Comparison of realistic head modeling methods in EEG source imaging - biomed 2010

EEG inverse source imaging aims at reconstructing the underlying current distribution in the human brain using potential differences measured non-invasively from the head surface. A critical component of source reconstruction is the head volume conductor model used to reach an accurate solution of the associated forward problem, i.e., the simulation of the EEG for a known current source in the brain. The volume conductor model contains both the geometry and the electrical conduction properties of the head tissues and the accuracy of both parameters has direct impact on the accuracy of the source analysis. This was examined in detail with two different human head models. Two realistic head models derived from an averaged T1-weighted MRI dataset of the Montreal Neurological Institute (MNI) were used for this study. These models were: (1) BEM Model: a four-shell surface-based Boundary Elements (BEM) head model; (2) FDM Model: a volume-based Finite Difference (FDM) model, which allows better modeling accuracy than BEM as it better represents the cortical structures, such as, sulci and gyri in the brain in a three-dimensional head model. How model accuracy description influences the EEG source localizations was studied with the above realistic models of the head. We present here a detailed computer simulation study in which the performances of the two realistic four-shell head models are compared, the realistic MNI-based BEM Model and the FDM Model. As figures of merit for the comparative analysis, the point spread function (PSF) maps and the lead field (LF) correlation coefficients are used. The obtained results demonstrate that a better description of realistic geometry can provide a factor of improvement particularly important when considering sources placed in the temporal or in the occipital cortex. In these situations, using a more refined realistic head model will allow a better spatial discrimination of neural sources.