Advances in the computational understanding of mental illness
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...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer Nature
2020
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| _version_ | 1797054768424681472 |
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| author | Huys, Q Browning, M Paulus, M Frank, M |
| author_facet | Huys, Q Browning, M Paulus, M Frank, M |
| author_sort | Huys, Q |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-06T19:01:55Z |
| format | Journal article |
| id | oxford-uuid:13d2d264-0194-4117-8466-4a9a1329569f |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:01:55Z |
| publishDate | 2020 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | oxford-uuid:13d2d264-0194-4117-8466-4a9a1329569f2022-03-26T10:16:03ZAdvances in the computational understanding of mental illnessJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:13d2d264-0194-4117-8466-4a9a1329569fEnglishSymplectic ElementsSpringer Nature2020Huys, QBrowning, MPaulus, MFrank, MComputational 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. |
| spellingShingle | Huys, Q Browning, M Paulus, M Frank, M Advances in the computational understanding of mental illness |
| title | Advances in the computational understanding of mental illness |
| title_full | Advances in the computational understanding of mental illness |
| title_fullStr | Advances in the computational understanding of mental illness |
| title_full_unstemmed | Advances in the computational understanding of mental illness |
| title_short | Advances in the computational understanding of mental illness |
| title_sort | advances in the computational understanding of mental illness |
| work_keys_str_mv | AT huysq advancesinthecomputationalunderstandingofmentalillness AT browningm advancesinthecomputationalunderstandingofmentalillness AT paulusm advancesinthecomputationalunderstandingofmentalillness AT frankm advancesinthecomputationalunderstandingofmentalillness |