Kohonen's network tries to mimick this in a simple way. Assume that the network is fully connected - all nodes in input layer are connected to all nodes in output layer. Thus, units close to the winner as well as the winner itself, have their weights updated appreciably. Weights associated with far away output nodes do not change significantly. It is here that the toplogical information is supplied.
Nearby units receive similar updates and thus end up responding to nearby input patterns.