{Reference Type}: Journal Article
{Title}: Can hubs of the human connectome be identified consistently with diffusion MRI?
{Author}: Gajwani M;Oldham S;Pang JC;Arnatkevičiūtė A;Tiego J;Bellgrove MA;Fornito A;
{Journal}: Netw Neurosci
{Volume}: 7
{Issue}: 4
{Year}: 2023
{Factor}: 4.98
{DOI}: 10.1162/netn_a_00324
{Abstract}: Recent years have seen a surge in the use of diffusion MRI to map connectomes in humans, paralleled by a similar increase in processing and analysis choices. Yet these different steps and their effects are rarely compared systematically. Here, in a healthy young adult population (n = 294), we characterized the impact of a range of analysis pipelines on one widely studied property of the human connectome: its degree distribution. We evaluated the effects of 40 pipelines (comparing common choices of parcellation, streamline seeding, tractography algorithm, and streamline propagation constraint) and 44 group-representative connectome reconstruction schemes on highly connected hub regions. We found that hub location is highly variable between pipelines. The choice of parcellation has a major influence on hub architecture, and hub connectivity is highly correlated with regional surface area in most of the assessed pipelines (ρ > 0.70 in 69% of the pipelines), particularly when using weighted networks. Overall, our results demonstrate the need for prudent decision-making when processing diffusion MRI data, and for carefully considering how different processing choices can influence connectome organization.