Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder
Mohammad S E Sendi1,2,3, Elaheh Zendehrouh4, Jing Sui3,5,6,7
1Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA.
Abstract:
Background: Major depressive disorder (MDD) is a severe mental illness marked by a continuous sense of sadness and a loss of interest. The default mode network (DMN) is a group of brain areas that are more active during rest and deactivate when engaged in task-oriented activities. The DMN of MDD has been found to have aberrant static functional network connectivity (FNC) in recent studies. In this work, we extend previous findings by evaluating dynamic functional network connectivity (dFNC) within the DMN subnodes in MDD. Methods: We analyzed resting-state functional magnetic resonance imaging data of 262 patients with MDD and 277 healthy controls (HCs). We estimated dFNCs for seven subnodes of the DMN, including the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and precuneus (PCu), using a sliding window approach, and then clustered the dFNCs into five brain states. Classification of MDD and HC subjects based on state-specific FC was performed using a logistic regression classifier. Transition probabilities between dFNC states were used to identify relationships between symptom severity and dFNC data in MDD patients. Results: By comparing state-specific FNC between HC and MDD, a disrupted connectivity pattern was observed within the DMN. In more detail, we found that the connectivity of ACC is stronger, and the connectivity between PCu and PCC is weaker in individuals with MDD than in those of HC subjects. In addition, MDD showed a higher probability of transitioning from a state with weaker ACC connectivity to a state with stronger ACC connectivity, and this abnormality is associated with symptom severity. This is the first research to look at the dFC of the DMN in MDD with a large sample size. It provides novel evidence of abnormal time-varying DMN configuration in MDD and offers links to symptom severity in MDD subjects. Impact Statement This study is the first attempt that explored the temporal change on default mode network (DMN) connectivity in a relatively large cohort of patients with major depressive disorder (MDD). We also introduced a new hypothesis that explains the inconsistency in DMN functional network connectivity (FNC) comparison between MDD and healthy control based on static FNC in the previous literature. Additionally, our findings suggest that within anterior cingulate cortex connectivity and the connectivity between the precuneus and posterior cingulate cortex are the potential biomarkers for the future intervention of MDD.
More Related Videos
12:09Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
08:36Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
Published on: March 21, 2019
Related Concept Videos
Depressive Disorders: MDD and Dysthymia
Depressive Disorders: Etiology
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
Depression: Overview
Negative and Cognitive Symptoms of Schizophrenia
Negative Symptoms
Negative symptoms of schizophrenia manifest as deficits in normal emotional and behavioral functioning, profoundly impacting daily life. Individuals with schizophrenia often display a flat affect, characterized by a near-total absence of emotional expression,...
