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Modelling Learning in Alcohol Use Disorders: Moderators and Multivariate Risk Profiles

Subject Area Biological Psychiatry
Term from 2012 to 2020
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 186318919
 
Individuals suffering from alcohol use disorder (AUD) show striking dysfunctions in their learning and decision-making. Consequently, breakdowns in decision-making are central to the conceptualisation of substance dependence. Recent findings have emphasized the extent to which individuals with substance dependence continue to take drugs, despite understanding and acknowledging the devastating effect drug use has on their life and expressed desires (and attempts) to abstain. Detailed neurobiological and neurocomputational investigations of these processes in normal learning and addiction have emphasized the key and multiple roles of dopamine and the striatum. In the first funding period, we established two neuropsychological paradigms that measure both Pavlovian processing and habitual and goal-directed behaviour and are amenable to neurocomputational modelling. Psychosocial stressors and their affective valence can affect dysfunctional learning in AUD. In healthy adults there is increasing evidence that individual differences in cognitive abilities as assessed by neuropsychological tests, as well as individual differences in psychosocial vulnerabilities may moderate the arbitration between habitual and goal-directed behaviour; however, the role that psychosocial stressors and decreased cognitive capacities play in the development and maintenance of AUD with respect to learning mechanisms in individuals at risk or suffering from AUD, respectively, is largely unknown. Similarly, individual differences in learning profiles as risk factors for the development and maintenance of AUD have not yet been studied in interaction with such risk factors. Therefore, in the second funding period, our project will elucidate the influences of individual differences in psychosocial and neuropsychological risk factors for both Pavlovian and goal-directed learning processes in AUD. We will investigate individual differences in learning using (i) an experimental paradigm, (ii) statistical linear mixed-effects analyses and (iii) group and individual-level computational modelling. Our approach will be complemented by an individual differences, person- rather than variablecentred approach, which will use latent class and latent profile analyses to identify risk profiles (including moderators of risk factors) for the development and maintenance of AUD. Collectively, this approach will provide key insights into individual differences in risk profiles and learning mechanisms for the development and maintenance of AUD, which will in turn inform individualized prevention and intervention approaches.
DFG Programme Research Units
 
 

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