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This paper presents a new toolbox for MEEG source activity and connectivityestimation: Brain Connectivity Variable Resolution Tomographic Analysis version1.0 (BC-VARETA 1.0). It relies on the third generation of nonlinear methods forthe analysis of resting state MEEG Time Series. Into the state of the art ofMEEG analysis, the methodology underlying our tool (BC-VARETA) brings outseveral assets. First: Constitutes a Bayesian Identification approach of LinearDynamical Systems in the Frequency Domain, grounded in more consistent models(third generation). Second: Achieves Super-Resolution, through the iterativesolution of a Sparse Hermitian Source Graphical Model. Third: Tacklesefficiently in High Dimensional and Complex set up the estimation ofconnectivity. Fourth: Incorporates priors at the connectivity level bypenalizing the groups of variables, corresponding to the Gray Matter anatomicalsegmentation, and including a probability mask of the anatomically plausibleconnections. Along with the implementation of our method, we include in thistoolbox a benchmark for the validation of MEEG source analysis methods, thatwould serve for the evaluation of sophisticated methodologies (thirdgeneration). It incorporates two elements. First: A realistic simulationframework, for the generation of MEEG synthetic data, given an underlyingsource connectivity structure. Second: Sensitive quality measures that allowfor a reliable evaluation of the source activity and connectivityreconstruction performance, based on the Spatial Dispersion and Earth MoversDistance, in both source and connectivity space.

Third Generation MEEG Source Connectivity Analysis Toolbox (BC-VARETA 1.0) and Validation Benchmark