Glossary
Computational psychiatry
What is Computational Psychiatry?
Computational psychiatry uses mathematical models and data-analysis methods to investigate mental illness. It includes both theory-driven models of processes and data-driven approaches to prediction.
How it works
Huys, Maia, and Frank distinguish approaches that model possible mechanisms from machine-learning approaches that can predict outcomes without explaining the underlying mechanism. Improving classification and treatment selection is a research aim, not a result guaranteed by using a computational model.
Applied example
For example, researchers could model how a person updates expectations after rewards and losses, then ask whether the model helps predict depressive symptoms or treatment outcomes in new data. A value estimated from task performance is not, by itself, evidence of a biological impairment.
Why it matters
The field can connect theories with measurable predictions. Clinical use requires reliable measurement, independent validation, and evidence that the resulting decisions benefit patients.