Abstract
We assessed the processing capacity of establishing statistical summary representations of mean size in visual displays using the simultaneous-sequential method. Experiment 1 tested the capacity of summary representations across multiple ensembles. Four sets of stimuli, each composed of multiple circles with various diameters, were presented around fixation. The mean size of one of the four sets was either smaller or larger than that of the other sets. Observers searched for the odd set and reported whether its mean was smaller or larger. In the simultaneous condition, all four sets were presented concurrently; in the sequential condition, the sets appeared two at a time. Simultaneous performance was reliably worse than sequential performance, indicating that processing was limited capacity in this task. The limit was even as extreme as a fixed-rate bottleneck process. Experiment 2 tested the processing capacity of summary representations within a single ensemble. The same four sets, containing four items each, were arranged along an equally spaced grid to create the perception of a single set of sixteen items. Observers reported whether the average of the set was smaller or larger than the size of a probe circle that appeared afterward. Performance was equal across the simultaneous and sequential conditions, indicating unlimited-capacity processing. Contrary to existing claims, summary representations appear to be extracted independently only for items within single ensembles, and not across multiple ensembles. These results contribute to a developing understanding of capacity limitations in perceptual processing. When drawing similarities between the processes at each extreme, sensory and segmentation processes appear to have unlimited capacity while object and semantic processes have fixed capacity. The present study suggests that the formation of summary statistic representations for multiple ensembles across the visual field is more like object and semantic processing than it is like sensory or organizational processing.
Meeting abstract presented at VSS 2014