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.
