Investigation of spatial characteristics of meditation EEG using wavelet analysis and fuzzy classifier

The aim of this paper is to report our preliminary results of investigating the alpha spatial properties in Zen-meditation EEG (electroencephalograph). Results of practitioners (experimental group) were compared with that of non-practitioners (control group). We firstly applied wavelet transform to decomposing multi-channel EEG signals and reconstructing various EEG rhythms using wavelet coefficients. From the power ratio, we selected the candidates (normalized alpha-power vectors) for further spatial analysis. Fuzzy C-means based algorithm was applied to the normalized vectors to explore various brain spatial characteristics during meditation (or, at rest). Here we evaluated correlation coefficients to decide the number of clusters. From the results we found (1) during meditation, the possessing ration of a power in the frontal area of meditators increased more than that of the control subjects (during relaxation with eyes closed). Contrarily, in the parietal area the possessing ratio is decreased in the experimental group but increased in the control group. (2) The ratio of non-a waves in the control group decreased dramatically during relaxation but not in the experimental group. From the literatures, activating medial prefrontal cortex and anterior cingulated cortex during meditation may be the reason of increasing frontal alpha power.