POSTDOC: The Development of a 3D Parallel Finite Element Model for EEG and MEG Source Localization

点击翻译按钮获取中文摘要

The temporal dynamics of information processing in the brain can be studied using electroencephalography (EEG) or magnetoencephalpgrahpy (MEG), but the spatial resolution of these techniques is often poor due to crude mathematical models. Accuracy and resolution can be improved by using finite elements to model the realistic geometry and electrical conductivity of the head and grain. A 2D EEG source localization code based on a finite element method has been developed, but extending this to the 3D realistic-shaped head model will require a huge increase in computational speed. Source localization in a 3D finite element model requires the solution of a large system of equations (more than 100,000) for hundreds of iterations for each time point in a brainwave that may last for seconds. Therefore, to make this computations practicable the 3D EEG code will be optimized and parallelized to run on one of the CRAY supercomputers at the Pittsburgh Supercomputing Center or on a cluster of 80 Hewlett-Packard workstations at the University of Pittsburgh Medical Center. During the second year, a 3D MEG source localization code will be developed and parallelized. This is a straightforward and relatively simple task once the 3D EEG code is parallelized, because the solution of the same system of equations is needed for both EEG and MEG. The fellowship will help broaden the research Associate's knowledge in code optimization, code parallelization and the neurosciences through participation in formal courses, workshops, seminars and consultation with a group of multi-disciplinary advisops in computer science, mathematics, neurophysiology and engineering. The code developed from this project will be made available through the domain to help other researchers utilize accurate and efficient source localization models.