Brain network eigenmodes provide a robust and compact representation of the structural connectome in health and disease
Fig 4
A-C) The average angle variance of the eigenvectors from normal volunteers were calculated along with 95% confidence bounds and are shown in blue, with higher variance indicating less reliability in the eigenvector of interest. For comparison, the average angle variance of eigenvectors for randomly generated networks are shown in red. Note that for the second and third eigenvector, the average angle variance is significantly lower than the average angle between eigenvectors from random networks, whereas the same does not hold true for the fourth eigenvector in the FXCN atlas. D) The distribution of the eigenvalues across all healthy subjects is shown in blue, with the distribution of eigenvalues in random networks shown in red. The eigenvalues of ten healthy adults were calculated individually using brain graphs averaged from two MRI scans from each subject and were then normalized by their mean. The resulting eigen-spectra were then averaged across all ten subjects and its 95% confidence interval was plotted as error bars. Eigenmodes are numbered in increasing order of eigenvalues. Insets for the lowest and highest eigenmodes were added for clarity. Statistical significance marked as * was determined via two-sample t-tests with an α of 0.05. E-F) The second eigenmode for two randomly generated brains are shown for comparison.