title: Improved surface Laplacian estimates of cortical potential using realistic models of head geometry.
abstract: Surface Laplacian of scalp EEG can be used to estimate the potential distribution on the cortical surface as an alternative to invasive approaches. However, the accuracy of surface Laplacian estimation depends critically on the geometric shape of the head model. This paper presents a new method for computing the surface Laplacian of scalp potential directly on realistic scalp surfaces in the form of a triangular mesh reconstructed from MRI scans. Unlike previous methods, this algorithm does not resort to any surface fitting proxy and can improve the surface Laplacian estimation of cortical potential patterns by as much as 34% on realistically shaped head models. Simulations and experimental data are presented to demonstrate the advantage of the proposed method over the conventional spherical approximation and the utility of a more accurate surface Laplacian method for estimating cortical potentials from scalp electrodes.
authors.affiliation: Department of Cognitive Sciences, University of California, Irvine, CA 92697, USA. sdeng@uci.edu
authors.forename: Siyi
authors.initials: S
authors.lastname: Deng
authors.forename: William
authors.initials: W
authors.lastname: Winter
authors.forename: Samuel
authors.initials: S
authors.lastname: Thorpe
authors.forename: Ramesh
authors.initials: R
authors.lastname: Srinivasan
mesh_terms: D000465:Algorithms; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000502:physiology*; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D005074:Evoked Potentials, Visual / Q000502:physiology; D006801:Humans; D008953:Models, Anatomic; D012535:Scalp / Q000033:anatomy & histology* / Q000502:physiology*