Computational models of musical structure reveal cortical encoding of pitch and rhythm expectations during naturalistic music listening.

Key variables required for pain perception in the context of a predictive coding model are correlated with distinct oscillatory profiles.

Bayesian integration is able to predict placebo treatment outcomes by focusing especially on the influence of the precision of expectations.

Learned expectations allow for a distinct anticipatory distractor representation at the feature but not at the spatial level.

Cerebellar degeneration disrupts the use of interval-based temporal cues, but not rhythmic cues, to proactively modulate perceptual sensitivity, implicating the cerebellum in temporal control of visual attention.

When a person listens to music, their brain continually predicts upcoming notes, based on that person's likely lifelong musical experience.

Pain processing in certain brain regions implements predictive coding principles, offering a novel perspective on the neural basis of pain perception.

With extended practice, stimulus expectations modulate activity in early visual areas that encode the sensory evidence for perceptual choices.

The subcortical visual pathway through the midbrain superior colliculus is responsible for visually evoked Pavlovian conditioning and dopamine neuron responses with predicted value in monkeys, which remained after lesioning V1.

Context-based object recognition causally relies on both scene- and object-selective cortex, with scene-selective cortex generating expectations (at 160-200 ms after onset) that disambiguate object representations in object-selective cortex (at 260-300 ms after onset).