Graph theory analysis applied to FA maps

Graph theory analysis applied to FA maps, to study differences in WM structural connectivity associated with obesity.

Scripts developed for the following research project.

Differences in WM structural connectivity were sought by comparing graph measures from young women with normal weight (Dnorm) and obesity (Dover), studying FA-based inter-tract correlation matrices. Undirected binary adjacency matrices were created from WM inter-tract correlation matrices. Sixteen global graph measures were compared between the Dnorm and Dover groups. At the nodal level, four graph measures were compared. Optimal community structures were calculated using the Louvain community detection algorithm. This was done considering all network, as well as the left and right hemispheres separately.