Estimating function from structure in epileptics using graph diffusion model

The relationship between anatomic and resting state functional connectivity (FC) of large-scale brain networks has been of interest and has been investigated in a number of articles. In a recent article we introduced a graph diffusion model which predicts the functional network from the structural network in healthy brains. In this work we apply the graph diffusion model to two types of epilepsy, medial temporal sclerosis epilepsy (TLE-MTS), and MRI-normal temporal lobe epilepsy (TLE-no). We show that it is possible to estimate function from structure in non-healthy brains. We conclude that TLE-MTS on average requires a higher graph diffusion depth to estimate FC than both the healthy or the TLE-no groups. This suggests that an overly strong FC/SC relationship might be a sign of poor brain condition.