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Award ID contains: 1921735

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  1. In the laboratory, visual search is often studied using uniform backgrounds. This contrasts with search in daily life, where potential search items appear against more complex backgrounds. In the present study, we examined the effects of background complexity on a parallel visual search under conditions where objects are easily segregated from the background. Target–distractor similarity was sufficiently low such that search could unfold in parallel, as indexed by reaction times that increase logarithmically with set size. The results indicate that when backgrounds are relatively simple (sandy beach with water elements), search efficiency is comparable to search using a solid background. When backgrounds are more complex (child bedroom or checkerboard), logarithmic search slopes increase compared to search on solid backgrounds, especially at higher levels of target–distractor similarity. The results are discussed in terms of different theories of visual search. It is proposed that the complex visual information occurring in between distractors slows down individual distractor rejection times by weakening the strength of interitem interactions. 
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    Abstract Objects differ from one another along a multitude of visual features. The more distinct an object is from other objects in its surroundings, the easier it is to find it. However, it is still unknown how this distinctiveness advantage emerges in human vision. Here, we studied how visual distinctiveness signals along two feature dimensions—shape and surface texture—combine to determine the overall distinctiveness of an object in the scene. Distinctiveness scores between a target object and distractors were measured separately for shape and texture using a search task. These scores were then used to predict search times when a target differed from distractors along both shape and texture. Model comparison showed that the overall object distinctiveness was best predicted when shape and texture combined using a Euclidian metric, confirming the brain is computing independent distinctiveness scores for shape and texture and combining them to direct attention. 
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