Figure 12. Hebbian learning results in lognormal weight distribution independent of gain distribution.

Given is a lognormal input rate ${\sigma }_{R^I}^{*}=2,{\mu }_{R^I}^{*}=\mathrm{4.95.}$ A: Initial weight configurations: Gaussian (grey) or uniform (blue). B: After Hebbian learning using Gaussian gain distribution (grey, blue as before). C: After Hebbian learning using uniform gain distribution (grey, blue as before). D: After Hebbian learning using lognormal gain distribution. $({\sigma }_G^{*}=1.37,{\mu }_G^{*}=32.7)$ (grey, blue as before).