Abstract
We study the influence of realistic head modeling on the EEG forward problem. To this end, we define a high-resolution patient-specific realistic head model from 3T-MRI and DWI data. Further, we performed a nine tissues segmentation and a white matter anisotropy estimation. Then we solve the forward problem using a state-of-the-art FDM solution that allows volumetric voxelwise anisotropic definition in a reciprocity sensors space. Finally, we compared the 9-tissues realistic head model against the commonly used 5-tissues isotropic representation. Our results show significant potential deviations due to the white matter anisotropy, and radio to tangential patterns in the outer skull regions as a direct effect of essential tissues like fat or muscle. Moreover, we analyze the dipole estimation errors in a parametric inverse setup, finding DLE’s larger than 20 mm. Additionally, we study the influence of neglecting the blood vessels, finding DLE’s larger than 4 mm in deep brain areas.
This research was supported by the research project 36706 “BrainScore: Sistema compositivo, gráfico y sonoro creado a partir del comportamiento frecuencial de las señales cerebrales”, funded by Universidad de Caldas and Universidad Nacional de Colombia.
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Morales, E.C., Villar, Y.R.C., Cardona, H.F.T., Acosta, C.D., Dominguez, G.C. (2018). Influence of Realistic Head Modeling on EEG Forward Problem. In: Wang, S., et al. Brain Informatics. BI 2018. Lecture Notes in Computer Science(), vol 11309. Springer, Cham. https://doi.org/10.1007/978-3-030-05587-5_4
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DOI: https://doi.org/10.1007/978-3-030-05587-5_4
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