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Abstract #1929

Quantifying the Intra- And Inter-Subject Variability of Whole-Brain Structural Networks from Diffusion MRI

Colin R. Buchanan1, Krzysztof Gorgolewski1, Cyril R. Pernet2, Amos J. Storkey1, Mark E. Bastin2

1School of Informatics, University of Edinburgh, Edinburgh, United Kingdom; 2School of Molecular & Clinical Medicine, University of Edinburgh, Edinburgh, United Kingdom

We assessed the intra and intersubject variability of graph-theoretic measures of brain connectivity obtained from diffusion MRI (dMRI). Our method involves: 1) segmentation of cortical regions from high-resolution 3D T1-weighted volume scans; 2) construction of structural networks from dMRI data using established tractography algorithms with seed points placed in cortical regions; 3) graph-theoretic analysis of cortico-cortical connections; 4) quantification of between-subject and within-subject differences of network metrics using a percentile bootstrap technique. Results show that four commonly used network metrics can be produced consistently between imaging sessions with interscan difference of less than 6%.