Home > Publications database > Brain‐based ranking of cognitive domains to predict schizophrenia |
Journal Article | FZJ-2019-04012 |
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2019
Wiley-Liss
New York, NY
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Please use a persistent id in citations: http://hdl.handle.net/2128/23670 doi:10.1002/hbm.24716
Abstract: Schizophrenia is a devastating brain disorder that disturbs sensory perception, motoraction, and abstract thought. Its clinical phenotype implies dysfunction of variousmental domains, which has motivated a series of theories regarding the underlyingpathophysiology. Aiming at a predictive benchmark of a catalog of cognitive functions,we developed a data-driven machine-learning strategy and provide a proof ofprinciple in a multisite clinical dataset (n = 324). Existing neuroscientific knowledge ondiverse cognitive domains was first condensed into neurotopographical maps. Wethen examined how the ensuing meta-analytic cognitive priors can distinguishpatients and controls using brain morphology and intrinsic functional connectivity.Some affected cognitive domains supported well-studied directions of research onauditory evaluation and social cognition. However, rarely suspected cognitivedomains also emerged as disease relevant, including self-oriented processing of bodilysensations in gustation and pain. Such algorithmic charting of the cognitive landscapecan be used to make targeted recommendations for future mental health research.
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