Fig. 6: Age-related patterns of GWM-HFN and GM-GM connectivity and their direct comparison.

A, D Scatter plot illustrating the negative linear correlation between mean GWM-HFN connectivity and age (r = -0.252, p = 1.0 × 10⁻⁰⁷), while (D) shows the contrasting inverted U-shaped quadratic relationship for the benchmark GM-GM network. In both plots, each dot represents an individual, and its color indicates the density of overlapping data points. The red line depicts the fitted linear regression, and the shaded region represents the 95% confidence interval of the linear fit. B, E Circular connectograms depicting edge-level age effects for GWM-HFN and GM-GM networks, respectively. For each, the left panel shows linear effects (blue: negative, red: positive), and the right panel shows quadratic effects (green: inverted U-shaped, purple: U-shaped), with line thickness representing effect magnitude. Brain regions are color-coded according to their associated functional networks. C Clustered bar chart showing the proportion of significant age-related edges for the GWM-HFN framework, distributed across the seven functional networks and separated into within-network and between-network connections. F Heatmap illustrating the overlap of significant age-sensitive edges between the two frameworks. Red indicates edges significant in both methods (overlap), yellow indicates edges specific to GWM-HFN, and green indicates edges specific to GM-GM. G Scatterplots showing the significant positive correlation between the effect sizes (t-values) of overlapping age-sensitive edges for negative linear effects (left panel) and inverted U-shaped quadratic effects (right panel). H Scatter plot showing the positive correlation between age and the similarity of GWM-HFN and GM-GM connectivity patterns (r = 0.311, p = 3.0 × 10⁻¹¹), indicating greater convergence between the two methods in older individuals. n = 440 biologically independent participants (SALD dataset).