One set of properties that may emerge when attention is distributed over an array of similar items is the general statistics of the set. We investigated mean size perception using three different methods: a change detection "flicker" task, implicit priming, and a dual task paradigm. In the change detection task, participants discriminated a change of size from a change of location of an array of circles of different sizes. The changes either did or did not result in a mean change of size. Performance was more efficient when the mean size changed than when it did not, suggesting that the mean is perceptually represented. In the implicit priming task, we used a same-different size judgment on two circles, preceded by a prime display containing 12 circles of two different sizes. One or both of the target circles could match either the mean size (that was never presented), or one of the two primed sizes, or a size that was 20% larger or smaller than a presented size. The priming benefit was as large when the targets matched the mean size of the prime display as when they matched a size that was actually presented. To manipulate the deployment of attention, we used a dual task paradigm in which the secondary task required either global or focused attention. Thresholds for judging the mean size of circles in the array were lower when the concurrent task required global compared to local attention, even when the secondary tasks were closely matched in difficulty. The results support the proposal that we preserve statistical information from sets of similar objects rather than representing all the detailed information and that this information is best extracted when attention is globally deployed. Means of sets may be one ingredient of a schematic representation that could explain our coherent perception of a visual scene.
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