Uncertainty Estimation Performance.

<p>In this figure we show that subjects are able to discern the different levels of uncertainty added to the cues. (<b>A</b>) <b>Objective Uncertainty.</b> We plot the mean error range (twice the mean absolute deviation of the final mean estimate) SEM, for different levels of (solid blobs and error bars), for perturbed (red) and unperturbed (blue) trials. In addition we overlay the average results for each subject (faded lines). Subjects show statistically significantly increased errors as a result of both cue uncertainty and the presence of perturbations. Between-subject variability is low, as indicated by the distinct separation between red and blue lines and the consistency of the gradient. (<b>B</b>) <b>Subjective Uncertainty.</b> We plot the average width of subject’s confidence window at the end of the trial for each and perturbation, similar to A. Subjects show a statistically significantly increased confidence window as a result of both cue uncertainty and the presence of perturbations, mimicking the objective uncertainty. However, between-subject variability is high, indicating that different subjects have widely differing abilities at estimating uncertainty. (<b>C</b>) <b>Subjective-Objective Mapping.</b> We combine per-subject data from A and B, plotting the mean error for each condition versus the confidence reported. The ideal mapping is shown by the dotted line. Subjects consistently over-estimate the objective uncertainty. (<b>D</b>) <b>Grouped Subjective-Objective Mapping.</b> We plot the average mapping across subjects the SEM in each direction. This demonstrates the consistency with which subjects over-estimate their objective uncertainty.