title: A spline framework for estimating the EEG surface laplacian using the Euclidean metric.
abstract: This letter develops a framework for EEG analysis and similar applications based on polyharmonic splines. This development overcomes a basic problem with the method of splines in the Euclidean setting: that it does not work on low-degree algebraic surfaces such as spherical and ellipsoidal scalp models. The method's capability is illustrated through simulations on the three-sphere model and using empirical data.
authors.affiliation: Center for the Study of Language and Information, Stanford University, Stanford, CA, 94305-4101, USA. claudioc@stanford.edu
authors.forename: Claudio G
authors.initials: CG
authors.lastname: Carvalhaes
authors.forename: Patrick
authors.initials: P
authors.lastname: Suppes
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography; D006801:Humans; D012815:Signal Processing, Computer-Assisted