{"title":"Peculiarity Oriented Multi-Aspect Brain Data Analysis for Studying Human Multi-Perception Mechanism","authors":"Ning Zhong, S. Motomura, Jing-long Wu","doi":"10.1109/SAINTW.2005.94","DOIUrl":null,"url":null,"abstract":"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 extracted from 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 wayfor automatic analysis and understanding of human brain data to replace human-expert centric visualization. We attempt to change the perspective of cognitive scientists from a single type of experimental data analysis towards a holistic view.","PeriodicalId":220913,"journal":{"name":"2005 Symposium on Applications and the Internet Workshops (SAINT 2005 Workshops)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 Symposium on Applications and the Internet Workshops (SAINT 2005 Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAINTW.2005.94","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
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 extracted from 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 wayfor automatic analysis and understanding of human brain data to replace human-expert centric visualization. We attempt to change the perspective of cognitive scientists from a single type of experimental data analysis towards a holistic view.