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Cooperative coding of continuous variables in networks with sparsity constraint

Fig 8

Cooperative coding in an excitatory spiking network of leaky integrate-and-fire neurons.

(A) Network wiring diagram. Connections are marked in black if their strength depends on RF size, and in gray otherwise. (B) Single neuron transfer function (black solid) and threshold-linear fit (gray dashed). Inset highlights onset nonlinearity. (C) Top: Simulated vs. target RF size. Light gray crosses: networks with analytically computed weights; black circles: networks with numerically optimized weights. Middle: excitatory synaptic weights (normalized for arbitrary indegree: the voltage increase in response to one spike is given by ) . Bottom: Feedforward input to stimulated population (on) and to others (off), used both for networks with analytically or numerically computed weights. Left and right dashed vertical lines mark example simulation shown in (D) and (E). The target RF peak rate was set here to Hz. (D) Example simulation for target RF size . Top: Binned average firing rates of 41 feature populations. Middle: Raster plot showing spikes of 10 exemplary neurons from each feature population. Color codes distance from the stimulated population (population index 21, the population includes neurons 200-209 shown in black). Bottom: Feedforward stimulation. Right: Stationary population rates (gray), exponential fit (black dashed), and target rate profile (red). (E) Example simulation for target RF size . All panels are as in (D).

doi: https://doi.org/10.1371/journal.pcbi.1012156.g008