Crowding results from optimal integration of visual targets with contextual information.

ABSTRACT: Crowding is the inability to recognize an object in clutter, usually considered a fundamental low-level bottleneck to object recognition. Here we advance and test an alternative idea, that crowding, like predictive phenomena such as serial dependence, results from optimizing strategies that exploit redundancies in natural scenes. This notion leads to several testable predictions: crowding should be greatest for unreliable targets and reliable flankers; crowding-induced biases should be maximal when target and flankers have similar orientations, falling off for differences around 20°; flanker interference should be associated with higher precision in orientation judgements, leading to lower overall error rate; effects should be maximal when the orientation of the target is near that of the

SUBMITTER: Cicchini GM 

PROVIDER: S-EPMC9525686 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature