Abstract

Depression is characterized by poor emotion regulation that makes it difficult to escape the effects of emotional pain, but the neuromodulation behind these symptoms is still unclear. This study investigated the neural mechanism of emotional state-related responses during music stimuli in participants with major depressive disorder (MDD) compared to never-depressed (ND) controls. A novel two-level feature selection method, integrating recursive feature elimination based on support vector machine (SVM-RFE) and random forest algorithm (RF), was proposed to screen emotional recognition brain regions (ERBRs). On this basis, the differences of functional connectivity (FC) were systematically analyzed by two-sample t-test. The results demonstrate that ND participants show eight pairs of FCs with a significant difference between positive emotional music stimuli (pEMS) versus negative emotional music stimuli (nEMS) in 15 ERBRs of MDD, but the participants with MDD show one pair of significant difference in FC. The decreased number reflects the fuzzy response to positive and negative emotions in MDD, which appears to arise from obstacle to emotional cognition and regulation. Furthermore, there was no significant difference in FC between MDDs and NDs under pEMS, but a significant difference was detected between the two groups under nEMS (p < 0.01), revealing a 'bias' against the negative state in MDD. The current study may help to better comprehend the abnormal evolution from normal to depression and inform the utilization of pEMS in formal treatment for depression.

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