Highlights•The combination of data-driven machine learning and theory-driven
computational models holds great promise for psychiatry.•Machine-learning analyses of …

Improvements in understanding the neurobiological basis of mental illness have
unfortunately not translated into major advances in treatment. At this point, it is clear that …

Computational models have great potential to revolutionise psychiatry research and clinical
practice. These models are now used across multiple subfields, including computational …

Importance Major depressive disorder (MDD) is associated with deficits in representing
reward prediction errors (RPEs), which are the difference between experienced and …

Loss aversion is a central element of prospect theory, the dominant theory of decision
making under uncertainty for the past four decades, and refers to the overweighting of …

Making effective decisions during approach-avoidance conflict is critical in daily life.
Aberrant decision-making during approach-avoidance conflict is evident in a range of …

We separate for the first time the roles of cognitive and motivational factors in shaping age
differences in decision making under risk. Younger and older adults completed gain, loss …

Modern theories of decision-making typically model uncertainty about decision options
using the tools of probability theory. This is exemplified by the Savage framework, the most …

An examination of the cognitive tools that the mind uses to grapple with uncertainty in the
real world. How do humans navigate uncertainty, continuously making near-effortless …

A number of developmental theories have been proposed that make differential predictions
about the links between age and temporal discounting, or the devaluation of future rewards …