Figure 5.

Discriminative weight structure of classifier. A, B, The weights of the support vector classifier are depicted for all connections within hemisphere (A) and between hemispheres (B) for the network of eight ROIs. The nodes of the graph correspond to the ROIs (compare Fig. 2). The line thickness is proportional to the absolute value of the respective dimension of the average weight vector. Hence, it is related to the amount of information about the two conditions that is present in the temporal correlation between the respective region pair. The line color gives information of the sign of the weight corresponding to the connection (black, minus; white, plus). Numbers at the bottom right of A and B indicate the number of black and white lines in the two graphs. The number of black lines in A, and thus, the number of white lines in B, are significantly higher than expected by chance (p = 0.04). C, Illustration of weights versus connections for all cross-folds individually. For every connection (x-axis), the corresponding weight is plotted for all seven cross-folds. Black triangles depict intrahemispheric connections; white squares are interhemispheric connections. Connections are ordered to confirm with A and B: intrahemispheric connections on the left, interhemispheric connections on the right.