Toward a better understanding of target distinctiveness in visual search: How color, shape, and texture information combine to guide search.

People often search for objects distinctive from other objects in the scene along multiple feature dimensions like color and shape. A target distinctive in more than one dimension can lead to an easier search, but it also increases the complexity of modeling search behaviors. Building upon previous research on how people search using information along two feature dimensions, we explored how search unfolds when the target and distractors differ along the dimensions of color, shape, and texture (a tridimensional search). Using a behavioral-computational approach, we found that the target-distractor distinctiveness signal along each dimension combines in a weighted orthogonal way to guide tridimensional searches. Additionally, across two sets of experiments, we demonstrated that the weight assigned to each dimension varied according to its relative usefulness. When the color distinctiveness was most pronounced (Set 1), there was a much stronger prioritization of color information over information carried by shape and texture. When the distinctiveness along individual dimensions was more balanced (Set 2), the weights were distributed more evenly across the three dimensions, but a color prioritization remained. These results have broad implications for cognitive neuroscience, as they place constraints on how visual information from different dimensions is integrated to produce an overall guidance signal, and demonstrate how attention might be flexibly allocated across channels in response to the ecological aspects of the environment. This study should also interest modelers in cognitive science because it demonstrates an approach to understand behavior in complex scenarios based on performance indices estimated under simpler conditions. (PsycInfo Database Record (c) 2026 APA, all rights reserved).