• Login
    View Item 
    •   ORKA Home
    • Conditions, Lifestyle Factors & Interventions
    • Conditions
    • Mental Disorders (General)
    • View Item
    •   ORKA Home
    • Conditions, Lifestyle Factors & Interventions
    • Conditions
    • Mental Disorders (General)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Advances in the computational understanding of mental illness

    Thumbnail
    Date
    2020-07
    Author
    Browning, Michael
    Metadata
    Show full item record
    Citation
    Quentin J M Huys, Michael Browning, Martin Paulus, Michael J Frank. Advances in the computational understanding of mental illness. Neuropsychopharmacology . 2020 Jul 3
    Abstract
    Computational psychiatry is a rapidly growing field attempting to translate advances in computational neuroscience and machine learning into improved outcomes for patients suffering from mental illness. It encompasses both data-driven and theory-driven efforts. Here, recent advances in theory-driven work are reviewed. We argue that the brain is a computational organ. As such, an understanding of the illnesses arising from it will require a computational framework. The review divides work up into three theoretical approaches that have deep mathematical connections: dynamical systems, Bayesian inference and reinforcement learning. We discuss both general and specific challenges for the field, and suggest ways forward.
    URI
    https://oxfordhealth-nhs.archive.knowledgearc.net/handle/123456789/550
    Published online at:
    https://DOI: 10.1038/s41386-020-0746-4
    Collections
    • Mental Disorders (General) [52]

    Oxford Health copyright © 2019
    Contact Us | Send Feedback | JSPUI
    Powered by KnowledgeArc
     

     

    Browse

    All of ORKACommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsContributor DisciplineThis CollectionBy Issue DateAuthorsTitlesSubjectsContributor Discipline

    My Account

    Login

    Researcher Profiles

    Researchers

    Oxford Health copyright © 2019
    Contact Us | Send Feedback | JSPUI
    Powered by KnowledgeArc