Anhedonia and amotivation are common in depressive presentations, and putatively thought to be caused by alterations in the ways in which the brain anticipates, evaluates, and adaptively uses reward-related information. However, reward processing is a complex, multi-circuit phenomenon, and the precise neural mechanisms that contribute to the absence or reduction of typical hedonic and motivational outputs seen in the clinic are still being elucidated. Heterogeneity in the clinical presentation of depression has long been a rule rather than an exception, including individual variation in symptoms, severity, and treatment response. This heterogeneity complicates understanding of depressive pathophysiology and thwarts progress toward personalized disease classification and treatment planning. If the goal of personalized medicine in psychiatric care is to be realized, biomarkers that account for the full range of depressive presentations need to be developed (and ultimately validated). Discovery of biomarkers that go beyond the level of aggregate disease definitions to account for neurobiological variation that presumably underlies distinct clinical manifestations is critical to this larger effort. The proposed work combines clinically motivated questions with in-depth study of neurobiological mechanisms to evaluate how reward system neurobiology contributes to expression of reward-related deficits, such as anhedonia and amotivation in major depressive disorder (MDD), with a particular emphasis on understanding depressive heterogeneity. Conceptually, we will use a multi-measure approach, by studying Veterans with i) a passive slot machine reward task to isolate brain responses to reward anticipation and receipt in the absence of confounding higher-order cognitive demands, and ii) a delay-discounting task to assess higher-order aspects of reward processing necessary for reward valuation and decision-making. Methodologically, we will use a multi-modality approach by combining fMRI, EEG, and behavioral assessment, to more fully characterize reward-related brain functions and their clinical correlates. In addition to evaluating reward effects between Veterans with MDD and healthy controls (HC), and examining depressive heterogeneity within a large (n=150) MDD group, we will also focus on understanding the relationship between reward processing and clinical features of high relevance to depression, with an emphasis on suicidality. Specific Aim 1 will establish MDD deficits in reward processing at the level of group averages (i.e., case-control comparisons of MDD vs. HC). Specific Aim 2 will examine the extent to which data-driven subtyping of MDD can derive “biotypes” in Veterans, based on our EEG and fMRI reward processing metrics, that segregate clinically relevant features. Specific Aim 3 will compare subgroups of MDD with varying levels of suicidality.

Major Depressive Disorder is the leading cause of disability in the United States for ages 15-44, with associated substantial healthcare system costs. Estimates among the Veteran population for major depressive disorder prevalence are about 11%. This study will provide insights into whether reward processing measures of brain functioning and behavior are useful for improving aspects of treatment planning, suicide risk assessment, and cognitive-behavioral therapy response prediction. Mental healthcare practitioners need treatment predictors that account for the full extent of depressed individuals seen in the clinic in order to realize the goal of personalized healthcare. Studies like the one proposed here are vital to this larger effort in that they are poised to discover biomarkers to account for neurobiological variation presumably underlying distinct individual clinical responses. A refined depression taxonomy, informed by clinical neuroscience, could then be harnessed to improve diagnosis, increase treatment precision, or enhance prediction of suicide risk.