%0 Journal Article %A E. Gonzalez-Moreira %A D. Paz-Linares %A E. Martinez-Montes %A P. Valdes-Hernandez %A Jorge Bosch-Bayard %A M.L. Bringas-Vega %A P. Valdés-Sosa %T Populational Super-Resolution Sparse M/EEG Sources and Connectivity Estimation %D 2018 %R 10.1101/346569 %J bioRxiv %P 346569 %X In this paper, we describe a novel methodology, BC-VARETA, for estimating the Inverse Solution (sources activity) and its Precision Matrix (connectivity parameters) in the frequency domain representation of Stationary Time Series. The aims of this method are three. First: Joint estimation of Source Activity and Connectivity as a frequency domain linear dynamical system identification approach. Second: Achieve super high resolution in the connectivity estimation through Sparse Hermitian Sources Graphical Model. Third: To be a populational approach, preventing the Inverse Solution and Connectivity statistical analysis across subjects as a postprocessing, by modeling population features of Source Activity and Connectivity. Our claims are supported by a wide simulation framework using realistic head models, realistic Sources Setup, and Inverse Crime effects evaluation. Also, a fair quantitative analysis is performed, based on a diversification of quality measures on which state of the art Inverse Solvers were tested. %U https://www.biorxiv.org/content/biorxiv/early/2018/06/13/346569.full.pdf