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Madison Elliott, Ronald Rensink; Limits to Attentional Selection of Features. Journal of Vision 2017;17(10):56. doi: https://doi.org/10.1167/17.10.56.
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Longstanding questions exist about how features like color and orientation are selected by visual attention (Theeuwes, 2013; Brawn & Snowden, 1999; Treisman, 1988). Here, we present a new methodology to investigate this issue. This methodology is based on the perception of Pearson correlation r in scatterplots containing both a "target" population, and an irrelevant "distractor" population, which is to be disregarded. Observers viewed two such scatterplots side-by-side (each containing a target and a distractor population), and were asked to identify the one with the higher target correlation. Methods from Rensink & Baldridge (2010) were used to measure discrimination via just noticeable differences (JNDs) at 75% correct. Target items were always black, and the background always white. Distractor items differed in color or in orientation (Fig. 1). In our color manipulation, distractor dots were one of four shades of red. In our orientation manipulation, target dots were replaced with horizontal lines, and distractors were lines oriented at 30, 45, 60, and 90 degrees. In conditions where there were no distractor populations, JNDS were proportional to the distance from r = 1, consistent with the results of earlier studies. In two-population conditions, however, the slope of the JND lines increased, indicating interference from the irrelevant distractors. Two forms of interference were found. In our color manipulation, when the distractor dots were light pink (and most different from the target dots), interference was low, but when they were dark red (and most similar to the target dots), interference was high. Meanwhile, in our orientation manipulation, interference was high for distractors at 60 and 90 degree, but low for distractors at 30 and 45 degrees. This suggests that attentional selection may differ for different features. It also shows that this methodology may be a useful new way to examine attentional selection.
Meeting abstract presented at VSS 2017
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