Behavioral and neurocognitive mechanisms linking peer victimization to adolescent psychopathology - PROJECT SUMMARY/ABSTRACT Adolescence is a period of heightened vulnerability for many forms of psychopathology, particularly depression, anxiety, and suicidal behaviors. Disorders that emerge during this time have lasting consequences, including elevated risk of recurrence, and poor psychosocial functioning. This vulnerability comes at a time when peer victimization becomes more common and emotional and physiological responses to peer rejection are elevated, rendering victimization particularly damaging during adolescence. Despite the strong links between peer victimization and internalizing problems during adolescence, the behavioral and neural mechanisms underlying this association remain unclear, limiting our ability to prevent the onset of victimization-related psychopathology in youth. The proposed project will test a novel conceptual model, in which it is proposed that two underlying dimensions of peer victimization, peer threat (e.g., presence of negative social experiences, like rejection) and peer deprivation (e.g., absence of positive social experiences, like ostracism) differentially shape neurocognitive processes and social behaviors that have relevance for psychopathology. Specifically, it is argued that peer threat influences neurocognitive and behavioral processes in ways that enhance threat detection and processing (Aim 1), whereas experiences of peer deprivation may contribute to blunted reward sensitivity and low social motivation (Aim 2). The project will then examine whether neurocognitive and behavioral alterations serve as mechanisms linking peer victimization with internalizing psychopathology (Aim 3). The proposed research will test this conceptual model by using a combination of experimental behavioral and fMRI tasks, as well as an intensive longitudinal design, leveraging advancements in digital phenotyping, computational neuroscience, and predictive modeling approaches. Critically, by implementing advanced statistical machine learning methods for predictive modeling, the proposed research may be able to identify patterns of real-world social behavior that are influenced by victimization and, in turn, predict the emergence of psychopathology. Identifying developmental processes that are disrupted following peer victimization and ultimately lead to psychopathology is a necessary first step in developing targeted intervention approaches. This award will also provide the candidate, who has a strong background in developmental social neuroscience and clinical science, with critical training in the implementation of digital phenotyping, computational modeling, and advanced statistical techniques to promote a successful transition to an independent research career.
