I'm currently looking a little bit closer at growing self-organising maps for a grant proposal. These are derived from the famous Kohonen map, a kind of neural network which establishes a correspondence between a high dimensional input space and a lower dimensional one (almost always 2 dimensions, but not necessarily). Whereas soms work with a fixed number of nodes, growing soms unfold with time. This makes them useful for e.g. language acquisition modeling (especially since these are unsupervised networks).