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Computational Intelligence and Neuroscience
Volume 2010 (2010), Article ID 972060, 11 pages
http://dx.doi.org/10.1155/2010/972060
Research Article

Realistic and Spherical Head Modeling for EEG Forward Problem Solution: A Comparative Cortex-Based Analysis

1DEEI, University of Trieste, Via A. Valerio 10, 34127 Trieste, Italy
2Department of Neurological Sciences, University of Naples Federico II, II Policlinico Padiglione 17, Via S. Pansini 5, 80131 Naples, Italy
3Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands

Received 24 June 2009; Revised 20 August 2009; Accepted 9 November 2009

Academic Editor: Fabio Babiloni

Copyright © 2010 Federica Vatta et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.