ArticleFrontiers in human neuroscience2024
Global sensitivity of EEG source analysis to tissue conductivity uncertainties.
Article in Frontiers in human neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Forward model of rat electroencephalogram: influence of inhomogeneous and anisotropic skull.Scientific reports · 2026Article
- Appropriate Null Models for Testing the Effect of the Head Model on MEG Functional Connectivity Fingerprinting.Brain topography · 2026Article
- High-definition MEG source estimation using the reciprocal boundary element fast multipole method.NeuroImage · 2025Article
- Comparison of tripolar and traditional EEG recording of the visual evoked potential.Vision research · 2025Article
- A Case Study on EEG Signal Correlation Towards Potential Epileptic Foci Triangulation.Sensors (Basel, Switzerland) · 2024Article
- Improving EEG Forward Modeling Using High-Resolution Five-Layer BEM-FMM Head Models: Effect on Source Reconstruction Accuracy.Bioengineering (Basel, Switzerland) · 2024Article
- Accuracy of dipole source reconstruction in the 3-layer BEM model against the 5-layer BEM-FMM model.bioRxiv : the preprint server for biology · 2024Article
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Abstract
Introduction: To reliably solve the EEG inverse problem, accurate EEG forward solutions based on a detailed, individual volume conductor model of the head are essential. A crucial-but often neglected-aspect in generating a volume conductor model is the choice of the tissue conductivities, as these may vary from subject to subject. In this study, we investigate the sensitivity of EEG forward and inverse solutions to tissue conductivity uncertainties for sources distributed over the whole cortex surface. Methods: We employ a detailed five-compartment head model distinguishing skin, skull, cerebrospinal fluid, gray matter, and white matter, where we consider uncertainties of skin, skull, gray matter, and white matter conductivities. We use the finite element method (FEM) to calculate EEG forward solutions and goal function scans (GFS) as inverse approach. To be able to generate the large number of EEG forward solutions, we employ generalized polynomial chaos (gPC) expansions. Results: For sources up to a depth of 4 cm, we find the strongest influence on the signal topography of EEG forward solutions for the skull conductivity and a notable effect for the skin conductivity. For even deeper sources, e.g., located deep in the longitudinal fissure, we find an increasing influence of the white matter conductivity. The conductivity variations translate to varying source localizations particularly for quasi-tangential sources on sulcal walls, whereas source localizations of quasi-radial sources on the top of gyri are less affected. We find a strong correlation between skull conductivity and the variation of source localizations and especially the depth of the reconstructed source for quasi-tangential sources. We furthermore find a clear but weaker correlation between depth of the reconstructed source and the skin conductivity. Discussion: Our results clearly show the influence of tissue conductivity uncertainties on EEG source analysis. We find a particularly strong influence of skull and skin conductivity uncertainties.
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