Psychological well-being modulates neural synchrony during naturalistic fMRI
Bibliographic record
Abstract
Psychological well-being (PWB) is a combination of feeling good and functioning efficiently, and has a significant relationship with physical and mental health. Previous research has shown that PWB is associated with improvements in selective attention, mindfulness, semantic self-images, and adaptive decision making, however, it is unclear how these differences manifest in the brain. Naturalistic stimuli better encapsulate everyday experiences and can elicit more "true-to-life" neural responses. The current study seeks to identify how differing levels of PWB modulate neural synchrony in response to an audiovisual film. With consideration of the inherent variability of the literature, we aim to ascertain the validity of the regions previously associated with PWB. We identified that higher levels of PWB were associated with heightened stimulus driven neural synchrony in the bilateral superior parietal lobule, right planum temporale, and left superior temporal gyrus, and that lower levels of PWB were associated with heightened neural synchrony in the bilateral lateral occipital cortex and precuneus. Taken together, this research suggests that there is an association between differing levels of PWB and differential neural synchrony during movie-watching. PWB may therefore have an effect on complex, multimodal processing.
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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) | 0.001 | 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".