Abstract #3437

Methodological considerations on graph theoretical analysis of structural brain networks

Timo Roine¹, Ben Jeurissen¹, Daniele Perrone², Jan Aelterman², Wilfried Philips², Jan Sijbers¹, and Alexander Leemans³

¹iMinds-Vision Lab, Department of Physics, University of Antwerp, Wilrijk (Antwerp), Belgium, ²Ghent University-iMinds/Image Processing and Interpretation, Ghent, Belgium, ³Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands

We studied the reproducibility of whole-brain structural brain connectivity networks reconstructed with constrained spherical deconvolution based probabilistic fiber tractography. Our main finding is that a low spherical harmonics order decreases the reproducibility of graph measures in connectomics. This is most likely caused by the wider peaks in the fiber orientation distributions, which increase the variation in orientations sampled by the tractography algorithm. Based on our observations, we recommend using spherical harmonics decomposition with an order of at least eight whenever the data allows so. In addition, threshold value was important for binary networks, and some network properties were highly intercorrelated.

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