Changes to sensory predictions are encoded by beta oscillations, surprise due to prediction violations by gamma oscillations, and alpha oscillations may have a role in controlling the precision of predictions.
Brain responses in humans demonstrate that the analysis of crowded acoustic scenes is based on a mechanism that infers the predictability of sensory information and up-regulates processing for reliable signals.
Recordings from serotonin-producing neurons in the brain reveal that these neurons are highly activated by sudden changes in previously familiar environments, potentially explaining why serotonin is important for learning to adapt to such changes.
Activation of the subthalamic nucleus (STN) pauses or disrupts behavior, while STN inhibition reduces the disruptive effects of surprise, indicating that STN activation is both sufficient and necessary for behavioral inhibition.
Computational modeling, and empirical behavioral and EEG results show that learning relies not only on comparing current events to past experience, but integrates response-based outcome predictions and confidence.