Human head models for the EEG forward problem

Solution of the forward problem using realistic head models is necessary for accurate EEG source analysis. For this purpose, realistic shapes of head tissues have been derived from a set of 2-D magnetic resonance images (MRI) by extracting surface boundaries for the major tissues, such as the scalp, the skull, the cerebrospinal fluid (CSF), the white matter and the gray matter. From boundary data a 3-D volume generic head model has been constructed and a mesh for an arbitrary complexity head shape has been generated for finite-element method (FEM) modelling. This paper first addresses the use of this realistic Finite Elements head model to solve the EEG forward problem. The influence of head model complexity on the electrical potentials values on the scalp is then examined with different human head models. It was shown that the structure of the anatomical surfaces of the CSF, the gray and the white matter could significantly influence the signal data calculated on the scalp.