Brain Function Analysis System on a metacomputer

Understanding of higer brain function is one of the most important scientific issue for human beings. For the purpose, analysis of brain functional data obtained through medical devices such as EEG, ECoG, and fMRI takes a role of importance. In this study, we had promoted research and development on brain funtional analysis system for MEG (magnetoencephalography), which can detect the change in magnetic field caused from brain activities, by leveraging Grid computing technology. Speficially, the system allows scientists to efficiently perform wavelet analysis to brain functional data obtained from multiple MEG sensors and then cross-correlation analysis to the anlyzed data on a Grid environment composed of multile computational resources, each of which may be located on a different organization. Also, we had worked on visualization software of analysis results.
 
This research was partly supported by MEXT IT program “Construction of supercomputer network” promoted by the Cybermedia Center, Osaka University.

Research achievements(Paper)：

• Rajkumar Buyya, Susumu Date, Yuko Mizuno-Matsumoto, Srikumar Venugopal, and David Abramson, Neuroscience Instrumentation and Distributed Analysis of Brain Activity Data: A Case for eScience on Global Grids, Journal of Concurrency and Computation: Practice and Experience (CCPE), Wiley Press, New York, USA, Vol. 17, No. 15, pp. 1783-1798, Dec. 2005.
• Yuko Mizuno-Matsumoto, Satoshi Ukai, Ryohei Ishii, Susumu Date, Takeshi Kaishima, Kazuhiro Shinosaki, Shinji Shimojo, Masatoshi Takeda, Shin’ichi Tamura, Tsuyoshi Inouye, “Wavelet-crosscorrelation analysis: non-stationary analysis of neurophysiological signals”, Brain Topography, Vol. 17, No. 4, pp.237-252, Jun. 2005.
• Susumu Date, Yuko Mizuno-Matsumoto, Shin’ichi Tamura, Yoshinobu Sato, A Zoroofi Reza, Yuji Tabuchi, Shinji Shimojo, Youki Kadobayashi, Haruyuki Tatsumi, Hiroki Nogawa, Kazuhiro Shinosaki, Masatoshi Takeda, Ken Inoue, Hideo Miyahara, “Metacomputing Environment for Magnetoencephalography(MEG)”, Medical Imaging Technology, Vol.18, No.1, pp.47-59, Jan. 2000.