Synchrony analysis of paroxysmal gamma waves in Bhramari Pranayama meditation EEG
Meditation refers to a range of practices that contains techniques used to promote relaxation, generate natural energy or vital force and cultivate compassion. It is an interesting topic which however has received poor attention in the neural signal procession. Electroencephalograms (EEG) i...
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sg-ntu-dr.10356-649862023-07-04T15:48:02Z Synchrony analysis of paroxysmal gamma waves in Bhramari Pranayama meditation EEG Guan, Hang Jing Jin School of Electrical and Electronic Engineering Justin Dauwels DRNTU::Engineering::Electrical and electronic engineering Meditation refers to a range of practices that contains techniques used to promote relaxation, generate natural energy or vital force and cultivate compassion. It is an interesting topic which however has received poor attention in the neural signal procession. Electroencephalograms (EEG) is a scientific technique applied to record electrical activity of the brain. Recently, it has been claimed paroxysmal gamma waves (PGWs) have been found in Bhramari Pranayama (BhPr) meditation EEG. In this dissertation, an analysis of the synchrony on PGWs is performed to have a better knowledge of functional connectivity patterns in the brain during BhPr meditation. In order to quantitatively assess the synchrony between pairs of PGW sequences, the method "Stochastic Event Synchrony" (SES) is introduced into the picture. There are seven subjects with three levels of expertise in practicing BhPr provided for the synchrony analysis. Stable connectivity patterns are observed with moderate strength during exhalation periods of BhPr meditation. In addition, the connection strength distribution is most concentrated for the subject with the level of expertise in practicing BhPr meditation. Master of Science (Power Engineering) 2015-06-10T03:22:04Z 2015-06-10T03:22:04Z 2014 2014 Thesis http://hdl.handle.net/10356/64986 en 59 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Guan, Hang Synchrony analysis of paroxysmal gamma waves in Bhramari Pranayama meditation EEG |
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Meditation refers to a range of practices that contains techniques used to promote
relaxation, generate natural energy or vital force and cultivate compassion. It is an
interesting topic which however has received poor attention in the neural signal procession.
Electroencephalograms (EEG) is a scientific technique applied to record electrical
activity of the brain. Recently, it has been claimed paroxysmal gamma waves (PGWs)
have been found in Bhramari Pranayama (BhPr) meditation EEG.
In this dissertation, an analysis of the synchrony on PGWs is performed to have a better
knowledge of functional connectivity patterns in the brain during BhPr meditation. In
order to quantitatively assess the synchrony between pairs of PGW sequences, the
method "Stochastic Event Synchrony" (SES) is introduced into the picture. There are
seven subjects with three levels of expertise in practicing BhPr provided for the
synchrony analysis. Stable connectivity patterns are observed with moderate strength
during exhalation periods of BhPr meditation. In addition, the connection strength
distribution is most concentrated for the subject with the level of expertise in practicing
BhPr meditation. |
author2 |
Jing Jin |
author_facet |
Jing Jin Guan, Hang |
format |
Theses and Dissertations |
author |
Guan, Hang |
author_sort |
Guan, Hang |
title |
Synchrony analysis of paroxysmal gamma waves in Bhramari Pranayama meditation EEG |
title_short |
Synchrony analysis of paroxysmal gamma waves in Bhramari Pranayama meditation EEG |
title_full |
Synchrony analysis of paroxysmal gamma waves in Bhramari Pranayama meditation EEG |
title_fullStr |
Synchrony analysis of paroxysmal gamma waves in Bhramari Pranayama meditation EEG |
title_full_unstemmed |
Synchrony analysis of paroxysmal gamma waves in Bhramari Pranayama meditation EEG |
title_sort |
synchrony analysis of paroxysmal gamma waves in bhramari pranayama meditation eeg |
publishDate |
2015 |
url |
http://hdl.handle.net/10356/64986 |
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1772828325452972032 |