Amygdala and prefrontal cortex activity varies with individual differences in the emotional response to psychosocial stress.
Bibliographic record
Abstract
Stress elicits a variety of psychophysiological responses that show large interindividual variability. Determining the neural mechanisms that mediate individual differences in the emotional response to stress would provide new insight that would have important implications for understanding stress-related disorders. Therefore, the present study examined individual differences in the relationship between brain activity and the emotional response to stress. In the largest stress study to date, 239 participants completed the Montreal Imaging Stress Task (MIST) while heart rate, skin conductance response (SCR), cortisol, self-reported stress, and blood oxygen level dependent (BOLD) functional MRI (fMRI) signal responses were measured. The relationship between differential responses (heart rate, SCR, cortisol, and self-reported stress) and differential BOLD fMRI data was analyzed. Dorsolateral prefrontal cortex (PFC), dorsomedial PFC, ventromedial PFC, and amygdala activity varied with the behavioral response (i.e., SCR and self-reported stress). These results suggest the PFC and amygdala support processes that are important for the expression and regulation of the emotional response to stress, and that stress-related PFC and amygdala activity underlie interindividual variability in peripheral physiologic measures of the stress response. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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) | 0.000 | 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) | 0.003 | 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".