Abstract: Ubiquitously expressed genes have been implicated in a variety of specific behaviors, including responses to ethanol. However, the mechanisms that confer this behavioral specificity have remained elusive. Previously, we showed that the ubiquitously expressed small GTPase Arf6 is required for normal ethanol-induced sedation in adult Drosophila. Here, we show that this behavioral response also requires Efa6, one of (at least) three Drosophila Arf6 guanine exchange factors. Ethanol-naive Arf6 and Efa6 mutants were sensitive to ethanol-induced sedation and lacked rapid tolerance upon re-exposure to ethanol, when compared with wild-type flies. In contrast to wild-type flies, both Arf6 and Efa6 mutants preferred alcohol-containing food without prior ethanol experience. An analysis of the human ortholog of Arf6 and orthologs of Efa6 (PSD1-4) revealed that the minor G allele of single nucleotide polymorphism (SNP) rs13265422 in PSD3, as well as a haplotype containing rs13265422, was associated with an increased frequency of drinking and binge drinking episodes in adolescents. The same haplotype was also associated with increased alcohol dependence in an independent European cohort. Unlike the ubiquitously expressed human Arf6 GTPase, PSD3 localization is restricted to the brain, particularly the prefrontal cortex (PFC). Functional magnetic resonance imaging revealed that the same PSD3 haplotype was also associated with a differential functional magnetic resonance imaging signal in the PFC during a Go/No-Go task, which engages PFC-mediated executive control. Our translational analysis, therefore, suggests that PSD3 confers regional specificity to ubiquitous Arf6 in the PFC to modulate human alcohol-drinking behaviors.
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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).