Figure 14. Hebbian or homeostatic gain learning determine lognormal or Gaussian outcome.

Given is a lognormal input rate ${\sigma }_{R^I}^{*}=2,{\mu }_{R^I}^{*}=4.95$. A: Initial Configuration: Gaussian (grey) or uniform (blue). B and C: Hebbian learning using lognormal or Gaussian weights, resulting gain distribution is lognormal. D and E: Homeostatic learning using lognormal or Gaussian weights, resulting gain distribution is Gaussian.