Functional MRI connectivity accurately distinguishes cases with psychotic disorders from healthy controls, based on cortical features associated with neurodevelopment
Abstract:Background. Machine learning (ML) can distinguish cases with psychotic disorder from healthy controls based on magnetic resonance imaging (MRI) data, with reported accuracy in the range 60-100%. It is not yet clear which MRI metrics are the most informative for case-control ML.Methods. We analysed multi-modal MRI data from two independent case-control studies of patients with psychotic disorders (cases, N = 65, 28; controls, N = 59, 80) and compared ML accuracy across 5 MRI metrics. Cortical thickness, mean di… Show more
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