Episodes in Space: A Modeling Study of Hippocampal Place Representation

A computer model of learning and representing spatial locations is studied. The model builds on biological constraints and assumptions drawn from the anatomy and physiology of the hippocampal formation of the rat. The emphasis of the presented research is on the usability of a computer model originally proposed to describe episodic memory capabilities of the hippocampus in a spatial task. In the present model two modalities – vision and path integration – are contributing to the recognition of a given place. We study how place cell activity emerges due to Hebbian learning in the model hippocampus as a result of random exploration of the environment. The model is implemented in the Webots mobile robotics simulation software. Our results show that the location of the robot is well predictable from the activity of a population of model place cells, thus the model is suitable to be used as a basic building block of location-based navigation strategies. However, some properties of the stored memories strongly resembles that of episodic memories, which do not match special spatial requirements.