Object expectations alter information use during visual recognition

Prior expectations influence how we perceive and recognize objects. However, how they do so remains unclear, especially in the case of real-world complex objects. Expectations of objects may affect which features are used to recognize them subsequently. In this study, we used reverse correlation to reveal with high precision how the use of information across time is modulated by real-world object expectations in a visual recognition task. We show that coarse information leads to accurate responses earlier when an object is expected, indicating that observers use diagnostic features earlier in this situation. We also demonstrate an increased variability in the use of coarse information depending on the expected object, indicating that observers adopt a more specialized recognition strategy when they expect a specific object. In summary, our results reveal potential mechanisms underlying the effect of expectations on the recognition of complex objects.