Fig 6. An example of the STDP weight maps of a SEM classifier after learning (A, B) and the time evolution of ITDP weights (C).

Each weight map represents the presynaptic weight values that project to each of four WTA neurons (which each fire dominantly for one of the classes). The grey area shows pixels disabled by preprocessing, and each colored pixel represent the difference of the weights from the two input neurons for the corresponding pixel (white pixels represent unselected features). So as to use all features, a quarter of pixels are evenly selected from the supersampled image in order to use all pixels of the original data.