Search

The lack of computational power within an organization for analyzing scientific data, and the distribution of knowledge (by scientists) and technologies (advanced scientific devices) are two major problems commonly observed in scientific disciplines. One such scientific discipline is brain science. The analysis of brain activity data gathered from the MEG (Magnetoencephalography) instrument is an important research topic in medical science since it helps doctors in identifying symptoms of diseases. The data needs to be analyzed exhaustively to efficiently diagnose and analyze brain functions and requires access to large-scale computational resources. The potential platform for solving such resource intensive applications is the Grid. This paper describes a MEG data analysis system developed by us, leveraging Grid technologies, primarily Nimrod-G, Gridbus, and Globus. This paper explains the application of economy-based grid scheduling algorithms to the problem domain for on-demand processing of analysis jobs., Comment: Technical Report, Grid Computing and Distributed Systems (GRIDS) Lab, Dept. of Computer Science and Software Engineering, The University of Melbourne, Australia

SAM(g2) analysis, a combination of synthetic aperture magnetometry (SAM) and excess kurtosis (g2) method, is a novel epilepsy analysis procedure based on a spatial filtering technique. By producing a three-dimensional image of the g2 values and superimposing them onto a patient's MR images, this analysis can automatically estimate spike localization from raw MEG epilepsy signals including spikes. The aim of this study is to examine SAM(g2) analysis using MEG signals of an epileptic patient, whose clinical symptoms of colored elementary visual auras had ceased in accordance with the changes of the estimated localizations of the equivalent current dipoles (ECDs) of the interictal spikes. His visual auras were experienced in 1997, while they ceased in 1999 with effective medication. The patient provided written informed consent for the experimental procedures. The MEG signals were recorded in 1997 and 1999, and were analyzed using both ECD and SAM(g2) analyses. For the MEG signals of 1997, ECD analysis estimated most of the interictal spikes in the right fusiform and inferior temporal gyri, which subserve human color processing. SAM(g2) analysis also estimated them in the same areas. For those of 1999, both ECD and SAM(g2) analyses estimated them in the right transverse gyrus of Heschl. As well as ECD analysis, SAM(g2) analysis successfully estimated the changes of the localizations of the interictal spikes in accordance with the changes of the patient's clinical symptoms, indicating that SAM(g2) analysis is useful for detection of interictal spike localization in epileptic patients.