A Mindfulness-Based Intervention to Reduce Altered Brain Reward Function in Cannabis Use Disorder: A Double-Blind, Active and Passive, Randomised Controlled fMRI Trial
Bibliographic record
Abstract
Cannabis Use Disorder (CUD) affects ~ 50 million individuals worldwide and is associated with alterations in brain reward pathways. Mindfulness-based interventions (MBIs) show promise in reducing substance use and aberrant brain function in substance use disorders (SUD), but the effects on CUD or brain reward function have not been investigated. To examine whether a 2-week MBI vs. active control (i.e., closely matched relaxation) and passive control (i.e., no intervention) affected brain reward function in CUD using the Monetary Incentive Delay fMRI task, 49 individuals with moderate-to-severe CUD were randomised to: a 2-week MBI (n = 18), active control condition (n = 15), or passive control condition (n = 16), and assessed before and after the intervention. The effect of intervention-by-time was analysed using an exploratory whole-brain approach and a priori regions-of-interest approach (ROIs; ventral striatum, dorsal caudate, putamen, insula, cingulate, and orbitofrontal cortices). Whole-brain results revealed significant intervention-by-time effects. Post-MBI, there was: decreased cerebellum activity while anticipating monetary cues, increased parietal activity while receiving monetary wins, and decreased fusiform/superior frontal gyri (SFG) activity while receiving monetary wins. Post-relaxation, activity increased in several regions (i.e., hippocampus, insula, parietal cortex, fusiform, and SFG) during the receipt of monetary wins. Post-no intervention, activity increased in the cerebellum while anticipating monetary cues, and decreased in other areas (i.e., parietal cortex, hippocampus, and insula) while receiving monetary wins. There were no significant intervention-by-time effects using the ROI approach. Overall, MBI, matched relaxation, and no intervention may share changes in partially overlapping brain regions in distinct directions.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.006 | 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".