Simulation results of the model in the schedule depicted in <b>Figure 2</b>.

<p>The model is simulated under two scenarios: moderate training (left column), and extensive training (right column). In the moderate training scenario, the agent has experienced the environment for 40 trials before devaluation treatment, whereas in the extensive training scenario, 240 pre-devaluation training trials have been provided. In sum, the figure shows that after extensive training, but not moderate training, the signal is below at the time of devaluation (Plot against ). Thus, the behaviour in the second scenario, but not the first, doesn't change right after devaluation (Plot against . Also, plot against ). The low value of the signal at the time of devaluation for the second scenario is because there is little overlap between the distribution functions of the values of the two available choices (Plots and ). The opposite is true for the first scenario (Plots and ). Numbers along the horizontal axis in plots to , and to , represent trial numbers. Each “trial” ends when the simulated agent receives a reward; e.g. in the schedule of <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002055#pcbi-1002055-g002" target="_blank">Figure 2</a> , each time the agent chooses at state , the trial number is counted up. Plots and show the distribution functions of the habitual system over its estimated -values, at one trial before devaluation. Bar charts and show the average probability of performing at 10 trials before (filled bars) and 10 trials after (empty bars) devaluation. All data reported are means over 3000 runs. The for all bar charts is close to zero and thus, not illustrated.