Abstract
The finite element method (FEM) is a numerical method that is often used for solving electroencephalography (EEG) forward problems involving realistic head models. In this study, FEM solutions obtained using three different mesh structures, namely coarse, densely refined, and adaptively refined meshes, are compared. The simulation results showed that the accuracy of FEM solutions could be significantly enhanced by adding a small number of elements around regions with large estimated errors. Moreover, it was demonstrated that the adaptively refined regions were always near the current dipole sources, suggesting that selectively generating additional elements around the cortical surface might be a new promising strategy for more efficient FEM-based EEG forward analysis.
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Acknowledgements
This work was supported in part by Institute for Information & communications Technology Promotion (IITP) Grant funded by the Korea government (MSIT) (2017-0-00432) and in part by the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2015M3C7A1031969).
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Lee, C., Im, CH. New Strategy for Finite Element Mesh Generation for Accurate Solutions of Electroencephalography Forward Problems. Brain Topogr 32, 354–362 (2019). https://doi.org/10.1007/s10548-018-0669-0
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DOI: https://doi.org/10.1007/s10548-018-0669-0