Insular Cortex Mediates Increased Pain Tolerance in Yoga Practitioners
Bibliographic record
Abstract
Yoga, an increasingly popular discipline among Westerners, is frequently used to improve painful conditions. We investigated possible neuroanatomical underpinnings of the beneficial effects of yoga using sensory testing and magnetic resonance imaging techniques. North American yogis tolerated pain more than twice as long as individually matched controls and had more gray matter (GM) in multiple brain regions. Across subjects, insular GM uniquely correlated with pain tolerance. Insular GM volume in yogis positively correlated with yoga experience, suggesting a causal relationship between yoga and insular size. Yogis also had increased left intrainsular white matter integrity, consistent with a strengthened insular integration of nociceptive input and parasympathetic autonomic regulation. Yogis, as opposed to controls, used cognitive strategies involving parasympathetic activation and interoceptive awareness to tolerate pain, which could have led to use-dependent hypertrophy of insular cortex. Together, these findings suggest that regular and long-term yoga practice improves pain tolerance in typical North Americans by teaching different ways to deal with sensory inputs and the potential emotional reactions attached to those inputs leading to a change in insular brain anatomy and connectivity.
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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 | 0.001 |
| 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) | 0.003 | 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".