Tissue conductivity anisotropy inhomogeneity study in EEG head modelling

Abstract

This study investigates the effects of anisotropic inhomogeneous tissue conductivity with local variations on the electroencephalogram (EEG) forward computation. Human head modelling for the forward computation using finite element method (FEM) requires a large set of elements to represent the head geometry. Anatomically, the electrical property of each element is different, even though it represents the same type of tissue. At microscopic level, tissues are anisotropic and inhomogeneous. However, most of the researchers implement the computation for the homogeneous case. This paper presents a numerical approach to model a human head by using statistical conductivity approximation (SCA) technique for the computation based on white matter (WM) and skull anisotropic inhomogeneity. FEM is used to model the head volume conductor with WM and skull anisotropic inhomogeneous conductivity estimated by the volume constrained method. A current dipole is also used inside the gray matter to simulate the brain electrical activity. The experimental results show that the anisotropic inhomogeneous tissue conductivity has effects on the scalp EEG..