Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity.

ABSTRACT: Recently, functional network connectivity (FNC, defined as the temporal correlation among spatially distant brain networks) has been used to examine the functional organization of brain networks in various psychiatric illnesses. Dynamic FNC is a recent extension of the conventional FNC analysis that takes into account FNC changes over short periods of time. While such dynamic FNC measures may be more informative about various aspects of connectivity, there has been no detailed head-to-head comparison of the ability of static and dynamic FNC to perform classification in complex mental illnesses. This paper proposes a framework for automatic classification of schizophrenia, bipolar and healthy subjects based on their static and dynamic FNC features. Also, we compare cross-validated classific

SUBMITTER: Rashid B 

PROVIDER: S-EPMC4912868 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature