An online system for neuroelectromagnetic source imaging

Electroencephalography (EEG) and magnetoencephalography (MEG) provide insight into neuronal processes in the brain in a real-time scale. Brain activity can be modeled in terms of a source distribution found by solving the bioelectromagnetic inverse problem, e.g. using linear source reconstruction methods. Such methods are particularly suitable to be used on modern highly parallel processing systems, such as widely available graphic processing units (GPUs). The utilization of these capabilities paves the way for online neuroelectromagnetic source imaging. We present a system that, according to its modular scheme, can be configured in a very flexible way using graphical building blocks. It allows to use different preprocessing algorithms together with a linear source reconstruction method. The algorithms use both CPU and GPU resources.