Stereotypical hippocampal clustering predicts navigational success in virtualized real-world environments

Abstract Structural differences along the long-axis of the hippocampus have long been believed to underlie meaningful functional differences, such as the granularity of information processing. Recent findings show that data-driven parcellations of the hippocampus sub-divide the hippocampus into a 10-cluster map with anterior-medial, anterior-lateral, and posteroanterior-lateral, middle, and posterior components. We tested whether task and experience could modulate this clustering using a spatial learning experiment where subjects were trained to virtually navigate a novel neighborhood in a Google Street View-like environment over a two-week period. Subjects were scanned while navigating routes early in training and at the end of their two-week training. Using the 10-cluster map as the ideal template, we find that subjects who eventually learn the neighborhood well have hippocampal cluster-maps consistent with the ideal—even on their second day of learning—and their cluster mappings do not change over the two week training period. However, subjects who eventually learn the neighborhood poorly begin with hippocampal cluster-maps inconsistent with the ideal, though their cluster mappings become more stereotypical by the end of the two week training. Interestingly this improvement seems to be route specific as even after some early improvement, when a new route is navigated participants’ hippocampal maps revert back to less stereotypical organization. We conclude that hippocampal clustering is not dependent solely on anatomical structure, and instead is driven by a combination of anatomy, task, and importantly, experience. Nonetheless, while hippocampal clustering can change with experience, efficient navigation depends on functional hippocampal activity clustering in a stereotypical manner, highlighting optimal divisions of processing along the hippocampal anterior-posterior and medial-lateral-axes.