Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes
Spencer Rooke, Zhaoze Wang, Ronald W. Di Tullio, Vijay Balasubramanian
Abstract
Many animals learn cognitive maps of their environment - a simultaneous representation of context, experience, and position. Place cells in the hippocampus, named for their explicit encoding of position, are believed to be a neural substrate of these maps, with place cell “remapping” explaining how this system can represent different contexts. Briefly, place cells alter their firing properties, or “remap”, in response to changes in experiential or sensory cues. Substantial sensory changes, produced, e.g., by moving between environments, cause large subpopulations of place cells to change their tuning entirely. While many studies have looked at the physiological basis of remapping, we lack explicit calculations of how the contextual capacity of the place cell system changes as a function of place field firing properties. Here, we propose a geometric approach to understanding population level activity of place cells. Using known firing field statistics, we investigate how changes to place cell firing properties affect the distances between representations of different environments within firing rate space. Using this approach, we find that the number of contexts storable by the hippocampus grows exponentially with the number of place cells, and calculate this exponent for environments of different sizes. We identify a fundamental trade-off between high resolution encoding of position and the number of storable contexts. This trade-off is tuned by place cell width, which might explain the change in firing field scale along the dorsal-ventral axis of the hippocampus. We demonstrate that clustering of place cells near likely points of confusion, such as boundaries, increases the contextual capacity of the place system within our framework and conclude by discussing how our geometric approach could be extended to include other cell types and abstract spaces.
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- REMI: Reconstructing Episodic Memory During Internally Driven Path PlanningZhaoze Wang, Genela Morris, Dori Derdikman, Pratik Chaudhari et al.NeurIPS 2025 · 5 citations
- The Hippocampal Place Field Gradient: A Bio-inspired Framework Building Multiscale Representation for Better Sample EfficiencyShujun Zhou, Junrong Qi, Guozhang ChenICML 2026
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