Combining visual and proprioceptive information in a model of spatial learning and navigation

Animals can adopt different navigation strategies according to the environment and the task they have to solve. The process of selecting the appropriate navigation strategy in mammals involves parallel pathways. The hippocampus has been thought to be the potential basis for a first type of navigation strategy in which a representation of the space is required. This representation uses spatially tuned neurons (place cells) found in the rat hippocampus. A second, different, navigation strategy that involves the dorsal striatum in the basal ganglia, is used by rats if the target can be identified by a visible cue. This work presents a computational model of the rat hippocampus and its interactions with the basal ganglia, able to reproduce neurobehavioral experiments regarding self-localisation, integration of sensory and proprioceptive information, and automatic selection of appropriate navigation strategies.