Computational psychiatry is a heterogeneous field at the intersection of computational neuroscience and psychiatry. Incorporating methods from psychiatry, psychology, neuroscience, behavioral economics, and machine learning, computational psychiatry focuses on building mathematical models of neural or cognitive phenomena relevant to psychiatric diseases. The models span a wide range – from biologically detailed models of neurons or networks to abstract models describing high-level cognitive abilities of an organism. Psychiatric diseases are conceptualized either as an extreme of normal function or as a consequence of alterations in parts of the model.
As in computational neuroscience more generally, the building of models forces key concepts to be made concrete and hidden assumptions to be made explicit. One critical function of these models in the setting of psychiatry is their ability to bridge between low-level biological and high-level cognitive features. While many...
KeywordsDepression Dopamine Schizophrenia Serotonin Noradrenaline
I thank Dominik Bach, Kay H. Brodersen, Anthony Cruickshank, Peter Dayan, Marc Guitart-Masip, Helene Haker, Gregor Hasler, Falk Lieder, Tiago Maia, John Milton, Michael Moutoussis, Peggy Seriès, and Klaas Enno Stephan for informative comments and discussions on an earlier version of this contribution.
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