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EEG and MEG source localization using recursively applied (RAP) MUSIC

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2 Author(s)
Mosher, J.C. ; Los Alamos Nat. Lab., NM, USA ; Leahy, R.M.

The multiple signal characterization (MUSIC) algorithm locates multiple asynchronous dipolar sources from electroencephalography (EEG) and magnetoencephalography (MEG) data. A signal subspace is estimated from the data, then the algorithm scans a single dipole model through a three-dimensional head volume and computes projections onto this subspace. To locate the sources, the user must search the head volume for local peaks in the projection metric. We describe a novel extension of this approach which we refer to as RAP (recursively applied) MUSIC. This new procedure automatically extracts the locations of the sources through a recursive use of subspace projections, which uses the metric of principal correlations as a multidimensional form of correlation analysis between the model subspace and the data subspace. The dipolar orientations, a form of "diverse polarization", are easily extracted using the associated principal vectors.

Published in:

Signals, Systems and Computers, 1996. Conference Record of the Thirtieth Asilomar Conference on

Date of Conference:

3-6 Nov. 1996