  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.
