bioRxivNeurosciencePreprint
Electroencephalographic dynamics of rhythmicbreath-based meditation
Vaibhav TripathiiD, Lakshmi Bhasker, Chhaya KharyaiD, Manvir BhatiaiD, Vinod Kochupillai
- Citations
- 6
Abstract
Meditation has been practised for millennia but the neuroscientific understanding of the dynamics is still lacking. Sudarshan Kriya Yoga (SKY) is an evidence based breathing based meditation technique that utilizes rhythmic breathing to induce a deep state of relaxation and calm. Multiple studies have found benefits of the SKY technique from genetic, physiological, psychological to behaviour levels. We collected Electroencephalographic (EEG) data in 43 subjects who underwent the SKY technique and analysed the brain rhythms at different stages of the technique namely preparatory breathing (Pranayama), rhythmic breathing (Kriya) and meditation (Yoga Nidra) using newly developed methods to analyse periodic and aperiodic components. Alpha waves amplitude in the parieto-occipital region decreased as the rhythmic breathing progressed and dropped sharply during the meditation period. Theta amplitudes and peak frequency increased in the centro-frontal region during the rhythmic breathing period but were marked by sustained low theta waves during the meditation period. The delta wave amplitude was not affected by breathing but both delta band power and peak frequency increased during the meditation period in the centro-frontal region. We also saw a decrease in the 1/f aperiodic signal across the brain during the meditation period suggesting a modification of excitation-inhibition balance. We see an overall slowing down of brain oscillations from alpha to theta to delta as the meditation progressed. The paper studies in depth the transitional dynamics of the SKY technique analysing the alpha, theta, delta waves and aperiodic signals and demonstrates that each phase in a breathing based meditation has a unique electrophysiological signature.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
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