A. Dogandzic et A. Nehorai, Estimating evoked dipole responses in unknown spatially correlated noise with EEG/MEG arrays, IEEE SIGNAL, 48(1), 2000, pp. 13-25
We present maximum likelihood (ML) methods for estimating evoked dipole res
ponses using electroencephalography (EEG) and magnetoencephalography (MEG)
arrays, which allow for spatially correlated noise between sensors with unk
nown covariance. The electric source is modeled as a collection of current
dipoles at fixed locations and the head as a spherical conductor. We permit
the dipoles' moments to vary with time by modeling them as linear combinat
ions of parametric or nonparametric etc. basis functions. We estimate the d
ipoles' locations and moments and derive the Cramer-Rao bound for the unkno
wn parameters. We also propose an ML-based method for scanning the brain re
sponse data, which can be used to initialize the multidimensional search re
quired to obtain the true dipole location estimates. Numerical simulations
demonstrate the performance of the proposed methods.