Test GCN with different brain graphs

[zhangyu2ustc]

the first step of GCN is to construct a populational graph.
there are three types of brain graphs we could choose:

1. spatial neighborhood
2. structural covariance
3. RSFC

In the 2nd and 3rd graphs, we need to additionally construct a sparse KNN graph because it is very dense which might cause computational problems

Note, previously I had made a mistake by taking the weakest connections for the KNN graph, which has worsen the performance of GCN. Now it worked and we could compare them.

[zhangyu2ustc]

the performance of using different brain graphs are very similar.
for motor classification (epochs=40):
train_acc test_acc
spatial: 0.94 0.90
SC: 0.93 0.90
RSFC: 0.93 0.90

we need to figure out the reason. After plotting the Adj-matrix using imshow, we do see a big difference between brain graphs. Why the performance did not change?
maybe during KNN-graph setting?