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Recent studies proposed the use of Total Correlation to describe functionalconnectivity among brain regions as a multivariate alternative to conventionalpair-wise measures such as correlation or mutual information. In this work webuild on this idea to infer a large scale (whole brain) connectivity networkbased on Total Correlation and show the possibility of using this kind ofnetworks as biomarkers of brain alterations. In particular, this work usesCorrelation Explanation (CorEx) to estimate Total Correlation. First, we provethat CorEx estimates of total correlation and clustering results are trustablecompared to ground truth values. Second, the inferred large scale connectivitynetwork extracted from the more extensive open fMRI datasets is consistent withexisting neuroscience studies but, interestingly, can estimate additionalrelations beyond pair-wise regions. And finally, we show how the connectivitygraphs based on Total Correlation can also be an effective tool to aid in thediscovery of brain diseases.

Functional Connectome of the Human Brain with Total Correlation