Analyzing Interactions between Cue-Guided and Place-Based Navigation with a Computational Model of Action Selection: Influence of Sensory Cues and Training

The hypothesis of multiple memory systems involved in different learning of navigation strategies has gained strong arguments through biological experiments. However, it remains difficult for experimentalists to understand how these systems interact. We propose a new computational model of selection between parallel systems involving cue-guided and place-based navigation strategies that allows analyses of selection switches between both control systems, while providing information that is not directly accessible in experiments with animals. Contrary to existing models of navigation, its module of selection is adaptive and uses a criterion which allows the comparison of strategies having different learning processes. Moreover, the spatial representation used by the place-based strategy is based on a recent hippocampus model. We illustrate the ability of this navigation model to analyze animal behavior in experiments in which the availability of sensory cues, together with the amount of training, influence the competitive or cooperative nature of their interactions.