Functional Connectome of the Human Brain with Total Correlation

Abstract

Recent studies proposed the use of Total Correlation to describe functional connectivity among brain regions as a multivariate alternative to conventional pairwise measures such as correlation or mutual information. In this work, we build on this idea to infer a large-scale (whole-brain) connectivity network based on Total Correlation and show the possibility of using this kind of network as biomarkers of brain alterations. In particular, this work uses Correlation Explanation (CorEx) to estimate Total Correlation. First, we prove that CorEx estimates of Total Correlation and clustering results are trustable compared to ground truth values. Second, the inferred large-scale connectivity network extracted from the more extensive open fMRI datasets is consistent with existing neuroscience studies, but, interestingly, can estimate additional relations beyond pairwise regions. And finally, we show how the connectivity graphs based on Total Correlation can also be an effective tool to aid in the discovery of brain diseases.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 25, 2022
Source ID
10.3390/e24121725

Entities

People

  • Greg Ver Steeg
  • Jesus Malo
  • Qiang Li
  • Shujian Yu

Organizations

  • Defense Advanced Research Projects Agency
  • Research Council of Norway

Tags

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Medical Imaging.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference