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- W4313706728 abstract "Schizotypal traits can be conceptualized as a phenotype for schizophrenia spectrum disorders. As such, a better understanding of schizotypal traits could potentially improve early identification and treatment of schizophrenia. We used connectome-based predictive modelling (CPM) based on whole-brain resting-state functional connectivity to predict schizotypal traits in 82 healthy participants. Results showed that only the negative network could reliably predict an individual's schizotypal traits (r = 0.29). The 10 nodes with the highest edges in the negative network were those known to play a key role in sensation and perception, cognitive control as well as motor control. Our findings suggest that CPM might be a promising approach to improve early identification and prevention of schizophrenia from a spectrum perspective." @default.
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- W4313706728 date "2023-03-01" @default.
- W4313706728 modified "2023-09-30" @default.
- W4313706728 title "Neural correlates of schizotypal traits: Findings from connectome-based predictive modelling" @default.
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- W4313706728 doi "https://doi.org/10.1016/j.ajp.2022.103430" @default.
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