Recent findings suggest that humans represent uncertainty for statistically optimal decision making and learning. However, it is unknown whether such representations of uncertainty extend to multiple low-level elements of visual stimuli, although this would be crucial for optimal probabilistic representations. We examined how subjects’ subjective assessment of uncertainty about the orientations of multiple elements in a visual scene and their performance in a perceptual task are related. Stimuli consisted of 1–4 Voronoi patches within a circular 2º wide area, each patch filled with gray-scale Gabor wavelets drawn from distributions with different mean orientations. After a 2 s presentation, the stimulus disappeared and the subjects had to select the overall orientation around a randomly specified location within the area of the stimulus, and report their confidence in their choice. We found that subjects’ performance, as measured by the accuracy of the selected orientation, and their uncertainty judgment were strongly correlated (p<0.00001) even if multiple different orientations were present in the stimulus, and independently of the number of patches. These results suggest that humans not only represent low-level orientation uncertainty, but that this representation goes beyond capturing a general mean and variance of the entire scene.

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