One way to avoid overfitting is to trim spurious interactions Wij -> O. This constraint forces the network to economize on the neural circuitry, thereby driving

One way to avoid overfitting is to trim spurious interactions Wij -> O. This constraint forces the network to economize on the neural circuitry, thereby driving the system to find an optimal network topology. Hypothetically this should favor certain circuit-design principles. I don't know how much work has been done in artificial neural networks but there has been quite a bit of work gone with artificial gene regulatory networks which utilize the same mathematical model of integrating weighted inputs and passing this through some kind of sigmoidal/logistic function.