Hebbian learning analysis of a grid cell based cognitive mapping system

Abstract

It is believed that animals sense the environment by encoding the spatial information into an internal representation. Grid cells in the rat entorhinal cortex are found with periodic firing fields and have been hypothesized as the basis for the ‘cognitive map’. This paper presents a grid-cell based computational model for cognitive map building together with an analysis of the learning from grid cells to place cells. Experiment results demonstrate that the learning from grid cells to place cells plays an important role affecting the performance of map building and that the proposed computational model provides an alternative approach for robot mapping.