Neurotransmitters serve as chemical messengers playing a crucial role in information
processing throughout the nervous system, and are essential for healthy physiological and …

Psychiatric disorders encompass complex aberrations of cognition and affect and are
among the most debilitating and poorly understood of any medical condition. Current …

Sequential decision making, commonly formalized as Markov Decision Process (MDP)
optimization, is an important challenge in artificial intelligence. Two key approaches to this …

There is and has been a fruitful flow of concepts and ideas between studies of learning in
biological and artificial systems. Much early work that led to the development of …

Reinforcement learning (RL) is a framework of particular importance to psychology,
neuroscience and machine learning. Interactions between these fields, as promoted through …

To make decisions, animals must evaluate candidate choices by accessing memories of
relevant experiences. Yet little is known about which experiences are considered or ignored …

Distinct model-free and model-based learning processes are thought to drive both typical
and dysfunctional behaviours. Data from two-stage decision tasks have seemingly shown …

Humans and animals are capable of evaluating actions by considering their long-run future
rewards through a process described using model-based reinforcement learning (RL) …

Translating advances in neuroscience into benefits for patients with mental illness presents
enormous challenges because it involves both the most complex organ, the brain, and its …

Importance Abnormal reward processing is suggested to underlie the formation of psychotic
symptoms, likely driven by elevated ventral striatal (VS) dopamine levels. Functional …