Average accuracy and RT across subjects (N = 34) as a function of option pairs in the learning phase (A) and option value differences (derived from the experimental reward probabilities) in the transfer phase (B) that indicated small (s), medium (m) or large (l) value differences between presented options. (C): Real and simulated choice accuracy as a function of run number in the learning phase, split by option pair. For all option pairs, simulated and real accuracy was very similar, with real EF accuracy being slightly underestimated by the model. (D): Group-level posterior distributions of the obtained parameter estimates for β, αGain and αLoss. (E): Model estimates of value beliefs for each option at the end of the learning phase. β/100 ...
<p>(A) An example of behavioral performance and predictions made by the models. Vertical black lines...
<p>Grey lines represent the median used to compute proportions of high and low scores in good and po...
(A) Geometric average likelihood per trial for each model (i.e., average total log likelihood divide...
a. The reward sensitivity beta scales how action weights (i.e., a combination of estimated probabili...
(A): During learning, 3 option pairs were presented in random order. Participants had to select the ...
<p>(<i>A</i>) Bayesian Information Criterion scores for each model (a low score is better). Models b...
Behavioral results and model fits in Experiments 1(A) and 2 (B). Top: Learning performance (i.e. per...
A. Decomposing model behavior into two metrics. We examined model behavior along two specific aspect...
A. The values of the two available rewards are shown with the dotted lines. The average drift rate μ...
<p>(A) In experiment 2 the rewards’ mean and variance of the bad option (black lines) were kept cons...
a. Simulation of N = 50,000 players shows high rewards for different combinations of learning rate f...
<p>Choice performance was measured as the percentage of trials in which participants selected the mo...
<p>(<b>A</b>) Plotted is the average (across subjects) normalized RT for three types of trials. The ...
(A) The contribution of serial hypothesis testing (SHT) was inversely correlated with reaction time ...
<p>Left: Correlation between likeability rating and simulation richness (number of details reported ...
<p>(A) An example of behavioral performance and predictions made by the models. Vertical black lines...
<p>Grey lines represent the median used to compute proportions of high and low scores in good and po...
(A) Geometric average likelihood per trial for each model (i.e., average total log likelihood divide...
a. The reward sensitivity beta scales how action weights (i.e., a combination of estimated probabili...
(A): During learning, 3 option pairs were presented in random order. Participants had to select the ...
<p>(<i>A</i>) Bayesian Information Criterion scores for each model (a low score is better). Models b...
Behavioral results and model fits in Experiments 1(A) and 2 (B). Top: Learning performance (i.e. per...
A. Decomposing model behavior into two metrics. We examined model behavior along two specific aspect...
A. The values of the two available rewards are shown with the dotted lines. The average drift rate μ...
<p>(A) In experiment 2 the rewards’ mean and variance of the bad option (black lines) were kept cons...
a. Simulation of N = 50,000 players shows high rewards for different combinations of learning rate f...
<p>Choice performance was measured as the percentage of trials in which participants selected the mo...
<p>(<b>A</b>) Plotted is the average (across subjects) normalized RT for three types of trials. The ...
(A) The contribution of serial hypothesis testing (SHT) was inversely correlated with reaction time ...
<p>Left: Correlation between likeability rating and simulation richness (number of details reported ...
<p>(A) An example of behavioral performance and predictions made by the models. Vertical black lines...
<p>Grey lines represent the median used to compute proportions of high and low scores in good and po...
(A) Geometric average likelihood per trial for each model (i.e., average total log likelihood divide...