Bayesian theories posit that perception is the result of combining expectations with the sensory input, and that expectations are updated when that sensory input is surprising – i.e., deviates from the expectation. To be adaptive, expectations should only be updated when the surprising observation reveals that the world is actually different from our models, but it is not yet clear how this...
Salient but task-irrelevant distractors interfere less with visual search when they appear in a display region where distractors have appeared more frequently in the past. In this study we tested two different theories of such statistical distractor-location learning. It could reflect the (re-)distribution of a global, limited attentional ‘inhibition resource’. Accordingly, changing the...
Error-based theories of language acquisition posit that predictions are a key part of language processing throughout the lifespan. They suggest that adults and children are constantly anticipating upcoming input and use discrepancies to update their linguistic knowledge from the very earliest stages of development. However, linguistic predictions are challenging to target experimentally, and...