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Natural scene statistics predict how humans pool information across space in surface tilt estimation

Fig 6

Conditional distributions of groundtruth tilt given the value of the tilt estimate.

Each subplot shows the distribution of groundtruth tilt given a particular local estimate value . For example, the fifth subplot in the first row shows the distribution of groundtruth tilts given that the local tilt estimate had a value of 120º (i.e., ). The fact that the conditional distributions of groundtruth tilt are approximately shift-invariant indicates that each local tilt estimate, regardless of its value, provides approximately equally reliable information about groundtruth tilt. Gray regions represent 95% confidence intervals from Monte Carlo simulations of 1000 experimental datasets. Confidence intervals at non-cardinal tilts (e.g., = 30º, 60º, 120º, 150º, etc.) are larger in part because the local model produces fewer non-cardinal tilt estimates, in keeping with the prior probability distribution over tilt, which has peaks at the cardinal tilts (e.g., τ = 0º, 90º, etc.; see Fig 2C).

doi: https://doi.org/10.1371/journal.pcbi.1007947.g006