Figure 10.

Plots accompanying another reservoir computing example, in which an input population of size equal to the CIFAR-10 data dimensionality is connected to a population of 625 LIF neurons, which is recurrently connected to itself. (A) Spikes recorded from the input and output layers of the two layer reservoir network. (B) Voltages recorded from the output of the two layer reservoir network. (C) Raw input and its reconstruction, computed by summing Poisson-distributed spike trains over the time dimension. (D) Weights from input to output neuron populations, initialized initialized from the distribution $\mathcal{N}(0,1)$. (E) Recurrent weights of the output population, initialized from the distribution $\mathcal{N}(0,\frac{1}{2})$.