Reduced Fear-Conditioned Pain Modulation in Experienced Meditators: A Preliminary Study
Bibliographic record
Abstract
OBJECTIVE: Mindfulness-based practice is a form of cognitive/affective training that may help reduce suffering by attenuating maladaptive anticipatory processes. This study's objective was to examine the pain modulating impact of classical fear learning in meditation practitioners. METHODS: The hyperalgesic effects of pain expectation and uncertainty were assessed outside formal meditation in 11 experienced meditators (>1000 hours) compared with meditation-naive controls during a Pavlovian classical fear-conditioning paradigm involving two visual stimuli (CS+/CS-), one of which (CS+) co-terminated with a noxious electrical stimulus (unconditioned stimulus) on 50% of trials. A Rescorla-Wagner/Pearce-Hall hybrid model was fitted onto the conditioned skin conductance responses using computational modeling to estimate two learning parameters: expected shock probability and associability (i.e., uncertainty). RESULTS: Using a scale ranging between 0 (no pain) and 100 (extremely painful), meditators reported less pain (M = 19.9, SE = 5.1 for meditators, M = 32.4, SE = 2.4 for controls) but had comparable spinal motor responses (nociceptive flexion reflex) to the unconditioned stimulus. Multilevel mediation analyses revealed that meditators also exhibited reduced hyperalgesic effects of fear learning on higher-order pain responses but comparable effects on the nociceptive flexion reflex. These results suggest that mindfulness affects higher-order perceptual processes to a greater extent than from descending inhibitory controls. Furthermore, meditators showed reduced hyperalgesic effects of fear conditioning with no significant group difference in conditioned learning as evidenced by discriminative anticipatory skin conductance responses and learning parameters derived from computational modeling. CONCLUSIONS: These results highlight potential mechanisms underlying mindfulness-related hypoalgesia, relevant to clinical conditions in which repeated pain exposure might reinforce hyperalgesic processes through fear conditioning.
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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 | 0.000 |
| 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) | 0.002 | 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".