Early life stress modulates amygdala‐prefrontal functional connectivity: Implications for oxytocin effects
Bibliographic record
Abstract
Recent evidence suggests that early life stress (ELS) changes stress reactivity via reduced resting state functional connectivity (rs-FC) between amygdala and the prefrontal cortex. Oxytocin (OXT) modulates amygdala connectivity and attenuates responses to psychosocial stress, but its effect appears to be moderated by ELS. Here we first investigate the effect of ELS on amygdala-prefrontal rs-FC, and examine whether ELS-associated changes of rs-FC in this neural circuit predict its response to psychosocial stress. Secondly, we explore the joint effect of OXT and ELS on the amygdala-prefrontal circuit. Eighteen healthy young males participated in a resting-state fMRI study of OXT effects using a double-blind, randomized, placebo-controlled, within-subject crossover design. We measured the rs-FC to bilateral amygdalae and subsequently assessed changes of state anxiety and prefrontal responses to psychosocial stress. Multiple linear regressions showed that ELS, specifically emotional abuse, predicted reduced rs-FC between the right amygdala and pregenual anterior cingulate cortex (pgACC), which in turn predicted elevated state anxiety after psychosocial stress. In subjects with lower ELS scores, stronger pgACC-amygdala rs-FC predicted stronger pgACC deactivation during the psychosocial stress task, and this rest-task interaction was attenuated by OXT. In subjects with higher ELS scores however, the rest-task interaction was altered and OXT showed no significant effect. These findings highlight that ELS reduces pgACC-amygdala rs-FC and alters how rs-FC of this circuit predicts its stress responsiveness. Such changes in pgACC-amygdala functional dynamics may underlie the altered sensitivity to the effects of OXT after ELS.
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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".