Memory over 24 hours was impaired in Parkinson's patients off, rather than on, dopaminergic medication during reinforcement learning, whereas dopamine did not affect positive and negative reinforcement, in contrast to previous studies.

fMRI evidence for off-task replay predicts subsequent replanning behavior in humans, suggesting that learning from simulated experience during replay helps update past policies in reinforcement learning.

The human brain is capable of implementing inverse reinforcement learning, where an observer infers the hidden reward structure of a decision problem solely through observing another individual take actions.

Computational modeling suggests that feedback between striatal cholinergic neurons and spiny neurons dynamically adjusts learning rates to optimize behavior in a variable world.

A mathematical model built around the assumption that the desire to maintain internal homeostasis drives the behavior of animals, by affecting their learning processes, can explain many real-world behaviors, including some that might otherwise appear irrational.

Confidence-dependent reinforcement learning is active and produces trial-to-trial choice updating even in well-learned perceptual decisions without explicit reward biases, across species and sensory modalities.

Cerebellar climbing fibers can generate learned reward-predictive instructional signals, suggesting a role for cerebellar learning in the reinforcement of reward-driven behaviors.

Patients with DYT1 dystonia show aberrant risk-aversion in a simple decision-making task, in accordance with predictions of a reinforcement learning model of corticostriatal trial-and-error learning.

Neural confidence signals can take the role of reward signals and explain perceptual learning without external feedback as a form of internal reinforcement learning.

The finding that fly maggots, equipped with only 10,000 neurons, process reinforcement not only by value but also by specific quality reveals a basic operating principle of brains and challenges current models of memory organization.