Attention to object categories: Selection history determines the breadth of attentional tuning during real-world...

People excel at learning the statistics of their environments. For instance, people rapidly learn to pay attention to locations that frequently contain visual search targets. Here, we investigated how frequently finding specific objects as search targets influences attentional selection during real-world object search. We investigated how learning that a specific object (e.g., a coat) is task-relevant affects searching for that object and whether a previously frequent target would influence search more broadly for all items of that target's category (e.g., all coats). Across five experiments, one or more objects from a single category were likely targets during a training phase, after which objects from many categories became equally likely to be targets in a neutral testing phase. Participants learned to find a single frequent target object faster than other objects (Experiment 1, N = 44). This learning was specific to that object, with no advantage in finding a novel category-matched object (Experiment 2, N = 32). In contrast, learning to prioritize multiple exemplars from one category spread to untrained objects from the same category, and this spread was comparable whether participants learned to find two, four, or six exemplars (Experiment 3, N = 72). These differences in the breadth of attention were due to variability in the learning environment and not differences in task (Experiment 4, N = 24). Finally, a set-size manipulation showed that learning affects attentional guidance itself, not only postselective processing (Experiment 5, N = 96). These experiments demonstrate that the breadth of attentional tuning is flexibly adjusted based on recent experience to effectively address task demands. (PsycInfo Database Record (c) 2024 APA, all rights reserved).