Our brains have many local loops in their neural networks. These local loops inhibit the neurons that activate them. This plays a major role in the stability of brainwave patterns. The neurons of these local loops learn like any other neuron, so inhibition can increase over time. Thus errors are "forward" propagated in a loopy model.
