A finite-element reciprocity solution for EEG forward modeling with realistic individual head models

作者：Ziegler Erik; Chellappa Sarah L; Gaggioni Giulia; Ly Julien Q M; Vandewalle Gilles; Andre Elodie; Geuzaine Christophe; Phillips Christophe^*

来源：NeuroImage, 2014, 103: 542-551.

DOI：10.1016/j.neuroimage.2014.08.056

• Electroencephalography
• EEG
• Forward model
• Diffusion

We present a finite element modeling (FEM) implementation for solving the forward problem in electroencephalography (EEG). The solution is based on Helmholtz%26apos;s principle of reciprocity which allows for dramatically reduced computational time when constructing the leadfield matrix. The approach was validated using a 4-shell spherical model and shown to perform comparably with two current state-of-the-art alternatives (OpenMEEG for boundary element modeling and SimBio for finite element modeling). %26lt;br%26gt;We applied the method to real human brain MRI data and created a model with five tissue types: white matter, gray matter, cerebrospinal fluid, skull, and scalp. By calculating conductivity tensors from diffusion-weighted MR images, we also demonstrate one of the main benefits of FEM: the ability to include anisotropic conductivities within the head model. Root-mean square deviation between the standard leadfield and the leadfield including white-matter anisotropy showed that ignoring the directional conductivity of white matter fiber tracts leads to orientation-specific errors in the forward model. %26lt;br%26gt;Realistic head models are necessary for precise source localization in individuals. Our approach is fast, accurate, open-source and freely available online.

• 出版日期2014-12