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Estimating vector fields using sparse basis field expansions
Stefan Haufe · Vadim Nikulin · Andreas Ziehe · Klaus-Robert Müller · Guido Nolte

Mon Dec 08 08:45 PM -- 12:00 AM (PST) @

We introduce a novel framework for estimating vector fields using sparse basis field expansions (S-FLEX). The notion of basis fields, which are an extension of scalar basis functions, arises naturally in our framework from a rotational invariance requirement. We consider a regression setting as well as inverse problems. All variants discussed lead to second-order cone programming formulations. While our framework is generally applicable to any type of vector field, we focus in this paper on applying it to solving the EEG/MEG inverse problem. It is shown that significantly more precise and neurophysiologically more plausible location and shape estimates of cerebral current sources from EEG/MEG measurements become possible with our method when comparing to the state-of-the-art.

Author Information

Stefan Haufe (Berlin Institute of Technology)
Vadim Nikulin
Andreas Ziehe (Fraunhofer FIRST)
Klaus-Robert Müller (TU Berlin)
Guido Nolte

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