Scientific applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific applications than we could ever achieve in a single compute resource.In this paper, we present the processing of Image Registration (IR) for Functional Magnetic Resonance Imaging(fMRI) studies on global Grids. We characterize the application, list its requirements and transform it to a workflow. We then execute the application on Grid’5000 platform and present extensive performance results. We show that the IR application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.