EEG Phase Slips Reveal Detailed Brain Activity Patterns of Novice Vipassana Meditators During Decision Making Tasks

A novel approach using four EEG-based biomarkers—potentials, their first-order derivatives, and phase slip rates derived from each—distinguished novice Vipassana meditators from non-meditator controls. Phase slip rates, discontinuities in instantaneous phase representing cortical phase transitions, were computed from 128-channel EEG data collected during a visual oddball task. Eight novice Vipassana subjects and eight non-meditator controls each completed 50 trials; 44 artifact-free trials per subject were averaged. Spatiotemporal profiles of all four biomarkers differed significantly between groups, and the novice Vipassana subjects showed faster object recognition. The findings suggest phase slip rates offer a promising set of biomarkers for quantitative task-based EEG analyses.

Study at a glance

Abstract

Abstract Our study adopted a novel approach, utilizing four biomarkers, namely EEG potentials, their first-order derivatives, and phase slip rates derived from each, to discern the differences between novice Vipassana (NVP) subjects and non-meditator controls (NMC). Phase slip rates are discontinuities in instantaneous phase that represent cortical phase transitions, indicating a significant change in the overall brain state. We employed 128-channel EEG data from eight NMC and eight NVP subjects, collected during a gamified protocol, to investigate object identification within a visual oddball paradigm. EEG was continuously acquired during the 50 trials for each subject. We retained 44 artifact-free trials per subject (the minimum common across all subjects) and computed within-subject averages. The EEGs were then averaged separately for NMC and NVP subjects. The EEG was filtered in the alpha band, and the phase was extracted using the Hilbert transform, unwrapped, and the phase slip rates were computed. A montage layout of electrodes was used to make the spatiotemporal plots of biomarkers. Our findings revealed that the spatiotemporal profiles of all four biomarkers differed significantly between the two groups of subjects. Furthermore, the NVP subjects demonstrated faster object recognition. These results not only provide a unique method to use phase slip rates to quantify cognitive differences between NMC and NVP subjects but also present a promising set of biomarkers for quantitative task-based EEG analyses.