ABSTRACT
This paper introduces a new technique for the localization of brain electromagnetic activity: a spatio-temporal fit (SPTF). This algorithm uses some properties of the principal component analysis and makes no assumptions about the number of sources to be located. It was applied to both simulated and real MEG/EEG signals and was compared to the well-known moving dipole fit (MDF) technique. For the simulations, we constructed extended sources, rather than single dipoles, that respected realistic anatomical and temporal properties. From these, we generated, under different noise conditions, MEG and EEG signals from which localization was performed. The real signals were auditory evoked fields. Firstly, it appeared that the SPTF was able to separate simultaneously activated sources even on strongly noisy signals while, most of the time, the MDF failed to give a clear description of the source configuration. Secondly, although we used the same head model to both generate the signals and locate the sources, localization for EEG was inferior to that for MEG. In conclusion, since in all test conditions the SPTF is found to be far superior to MDF, we suggest the use SPTF for the localization of equivalent dipoles.
