Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning

Abstract

We model hippocampal place cells and head-direction cells by combin-ing allothetic (visual) and idiothetic (proprioceptive) stimuli. Visual in-put, provided by a video camera on a miniature robot, is preprocessed by a set of Gabor filters on 31 nodes of a log-polar retinotopic graph. Unsu-pervised Hebbian learning is employed to incrementally build a popula-tion of localized overlapping place fields. Place cells serve as basis func-tions for reinforcement learning. Experimental results for goal-oriented navigation of a mobile robot are presented. 1