Peculiarity oriented multi-aspect brain data analysis for studying human multi-perception mechanism

In order to investigate the structure of advanced human brain activities, various brain analysis methods are required. It has been observed that multiple brain data such as fMRI brain images and EEG brain waves extractedfrom human multi-perception mechanism involved in a particular task are peculiar ones with respect to the specific state or the relatedpart of a stimulus. Based on this point of view, we propose a way of peculiarity oriented mining for multi-aspect analysis in multiple human brain data, without using conventional image processing to fMRI brain images and frequency analysis to brain waves. The proposed approach provides a new way for automatic analysis and understanding of human brain data to replace human-expert centric visualization. We attempt to change the perspective of cognitive scientistsfrom a single type of experimental data analysis towards a holistic view.