Microstate analysis of alpha-event brain topography during chan meditation

This paper reports our preliminary result of microstate analysis for the spatiotemporal characteristics of Chan-meditation brain wave (electroencephalograph, EEG) based on time-varying dipolar-vector model of the alpha-map. Microstate behavior reveals subtle transience of focalized event. Multi-chan...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 2; pp. 717 - 721
Main Authors Pei-Chen Lo, Qiang Zhu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
brain mapping
Chan meditation
Cybernetics
electroencephalograph (EEG)
frontal alpha
Machine learning
Mahalanobis Fuzzy C-means (M-FCM)
Microstate analysis
Surfaces
wavelet decomposition
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Summary:This paper reports our preliminary result of microstate analysis for the spatiotemporal characteristics of Chan-meditation brain wave (electroencephalograph, EEG) based on time-varying dipolar-vector model of the alpha-map. Microstate behavior reveals subtle transience of focalized event. Multi-channel alpha-event epochs were identified by Wavelet decomposition and feature extraction. Global field power was adopted as the criterion to choose alpha-map candidates (normalized alpha-power vectors), that were further classified by mahalanobis fuzzy C-means into different region-focalization states. Transition between various alpha-event focalization states was ready to be explored via microstate analysis. Our findings reveal that Chan-meditation practitioners exhibit longer duration of frontal alpha-event microstate, reflecting sustained stability of the brain generators.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212377