EEG and MEG: forward modeling

Munck, J.C. de; Wolters, Carsten H.; Clerc, Maureen

doi:10.1017/cbo9780511979958.006

Cited by 42 publications

(52 citation statements)

References 100 publications

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“…The EEG forward problem can be solved by providing a solution to Poisson's equation which results from the quasistatic Maxwell's equations [1], [2]. Let Ω ⊂ R 3 denote the head domain and ∂Ω its surface.…”

Section: Theory a A Discontinuous Galerkin (Dg-fem) Methods For Smentioning

confidence: 99%

“…For standard CG-FEM, several different source models have been proposed, such as the partial integration [12], [17], [19], the Saint-Venant [2], [20], the Whitney or Raviart Thomas [18], [37] or the subtraction approach [13], [38]. In principle, the presented method is applicable to any given source model.…”

Section: A Source Modelmentioning

confidence: 99%

“…In order to reduce the computational load when solving the EEG forward problem for many sources, we use a fast transfer matrix approach [2], [12], [14] , which is also related to the adjoint method [40]. In most cases, we are not interested in the potential in the whole volume conductor, but only in the potential difference at a set of N e electrode positions p 1 , .…”

Section: B Transfer Matrixmentioning

confidence: 99%

“…The localization of current sources in the human brain from surface electroencephalography (EEG) measurements (the inverse problem) requires a model for the forward problem, i.e., the determination of surface potentials from current sources in the cortical sheet of the human brain [1], [2]. Several different approaches have been proposed to solve the EEG forward problem.…”

Section: Introductionmentioning

confidence: 99%

“…The latter were shown to produce highly accurate solutions [19]. In combination with transfer matrices and efficient linear solvers [2], [12], [14], the computational effort could be reduced. By using volumetric meshes, they are able to handle anisotropic conductivities and complex model geometries [21].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

The Unfitted Discontinuous Galerkin Method for Solving the EEG Forward Problem

Nusing

Wolters

Brinck

et al. 2016

IEEE Trans. Biomed. Eng.

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Abstract-Objective: The purpose of this study is to introduce and evaluate the unfitted discontinuous Galerkin finite element method (UDG-FEM) for solving the electroencephalography (EEG) forward problem. Methods: This new approach for source analysis does not use a geometry conforming volume triangulation, but instead uses a structured mesh that does not resolve the geometry. The geometry is described using level set functions and is incorporated implicitly in its mathematical formulation. As no triangulation is necessary, the complexity of a simulation pipeline and the need for manual interaction for patient specific simulations can be reduced and is comparable with that of the FEM for hexahedral meshes. In addition, it maintains conservation laws on a discrete level. Here, we present the theory for UDG-FEM forward modeling, its verification using quasi-analytical solutions in multi-layer sphere models and an evaluation in a comparison with a discontinuous Galerkin (DG-FEM) method on hexahedral and on conforming tetrahedral meshes. We furthermore apply the UDG-FEM forward approach in a realistic head model simulation study. Results: The given results show convergence and indicate a good overall accuracy of the UDG-FEM approach. UDG-FEM performs comparable or even better than DG-FEM on a conforming tetrahedral mesh while providing a less complex simulation pipeline. When compared to DG-FEM on hexahedral meshes, an overall better accuracy is achieved. Conclusion: The UDG-FEM approach is an accurate, flexible and promising method to solve the EEG forward problem. Significance: This study shows the first application of the UDG-FEM approach to the EEG forward problem.

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Section: Theory a A Discontinuous Galerkin (Dg-fem) Methods For Smentioning

confidence: 99%