EEG-Based Characterization of Samatha and Vipassana Meditation States
M. A. B. C. A. Bandaranayake, K. P. U. Chandrathilake, J. L. S. Jayasekara, S. T. Piyasena, A. T. L. K. Samrasinghe, Wageesha N. Manamperi
arXiv Preprint Archive August 10, 2026 preprint
Study at a glance
AI-extracted from the abstract| Characteristics | Observational study |
|---|---|
| Sample size | 12 |
| Population | Experienced meditators |
| Topics | Meditation |
| Keywords | Eess.sp |
| Key findings | EEG signals differentiated Samatha and Vipassana meditation states, with the most pronounced differences in the delta frequency band, indicating condition-dependent neural activity. |
Abstract
Meditation has been associated with a range of cognitive and physiological benefits. However, the underlying neural mechanisms of different meditation practices are not yet fully understood. This study investigates whether electroencephalogram (EEG) signals can be used to characterize and distinguish two commonly practiced meditation techniques, namely Samatha and Vipassana, which involve distinct cognitive processes, with Samatha emphasizing sustained concentration and Vipassana emphasizing mindful observation and insight. By extracting features such as band power, coherence and wavelet entropy from EEG signals recorded during pre-meditation resting, Samatha, and Vipassana states, we provide an assessment of how spectral power, signal complexity, and functional connectivity differentiate these practices. Preliminary results from $12$ experienced meditators indicate condition-dependent EEG differences, with the most pronounced effects observed in the delta frequency band. These results demonstrate the utility of EEG-based metrics for the objective characterization of meditation and advance our comprehension of the neural processes underlying different contemplative practices.