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Computational Psychiatry Meets Genetics: Reinforcement Learning in Early Psychosis and In Relation to Clinical and Molecular Genetic Risk for Schizophrenia

Murray, G; Montagnese, M; Knolle, F; Griffin, J; Haarsma, J; Richards, A; Vertes, P; ... Goodyer, I; + view all (2019) Computational Psychiatry Meets Genetics: Reinforcement Learning in Early Psychosis and In Relation to Clinical and Molecular Genetic Risk for Schizophrenia. Presented at: 26th World Congress of Psychiatric Genetics (WCPG), Glasgow, Scotland. Green open access

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Type: Conference item (Presentation)
Title: Computational Psychiatry Meets Genetics: Reinforcement Learning in Early Psychosis and In Relation to Clinical and Molecular Genetic Risk for Schizophrenia
Event: 26th World Congress of Psychiatric Genetics (WCPG)
Location: Glasgow, Scotland
Dates: 11 - 15 October 2018
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.euroneuro.2018.08.319
Publisher version: https://doi.org/10.1016/j.euroneuro.2018.08.319
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Clinical, Edu and Hlth Psychology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10079684
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