Brain network eigenmodes provide a robust and compact representation of the structural connectome in health and disease
Fig 6
A) The Pearson’s correlation coefficient was calculated between the eigenmode importance maps and edge density maps from [15, 16]. Each edge density map (rich club, feeder, and local connections) represent the density of white matter connections throughout the brain and were calculated on the same group of healthy adult subjects used to generate the averaged importance maps shown in Fig 2. Each edge density map was then averaged across all subject and then the Pearson correlation of white matter voxels was taken between each density map and the averaged eigenmode importance maps in Fig 2. The error bars reflect the 95% confidence intervals of the Pearson’s correlation coefficient. B) The Pearson’s correlation coefficient was calculated between each averaged eigenmode importance map and shown as a heatmap where brighter squares indicate a higher correlation between the pair of eigenmodes shown on the x and y axes.