Hippocampal Based Model Reveals the Distinct Roles of Dentate Gyrus and CA3 during Robotic Spatial Navigation

Abstract

Animals are exemplary explorers and achieve great navigational performances in dynamic environments. Their robotic counterparts still have difficulties in self-localization and environment mapping tasks. Place cells, a type of cell firing at specific positions in the environment, are found in multiple areas of the hippocampal formation. Although, the functional role of these areas with a similar type of cell behavior is still not clearly distinguished. Biomimetic models of navigation have been tested in the context of computer simulations or small and controlled arenas. In this paper, we present a computational model of the hippocampal formation for robotic spatial representation within large environments. Necessary components for the formation of a cognitive map [1], such as grid and place cells, were obtained through attractor dynamics. Prediction of future hippocampal inputs was performed through self-organization. Obtained data suggests that the integration of the described components is sufficient for robotic space representation. In addition, our results suggest that dentate gyrus (DG), the hippocampal input area, integrates signals from different dorsal-ventral scales of grid cells and that spatial and sensory input are not necessarily associated in this region. Moreover, we present a mechanism for prediction of future hippocampal events based on associative learning.