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Kyle Killebrew, Christopher Blair, Gideon Caplovitz; Summary statistics influence how individuals are perceived in noise.. Journal of Vision 2014;14(10):882. doi: 10.1167/14.10.882.
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© ARVO (1962-2015); The Authors (2016-present)
It has been consistently demonstrated that human observers are able to extract statistical averages from groups of objects in a variety of different feature domains, including but not limited to orientation, color, size, and facial expression. However, little known about how this summary information is used and what function it may serve. Here, we tested the hypothesis that one function may be to fill-in information under conditions of visual uncertainty. That is to say, in suboptimal viewing conditions in which object individuation may be difficult, the visual system uses summary information to represent individual items. The current study was designed to explicitly test a prediction made by this hypothesis. The hypothesis makes a basic prediction that the perceived variability of a group should be underestimated, particularly in the presence of noise. That is because the percept of each individual item will be biased towards the extracted average. In two experiments, we used adaptive staircase procedures in which participants judged which of two groups of varying sized circles (two interval forced choice) had the greater mean (Experiment 1) or was more variable (Experiment 2). The results of Experiment 1 indicate that the presence of noise did not significantly impair participants' ability to extract the mean size of the array (Weber fraction). This suggests that in the presence of noise, this information is not lost. Consistent with the hypothesis, the results of Experiment 2 indicate that the perceived variability in size was significantly underestimated in the presence of noise. The results of this study suggest that the rapid and potentially pre-attentive extraction of summary information may be used in a top-down fashion to influence how the individuals of a group appear.
Meeting abstract presented at VSS 2014
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