Fig. 6.

Results of iterative feature reduction approach. At each iteration, the top final backtrack weighted connectome dynamic features were used to train neural networks with the correct participant labels, and to train neural networks with randomly permutated participant labels. At each iteration the difference in classification accuracy is recorded, and the greatest difference was achieved when the top $\mathit{k}=16$ connectome dynamic features are used.