Best-fitting parameters for the Bayesian model summarized per experiment and averaged for the entire group of subjects and per subgroup (optimists and pessimists).

<p>Each column presents the mean value, with the standard deviation between brackets. Significance of the differences is shown on the right of the table: an asterisk in the corresponding column (left to right: LOT-R; α/(α+β) which defines where the prior is centered; γ is the softmax decision parameter) indicates a p value less than 0.05 for a t-test between optimists and pessimists.</p

a) Cartoon of the task: subjects are presented with a sequence of stimuli (here: O₁, O₂, O₁) followed by a decision screen (D₁).

<p>Here the subject needs to choose between the yellow fractal and the square for which the reward probability is given by the number of blue dots (6 dots, indicating a probability of 60%). <u>Inset:</u> Example of a longer sequence of interleaved observation screens and decision screens. <b>b</b>) Performance of the subjects (% trials in which they chose the fractal stimulus) as a function of the difference between the observed reward rate of the fractal being considered and the reward probability of the square. Compared to pessimistic people (red, LOT-R≤mean LOT-R), optimistic people (blue, LOT-R>mean LOT-R) tend to overestimate the probability of reward associated with the uncertain fractal stimulus. Errors bars denote standard deviation. <b>c</b>) Correlation between subjects' LOT-R scores and the mean of their prior distribution p(c) that the fractal stimulus will lead to a reward (r = 0.438, p = 0.001). <b>d</b>) Examples of the prior distributions that were extracted for subjects 10 (pessimistic, LOT-R = 3) and 11 (optimistic, LOT-R = 22) based on their task performance.</p

Punishment avoidance experiment.

<p><b>a</b>) Cartoon of the task. The CS can either lead to a punishment (indicated by a sad face) or nothing. <b>b</b>) Performance of the subjects (percentage of trials in which they chose the fractal stimulus) as a function of the difference between the observed reward rate of the fractal being considered and the reward probability of the square. Pessimistic (red, LOT-R≤mean LOT-R) and optimistic people (blue, LOT-R>mean LOT-R) behave similarly. <b>c</b>) Correlation between subjects' LOT-R scores and the mean of their prior distribution p(c) that the fractal stimulus will lead to a reward (r = −0.049; p = 0.74).</p

Reduced uncertainty experiment.

<p><b>a</b>) Performance of the subjects (percentage of trials in which they chose the fractal stimulus) as a function of the difference between the observed reward rate of the fractal being considered and the reward probability of the square. Pessimistic (red, LOT-R≤mean LOT-R) and optimistic people (blue, LOT-R>mean LOT-R) behave similarly. Errors bars denote standard deviation. <b>b</b>) Correlation between subjects' LOT-R scores and the mean of their prior distribution p(c) that the fractal stimulus will lead to a reward (r = 0.009, p = 0.95).</p

Best-fitting parameters for the RL models summarized per experiment and averaged per group.

<p>Each value reported in the column shows mean values for different RL models (left to right: RL_ε; RL₂; RL_2b; RL_b) and X means that the variable is not used in a model. Significance of the differences is shown on the right of the table: an asterisk in the corresponding column indicates a p value less than 0.05 for a t-test between optimists and pessimists. Parameters ε+, ε− denote the learning rates for positive and negative errors respectively, v_o is the initial value of all CS, and τ is the softmax decision parameter.</p