The well-worn route revisited: Striatal and hippocampal system contributions to familiar route navigation.

Abstract

Classic research has shown a division in the neuroanatomical structures that support flexible (e.g., short-cutting) and habitual (e.g., familiar route following) navigational behavior, with hippocampal-caudate systems associated with the former and putamen systems with the latter. There is, however, disagreement about whether the neural structures involved in navigation process particular forms of spatial information, such as associations between constellations of cues forming a cognitive map, versus single landmark-action associations, or alternatively, perform particular reinforcement learning algorithms that allow the use of different spatial strategies, so-called model-based (flexible) or model-free (habitual) forms of learning. We sought to test these theories by asking participants (N = 24) to navigate within a virtual environment through a previously learned, 9-junction route with distinctive landmarks at each junction while undergoing functional magnetic resonance imaging (fMRI). In a series of probe trials, we distinguished knowledge of individual landmark-action associations along the route versus knowledge of the correct sequence of landmark-action associations, either by having absent landmarks, or "out-of-sequence" landmarks. Under a map-based perspective, sequence knowledge would not require hippocampal systems, because there are no constellations of cues available for cognitive map formation. Within a learning-based model, however, responding based on knowledge of sequence would require hippocampal systems because prior context has to be utilized. We found that hippocampal-caudate systems were more active in probes requiring sequence knowledge, supporting the learning-based model. However, we also found greater putamen activation in probes where navigation based purely on sequence memory could be planned, supporting models of putamen function that emphasize its role in action sequencing.