Oxytocin and vasopressin: linking pituitary neuropeptides and their receptors to social neurocircuits
Bibliographic record
Abstract
Oxytocin and vasopressin are pituitary neuropeptides that have been shown to affect social processes in mammals. There is growing interest in these molecules and their receptors as potential precipitants of, and/or treatments for, social deficits in neurodevelopmental disorders, including autism spectrum disorder. Numerous behavioral-genetic studies suggest that there is an association between these peptides and individual social abilities; however, an explanatory model that links hormonal activity at the receptor level to complex human behavior remains elusive. The following review summarizes the known associations between the oxytocin and vasopressin neuropeptide systems and social neurocircuits in the brain. Following a micro- to macro- level trajectory, current literature on the synthesis and secretion of these peptides, and the structure, function and distribution of their respective receptors is first surveyed. Next, current models regarding the mechanism of action of these peptides on microcircuitry and other neurotransmitter systems are discussed. Functional neuroimaging evidence on the acute effects of exogenous administration of these peptides on brain activity is then reviewed. Overall, a model in which the local neuromodulatory effects of pituitary neuropeptides on brainstem and basal forebrain regions strengthen signaling within social neurocircuits proves appealing. However, these findings are derived from animal models; more research is needed to clarify the relevance of these mechanisms to human behavior and treatment of social deficits in neuropsychiatric disorders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".