This model shows how spatial representations in 3D space could emerge using unsupervised neural networks. Model is a hierarchical one which means that it has multiple layers, where each layer has got a specific function to achieve. This architecture is more of a generalised one i.e. it gives rise to different kinds of spatial representations after training.
Soman K, Chakravarthy S, Yartsev MM (2018) A hierarchical anti-Hebbian network model for the formation of spatial cells in three-dimensional space. Nat Commun 9:4046 [PubMed]