This review considers computational psychiatry from a particular viewpoint: namely, a
commitment to explaining psychopathology in terms of pathophysiology. It rests on the …

In this Review, we discuss advances in computational neuroscience that relate to psychiatry.
We review computational psychiatry in terms of the ambitions of investigators, emerging …

This paper considers psychotic symptoms in terms of false inferences or beliefs. It is based
on the notion that the brain is an inference machine that actively constructs hypotheses to …

Computational Psychiatry aims to describe the relationship between the brain's
neurobiology, its environment and mental symptoms in computational terms. In so doing, it …

Computational psychiatry is a rapidly growing field attempting to translate advances in
computational neuroscience and machine learning into improved outcomes for patients …

Highlights•We summarize recent progress in computational and physiological
models.•These advances provide a basis for future diagnostic applications in psychiatry.•A …

This paper describes a variational free-energy formulation of (partially observable) Markov
decision problems in decision making under uncertainty. We show that optimal control can …

A considerable number of recent experimental and computational studies suggest that
subtle impairments of excitatory to inhibitory balance or regulation are involved in many …

Viewing the brain as an organ of approximate Bayesian inference can help us understand
how it represents the self. We suggest that inferred representations of the self have a …

The transition from adolescence to adulthood is a period when ongoing brain development
coincides with a substantially increased risk of psychiatric disorders. The developmental …