Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex

Firing fields of grid cells in medial entorhinal cortex show compression or expansion after manipulations of the location of environmental barriers. This compression or expansion could be selective for individual grid cell modules with particular properties of spatial scaling. We present a model for differences in the response of modules to barrier location that arise from different mechanisms for the influence of visual features on the computation of location that drives grid cell firing patterns. These differences could arise from differences in the position of visual features within the visual field. When location was computed from the movement of visual features on the ground plane (optic flow) in the ventral visual field, this resulted in grid cell spatial firing that was not sensitive to barrier location in modules modeled with small spacing between grid cell firing fields. In contrast, when location was computed from static visual features on walls of barriers, i.e. in the more dorsal visual field, this resulted in grid cell spatial firing that compressed or expanded based on the barrier locations in modules modeled with large spacing between grid cell firing fields. This indicates that different grid cell modules might have differential properties for computing location based on visual cues, or the spatial radius of sensitivity to visual cues might differ between modules.Author Summary: How do we navigate from one location to another and how do we represent space to accomplish this task? Researchers have collected data from the entorhinal cortex in rodents to answer these questions, finding grid cells that fire whenever a rodent traverses through an array of locations falling on the vertices of tightly packed equilateral triangles. Grid cells with large spacing (large side lengths of the triangles between firing fields) are distorted when the environment is manipulated, e.g. by pushing walls or inserting walls in a box. In contrast, grid cells of small spacing remain largely unaffected by such manipulations. We present a computational model to explain this behavior of grid cells. In our model information about the motion of features on the ground, which are unaffected by wall manipulations, drive grid cells with small spacing between firing fields, while static features like landmarks, which are affected by wall manipulations, drive grid cells with large spacing between firing fields. These differences could correspond to different positions within the visual field of the animal. This model puts forth a testable hypothesis about the type of features that drive grid cells of different spacing.