 In this study, we propose to investigate the predictive value of resting state and task related fMRI data collected at the pretreatment baseline and 2 weeks after treatment to predict remitters and non-remitters to desvenlafaxine antidepressant treatment at week 12 using machine learning classifier. Desvenlafaxine is a serotonin norepinephrine reuptake inhibitor SNRI with proven efficacy, and safety and is easy to administer in single daily dose. It has limited sedative and cognitive side effects such as drowsiness, lack of alertness and poor attention, which may confound early brain changes with treatment. This study will provide brain-based predictive biomarkers that can be tested prospectively in clinical trials and eventually in clinical practice for accuracy. 