Despite decades of research, affective disorders are prevalent and associated with significant morbidity and mortality. Unraveling the pathophysiology of affective disorders has been uniquely challenging because depressive syndromes are heterogeneous and have diverse etiologies. Thus, past studies aimed at identifying neural and genetic biomarkers that would improve the prediction of susceptibility, course of illness, and treatment response have yielded inconsistent results. The investigator proposes to address this problem by studying perimenopausal major depressive disorder (MDD), a depression subtype with a specific endocrine trigger (i.e., ovarian hormone withdrawal). Evidence supporting ovarian hormone withdrawal as a trigger for affective dysfunction in perimenopausal MDD includes the following: perimenopausal women show a temporal association between ovarian hormone withdrawal and the onset of mood symptoms; treatment with estrogen reduces mood symptoms; and blinded estradiol withdrawal re-precipitates depression in women with a history of perimenopausal MDD (manuscript in preparation). Focusing on perimenopausal MDD, a more homogeneous subtype with a specific endocrine trigger, will increase the likelihood of identifying meaningful neurobiological markers.One of the most powerful tools for understanding the neural mediators of MDD is brain imaging. Prior research suggests that the frontostriatal reward system is regulated by estradiol and implicated in MDD. However, neural mechanisms of perimenopausal MDD have never been studied. We will assess the neural reward system in perimenopausal women with and without MDD using functional magnetic resonance imaging (fMRI) at baseline and following estradiol treatment. The central hypothesis is that the neural reward system is hypoactive in perimenopausal MDD, and the antidepressant effects of a three-week transdermal estradiol intervention will be mediated by increased activity in the neural reward system, assessed using fMRI. The investigator will test the hypothesis by executing the following aims: