Fig. 4: Statistical properties of the connectome and cortical morphology, and their relationships with wiring parameters and age.

a The correlation matrix of connectome and morphological findings show how each measure correlates with every other measure. Measures 3–6 were included in the energy equation. Measures 7–11 are connectome measures not included in the energy equation. Measures 12–19 are cortical morphological measures. η and γ are each significantly correlated with a range of measures, both inside and outside of the energy equation. Correlation coefficient matrices are shown, the bottom row of which is highlighted and is reflected in the above radar plots (middle), in addition to the significance matrix (bottom), across varying numbers of top performing parameters, for each of the 19 measures investigated. b Radar plots depict the correlations between all measures and η (left) and γ (right) averaged across the top N = 500 parameters in the parameter space. All statistics were computed via two-tailed linear correlations, quoting the Pearson’s correlation coefficient. The asterisk, *, reflects significant correlations at p < 0.05. Note, the inner edge of the radar plot reflects negative correlations and the outer edge reflects positive correlations. Specific results for variable top performing parameters are provided in Supplementary Table 3. Further scatter plots are provided highlighting the relationship of wiring parameters with age. η has a significantly positive relationship with age (r = 0.325, p = 4.518 × 10⁻⁸) while γ has a weak non-significant negative relationship with age (r = −0.117, p = 0.054).