Acute psychosocial stress investigated by an imaging stress test: concept and preliminary results
Bibliographic record
Abstract
Social evaluative stress is an identified risk-factor for a plethora of psychiatric disorders. Yet, little is known about the neural correlates of psychosocial stress processing and the networks that translate psychosocial stress into an endocrine response. In this study we test a multimodal setup that integrates an experimental psychosocial stress intervention with BOLD-fMRI, stress hormone and mRNA measurements, psychometry as well as autonomic nervous system (ANS) measurements. Pilot Study In our pilot study we tested an adapted version of the Montreal Imaging Stress Test to apply psychosocial stress in 13 young subjects. The experiment consists of normal calculation task (10‘), calculation under stress (10’) and a switch back to normal calculation (10’). Generally, the cognitive workload is individually adjusted to the individual capabilities before in the 2nd sections performance monitoring, time pressure and negative feedback are used to induce stress. After optimized preprocessing, fMRI analysis focused on proof-of-concept contrasts of the cognitive elements of the task and on an exploration of connectivity changes (both on a whole brain atlas and selected limbic regions) as determined from the resting periods between the active blocks. Resultwise, the task related BOLD amplitude analysis yielded satisfying proof-of-concept patterns for the calculus, feedback-processing and motor response contrasts. Feedback-processing related striatal signals showed strong deactivation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".