Effects of predictions robustness and object-based predictions on subjective visual perception.

Abstract

Learned regularities about contextual associations between objects and scenes allow us to form predictions about the likely features of the environment, facilitating perception of noisy visual inputs. Studies have shown that blurred objects that can be predicted based on their scene context appear subjectively sharper than the same objects that cannot. Experiment 1 addressed whether this effect could be modulated by the robustness of context-based predictions. Participants performed a blur-matching task between two images, each depicting a blurred object in context. They had to adjust the blur level of the right object to match that of the left object (Target). Robustness of context-based predictions was manipulated via phase-coherence alteration in scene contexts. Results showed that robustly predicted objects were subjectively perceived as sharper than less predictable objects when the Target object was noisy. Experiment 2 addressed whether object-based predictions also sharpen the perception of scene contexts. Participants performed a blur-matching task between two scenes and had to adjust the blur level of the right scene context to match that of the left one (Target). One scene contained an intact object (predictable context), while the other had a phase-scrambled object (unpredictable context). Results showed that at objectively equal blur levels participants perceived predictable scenes as sharper than unpredictable ones, again only when the Target scene was noisy. These results suggest that perceptual sharpening mainly occurs when the visual signal is noisy and predictions are robust enough to disambiguate it, and reveal reciprocal influences between context- and object-based predictions in shaping visual perception.