title: Computational psychiatry.
abstract: Computational ideas pervade many areas of science and have an integrative explanatory role in neuroscience and cognitive science. However, computational depictions of cognitive function have had surprisingly little impact on the way we assess mental illness because diseases of the mind have not been systematically conceptualized in computational terms. Here, we outline goals and nascent efforts in the new field of computational psychiatry, which seeks to characterize mental dysfunction in terms of aberrant computations over multiple scales. We highlight early efforts in this area that employ reinforcement learning and game theoretic frameworks to elucidate decision-making in health and disease. Looking forwards, we emphasize a need for theory development and large-scale computational phenotyping in human subjects.
authors.affiliation: Virginia Tech Carilion Research Institute and Department of Physics, Virginia Tech, 2 Riverside Circle, Roanoke, VA 24016, USA. read@vt.edu
authors.forename: P Read
authors.initials: PR
authors.lastname: Montague
authors.forename: Raymond J
authors.initials: RJ
authors.lastname: Dolan
authors.forename: Karl J
authors.initials: KJ
authors.lastname: Friston
authors.forename: Peter
authors.initials: P
authors.lastname: Dayan
mesh_terms: D001689:Biological Psychiatry / Q000379:methods*; D001921:Brain / Q000503:physiopathology; D019295:Computational Biology / Q000379:methods*; D003210:Concept Formation; D003657:Decision Making; D005716:Game Theory; D006801:Humans; D001523:Mental Disorders / Q000503:physiopathology; D008959:Models, Neurological; D009488:Neurosciences / Q000379:methods*; D012054:Reinforcement, Psychology