Toward a Better Understanding of Target Distinctiveness in Visual Search: How Color, Shape, and Texture Information Combine to Guide Search.

Target distinctiveness is a key determinant of visual search performance: the greater the distinctiveness, the more efficient the search. Previous research has demonstrated that in bidimensional searches, where the target and distractors differ along two feature dimensions (e.g., color and shape), the distinctiveness of the target is the combination of the distinctiveness of the target along each individual feature dimension, according to different rules. Color and shape distinctiveness combine collinearly, while shape and texture combine orthogonally. Here, we examine how signals along color, shape, and texture dimensions combine to guide tridimensional searches, where the target differs from distractors along all three dimensions. Adopting a behavioral-computational approach, we used performance observed in unidimensional searches – where the target differed from distractors along one of the three dimensions – to predict performance in tridimensional searches, where they differed across all three dimensions. Two sets of experiments were conducted, utilizing the same paradigm but different stimuli, varying in the amount of target distinctiveness available across the three dimensions. In Set 1, the distinctiveness along color was more pronounced compared to shape and texture. In Set 2, distinctiveness across the three dimensions was more balanced. Both sets of experiments supported the idea that a weighted combination of distinctiveness along all three dimensions best predicted the tridimensional search performance. Additionally, we observed that participants in Set 1 assigned greater attentional weight to color compared to those in Set 2, indicating that the weighting across the three feature dimensions depends on the usefulness of the relevant dimensions.