Populational Super-Resolution Sparse M/EEG Sources and Connectivity Estimation

Gonzalez-Moreira, E.; Paz-Linares, D.; Martinez-Montes, E.; Valdes-Hernandez, P.; Bosch-Bayard, J.; Bringas-Vega, M. L.; Valdes-Sosa, P.

doi:10.1101/346569

bioRxiv · 10.1101/346569

Populational Super-Resolution Sparse M/EEG Sources and Connectivity Estimation

Gonzalez-Moreira, E.·Paz-Linares, D.·Martinez-Montes, E.·Valdes-Hernandez, P.·Bosch-Bayard, J.·Bringas-Vega, M. L.·Valdes-Sosa, P.

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Abstract

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.

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Gonzalez-Moreira, E., Paz-Linares, D., Martinez-Montes, E., Valdes-Hernandez, P., Bosch-Bayard, J., Bringas-Vega, M. L., Valdes-Sosa, P.. 2018-06-13. Populational Super-Resolution Sparse M/EEG Sources and Connectivity Estimation. https://doi.org/10.1101/346569

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