The aim of this paper is to evaluate the performance of an EEG source localization method that combines a finite element method (FEM) and the reciprocity theorem.The reciprocity method is applied to solve the forward problem in a four-layer spherical head model for a large number of test dipoles. To benchmark the proposed method, the results are compared with an analytical solution and two state-of-the-art methods from the literature. Moreover, the dipole localization error resulting from utilizing the method in the inverse procedure for a realistic head model is investigated with respect to EEG signal noise and electrode misplacement.The results show approximately 3% relative error between numerically calculated potentials done by the reciprocity theorem and the analytical solutions. When adding EEG noise with SNR between 5 and 10, the mean localization error is approximately 4.3 mm. For the case with 10 mm electrode misplacement the localization error is 4.8 mm. The reciprocity EEG source localization speeds up the solution of the inverse problem with more than three orders of magnitude compared to the state-of-the-art methods.The reciprocity method has high accuracy for modeling the dipole in EEG source localization, is robust with respect to noise, and faster than alternative methods.
Biomedical Engineering Letters, 2013, Vol 3, Issue 1, p. 8-16
Reciprocity theorem; EEG source localization; Finite element method; Inverse problem; MRI; Realistic head model