Similar States, Different Paths: Neurodynamics of diverse meditation techniques

Abstract Meditation encompasses diverse practices that train attention inward, in contrast to externally oriented task states. However, the neurodynamic features distinguishing meditative states from non-meditative states across traditions remain unclear. We analyzed high-density EEG data (N=170; 121 advanced meditators, 49 controls) across four traditions: Vipassana, Brahma Kumaris Raja Yoga, Heartfulness, and Isha Yoga. EEG features spanned oscillatory, aperiodic, nonlinear, and timescale components. Using random forest classifiers, we distinguished meditative from non-meditative states with robust classification performance (91%). Nonlinear features contributed the most, suggesting a core neurodynamic profile. Classification performance was higher in advanced meditators (92%) than in controls (85%), with distinct feature importance: nonlinear and aperiodic features dominated in meditators, and oscillatory and timescale features in controls. Each tradition showed distinct neurodynamic profiles, indicating technique-specific constellations. Our findings revealed shared yet distinct neurodynamic signatures across meditation techniques, suggesting that multiple neurodynamic pathways lead to meditative states.