Activation likelihood estimation (ALE) meta-analyses were used to examine the neural
correlates of prediction error in reinforcement learning. The findings are interpreted in the …

Reinforcement learning is an adaptive process in which an animal utilizes its previous
experience to improve the outcomes of future choices. Computational theories of …

Dual-system approaches to psychology explain the fundamental properties of human
judgment, decision making, and behavior across diverse domains. Yet, the appropriate …

Habits form a crucial component of behavior. In recent years, key computational models
have conceptualized habits as arising from model-free reinforcement learning mechanisms …

Animals adapt their behavior in response to informative sensory cues using multiple brain
circuits. The activity of midbrain dopaminergic neurons is thought to convey a critical …

We provide evidence that decisions are made by consulting memories for individual past
experiences, and that this process can be biased in favour of past choices using incidental …

Spatial navigation can serve as a model system in cognitive neuroscience, in which specific
neural representations, learning rules, and control strategies can be inferred from the vast …

It has long been recognized that the striatum is composed of distinct functional sub-units that
are part of multiple cortico-striatal-thalamic circuits. Contemporary research has focused on …

The hierarchical structure of human and animal behavior has been of critical interest in
neuroscience for many years. Yet understanding the neural processes that give rise to such …

A network of brain structures including hippocampus (HC), prefrontal cortex, and striatum
controls goal-directed behavior and decision making. However, the neural mechanisms …