Functional and effective connectivity in major depressive disorder patients with suicidal thoughts: A resting-state fMRI study

Abstract

Major Depressive Disorder (MDD) is one of the most prevalent psychological disorders all over the world. Suicide ideation is the most dangerous and crucial consequence of this mental disturbance that can lead to suicide attempting. In this study, we compared both functional and effective brain connectivity of female MDD patients having suicide thoughts with female healthy controls. We used COMBI algorithm for identifying independent components in resting state fMRI data (rsfMRI) of 32 female subjects (16 MDDs with suicide ideation and 16 healthy controls). We performed Group Information Guided Independent Component Analysis (GIG-ICA) as a back-reconstruction step and finally, extracted the static and Dynamic Functional Connectivity (DFC) for all participants. Besides that, Dynamic Effective Connectivity (DEC) was characterized using Dynamic Granger Causality (DGC). Significant connectivity differences were detected between some network pairs including: Auditory Network with right Executive Control Network (ECN), ventral Default Mode Network (DMN) with Visuospatial, right ECN with anterior Salience Network (SN), ventral DMN with Precuneus, dorsal DMN with Precuneus, Language with dorsal DMN, Language with posterior SN and Primary Visual with dorsal DMN. Except the connectivity difference between right ECN and anterior Salience network, other connectivity changes were consistent with previous studies. As far as we know, this is the first study to investigate the effective connectivity by the information extracted from ICA in this specific study group.