Realistic and spherical head modeling for EEG forward problem solution: a comparative cortex-based analysis

Authors:
Federica Vatta;Fabio Meneghini;Fabrizio Esposito;Stefano Mininel;Francesco Di Salle
Affiliations:
DEEI, University of Trieste, Trieste, Italy;DEEI, University of Trieste, Trieste, Italy;Department of Neurological Sciences, University of Naples Federico II, Naples, Italy and Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands;DEEI, University of Trieste, Trieste, Italy;Department of Cognitive Neuroscience, Maastricht University, The Netherlands
Venue:
Computational Intelligence and Neuroscience - Special issue on processing of brain signals by using hemodynamic and neuroelectromagnetic modalities
Year:
2010

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Improved localizadon of cortical activity by combining eeg and meg with mri cortical surface reconstruction: A linear approach

Journal of Cognitive Neuroscience

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Abstract

The accuracy of forward models for electroencephalography (EEG) partly depends on head tissues geometry and strongly affects the reliability of the source reconstruction process, but it is not yet clear which brain regions are more sensitive to the choice of different model geometry. In this paper we compare different spherical and realistic head modeling techniques in estimating EEG forward solutions from current dipole sources distributed on a standard cortical space reconstructed from Montreal Neurological Institute (MNI) MRI data. Computer simulations are presented for three different four-shell head models, two with realistic geometry, either surface-based (BEM) or volume-based (FDM), and the corresponding sensor-fitted spherical-shaped model. Point Spread Function (PSF) and Lead Field (LF) cross-correlation analyses were performed for 26 symmetric dipole sources to quantitatively assess models' accuracy in EEG source reconstruction. Realistic geometry turns out to be a relevant factor of improvement, particularly important when considering sources placed in the temporal or in the occipital cortex.