Buffering effects of amusement and awe on stress responses: Behavioral, physiological, and neural response
Bibliographic record
Abstract
The experience of positive emotions plays a crucial role in promoting mental and physical health. Laboratory studies have suggested that induced positive emotions facilitate stress recovery. However, how recovery from stress by discrete positive emotions temporally changes in psychological and physiological measurements, and what neural mechanisms underlie these processes remains unclear. Therefore, we investigated the buffering effects of amusement and awe on stress responses from psychological, physiological, and neural perspectives using photoplethysmography and functional magnetic resonance imaging (fMRI). Sixty-seven college students completed the Montreal Imaging Stress Task and viewed emotion-inducing videos designed to elicit amusement, awe, or neutral emotional states inside an MRI scanner. Our findings demonstrate that amusement and awe had buffering effects on perceived stress, whereas heart rate recovery immediately after emotion induction appeared to be similar across all conditions. Amusement led to faster recovery from perceived stress compared to the other conditions, whereas the increase in positive emotion in the awe condition persisted longer than that in the neutral condition. Compared to the neutral condition, the amusement and awe conditions were associated with reduced occipital gyrus activity during video viewing. Distinct neural activity patterns were observed for each emotion, suggesting that awe promotes the integration of expansive experiences with self-related information related to the default mode network, whereas amusement engages social and cognitive processes associated with the central executive network. These findings may eventually inform interventions to promote mental and physical health by cultivating positive emotions, and improve understanding of how discrete positive emotions influence stress responses.
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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 | 0.000 | 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) | 0.000 | 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".