On the Geometric Sensitivity of the MEG Inversion Algorithm

Abstract

Magnetoencephalography (MEG) is a non-invasive technique that measures the magnetic fields produced by brain's electrical currents. The basic inverse problem of magnetoencephalography (MEG) consists in estimating the neuronal current in the brain from the measurement of the magnetic field outside the head. The relative inversion algorithms, existing in medical devices, for the identification of excitation sources inside the brain using MEG data, are based on the assumption that the geometry of the brain-head system is spherical. Here, we present the error of identification of the dipole {({varvec{r}}}_{0}, {varvec{Q}}) using the inversion algorithm of spherical geometry. In particular, taking magnetoencephalographic measurements from realistic ellipsoidal model and using these data in a spherical model lead to a structural error. For the purpose of this paper, we make numerical investigation for different positions of the source, especially, locating sources at different depths and see how the error depends on depth. These results may have useful implications for the interpretation of the reconstructions obtained via the existing approaches.