A morphing map model for place field organization in large environments

Navigation and spatial memory, essential for animal survival, are founded on the hippocampal formation’s ability to host spatial neurons marking an animal’s position. Within controlled settings, the place cells of the hippocampus are activated in specific regions, the ‘place fields’. In this paper, we introduce a “morphing map algorithm” based on bat data from a 200-meter tunnel, highlighting a multifield, multiscale spatial representation of place fields. This algorithm posits that in vast environments, bats opt to select landmarks or ‘anchors’ for spatial representation. The method introduces a hyperbolic geometry in spatial representation, aligning with bat data from vast areas. We apply Procrustes distance to evaluate similarities between neural maps of bats and model-generated maps, revealing shared structure across bat maps, which might be dictated by common anchor points. Further explorations into anchor point ablation provide insights into their crucial role in map stability. The results present an evolved neural navigation strategy in expansive habitats and guide future spatial representation research across species.