An Examination of Affect-Related Brain Activity and Substance Use Among Adolescents



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Death and disability related to substance use disorder have increased substantially over the past couple of decades. Most adults with substance use disorder initiated substance use as adolescents, making adolescence a critical period for the prevention of substance use and substance use disorder. It is therefore important to identify risk factors for adolescent substance use. Recent research has demonstrated the role of altered affective processing in adolescent substance use. Unfortunately, most of this research has employed self-report and behavioral methods, which, while valuable, are limited in comparison to other methods, namely functional neuroimaging, in detecting subtle neural-level differences in affective processing and how it relates to adolescent substance use. Thus, the focus of this dissertation is on neural affective processing and adolescent substance use employing functional neuroimaging. In Study 1 of this dissertation, a systematic review of neuroimaging studies examining affective processing and adolescent substance use was conducted. Results revealed that higher activation in midcingulo-insular regions—particularly the striatum—to positive affective stimuli (e.g., monetary reward) was most often associated with initiation and low-level use of substances, whereas lower activation in these regions was most often associated with substance use disorder and higher-risk substance use. In regard to negative affective stimuli, most research demonstrated associations between higher activation of midcingulo-insular network regions and adolescent substance use. Associations between activation in additional network regions (e.g., frontoparietal, pericentral) and adolescent substance use were mixed. To extend findings from Study 1, Study 2 of this dissertation was an empirical study examining how patterns of neural activation in two standardized and one naturalistic affective processing tasks classify substance use as well as predict substance use intentions and expectancies in 11–15-year-old adolescents (n = 168). Machine learning analyses were performed. Results did not provide evidence that neural activation to negative or positive affective stimuli—neither standardized nor naturalistic—could reliably classify adolescent substance use and predict adolescent substance use intentions and expectancies. Implications of all findings, as well as limitations and directions for future research are discussed.