Multivariate Pattern Analysis of Whole-Brain Functional Connectivity in Major Depression

Abstract

Resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) studies have shown significant group differences in several regions and networks between depressed patients and healthy controls. This chapter conducted multivariate pattern analysis of whole-brain rs-fcMRI in major depression, which can be used to test the feasibility of identifying major depressive individuals from healthy controls. Twenty-four depressed patients and 29 demographically matched healthy volunteers were included in this study. Permutation tests were used to assess classifier performance. The experimental results demonstrate that 94.3% (P < 0.0001) of subjects were correctly classified via leave-one-out cross-validation, including 100% identification of all patients. The majority of the most discriminating functional connections were located within or across the default mode network, affective network, visual cortical areas, and cerebellum, thereby indicating that the disease-related resting-state network alterations may give rise to a portion of the complex of emotional and cognitive disturbances in major depression. Moreover, the amygdala, anterior cingulate cortex, parahippocampal gyrus, and hippocampus, which exhibit high discriminative power in classification, may play important roles in the pathophysiology of this disorder. The current study may shed new light on the pathological mechanism of major depression and suggests that whole-brain rs-fcMRI may provide potential effective biomarkers for its clinical diagnosis.