Factors influencing RT.

We used two sets of GLMs to predict the normalized RT as a function of the absolute difference in the actual (A) or estimated (B) probability of reward on the two objects presented on a given trial (absolute difference in actual/subjective reward probability), the trial number within a block of the experiment, the difference between BIC per trial (BICp) based on the best feature-based and object-based models (i.e., model-adoption index) for a given subject, and the reward outcome on the preceding trial. Reported values are the normalized regression coefficients (±s.e.m.), p-values for each coefficient (two-sided t-test), and adjusted R-squared for each experiment. No interaction term was statistically significant and thus, interactions terms are not reported here.