Title :
Microstate analysis of alpha-event brain topography during chan meditation
Author :
Lo, Pei-Chen ; Zhu, Qlang
Author_Institution :
Dept. of Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
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.
Keywords :
brain; electroencephalography; feature extraction; fuzzy set theory; medical signal processing; Chan-meditation brain wave; EEG; alpha-event brain topography; alpha-map; brain generator; electroencephalograph; feature extraction; global field power; mahalanobis fuzzy C-mean; microstate analysis; multichannel alpha-event epoch; region-focalization states; spatiotemporal characteristic; time-varying dipolar-vector model; wavelet decomposition; Cybernetics; Machine learning; Surfaces; Chan meditation; Mahalanobis Fuzzy C-means (M-FCM); Microstate analysis; brain mapping; electroencephalograph (EEG); frontal alpha; wavelet decomposition;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212377
