Abstract: Changes in reward processing have been identified as one important pathogenetic mechanism in alcohol addiction. The nonsynonymous single nucleotide polymorphism in the brain-derived neurotrophic factor (BDNF) gene (rs6265/Val66Met) modulates the central nervous system activity of neurotransmitters involved in reward processing such as serotonin, dopamine, and glutamate. It was identified as crucial for alcohol consumption in healthy adults and, in rats, specifically related to the function in the striatum, a region that is commonly involved in reward processing. However, studies in humans on the association of BDNF Val66Met and reward-related brain functions and its role for alcohol consumption, a significant predictor of later alcohol addiction, are missing. Based on an intermediate phenotype approach, we assessed the early orientation toward alcohol and alcohol consumption in 530 healthy adolescents that underwent a monetary incentive delay task during functional magnetic resonance imaging. We found a significantly lower response in the putamen to reward anticipation in adolescent Met carriers with high versus low levels of alcohol consumption. During reward feedback, Met carriers with low putamen reactivity were significantly more likely to orient toward alcohol and to drink alcohol 2 years later. This study indicates a possible effect of BDNF Val66Met on alcohol addiction-related phenotypes in adolescence.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).