Spatio-temporal dipole fitting methods such as RAP-MUSIC and R-MUSIC have demonstrated superior ability in the localization of a restricted number of independent sources, and also have the ability to reliably reproduce temporal waveforms. However, these algorithms experience difficulty in reconstructing multiple correlated sources. Accurate reconstruction of correlated brain activities is critical in synchronization analysis. The code below modifies the well-known inverse algorithm RAP-MUSIC to a multistage process which analyzes the correlation of candidate sources and searches for independent topographies (ITs) among pre-correlated groups. We call the resulting algorithm POP-MUSIC. You can read more about this algorithm in the following articles:
Schimpf, P.; Hesheng Liu; , "Localizing Synchronized Dipole Sources Using a Modified RAP-MUSIC Algorithm," 2nd International IEEE EMBS Conference on Neural Engineering, pp.132-135, 16-19 March 2005
Hesheng Liu; Schimpf, P.H.; , "Efficient localization of synchronous EEG source activities using a modified RAP-MUSIC algorithm," Biomedical Engineering, IEEE Transactions on , vol.53, no.4, pp.652-661, April 2006
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