This resting-state fMRI study compared static (sFNC) and dynamic functional network connectivity (dFNC) between 20 experienced meditators and 20 novice adults under eyes-open and eyes-closed conditions, using ICA, partial correlations with FFMQ subscales, and Bayesian logistic regression with cross-validation to identify neural markers of trait mindfulness.
Experienced meditators showed stronger sFNC between the left frontoparietal network (LFPN) and anterior default mode network (aDMN), positively correlated with the FFMQ Acting with Awareness subscale. At the dynamic level, they spent more time in a highly integrated network state and less time in a partially segregated state. sFNC-based classification achieved accuracy = 0.73 and AUC = 0.81; adding dFNC features or FFMQ scores did not meaningfully improve performance.
- Very small sample (n=40 total; 20 per group), limiting statistical power and generalizability. - Cross-sectional design prevents causal inference about whether meditation drives connectivity differences. - Data are not publicly available, limiting reproducibility.
Static LFPN–aDMN connectivity may serve as a candidate neural marker for trait mindfulness, but the small sample and cross-sectional design mean these findings are preliminary — not yet ready to guide clinical selection or monitoring of meditators.
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