title: Low resolution brain electromagnetic tomography in a realistic geometry head model: a simulation study.
abstract: It is of importance to localize neural sources from scalp recorded EEG. Low resolution brain electromagnetic tomography (LORETA) has received considerable attention for localizing brain electrical sources. However, most such efforts have used spherical head models in representing the head volume conductor. Investigation of the performance of LORETA in a realistic geometry head model, as compared with the spherical model, will provide useful information guiding interpretation of data obtained by using the spherical head model. The performance of LORETA was evaluated by means of computer simulations. The boundary element method was used to solve the forward problem. A three-shell realistic geometry (RG) head model was constructed from MRI scans of a human subject. Dipole source configurations of a single dipole located at different regions of the brain with varying depth were used to assess the performance of LORETA in different regions of the brain. A three-sphere head model was also used to approximate the RG head model, and similar simulations performed, and results compared with the RG-LORETA with reference to the locations of the simulated sources. Multisource localizations were discussed and examples given in the RG head model. Localization errors employing the spherical LORETA, with reference to the source locations within the realistic geometry head, were about 20-30 mm, for four brain regions evaluated: frontal, parietal, temporal and occipital regions. Localization errors employing the RG head model were about 10 mm over the same four brain regions. The present simulation results suggest that the use of the RG head model reduces the localization error of LORETA, and that the RG head model based LORETA is desirable if high localization accuracy is needed.
authors.affiliation: Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
authors.forename: Lei
authors.initials: L
authors.lastname: Ding
authors.forename: Yuan
authors.initials: Y
authors.lastname: Lai
authors.forename: Bin
authors.initials: B
authors.lastname: He
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping; D003198:Computer Simulation; D004566:Electrodes; D004569:Electroencephalography / Q000379:methods*; D055590:Electromagnetic Phenomena; D006257:Head / Q000473:pathology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008953:Models, Anatomic; D008962:Models, Theoretical; D012535:Scalp / Q000473:pathology; D012984:Software; D014054:Tomography / Q000379:methods*; D014793:Visual Cortex / Q000473:pathology