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Book Chapter

Forward modeling and tissue conductivities


Knösche,  Thomas R.
Methods and Development Group MEG and EEG - Cortical Networks and Cognitive Functions, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Haueisen, J., & Knösche, T. R. (2014). Forward modeling and tissue conductivities. In S. Supek, & C. J. Aine (Eds.), Magnetoencephalography (pp. 107-127). Berlin: Springer.

Cite as: https://hdl.handle.net/11858/00-001M-0000-002A-07F1-9
The neuroelectromagnetic forward model describes the prediction of measurements from known sources. It includes models for the sources and the sensors as well as an electromagnetic description of the head as a volume conductor, which are discussed in this chapter. First we give a general overview on the forward problem and discuss various simplifications and assumptions that lead to different analytical and numerical methods. Next, we introduce important analytical models which assume simple geometries of the head. Then we describe numerical models accounting for realistic geometries. The most important numerical methods for head modeling are the boundary element method (BEM) and the finite element method (FEM). The boundary element method describes the head by a small number of compartments, each with a homogeneous isotropic conductivity. In contrast, the finite element method discretizes the 3D distribution of the anisotropic conductivity tensor with the help of small volume elements. Subsequently, we discuss in some detail how electrical conductivity information is measured and how it is used in forward modeling. Finally, we briefly introduce the lead field concept.