Online Distributed Source Localization from EEG/MEG Data

Abstract

Electroencephalography (EEG) and Magnetoencephalography (MEG) provide insight into neuronal processes in the brain in a real-time scale. This renders these modalities particularly interesting for online analysis methods, e.g. to visualize brain activity in real-time. 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). We present a system that, according to its modular scheme, can be configured in a very flexible way using graphical building blocks. Different preprocessing algorithms together with a linear source reconstruction method can be used for online analysis. The algorithms use both CPU and GPU resources. We tested our system in a simulation and in a realistic experiment.