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Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Neural correlates of schizotypal traits: Findings from connectome-based predictive modelling
Tao Chen1, Jia Huang2, Ji-Fang Cui3
1Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China; The University of Sydney, Brain and Mind Centre, Sydney, Australia; The University of Sydney, School of Psychology, Sydney, Australia.
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.
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