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

Prior expectations, induced by statistical learning, affect sensory processing only for attended stimuli, thereby constraining neurocomputational theories that cast perception as an inferential process integrating prior knowledge and sensory evidence.

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.

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

Cross-modal stimuli are represented in the primary gustatory cortex according to their sensory identity, associability and predictive value.

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

Cell biological features are subject to stochastic forces of mutation and random genetic drift, which together cause lineages exposed to identical selection pressures to diverge, and mean phenotypes to deviate from expectations under optimizing selection.

A computational model explains how the brain chooses between creating a new memory versus updating an old one when faced with an event that defies expectations.

Autistic traits are associated with weaker influence of prior expectations in visual perception, which is due to more precise sensory representations.