Hippocampal Signal Complexity Predicts Navigational Performance: Evidence From a Two-Week VR Training Program

Evidence from rodents has revealed that the hippocampus processes information in a graded manner along its long-axis, with anterior regions encoding coarse information and posterior regions encoding fine-grained information. During navigation tasks with humans, similar patterns have been shown, with granularity of representation and rate of signal varying along the long-axis. However, the stability of these signals and their relationship to navigational performance remain unclear. In this study, we conducted a 2-week training program where 26 participants (6 M; 20 F) learned to navigate through a novel city environment. We investigated inter-voxel similarity (IVS; a measure of representational granularity) and temporal auto-correlation (a measure of signal change) in the hippocampus. Specifically, we examined how these signals were influenced by navigational ability (stronger vs. weaker spatial learners), training session, and navigational dynamics. Our results suggested that stronger learners tended to exhibit an anterior-posterior distinction in IVS in the right hippocampus, whereas weaker learners showed less pronounced patterns. Additionally, lower general IVS levels in the hippocampus were linked to better early learning. These findings suggest that signal complexity in the hippocampus may play a role in successful navigation and that efficient organization of scales of representation could be beneficial for navigation.