Functional connectivity changes in meditators and novices during yoga nidra practice.
Level 4 - case-series / case-control
Cross-sectional comparative neuroimaging study without longitudinal intervention or randomization
PubMed 38839877 · doi:10.1038/s41598-024-63765-7
What was done
Researchers conducted an fMRI investigation comparing 30 experienced meditators to 31 novice controls during wakeful resting states and guided yoga nidra (YN) practice. General linear model (GLM) analysis evaluated responses to audio instructions, and seed-based functional connectivity (FC) was used to measure default mode network (DMN) connectivity during YN and pre/post resting states.
What was found
The abstract reports no exact numerical statistics, effect sizes, or p-values. GLM analysis showed auditory cue activation without concurrent DMN deactivation. During YN, experienced meditators exhibited significantly reduced DMN functional connectivity compared to novice controls. Comparing YN to resting state, meditators showed DMN decoupling whereas novices showed increased DMN connectivity. No baseline differences were found between groups during pre- and post-practice resting scans. Reduced DMN connectivity during YN correlated with self-reported cumulative hours of meditation and yoga experience.
Why it matters
This study provides neural evidence that experienced practitioners experience yoga nidra through distinct default mode network decoupling, supporting the concept of a state combining deep physical rest with preserved awareness.
Limits
The study is cross-sectional and cannot establish whether neural differences reflect training effects or baseline self-selection among meditators. The sample size is modest (n = 61 total), cumulative practice was self-reported and vulnerable to recall bias, and the abstract omits quantitative effect sizes, statistical thresholds, and specific demographic details.
Cited by
- supports Brain imaging studies show that during yoga nidra (non-sleep deep rest), regional pockets of the brain enter sleep patterns rather than global sleep.