the VTA increased the dopamine signal in the nAcc. Finally, high compared with low LG mothers show greater increases in dopamine signal in the nAcc during bouts of pup LG, and this difference is abolished with infusions of an oxytocin receptor antagonist directly into the VTA. These studies reveal a direct effect of oxytocin on dopamine release within the mesocorticolimbic dopamine system and are consistent with previous reports of oxytocin-dopamine interactions in the establishment and maintenance of social bonds.
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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".