Modeling Rodent Head-direction Cells and Place Cells for Spatial Learning in Bio-mimetic Robotics

We propose a computational model which is consistent with several neurophysiological findings concerning biological head-direction cells and hippocampal place cells. The model consists of two separate neural systems providing directional and place coding representations, respectively. These two modules are strongly coupled and interact with each other to form a unitary spatial learning system. We stress the importance of correlating idiothetic and allothetic signals to determine the dynamics of the system in order to stabilize head-direction and place representations over time. We give experimental results obtained by implementing the entire model on a real mobile robot.