In this graphical scheme, nodes represent variables of interest (squares: discrete variables; circles: continuous variables) and arrows indicate dependencies between these variables. Shaded nodes represent observed variables, here rewards () and choices () for each trial (), subject (), and drug condition (). For each subject and drug condition, the observed rewards until trial t-1 determine (deterministically) choice probabilities () on trial , which in turn determine (stochastically) the choice on that trial. The exact dependencies between previous rewards and choice probabilities are specified by the different cognitive models and their model parameters (). Note that the double-bordered node indicates that the choice probability is fully determined by its parent nodes, that is the reward history and the model parameters. As the model parameters differ between all applied cognitive models, they are indicated here by an as a placeholder for one or more model parameter(s). Still, the general modeling scheme was the same for all models: Model parameters were estimated for each subject and drug condition and were assumed to be drawn from a group-level normal distribution with mean and standard deviation for any parameter . Note that group-level parameters were estimated separately for each drug condition. Each group-level mean () was assigned a non-informative (uniform) prior between the limits and as listed above. Each group-level standard deviation () was assigned a half Cauchy distributed prior with location parameter 0 and scale 1. Subject-level parameters included , , and depending on the cognitive model (see Table 1).