Estimating brain's functional graph from the structural graph's Laplacian

The interplay between the brain’s function and structure has been of immense interest to the neuroscience and connectomics communities. In this work we develop a simple linear model relating the structural network and the functional network. We propose that the two networks are related by the structural network’s Laplacian up to a shift. The model is simple to implement and gives accurate prediction of function’s eigenvalues at the subject level and its eigenvectors at group level.