Spatio-temporal modeling of neuromagnetic data: II. Multi-source resolvability of a MUSIC-based location estimator

A MUItiple SIgnal Classification-based (MUSIC) approach for neuromagnetic multi-source localization (Mosher et al. [1992] (IEEE Trans Med Eng BME-39:541-557) was evaluated through numerical simulations and by applying it to visually evoked neuromagnetic responses. A series of two-dipole and three-dipole spatio-temporal data were generated to examine effects of 1) source configurations, 2) temporal correlations, 3) noise, and 4) subspace dimensionality assumptions on the number of MUSIC metric maxima, their amplitudes, and how the resulting metric maxima locations relate to the actual source locations. In its present form, i.e., using simple one-dipole scanning over an assumed source subspace, MUSIC resulted either in 1) peaks sufficiently close to 1, but fewer than the actual number of sources which affected location estimation accuracy, or 2) the peaks were too low to qualify as source locations. Our simulations indicate difficulties in defining threshold values as to which peak values are close enough to 1 while avoiding significant type II errors (i.e., accepting peaks which should not be interpreted as source locations). Modifications to the MUSIC approach are necessary in order for the method to be considered of practical value for reliably localizing multiple neuromagnetic sources in empirical cases in which a high degree of temporal correlation between sources is likely (e.g., visual data).