Abstract
One possible way to examine brain connectivity is to study correlations between signals recorded from different areas. The recent trends couple the signal processing based on data-driven mathematical methods with graph analysis performed on the connectivity matrix. The connectivity matrices can be evaluated by using several methods, and different toolboxes are available. The aim of the proposed platform is to create an embedded environment where it is possible to study brain connectivity through different methods and at the same time to compare the results. For this purpose different procedures are developed: from frequency and lag selection in the case of time or frequency varying analyses, to binary graph creation and binary and weighted graph comparisons. This software is realized with a high level of modularity, making it possible to integrate new analysis methods and clustering approaches.
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