A novel perturbation based compression complexity measure for networks.

ABSTRACT: Measuring complexity of brain networks in the form of integrated information is a leading approach towards building a fundamental theory of consciousness. Integrated Information Theory (IIT) has gained attention in this regard due to its theoretically strong framework. Nevertheless, it faces some limitations such as current state dependence, computational intractability and inability to be applied to real brain data. On the other hand, Perturbational Complexity Index (PCI) is a clinical measure for distinguishing different levels of consciousness. Though PCI claims to capture the functional differentiation and integration in brain networks (similar to IIT), its link to integrated information is rather weak. Inspired by these two perspectives, we propose a new complexity measure for brain n

SUBMITTER: Virmani M 

PROVIDER: S-EPMC6383034 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature