Dispositional mindfulness and the attenuation of neural responses to emotional stimuli
Bibliographic record
Abstract
Considerable research has disclosed how cognitive reappraisals and the modulation of emotional responses promote successful emotion regulation. Less research has examined how the early processing of emotion-relevant stimuli may create divergent emotional response consequences. Mindfulness--a receptive, non-evaluative form of attention--is theorized to foster emotion regulation, and the present study examined whether individual differences in mindfulness would modulate neural responses associated with the early processing of affective stimuli. Focus was on the late positive potential (LPP) of the event-related brain potential to visual stimuli varying in emotional valence and arousal. This study first found, replicating past research, that high arousal images, particularly of an unpleasant type, elicited larger LPP responses. Second, the study found that more mindful individuals showed lower LPP responses to high arousal unpleasant images, even after controlling for trait attentional control. Conversely, two traits contrasting with mindfulness--neuroticism and negative affectivity--were associated with higher LPP responses to high arousal unpleasant images. Finally, mindfulness was also associated with lower LPP responses to motivationally salient pleasant images (erotica). These findings suggest that mindfulness modulates neural responses in an early phase of affective processing, and contribute to understanding how this quality of attention may promote healthy emotional functioning.
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) | 0.001 | 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".