Combining lateral and elastic interactions: Topology-preserving elastic nets

We have developed a topology-preserving elastic net which combines both lateral and synaptic interactions to obtain topologically ordered representations (receptive fields) of an external stimulus. Existing neural models that preserve the topology by utilizing lateral interactions, such as the Kohonen-type maps, and by utilizing synaptic interactions, such as elastic-type nets, appear as limiting cases of this model. Utilizing both lateral and synaptic interactions can be beneficial for preservation of the topology.