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 multilayer 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 results show convergence to the quasi-analytical solution and indicate a good accuracy of UDG-FEM. 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.
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 multilayer 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 results show convergence to the quasi-analytical solution and indicate a good accuracy of UDG-FEM. 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.
Authors: Marios Antonakakis; Sophie Schrader; Andreas Wollbrink; Robert Oostenveld; Stefan Rampp; Jens Haueisen; Carsten H Wolters Journal: Hum Brain Mapp Date: 2019-08-09 Impact factor: 5.038
Authors: Maria Carla Piastra; Andreas Nüßing; Johannes Vorwerk; Harald Bornfleth; Robert Oostenveld; Christian Engwer; Carsten H Wolters Journal: Front Neurosci Date: 2018-02-02 Impact factor: 4.677
Authors: Maria Carla Piastra; Andreas Nüßing; Johannes Vorwerk; Maureen Clerc; Christian Engwer; Carsten H Wolters Journal: Hum Brain Mapp Date: 2020-11-06 Impact factor: 5.399