Resting-state network connectivity and metastability predict clinical symptoms in schizophrenia.

ABSTRACT:

Background

The functional architecture of resting-state networks (RSNs) is defined by their connectivity and metastability. Disrupted RSN connectivity has been amply demonstrated in schizophrenia while the role of metastability remains poorly defined. Here, we undertake a comprehensive characterisation of RSN organization in schizophrenia and test its contribution to the clinical profile of this disorder.

Methods

We extracted RSNs representing the default mode (DMN), central executive (CEN), salience (SAL), language (LAN), sensorimotor (SMN), auditory (AN) and visual (VN) networks from resting-state functional magnetic resonance imaging data obtained from patients with schizophrenia (n = 85) and healthy individuals (n = 48). For each network, we computed its functional cohes

SUBMITTER: Lee WH 

PROVIDER: S-EPMC6317903 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature