Subjects were informed in which range the probabilities could change but not about

their order or possible values. Also, as in previous work (den Ouden et al., 2010), they were explicitly instructed that the conditional probabilities were coupled as follows (f  : face; h  : house; ♪=↑♪=↑ : high tone; ♪=↓♪=↓ : low tone): equation(Equation 1) p(f|♪=↑)=1−p(h|♪=↑)=p(h|♪=↓)=1−p(f|♪=↓).p(f|♪=↑)=1−p(h|♪=↑)=p(h|♪=↓)=1−p(f|♪=↓). We ensured that the marginal probabilities of face and house outcomes were identical across the experiment and could thus not bias the participants’ predictions. This was achieved by requiring that (1) the probability of one outcome given a particular cue was the same as the probability of the other outcome given the other cue (Equation 1), and (2) in each block, both cue types appeared equally often and in random order. With these two manipulations, we ensured that, on average, before the PARP inhibitor cue was presented, the a priori probability of a face or a house occurring was 50% each. Thus, on SB431542 mw any given trial, it was not possible to make an informed prediction about the outcome before having heard the cue. In the behavioral study and first fMRI study, each trial was associated with a potential monetary reward. Specifically, at the end of each trial the visual outcome was presented for 150 ms in the center of the image, together with a coin (5 CHF or 0.05 CHF) randomly located in one of the

corners (Figure 1A). Critically, reward size was uncorrelated to the visual outcome to be predicted. In other words, high and low reward appeared randomly on 50% of the trials each, ensuring that any cue would predict any reward with 50% probability. At the end of the experiment, we applied a simple pay-out rule: 100 low-rewarding trials and one high-rewarding trial were randomly chosen, and the summed reward from correct trials only was paid out (note that the maximal possible net value for both low- and high-reward through trials was identical, i.e., 5 CHF). This procedure was used to motivate the participants to deliver

constantly high performance throughout the experiment: by minimizing the number of incorrect predictions about the visual outcome, participants would maximize their expected total reward. Although we instructed our participants explicitly that the reward sequence was random and could not be learned, one might wonder whether some subjects might nevertheless have tried to predict upcoming reward instead of visual outcomes. We therefore also modeled any putative learning of the orthogonal reward and performed model comparison to quantify whether predictions of visual outcomes or reward would better explain the subjects’ observed behavior (see below). Finally, in the second fMRI study, we omitted reward. This enabled us to examine experimentally whether behavior and fMRI activations would remain identical when monetary reward were absent.