Explicit access to detailed representations of feature distributions.

Abstract

The human visual system can quickly process groups of objects (ensembles) and build compressed representations of their features. What does the conscious perception of ensembles consist of? Observers' explicit access to ensemble representations has been considered very limited - any distributional aspects beyond simple summary statistics, such as the mean or variance, cannot be explicitly accessed. In contrast, we demonstrate that the visual system can represent ensemble distributions in detail, and observers have reliable explicit access to these representations. In our new paradigm (Feature Frequency Report), observers viewed 36 disks of various colors for 800 ms and then reported the frequency of a randomly chosen color using a slider. The sets had Gaussian, uniform, or bimodal color distributions with a random mean color. The distributions of responses - both aggregated and separate for each observer - followed the shape of the presented distribution. Modeling revealed that performance reflected integrated information from the whole set rather than sub-sampling. After only brief exposure to a color set, the visual system can build detailed representations of feature distributions that observers have explicit access to. This result necessitates a fundamental rethinking of how ensembles are processed. We suggest that such distribution representations are the most natural way for the visual system to represent groups of objects. Explicit feature distribution representations may contribute to people 's impression of having a rich perceptual experience despite severe attentional and working memory limitations.