title: A finite-element reciprocity solution for EEG forward modeling with realistic individual head models.
abstract: We present a finite element modeling (FEM) implementation for solving the forward problem in electroencephalography (EEG). The solution is based on Helmholtz'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). 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. Realistic head models are necessary for precise source localization in individuals. Our approach is fast, accurate, open-source and freely available online.
authors.affiliation: Cyclotron Research Centre, University of Liège, Liège, Belgium. Electronic address: erik.ziegler@ulg.ac.be.
authors.forename: Erik
authors.initials: E
authors.lastname: Ziegler
authors.affiliation: Cyclotron Research Centre, University of Liège, Liège, Belgium.
authors.forename: Sarah L
authors.initials: SL
authors.lastname: Chellappa
authors.affiliation: Cyclotron Research Centre, University of Liège, Liège, Belgium.
authors.forename: Giulia
authors.initials: G
authors.lastname: Gaggioni
authors.affiliation: Cyclotron Research Centre, University of Liège, Liège, Belgium.
authors.forename: Julien Q M
authors.initials: JQM
authors.lastname: Ly
authors.affiliation: Cyclotron Research Centre, University of Liège, Liège, Belgium.
authors.forename: Gilles
authors.initials: G
authors.lastname: Vandewalle
authors.affiliation: Cyclotron Research Centre, University of Liège, Liège, Belgium.
authors.forename: Elodie
authors.initials: E
authors.lastname: André
authors.affiliation: Department of Electrical Engineering and Computer Science, University of Liège, Liège, Belgium.
authors.forename: Christophe
authors.initials: C
authors.lastname: Geuzaine
authors.affiliation: Cyclotron Research Centre, University of Liège, Liège, Belgium; Department of Electrical Engineering and Computer Science, University of Liège, Liège, Belgium. Electronic address: c.phillips@ulg.ac.be.
authors.forename: Christophe
authors.initials: C
authors.lastname: Phillips
mesh_terms: D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D038524:Diffusion Magnetic Resonance Imaging; D004569:Electroencephalography; D020342:Finite Element Analysis; D006257:Head; D006801:Humans; D008959:Models, Neurological; D008962:Models, Theoretical
keywords: Diffusion; EEG; Electroencephalography; Forward model