Analysis of Meditation vs. Sensory Engaged Brain States Using Shannon Entropy and Pearson’s First Skewness Coefficient Extracted from EEG Data

Author:

Davis Joshua J. J.1,Kozma Robert234,Schübeler Florian5

Affiliation:

1. Department of Physics, Dodd-Walls Centre for Photonics and Quantum Technologies, University of Auckland, Auckland 1142, New Zealand

2. Department of Mathematics, University of Memphis, Memphis, TN 38152, USA

3. Kozmos Research Laboratories, Boston, MA 02215, USA

4. School of Informatics, Obuda University, H-1034 Budapest, Hungary

5. The Embassy of Peace, Whitianga, Coromandel 3591, New Zealand

Abstract

It has been proposed that meditative states show different brain dynamics than other more engaged states. It is known that when people sit with closed eyes instead of open eyes, they have different brain dynamics, which may be associated with a combination of deprived sensory input and more relaxed inner psychophysiological and cognitive states. Here, we study such states based on a previously established experimental methodology, with the aid of an electro-encephalography (EEG) array with 128 electrodes. We derived the Shannon Entropy (H) and Pearson’s 1st Skewness Coefficient (PSk) from the power spectrum for the modalities of meditation and video watching, including 20 participants, 11 meditators and 9 non-meditators. The discriminating performance of the indices H and PSk was evaluated using Student’s t-test. The results demonstrate a statistically significant difference between the mean H and PSk values during meditation and video watch modes. We show that the H index is useful to discriminate between Meditator and Non-Meditator participants during meditation over both the prefrontal and occipital areas, while the PSk index is useful to discriminate Meditators from Non-Meditators based on the prefrontal areas for both meditation and video modes. Moreover, we observe episodes of anti-correlation between the prefrontal and occipital areas during meditation, while there is no evidence for such anticorrelation periods during video watching. We outline directions of future studies incorporating further statistical indices for the characterization of brain states.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference61 articles.

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4. Buzsáki, G. (2006). Rhythms of the Brain, Oxford University Press.

5. Davis, J.J.J., Schübeler, F., Ji, S., and Kozma, R. (2020, January 11–14). Discrimination Between Brain Cognitive States Using Shannon Entropy and Skewness Information Measure. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020), Toronto, ON, Canada.

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