Regulation of social behaviors is necessary to achieve social inclusion, establish relationships and sustain those relationships through adversity. Impairments in socio-emotional function and competence are prominent and debilitating features of major depression, yet are not traditionally recognized as cardinal symptoms of the disease. However, these deficits often persist in patients whose other mood symptoms have remitted and can predict risk of relapse, indicating an important role as a vulnerability factor. Understanding the neurobiology of socioaffective dysfunction in depression is thus important for determining the pathology of the disorder and developing effective treatments. Human imaging studies of depressive patients have consistently reported abnormal activity in the ventromedial prefrontal cortex (vmPFC), an area important for emotional processing and social cognition. Tracing studies in animals and tractography in humans have shown that the dorsal raphe nucleus (DRN) is a major projection target of the vmPFC. The DRN contains the most serotonin (5-HT) producing neurons in the brain and its output has been shown to regulate behaviors along an affiliative-agonistic axis, however it is neuronally heterogeneous. This thesis investigated the cytoarchitecture of the vmPFC-DRN microcircuit and its relevance to socioaffective behaviors using genetic mapping, whole cell electrophysiology and optogenetics. I showed that GABAergic neurons, which are the primary non-serotonergic neuronal population in the DRN, mediated top-down projections from the vmPFC onto mood-regulating 5-HT neurons and demonstrated the relevance of this pathway in mediating socioaffective decisions using the chronic social defeat stress (CSDS) paradigm. In addition, I used deep brain stimulation of the vmPFC as an antidepressant model to show that therapeutic response may rely on restoring the excitatory/inhibitory balance of inputs to 5-HT neurons. Together, these results will provide a better understanding of socioaffective circuitry and could lead to the development of more effective and efficient strategies to treat mood disorders.