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September 12, 20250 citationsOpen Access

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

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RKRatna Jyothi KakumanuANAjay Kumar NairASArun Sasidharan

Key Points

  • EEG phase slip rates revealed significant differences in brain patterns during decision-making tasks.
  • Novice vipassana meditators exhibited faster object recognition compared to non-meditator controls.
  • Using 128-channel EEG data, the study analyzed brain activity during a visual oddball paradigm.
  • Findings suggest phase slip rates could serve as meaningful biomarkers for cognitive differences in meditation.

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 first 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 over 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.

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Cite This Study

Kakumanu et al. (2025) studied this question.

synapsesocial.com/papers/68d44c4631b076d99fa55a66https://doi.org/10.1101/2025.09.03.674031
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