Many thanks to 2 anonymous reviewers for their helpful and constructive comments on the earlier version of the manuscript!

These findings support predictive processing theories according to which the relative weight of predictions over the processing of sensory inputs varies with their reliability. They also reveal reciprocal influences between context- and object-based predictions in shaping visual perception.

Our findings show that predictable objects and scenes were perceived as sharper than unpredictable ones. Perceptual sharpening emerged mainly when inputs were degraded (blurred) and scaled with the robustness of predictions.

In our second experiment, we manipulated the availability of object-based predictions about blurred scene contexts by embedding either an intact object (predictable context) or a fully phase-scrambled object (unpredictable context).

In our first experiment, blurred objects were embedded in a scene context. We manipulated the robustness of context-based predictions about the object by scrambling the scene’s phase spectrum at different levels.

We evaluated the perceived sharpness of blurred scenes and objects using a perceptual matching task (adjust the blur of the right image to match the left one).

Following our previous studies showing that scene-based predictions sharpen the perception of blurred objects, this study further asks whether this effect scales with the robustness of predictions and whether object-based predictions reciprocally sharpen the perception of scene context

C'est Franceinfo qui a craqué c'est bien un MEG et meta est juste à l'origine de l'IA qui traduit l'activité neuro en texte (et même ça c'est pas si nouveau même si peut-être pas à un niveau aussi avancé) ai.meta.com/blog/brain-a...