Abstract
Although psychiatry has a rich variety of models, most fail to span biological, psychological, and social domains. Computational psychiatry offers simple, direct ways of uniting these levels of explanation and analysis by providing notions that are applicable to each one. 1 Montague PR Dolan RJ Friston KJ Dayan P Computational psychiatry. Trends Cogn Sci. 2012; 16: 72-80 Summary Full Text Full Text PDF PubMed Scopus (446) Google Scholar Computational psychiatry holds, we argue, serious promise for development of comprehensive explanations and treatments for psychiatric illness; it can provide an account of how a person interacts with and is influenced by the world and so should be closely aligned to cognitive approaches in the investigation and treatment of mental illness. 2 Halligan PW David AS Cognitive neuropsychiatry: towards a scientific psychopathology. Nat Rev Neurosci. 2001; 2: 209-215 Crossref PubMed Scopus (105) Google Scholar We suggest that psychiatry has much to gain from harnessing the remarkable developments in computational neuroscience and the growing success in application of these techniques to our understanding of brain processes, cognition, and social interaction. This is the central goal of computational psychiatry, and the aim of this brief Personal View is to show its potential value. We give three linked examples relating to cognitive modelling of psychosis, neurochemical investigations, and integration of pharmacological and cognitive interventions. Although our focus is on psychosis and uses perspectives emerging from the field of learning and reinforcement, the points raised are applicable to other mental illnesses, and a great deal has been achieved with economic and game-theoretic perspectives. 3 Kishida KT King-Casas B Montague PR Neuroeconomic approaches to mental disorders. Neuron. 2010; 67: 543-554 Summary Full Text Full Text PDF PubMed Scopus (92) Google Scholar
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