  This paper presents a new toolbox for MEEG source activity and connectivity
estimation: Brain Connectivity Variable Resolution Tomographic Analysis version
1.0 (BC-VARETA 1.0). It relies on the third generation of nonlinear methods for
the analysis of resting state MEEG Time Series. Into the state of the art of
MEEG analysis, the methodology underlying our tool (BC-VARETA) brings out
several assets. First: Constitutes a Bayesian Identification approach of Linear
Dynamical Systems in the Frequency Domain, grounded in more consistent models
(third generation). Second: Achieves Super-Resolution, through the iterative
solution of a Sparse Hermitian Source Graphical Model. Third: Tackles
efficiently in High Dimensional and Complex set up the estimation of
connectivity. Fourth: Incorporates priors at the connectivity level by
penalizing the groups of variables, corresponding to the Gray Matter anatomical
segmentation, and including a probability mask of the anatomically plausible
connections. Along with the implementation of our method, we include in this
toolbox a benchmark for the validation of MEEG source analysis methods, that
would serve for the evaluation of sophisticated methodologies (third
generation). It incorporates two elements. First: A realistic simulation
framework, for the generation of MEEG synthetic data, given an underlying
source connectivity structure. Second: Sensitive quality measures that allow
for a reliable evaluation of the source activity and connectivity
reconstruction performance, based on the Spatial Dispersion and Earth Movers
Distance, in both source and connectivity space.
