We review the current state of knowledge on the computational and neural mechanisms of
reinforcement-learning with a particular focus on fronto-striatal circuits. We divide the …

Compulsive behaviour, an apparently irrational perseveration in often maladaptive acts, is a
potential transdiagnostic symptom of several neuropsychiatric disorders, including …

Regulating how fast to learn is critical for flexible behavior. Learning about the
consequences of actions should be slow in stable environments, but accelerate when that …

Every decision we make is accompanied by a sense of confidence about its likely outcome.
This sense informs subsequent behavior, such as investing more—whether time, effort, or …

It has long been suggested that human behavior reflects the contributions of multiple
systems that cooperate or compete for behavioral control. Here we propose that the brain …

Decisions in the natural world are rarely made in isolation. Each action that an organism
selects will affect the future situations in which it finds itself, and those situations will in turn …

Animal behavior is driven by multiple brain regions working in parallel with distinct control
policies. We present a biologically plausible model of off-policy reinforcement learning in the …

In recent years, brain science and neuroscience have greatly propelled the innovation of
computer science. In particular, knowledge from the neurobiology and neuropsychology of …

Our brain can be recognized as a network of largely hierarchically organized neural circuits
that operate to control specific functions, but when acting in parallel, enable the performance …

Computational models have become integral to human neuroimaging research, providing
both mechanistic insights and predictive tools for human cognition and behavior. However …