 Major depressive disorder MDD is a highly prevalent, chronic disabling condition with substantial morbidity and mortality. Depression currently is the fourth leading cause of global burden of disease DALYs and disability worldwide, and is expected to be second by 20201. Around one in eight people in Canada will develop depression during their lifetime, with the total cost to the Canadian economy estimated at 51 billion per year2. The costs of treating MDD are high in part due to limitations in effectiveness of antidepressant treatment. Approximately 60 of patients fail to remit to the first antidepressant prescribed3 and the subsequent selection of antidepressants remains a matter of trial and error. Using this trial and error approach, it may take a year or more to find the successful treatment for a patient4,5. The protracted ineffective treatment results in prolonged suffering, substantial morbidity, loss of productivity and an increased burden on patients family. Brain-based biomarkers could assist in predicting clinical response to treatment intervention and in tailoring treatment for individual patients. The results of previous neuroimaging studies that examined brain markers of treatment response were derived from group averages 6,-9 and have limited predictive value at individual level. Another limitation of these studies is that predictors derived from the pretreatment baseline brain scans could be influenced by many personal personality, childhood trauma, genotypes and clinical course, duration of illness, episodes, symptom clusters, and severity of symptoms and past medication exposure characteristics which may limit the generalizability. On the other hand, there is growing evidence that the early clinical response within 2 weeks of antidepressant treatment and EEG changes in the first week of treatment can predict later outcomes. Furthermore, early treatment changes in brain function may provide crucial information on the brains capacity to change with treatment and on the interactive effects between personal clinical characteristics and pharmacological factors, which may help differential prediction of treatment responses to two antidepressants. Hence, examining the predictive value of dynamic brain changes during the first two weeks of treatment in individual patients would improve statistical reliability and predictive accuracy and minimize the confounding effect inherent to pretreatment scans. 