Grid-to-place cells model based on radial basis function network

A novel model of grid cells (GCs) to place cells (PCs) based on radial basis function network (RBFN) is proposed. The connection between multi-scale GCs and a PC is established through RBFN. For each PC, it is associated with a learned RBFN. During vehicle's space exploration, PCs and RBFNs are recruited flexibly after analysing the firing status of the existing PCs, and the transformation from GCs to a new PCs is learned for encoding a new location. As a result, PCs are generated incrementally to represent the explored space. Simulation results validate the proposed model is effective, and the firing characteristic of generated PCs is similar to that of biological PCs.