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Noam Khayat, Shaul Hochstein; Perceiving set mean and range: Automaticity and precision. Journal of Vision 2018;18(9):23. doi: https://doi.org/10.1167/18.9.23.
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© ARVO (1962-2015); The Authors (2016-present)
To compensate for the limited visual information that can be perceived and remembered at any given moment, many aspects of the visual world are represented as summary statistics. We acquire ensemble representations of element groups as a whole, spreading attention over objects, for which we encode no detailed information. Previous studies found that different features of items (from size/orientation to facial expression/biological motion) are summarized to their mean, over space or time. Summarizing is economical, saving time and energy when the environment is too rich and complex to encode each stimulus separately. We investigated set perception using rapid serial visual presentation sequences. Following each sequence, participants viewed two stimuli, member and nonmember, indicating the member. Sometimes, unbeknownst to participants, one stimulus was the set mean, and or the nonmember was outside the set range. Participants preferentially chose stimuli at/near the mean, a “mean effect,” and more easily rejected out-of-range stimuli, a “range effect.” Performance improved with member proximity to the mean and nonmember distance from set mean and edge, though they were instructed only to remember presented stimuli. We conclude that participants automatically encode both mean and range boundaries of stimulus sets, avoiding capacity limits and speeding perceptual decisions.
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