The Mindful Brain and Emotion Regulation in Mood Disorders
Bibliographic record
Abstract
Mindfulness involves nonjudgmental attention to present-moment experience. In its therapeutic forms, mindfulness interventions promote increased tolerance of negative affect and improved well-being. However, the neural mechanisms underlying mindful mood regulation are poorly understood. Mindfulness training appears to enhance focused attention, supported by the anterior cingulate cortex and the lateral prefrontal cortex (PFC). In emotion regulation, these PFC changes promote the stable recruitment of a nonconceptual sensory pathway, an alternative to conventional attempts to cognitively reappraise negative emotion. In neural terms, the transition to nonconceptual awareness involves reducing evaluative processing, supported by midline structures of the PFC. Instead, attentional resources are directed toward a limbic pathway for present-moment sensory awareness, involving the thalamus, insula, and primary sensory regions. In patients with affective disorders, mindfulness training provides an alternative to cognitive efforts to control negative emotion, instead directing attention toward the transitory nature of momentary experience. Limiting cognitive elaboration in favour of momentary awareness appears to reduce automatic negative self-evaluation, increase tolerance for negative affect and pain, and help to engender self-compassion and empathy in people with chronic dysphoria.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".