We have achieved several experimental breakthroughs in this project. Across multiple studies, we have contributed to a mechanistic understanding of how the brain builds and leverages abstract knowledge spaces.
Nau et al. (2018, Nat Neurosci) showed that entorhinal grid-like codes, traditionally known for supporting spatial navigation, also represent gaze trajectories during visual exploration. This suggests a general mechanism for mapping continuous information beyond physical space. Julian & Doeller (2021, Nat Neurosci) demonstrated that the hippocampus and entorhinal cortex store contextual memories, enabling flexible retrieval of information tied to different environments via processes such as remapping and realignment. Notably, trial-by-trial changes in these patterns predicted context-dependent behavior in ambiguous situations, highlighting how the hippocampal–entorhinal system organizes and retrieves information to guide behavior under uncertainty. Building on these findings, Garvert et al. (2023, Nat Neurosci) revealed that the brain dynamically acquires abstract knowledge by flexibly updating hippocampal cognitive maps based on task demands, shifting between spatial and predictive relational structures. The orbitofrontal cortex tracked which map best explained outcomes and guided updates in hippocampal representations, illustrating a general mechanism for adapting relational knowledge to support inference and decision-making.
Bellmund et al. (2022, Nat Comm) further showed that the hippocampus encodes temporal relations of events based on constructed timelines and generalizes these relations across similar sequences, combining mnemonic construction with abstract structural knowledge to support flexible memory and reasoning about time. Polti et al. (2022, eLife) found that the hippocampus rapidly encodes task-specific temporal regularities, guiding sensorimotor timing and enabling real-time behavioral adaptation. Extending this, Polti et al. (2023, bioRxiv) demonstrated that entorhinal grid-like signals track task regularities and behavioral biases, such as regression to the mean, during time estimation. This suggests that grid-like neural representations encode task structure by integrating sensory evidence with prior expectations, enabling predictive adjustments of behavior.
Collectively, these studies reveal that the hippocampal-entorhinal system employs a generalizable, map-like coding scheme—including grid-like representations and predictive mapping—to acquire, organize, and leverage abstract knowledge structures. This uncovers a core neural mechanism by which the brain transforms discrete experiences into flexible, relational knowledge, supporting inference, generalization, and imagination across spatial and conceptual domains.
