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Abstract #0674

A Study of Effect of Compiling Method on Interregional Connectivity Maps of Brain Networks via Diffusion Tractography

Longchuan Li1, James Rilling2, Todd Preuss3, Frederick Damen4, Xiaoping Hu4

1School of Medicine, Emory University/Georiga Institute of Technology, Atlanta, GA, USA; 2Division of Psychobiology, Yerkes National Primate Research Center, Atlanta, GA, USA; 3Division of Neuroscience, Yerkes National Primate Research Center, Atlanta, GA, USA; 4Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA

Estimating interregional structural connections of the brain via diffusion tractography can be a complex procedure and chosen parameters may affect the outcomes of the connectivity matrix. Here, we investigated the influence of reconstruction method on connectivity maps of brain networks. Specifically, we applied three reconstruction methods, i.e., initiating tracking from deep white matter (method #1, M1), from gray matter/white matter interface (M2), and from gray matter /white matter interface with thresholded tract volume (M3) as the connectivity index, on the same set of diffusion MR data. Hub identification was then calculated and compared across methods. Despite moderate to high correlations in the graph theoretic measures across different methods, significant variability was observed in the identified hubs, highlighting the importance of including reconstruction method as a variable influencing network parameters across studies. Consistent with the prior reports, left precuneus was unanimously identified as a hub region in all three methods, suggesting its prominent structural role in brain networks.