Predictive Representations in Hippocampal and Prefrontal Hierarchies

As we navigate the world we learn about associations among events, extract relational structures, and store them in memory. This relational knowledge, in turn, enables generalization, inference, and hierarchical planning. Here we investigated relational knowledge during spatial navigation as multiscale predictive representations in the brain. We hypothesized that these representations are organized at multiple scales along posterior to anterior hierarchies in prefrontal and hippocampal regions. To test this, we conducted model based representational similarity analyses of neuroimaging data measured during virtual reality navigation of familiar and unfamiliar paths with realistically long distances. We tested the pattern similarity of each point, along each navigational path, to a weighted sum of its successor points within different temporal horizons. Predictive similarity was significantly higher for familiar paths. Overall, anterior PFC showed predictive horizons at the largest scales (~875m) and posterior hippocampus at the lowest (~25m), while the anterior hippocampus (~175m), prepolar PFC, and orbitofrontal regions (~350m) were in between. These findings support the idea that predictive representations are maintained at higher scales of abstraction in the anterior PFC, and unfolded at lower scales by prepolar PFC and hippocampal regions. This representational hierarchy can support generalization, hierarchical planning, and subgoals at multiple scales.