Improving EEG source analysis using prior knowledge

The research described in this thesis covers different aspects of EEG and ERP source modeling. Both basic research in volume conduction and source modeling, as well as application of inverse source modeling techniques to experimental data are described. This thesis demonstrates how prior information can be applied in physical models that are used for source analysis of the EEG. It shows that realistic volume conduction models can be used that incorporate holes in the skull. The accurate placement of electrodes for high-density EEG measurements is described. It discusses how information on symmetry of sources in the brain can be used, and what the influence of incorrectly assumed symmetry in the sources is. The application of prior information on source locations is demonstrated in a forward modeling approach. A high-resolution EEG experiment is described to which source analysis was applied, making use of the prior information available in this experiment. In general, this thesis demonstrates that the application of source modeling can provide valuable information in EEG analysi