Matteo Bastiani1, 2, Rainer Goebel1, Alard Roebroeck1
1Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; 2Forschungszentrum Jlich, Jlich, Northreinwestfalen, Germany
This work focuses on reconstructing the macroscopic human cortical connectome using diffusion weighted imaging. This can be represented as a graph where cortical patches are nodes and white-matter connections are edges. The effects on estimating the most common graph measures when using single versus multi direction diffusion models, deterministic versus probabilistic tractography, and local versus global measure-of-fit of the reconstructed fiber trajectories are evaluated. We show that these choices, together with anisotropy, curvature and probabilistic threshold parameters can strongly affect connection density, small-worldness and cortical connection hubs. This is an important consideration for studies using these measures as dependent variables.