A Comparison of Regularization Techniques for Magnetoencephalography Source Reconstruction

In this paper, the abilities of the generalized cross validation (GCV) method and the L-curve method for the determination of the optimal regularization parameter are studied and compared for magnetoencephalography (MEG) source reconstruction. The results verify that the GCV method is a better choice when the measurement noise is relatively high, and the L-curve method seems to be more effective when the source is mainly dominated by errors such as brain perturbation.