Lower perceived stress enhances neural synchrony in perceptual and attentional cortices during naturalistic processing
Bibliographic record
Abstract
Abstract Perceived stress is the subjective appraisal of the level of stress experienced by an individual in response to external or internal demands. Recent research on perceived stress has highlighted its role in influencing cognition, leading to a disruption in cognitive processes, such as emotional processing, attention, and perception. However, most neuroimaging studies examining stress have used static stimuli (e.g., still images) that do not encapsulate real-life multimodal processing in the brain. The current research uses data from the Naturalistic Neuroimaging Database (v2.0; Aliko et al., 2020) to examine differences in neural synchrony (as measured by intersubject correlations; ISCs) associated with perceived stress using functional magnetic resonance imaging (fMRI). We evaluated how self-reported perceived stress levels influence neural synchrony patterns in response to different naturalistic stimuli by examining the differences in neural synchrony between individuals with low and high perceived stress levels. We determined that lower perceived stress was observed with greater neural synchrony areas associated with perceptual and attention processing, including the lateral occipital cortex, superior temporal gyrus, superior parietal lobule, orbital frontal cortex, and the occipital pole. These results indicate that high levels of perceived stress heavily alter neural processing of complex audiovisual stimuli. Together, these results provide evidence that perceived stress influences cognitive processing in everyday life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".