Novelty-seeking tendencies in adolescents may promote innovation as well as problematic impulsive behaviour, including drug abuse. Previous research has not clarified whether neural hyper- or hypo-responsiveness to anticipated rewards promotes vulnerability in these individuals. Here we use a longitudinal design to track 144 novelty-seeking adolescents at age 14 and 16 to determine whether neural activity in response to anticipated rewards predicts problematic drug use. We find that diminished BOLD activity in mesolimbic (ventral striatal and midbrain) and prefrontal cortical (dorsolateral prefrontal cortex) regions during reward anticipation at age 14 predicts problematic drug use at age 16. Lower psychometric conscientiousness and steeper discounting of future rewards at age 14 also predicts problematic drug use at age 16, but the neural responses independently predict more variance than psychometric measures. Together, these findings suggest that diminished neural responses to anticipated rewards in novelty-seeking adolescents may increase vulnerability to future problematic drug use.

Multivariate analyses provide a more accurate characterization of the association between brain alterations and psychosis because they enable the modeling of other key factors that influence neuroimaging phenotypes.

for the IMAGEN Consortium IMPORTANCE Alcohol abuse correlates with gray matter development in adolescents, but the directionality of this association remains unknown. OBJECTIVE To investigate the directionality of the association between gray matter development and increase in frequency of drunkenness among adolescents. DESIGN, SETTING, AND PARTICIPANTS This cohort study analyzed participants of IMAGEN, a multicenter brain imaging study of healthy adolescents in 8 European sites in Germany

Most psychopathological disorders develop in adolescence. The biological basis for this development is poorly understood. To enhance diagnostic characterisation, and develop improved targeted interventions, it is critical to identify behavioural symptom groups that share neural substrates. We ran analyses to find relations between behavioral symptoms, and neuroimaging measures of brain structure and function in adolescence. We found two symptom groups, consisting of anxiety/depression and executive dysfunction symptoms respectively, which correlated with distinct sets of brain regions and interregional connections, measured by structural and functional neuroimaging modalities. We found that the neural correlates of these symptom groups were present before behavioural symptoms had developed. These neural correlates showed case-control differences in corresponding psychiatric disorders, depression and ADHD, in independent clinical samples. By characterising behavioral symptom groups based on shared neural mechanisms, our results provide a framework for developing a classification system for psychiatric illness, which is based on quantitative neurobehavioural measures.

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCA) to determine the co-variation between brain imaging metrics of WM-network activation and connectivity and non-imaging measures relating to sensorimotor processing, affective and non-affective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health datasets; and a modular level, testing associations between subsets of the two datasets. The behavioral-health and neuroimaging datasets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network.