Statistical summary representations of bound features.

Abstract

The visual system can efficiently summarize various lower-level and higher-level features of ensembles. However, no research to date has directly investigated how different features interact with each other within a single summary and whether people can efficiently report an integrated summary of two feature dimensions. In the first two experiments, we specifically investigated whether individuals can integrate spatial and size information to report a bound spatial summary, the center of mass (CoM), as efficiently as the centroid, which is devoid of size information. Both experiments revealed that viewers were equally accurate in extracting the centroid and the CoM, with the size distribution inadvertently affecting the centroid estimates. In the final experiment, we investigated whether encouraging observers to attend to individual item size would cause the centroid estimates to be biased toward the CoM. When item size was task-irrelevant, as in the centroid task, observers were able to selectively focus on spatial location, eliminating any impact from the size distribution. Taken together, these findings demonstrate that viewers are capable of extracting integrated summaries, possibly through a mechanism that allows them to represent the spatial distribution of sizes. We discuss possible mechanisms that may support the extraction of integrated summaries, and highlight the need to consider multilevel mechanisms extending beyond simple feature- and object-based mechanisms.