Performance of the linear SVM classifier using the significant features (1,000 bootstrap resamples). Paired T-tests were conducted to show the significance of differences between performance indices with two level of p-value provided. For all three classification conditions, the combined feature set outperform each separate modality alone, with the classification accuracy for BP vs. MDD being 92.07%, BP vs. HC 80.78%, and MDD vs. HC 79.51%. Sensitivity and specificity rates share the same propensity. Moreover, functional features yielded better results than structural ones.