Two Dimensional Inverse Imaging (2DII) of Current Sources in Magnetoencephalography

A new magnetoencephalographic (MEG) technique for imaging the cortical distribution of neuronal activity is described. An iterative algorithm is employed, which successively alters an initial estimate of cortical source structure until it corresponds to the measured magnetic field data. In this new technique, the continuum of electrical activity across the cortical surface is modeled as a dense grid of thousands of single equivalent current dipoles. MEG imaging of both compact and extended sources is facilitated by a wavelet-like transformation of the source space into a sequence of successively smaller composite source structures. Two of these composite source structures are combined during each iterative step to generate an improved estimate of the cortical source structure. Thus, inversion of the complete gain matrix corresponding to thousands of cortical sources is not performed. The technique requires only moderate PC based resources even for very large source grids. In contrast to minimum norm MEG imaging methods, this new algorithm is insensitive to random noise in the data. If available, prior knowledge of source structure from other imaging techniques, such as PET, MRI and fMRI, is easily incorporated as additional constraints on the source structure solution. Source images solutions corresponding to simulated data are presented. In addition, the technique is applied to source imaging of real MEG data incorporating cortical structure from volumetric MRI data. These results demonstrate the capability of our new technique for imaging combinations of compact and extended source structures.