In many everyday decisions, individuals choose between trialling something novel or something they know well. Deciding when to try a new option or stick with an option that is …
Organisms learn from prediction errors (PEs) to predict the future. Laboratory studies using small financial outcomes find that humans use PEs to update expectations and link …
Deficits in reward learning are core symptoms across many mental disorders. Recent work suggests that such learning impairments arise by a diminished ability to use reward history …
Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the …
Background From a behavioural perspective anhedonia is defined as diminished interest in the engagement of pleasurable activities. Despite its presence across a range of psychiatric …
Recent evidence indicates that reward value encoding in humans is highly context dependent, leading to suboptimal decisions in some cases, but whether this computational …
The field of computational psychiatry advocates for the use of behavioral task-derived computational measures to improve our understanding, diagnosis and treatment of …
Mental illnesses arise from dysfunction in the brain. Although numerous extraneural factors influence these illnesses, ultimately, it is the science of the brain that will lead to novel …
Aberrant reward processing and poor self-regulation have a crucial role in the development of several adverse outcomes in youth, including mental health disorders and risky …