Characterizing positive and negative valence systems function in adolescent depression: An RDoC-informed approach integrating multiple neural measures

Abstract

Depression is a prevalent, debilitating, and costly disorder that often manifests in adolescence. There is an urgent need to understand core pathophysiological processes for depression to inform more targeted intervention efforts. The Research Domain Criteria (RDoC) Positive Valence Systems (PVS) and Negative Valence Systems (NVS) have both been implicated in depression symptomatology and vulnerability; however, the nature of NVS alterations is unclear across studies, and associations between single neural measures and symptoms are often small in magnitude and inconsistent. The present study advances characterization of depression in adolescence via an innovative data-driven approach to identifying subgroups of PVS and NVS function by integrating multiple neural measures (assessed by electroencephalogram [EEG]) relevant to depression in adolescents oversampled for clinical depression and depression risk based on maternal history (N = 129; 14–17 years old). Results of the k-means cluster analysis supported a two-cluster solution wherein one cluster was characterized by relatively attenuated reward and emotion responsiveness across valences and the other by relatively intact responsiveness. Youth in the attenuated responsiveness cluster reported significantly greater depressive symptoms and were more likely to have major depressive disorder diagnoses than youth in the intact responsiveness cluster. In contrast, associations of individual neural measures with depressive symptoms were non-significant. The present study highlights the importance of innovative neuroscience approaches to characterize emotional processing in depression across domains, which is imperative to advancing the clinical utility of RDoC-informed research.