An information theory framework for dynamic functional domain connectivity.

ABSTRACT:

Background

Dynamic functional network connectivity (dFNC) analyzes time evolution of coherent activity in the brain. In this technique dynamic changes are considered for the whole brain. This paper proposes an information theory framework to measure information flowing among subsets of functional networks call functional domains.

New method

Our method aims at estimating bits of information contained and shared among domains. The succession of dynamic functional states is estimated at the domain level. Information quantity is based on the probabilities of observing each dynamic state. Mutual information measurement is then obtained from probabilities across domains. Thus, we named this value the cross domain mutual information (CDMI).

Results

Strong CDMIs were observed

SUBMITTER: Vergara VM 

PROVIDER: S-EPMC5553686 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature