BrianNielsen's source [2 articles]

Abstract

An extension of the infomax algorithm of Bell & Sejnowski (1995) is presented that is able to separate the mixed sub- and super-Gaussian source distributions. The same learning rule has been derived by Girolami & Fyfe (1997) from the negentropy perspective for projection pursuit. Using a Laplacian prior we also propose a learning rule that is especially convenient to realize in hardware. The natural gradient extension is presented from different perspectives and the use of preprocessing steps is proposed to further ...

Abstract

We investigated spatial properties of the source distributions that generate scalp electroencephalographic (EEG) oscillations. The inherent complexity of the spatio-temporal dynamics of EEG oscillations indicates that conceptual models that view source activity as consisting only of a few "equivalent dipoles" are inadequate. We present an approach that uses volume conduction models to characterize the distinct spatial filtering of cortical source activity by average reference EEG, high-resolution EEG, and magnetoencephalography (MEG). By comparing these three measures, we can make inferences about the ...