4.6 Article

Anisotropic Conductivity of Rat Head Phantom and Its Influence on Electroencephalogram Source Localization

Journal

IEEE ACCESS
Volume 10, Issue -, Pages 9877-9888

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3143952

Keywords

Rat head phantom; electroencephalogram; source localization; white matter anisotropic conductivity; conductivity measurement; agar; 3D printing

Funding

  1. Czech Science Foundation [18-16218S]
  2. Internal Grant Agency of Brno University of Technology [FEKT-S-20-6526]

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This study focuses on the development of a simplified anisotropic rat head phantom and investigates the impact of anisotropic white matter on EEG source localization. The use of 3D printing technology for fabrication and the identification of areas most sensitive to neglecting anisotropy in the model are highlighted.
In this paper we deal with a simplified anisotropic rat head phantom development and the investigation of the influence of the anisotropic white matter on electroencephalogram source localization. The proposed phantom is based on the cubic cross cell composition combined with agar mixture to set desired electrical conductivity anisotropic ratio. For the fabrication of the phantom, the 3D printed technology is exploited. Starting from a real rat brain, we proposed a simplified brain model incorporating the actual dimensions, shape and conductivity parameters of both grey and white matter containing simultaneously relevant deep-brain electrical signal sources. Five testing dipoles were located in the areas corresponding to the active brain regions. A single dipole localization error was calculated by comparing an inverse solution with a dipole position obtained from a computer tomography image. Neglecting anisotropy had a rather weak effect on localization error of a single testing dipole in our model. The reliability map was computed and interpreted in terms of spatial similarity between distributed inverse solutions involving isotropic and anisotropic forward models. We found spatially specific error increases located close to the electrodes and in the vicinity of anisotropic compartment. Hence, areas to be most sensitive to neglecting anisotropy in our model were identified.

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