  According to the dominant view, time in perceptual decision making is used
for integrating new sensory evidence. Based on a probabilistic framework, we
investigated the alternative hypothesis that time is used for gradually
refining an internal estimate of uncertainty, that is to obtain an increasingly
accurate approximation of the posterior distribution through collecting samples
from it. In the context of a simple orientation estimation task, we
analytically derived predictions of how humans should behave under the two
hypotheses, and identified the across-trial correlation between error and
subjective uncertainty as a proper assay to distinguish between them. Next, we
developed a novel experimental paradigm that could be used to reliably measure
these quantities, and tested the predictions derived from the two hypotheses.
We found that in our task, humans show clear evidence that they use time mostly
for probabilistic sampling and not for evidence integration. These results
provide the first empirical support for iteratively improving probabilistic
representations in perceptual decision making, and open the way to reinterpret
the role of time in the cortical processing of complex sensory information.
