Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction

Abstract

Reliable EEG source analysis depends on sufficiently detailed and accurate head models. In this study, we investigate how uncertainties inherent to the experimentally determined conductivity values of the different conductive compartments influence the results of EEG source analysis. In a single source scenario, the superficial and focal somatosensory P20/N20 component, we analyze the influence of varying conductivities on dipole reconstructions using a generalized polynomial chaos (gPC) approach. We find that in particular the conductivity uncertainties for skin and skull have a significant influence on the EEG inverse solution, leading to variations in source localization by several centimeters. The conductivity uncertainties for gray and white matter were found to have little influence on the source localization, but a strong influence on the strength and orientation of the reconstructed source, respectively. As the CSF conductivity is most accurately determined of all conductivities in a realistic head model, CSF conductivity uncertainties had a negligible influence on the source reconstruction. This small uncertainty is a further benefit of distinguishing the CSF in realistic volume conductor models.

Keywords: EEG dipole reconstruction; EEG source analysis; conductivity estimation; conductivity uncertainty; finite element method; generalized polynomial chaos; head modeling; sensitivity analysis.

Figure 1

(A) Butterfly plot of preprocessed SEP data. Vertical black line marks +22.5 ms. (B) Topography plot of preprocessed SEP data at +22.5 ms. Values are indicated in μV.

Figure 2

(A) GFS source reconstruction (turquoise cone) and simulated electrode voltages for reconstructed source. (B) Standard deviation for each electrode for the multivariate distribution. The electrodes with the highest standard deviation (F2, F4, C4, CP4) are marked with their labels. All values in μV.

Figure 3

Sobol indices as a function of the electrode voltages.

Figure 4

Visualization of the source localizations for the multivariate distribution overlaid on the T1-MRI showing the full head (A–C) and a detail around the source locations (D–F). From left to right showing sagittal (A,D), coronal (B,E), and axial slices (C,F). Color bar ranges from low frequency of source localizations (blue) to high frequency of source localizations (red). Values are normalized to the maximum for each slice.

Figure 5

Scatter plots of source strength (A) and GoF (B) for GFS with fixed dipole location and orientation as a function of the tissue conductivity for univariate distributions. Dipole location and orientation are chosen according to the initial dipole reconstruction (see section 2.3). Conductivities are normalized to the interval from 0 to 1 for clarity of the visualization.

Figure 6

Scatter plots of change in elevation angle (ϑ, A) and GoF (B) for GFS with fixed dipole location and free orientation as a function of the tissue conductivity for univariate distributions. Dipole location is chosen according to the initial dipole reconstruction (see section 2.3). Conductivities are normalized to the interval from 0 to 1 for clarity of the visualization.

Figure 7

Scatter plots of source depth (A) and GoF (B) for GFS with free location and orientation as a function of the tissue conductivity for univariate distributions. Conductivities are normalized to the interval from 0 to 1 for clarity of the visualization. Plots for CSF and gray matter are slightly shifted in positive and negative y-direction, respectively, since sources for CSF, gray matter, and partially white matter are localized at the same depth.

Figure 8

Scatter plots of source depth as a function of the tissue conductivity for the multivariate distribution for skin (A) and skull (B).

Figure 9

Image plot of source depth as a function of skin and skull conductivities for the multivariate distribution. Contours mark isolines of the source depth.

Figure 10

Visualization of the source locations with maximal GoF for the uni- and multivariate distributions overlaid on the T1-MRI (blue - skin, green - skull, yellow - CSF, gray matter, white matter, red - multivariate). From left to right showing sagittal (A), coronal (B), and axial slice (C). In the sagittal slice (A) the visualizations for skin and CSF, gray matter, and white matter are overlaying.