 This is a source (state) GGM hidden by the MEEG observation equation , i. e. equivalent to a frequency domain Linear State Space Model (LSSM) . It is unhidden due to the Type II Likelihood approximated representation: Expected Log-Likelihood (ELL). The essential contributions here are a theory for HGGM solvers, and its implementation for the subsequent Maximization step of the H-HGGM ELL. Its efficacy is demonstrated in high resolution EEG simulations and a Steady State Visual Evoked potential.
<meaning-changed>  This is a source (state) GGM hidden by the MEEG observation equation , i. e. equivalent to a frequency domain Linear State Space Model (LSSM) . It is unhidden due to the Type II Likelihood approximated representation: Expected Log-Likelihood (ELL). The essential contributions here are a theory for HGGM solvers, and its implementation for the subsequent Maximization step of the H-HGGM ELL. Its efficacy is demonstrated in high resolution EEG simulations and a Steady State Visual Evoked potential.
 This is a source (state) GGM hidden by the MEEG observation equation , i. e. equivalent to a frequency domain Linear State Space Model (LSSM) but with sparse connectivity prior. The mathematical contribution here is the theory for high-dimensional and frequency-domain HIGGS solvers. We demonstrate that HIGGS can attenuate the leakage effect in the most critical case: the distortion EEG signal due to head volume conduction heterogeneities. Its application in EEG is illustrated with retrieved connectivity patterns from human Steady State Visual Evoked potential.