Optimal spatial filtering for brain oscillatory activity using the Relevance Vector Machine

Abstract

Over the past decade, various techniques have been proposed for localization of cerebral sources of oscillatory activity on the basis of magnetoencephalography (MEG) or electroencephalography recordings. Beamformers in the frequency domain, in particular, have proved useful in this endeavor. However, the localization accuracy and efficacy of such spatial… (More)
DOI: 10.1007/s10339-013-0568-y

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Cite this paper

@article{Belardinelli2013OptimalSF, title={Optimal spatial filtering for brain oscillatory activity using the Relevance Vector Machine}, author={Paolo Belardinelli and A. Jalava and Joachim Gross and Jan Kujala and Riitta Salmelin}, journal={Cognitive Processing}, year={2013}, volume={14}, pages={357-369} }