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Particle filtering, beamforming and multiple signal classification for the analysis of magnetoencephalography time series: a comparison of algorithms. (English) Zbl 1186.92030
Summary: We present a comparison of three methods for the solution of the magnetoencephalography inverse problem. The methods are: a linearly constrained minimum variance beamformer, an algorithm implementing multiple signal classification with recursively applied projection and a particle filter for Bayesian tracking. Synthetic data with neurophysiological significance are analyzed by the three methods to recover position, orientation and amplitude of the active sources. Finally, a real data set evoked by a simple auditory stimulus is considered.

MSC:
92C55Biomedical imaging and signal processing, tomography
92C20Neural biology
65R32Inverse problems (integral equations, numerical methods)
65C05Monte Carlo methods
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