TY - JOUR
T1 - Building a data-mining Grid for multiple human brain data analysis
AU - Zhong, Ning
AU - Hu, Jia
AU - Motomura, Shinichi
AU - Wu, Jing Long
AU - Liu, Chunnian
PY - 2005/5
Y1 - 2005/5
N2 - E-science is about global collaboration in key areas of science such as cognitive science and brain science, and the next generation of infrastructure such as the Wisdom Web and Knowledge Grids. As a case study, we investigate human multiperception mechanism by cooperatively using various psychological experiments, physiological measurements, and data mining techniques for developing artificial systems which match human ability in specific aspects. In particular, we observe fMRI (functional magnetic resonance imaging) and EEG (electroencephalogram) brain activations from the viewpoint of peculiarity oriented mining and propose a way of peculiarity oriented mining for knowledge discovery in multiple human brain data. Based on such experience and needs, we concentrate on the architectural aspect of a brain-informatics portal from the perspective of the Wisdom Web and Knowledge Grids. We describe how to build a data-mining grid on the Wisdom Web for multiaspect human brain data analysis. The proposed methodology attempts to change the perspective of cognitive scientists from a single type of experimental data analysis toward a holistic view at a long-term, global field of vision.
AB - E-science is about global collaboration in key areas of science such as cognitive science and brain science, and the next generation of infrastructure such as the Wisdom Web and Knowledge Grids. As a case study, we investigate human multiperception mechanism by cooperatively using various psychological experiments, physiological measurements, and data mining techniques for developing artificial systems which match human ability in specific aspects. In particular, we observe fMRI (functional magnetic resonance imaging) and EEG (electroencephalogram) brain activations from the viewpoint of peculiarity oriented mining and propose a way of peculiarity oriented mining for knowledge discovery in multiple human brain data. Based on such experience and needs, we concentrate on the architectural aspect of a brain-informatics portal from the perspective of the Wisdom Web and Knowledge Grids. We describe how to build a data-mining grid on the Wisdom Web for multiaspect human brain data analysis. The proposed methodology attempts to change the perspective of cognitive scientists from a single type of experimental data analysis toward a holistic view at a long-term, global field of vision.
KW - Brain-informatics portals
KW - Multiaspect human brain data analysis
KW - Peculiarity oriented mining
KW - The Wisdom Web
KW - The data-mining grid
UR - http://www.scopus.com/inward/record.url?scp=17644374765&partnerID=8YFLogxK
U2 - 10.1111/j.0824-7935.2005.00270.x
DO - 10.1111/j.0824-7935.2005.00270.x
M3 - Article
AN - SCOPUS:17644374765
SN - 0824-7935
VL - 21
SP - 177
EP - 196
JO - Computational Intelligence
JF - Computational Intelligence
IS - 2
ER -