The **data** can be fitted by the Bayesian model for the four yes rate curves (two configurations 3 two contextual contrasts) using only four parameters: k, r n , and the prior probabilities P(yes) colinear and P(yes) orthogonal , with each **data** point typically about one error bar size away from the model fit. As expected, P(yes) colinear . P(yes) orthogonal ( Figure 4E). However, both P(yes) colinear and P(yes) orthogonal are quite high. This we believe is the net result of combining two factors, one is the observers' internal prior to reach roughly equal numbers of ''yes'' and ''no'' responses, and the other is the contextual dependent priors from the statistical knowledge of the natural visual environment. Indeed, the average yes rate (over all trials and observers) is 57% 6 2%. The difference between the fitted P(yes) colinear and P(yes) orthogonal reflects the difference between the natural priors that has survived observers' internal prior imposed by the unnatural laboratory experiment.