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Abstract #2231

Graph-based network analysis of multi-echo resting-state fMRI data in people with high schizotypy

Kurtis Stewart1, Owen O'Daly1, Gareth J Barker1, Katrina McMullen2, Veena Kumari1, Steven CR Williams1, and Gemma Modinos1

1Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom, 2Centre for Brain Health, University of British Columbia, BC, Canada

We applied graph theoretical network analysis on multi-echo resting-state fMRI data to examine whether healthy people with subclinical psychotic-like experiences (schizotypy) show abnormal functional brain topology compared to similar subjects without such experiences. While we did not observe significant between-group differences in any connectivity measure (Local and global efficiency, Modularity, and Small-worldness), within the schizotypy group we found that modularity and small-worldness were directly related to the severity of subclinical psychotic-like experiences. This demonstrates the feasibility of applying graph theory on multi-echo rs-fMRI in individuals with vulnerability for psychotic disorders and encourages the application of these methods in psychosis research.

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