Extended Data Fig. 8: Learning MNIST with the simplified rate model.

A convolutional network whose architecture is described in Supplementary Table 3 was trained using backprop, feedback alignment, and burstprop. As in Fig. 6a,c, recurrent input was introduced at hidden layers to keep burst probabilities linear with respect to feedback signals.