Exploring EEG biomarkers in meditation, yoga, and mantra practices: a review of neural correlates and methodologies

This review systematically links EEG oscillations to relaxation achieved through mantras, yoga, and meditation. It defines EEG activity and examines individual brainwave bands associated with relaxation, while identifying gaps in the existing EEG literature. The work integrates traditional healing practices with modern EEG research, offering a comprehensive overview of methodologies, analysis techniques, and potential applications for understanding relaxation and well-being. It also highlights the relationship between mantras and EEG parameters, along with classification techniques, preprocessing steps, relaxation features, and accuracy outcomes used in EEG studies.

Study at a glance

Abstract

Studying EEG oscillations has attracted significant attention due to their potential impact on physiological, cognitive, psychomotor, and psycho-emotional aspects of human life. However, there is no consensus on what constitutes “EEG activity” or which indices best characterize it, particularly in the context of relaxation brought about by mantras, yoga, and meditation. This review provides a systematic framework linking EEG to relaxation from traditional healing practices. It defines EEG activity and investigates individual band activity associated with relaxation. Additionally, a gap analysis of EEG literature in this domain is conducted. By reading this review, one may gain comprehensive knowledge of the entire process of EEG-based research, including methodologies, analysis techniques, and potential applications for understanding relaxation and its effects on well-being. Notably, this work introduces a unique perspective by integrating traditional practices with modern EEG research, filling a crucial gap in the existing literature. Furthermore, it highlights the relationship between mantras and EEG parameters, as well as various classification techniques utilized in EEG studies, emphasizing their preprocessing steps, relaxation features, classification methods, and achieved accuracy.