Oxytocin enhances basolateral amygdala activation and functional connectivity in autistic women while processing emotional faces
Bibliographic record
Abstract
Background: Oxytocin is hypothesized to promote positive social interactions by enhancing the salience of social stimuli, which may be reflected by altered amygdala activation. While previous neuroimaging studies have reported that oxytocin enhances amygdala activation to emotional face stimuli in autistic men, effects in autistic women remain unclear. Methods: The influence of intranasal oxytocin on neural response to emotional faces vs. shapes were tested in 16 autistic and 21 non-autistic women by fMRI in a placebo-controlled, within-subjects, cross-over design. Effects of group (autistic vs. non-autistic) and drug condition (oxytocin vs. placebo) on the activation and functional connectivity of the basolateral amygdala, the brain’s “salience detector”, were assessed. Relationships between individual differences in autistic-like traits, social anxiety, salivary oxytocin levels, and amygdala activation were also explored.Results: Autistic and non-autistic women showed minimal activation differences in the placebo condition. Significant drug × group interactions were observed for both amygdala activation and functional connectivity. Oxytocin increased left basolateral amygdala activation among autistic women (35 voxel cluster, MNI coordinates of peak voxel = -22 -10 -28; mean change=+0.079%, t=3.159, ptukey=0.0166), but not non-autistic women (mean change =+0.003%, t=0.153, ptukey=0.999). Furthermore, oxytocin increased functional connectivity of the right basolateral amygdala with brain regions associated with socio-emotional information processing in autistic women, but not non-autistic women, thereby attenuating group connectivity differences observed in the placebo condition. Conclusions: This work demonstrates that intranasal oxytocin increases basolateral amygdala activation and connectivity in autistic women while processing emotional faces, which extends and specifies previous findings in autistic men.
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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) | 0.002 | 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".