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PROJECT SUMMARY / ABSTRACT In the United States, substance use behaviors contribute to the leading causes of mortality and morbidity of adolescents, and are associated with approximately $60 billion in economic costs per year. Negative peer influence is a major environmental risk factor for early initiation of substance use and other risky behaviors. However, group-based interventions and positive social supports are also beneficial for successful cessation of substance use and addictive behaviors. Thus, social influences can contribute to adaptive or maladaptive decision-making and depend on the context and nature of the influence. Despite the strong contribution of peer influence to individuals' risky (or safe) decision-making, the mechanistic processes underlying susceptibility and resilience to social influence have received limited investigation. Here, we combine a longitudinal cohort design, functional neuroimaging, novel behavioral economic paradigms, and a model-based approach to examine whether substance use, and changes in substance use, are related to individual differences in two mechanisms by which social information influences risky decision- making (Aims 1 & 2). To test the extent to which changes in substance use may also impact susceptibility to social influence, we will further examine reciprocal effects of substance use on the mechanisms of social influence over time (Aim 3). Our broad hypothesis is that biases in neural and behavioral processing of information from social others contribute to the development of substance use behaviors in adolescents and may explain why social others have an unusually large impact on certain adolescents' decisions to engage in substance use.
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Sub-second neurochemistry of error signals and affective processing in depression
Sub-second neurochemistry of error signals and affective processing in depression
Evaluating overlap and distinctiveness in neurocomputational loss and reward elements of the RDoC matrix
Evaluating overlap and distinctiveness in neurocomputational loss and reward elements of the RDoC matrix
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