Common and Dissociable Neural Activity After Mindfulness-Based Stress Reduction and Relaxation Response Programs
Bibliographic record
Abstract
OBJECTIVE: We investigated common and dissociable neural and psychological correlates of two widely used meditation-based stress reduction programs. METHODS: Participants were randomized to the Relaxation Response (RR; n = 18; 56% female) or the Mindfulness-Based Stress Reduction (MBSR; n = 16; 56% female) programs. Both programs use a "bodyscan" meditation; however, the RR program explicitly emphasizes physical relaxation during this practice, whereas the MBSR program emphasizes mindful awareness with no explicit relaxation instructions. After the programs, neural activity during the respective meditation was investigated using functional magnetic resonance imaging. RESULTS: Both programs were associated with reduced stress (for RR, from 14.1 ± 6.6 to 11.3 ± 5.5 [Cohen's d = 0.50; for MBSR, from 17.7 ± 5.7 to 11.9 ± 5.0 [Cohen's d = 1.02]). Conjunction analyses revealed functional coupling between ventromedial prefrontal regions and supplementary motor areas (p < .001). The disjunction analysis indicated that the RR bodyscan was associated with stronger functional connectivity of the right inferior frontal gyrus-an important hub of intentional inhibition and control-with supplementary motor areas (p < .001, family-wise error [FWE] rate corrected). The MBSR program was uniquely associated with improvements in self-compassion and rumination, and the within-group analysis of MBSR bodyscan revealed significant functional connectivity of the right anterior insula-an important hub of sensory awareness and salience-with pregenual anterior cingulate during bodyscan meditation compared with rest (p = .03, FWE corrected). CONCLUSIONS: The bodyscan exercises in each program were associated with both overlapping and differential functional coupling patterns, which were consistent with each program's theoretical foundation. These results may have implications for the differential effects of these programs for the treatment of diverse conditions.
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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 | 0.002 |
| 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".