Topological Properties of Large-Scale Cortical Networks Based on Multiple Morphological Features in Amnestic Mild Cognitive Impairment

Figure 5

Between-group differences in clustering coefficient () and characteristic path length () of different morphological features based networks. The graph shows the differences in and between NC and aMCI as a function of sparsity of geometric measures networks. The blue lines represent the mean values (open circles) and 95% confidence intervals of the between-group differences obtained from 1000 permutation tests at each sparsity value. The arrows indicate significant difference in or between the two groups. (a) Between-group differences in and as a function of sparsity of cortical thickness networks. (b) Between-group differences in and as a function of sparsity of gray matter volume networks. (c) Between-group differences in and as a function of sparsity of surface area networks. (d) Between-group differences in and as a function of sparsity of mean curvature networks. (e) Between-group differences in and as a function of sparsity of metric distortion (Jacobian) networks. (f) Between-group differences in and as a function of sparsity of sulcal depth networks. Thickness, cortical thickness. Volume, gray matter volume. Area, surface area. Curv, mean curvature. Sulc, sulcal depth. NC, normal controls.

(a) Thickness

(b) Volume

(c) Area

(d) Curv

(e) Jacobian

(f) Sulc