Human and animal studies suggest that human perception can be interpreted as probabilistic inference that relies on representations of uncertainty about sensory stimuli suitable for statistically optimal decision-making and learning. It has been proposed recently that the way the brain implements probabilistic inference is by drawing samples from the posterior probability distribution, where each sample consists of instantaneous activity of a population of neurons (Fiser et al, 2010). However, there is no experimental evidence thus far, showing that an internal representation of uncertainty can extend to low-level sensory attributes, nor that humans use sampling-based representations in perceptual judgment tasks. To address these questions, we created an orientation-matching task in which we measured both subjects’ performance and their level of uncertainty as they matched orientation of a randomly chosen element of the previously presented stimulus. Stimuli consisted of 2-7 differently oriented line segments shown spaced evenly on a circle extending 2 degrees of the visual field. In response to the first question, we found that subjects’ performance and subjective report of uncertainty were significantly correlated (r=0.37, p<.001) and that this correlation was independent of the number of oriented line segments shown. To address the second question, we varied the stimulus presentation time trial-to-trial to influence the number of samples available before making a judgment. Since samples are drawn sequentially, the prediction of the sampling-based representations is that precision of representing uncertainty will depend on the time available independent of the recorded performance. We found that decreasing the presentation time results in a significant decrease of the error-uncertainty correlation (p<0.05) while the performance levels remain constant. Thus, limiting the presentation time influences the reliability of uncertainty representation specifically, in agreement with sampling-based representations of uncertainty in the cortex, and in contrast with the predictions of other probabilistic representations.