Neural Correlates of Stress Recovery in a Positive Emotional Context
Bibliographic record
Abstract
Despite accruing evidence showing that positive emotions facilitate stress recovery, the neural basis for this effect remains unclear. To identify the mechanism underlying the beneficial effects from positive emotions on stress recovery, we compared stress recovery for people reflecting on a stressor while in a positive emotional context with that for people in a neutral context. We first conducted a behavioral pilot (n = 89), then recruited healthy community participants (n = 50) to complete the study in the MRI scanner. In the study, the participants did a stressful anagram task followed by a recovery period when they reflected on the stressor and watched a positive or neutral emotion inducing video. Participants reported in the moment pleasant and unpleasant mood ratings, and thoughts and personality data in retrospect. In addition to examining the between group differences in stress recovery based on the emotional context assignment, we also investigated how changes in positive mood correlated with neural activation changes to the stressor. We found evidence for positive emotions facilitating negative emotion recovery through enhancing cognitive control (decentering thoughts) and providing positive contextual information (positive video thoughts). Positive video thoughts also correlated with stronger vmPFC activation during stress recovery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".