Extended Data Fig. 4: Dynamics of the time-dependent rate model while learning MNIST.
From: Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits
a, Schematic of the network. The enlarged hidden layer population stresses the fact that the burst rate is equal to the event rate times the burst probability, with the event and burst probability nonlinearly integrating the feedforward and feedback signals, respectively. b, Example event rates (i, iii, v) and weights (ii, iv) for two consecutive examples during the first epoch. In (i), the teacher is illustrated as a dashed line. Learning intervals are indicated by light green vertical bars. c, Burst probabilities (i, iii) and differences of burst probabilities (ii, iv) for the same examples as in b.
