Brain sources estimation based on EEG and computer simulation technology (CST). (September 2018)

• Record Type: Journal Article
• Authors: Taha, Ibrahem; Cook, Gregory
• Is Part Of: Biomedical signal processing and control. Volume 46(2018)
• Page Start: 145
• Page End: 156
• Publication Date: 2018-09
• Subjects: Forward model -- Sources estimation -- EEG -- BCI -- CST; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2018.03.011
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: The EEG forward model has a significant influence on brain sources estimation. An EEG forward model based on EEG and Computer Simulation Technology (CST) is proposed. The proposed model employs MRI, EEG, and CST to generate the leadfield matrix. The result provides accurate EEG forward model to be used for brain sources estimation and BCI. Abstract: EEG source estimation aims to provide precise information about the location of active brain source that corresponds to the measured signals. The accuracy of EEG forward model significantly influences the accuracy and performance of the inverse problem. In this research, we propose a new method to model head volume conductor and generate a leadfield matrix. The solution is based on employing electromagnetic simulation (CST electromagnetic software) to generate a leadfield matrix of a realistic head. The geometrical data consist of three compartments (Brain, Skull, and Scalp) obtained from real human MRI data. Finite Element Method (FEM) was used in the CST low frequency solver to generate the forward model. We were able to demonstrate the use of the electromagnetic simulation solvers in solving the EEG forward problem. The result has been validated by comparing the scalp voltage potential distribution obtained using CST with scalp potential calculated using FieldTrip (EEG/MEG open source). To further validate the proposed technique, an inverse solution was able to estimate the location of active dipoles within brain successfully based on the calculated leadfield matrix using CST.