Symmetric analysis of EEG and fMRI using nonlinear models: a Simulation Study

In this paper, we introduce a new method of symmetric analysis of Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. We consider each signal as a projection of the real neural activations to find spatial sources and their related temporal sources. We use the sparsity of activated voxels as a constraint for solving the localization problem. Simulation results illustrate superiority of our method compared to the previous methods.