Podcast with Kate Jeffery on spatial cognition and grid cells

How does the brain build a map of three-dimensional space when a full volumetric representation would be prohibitively expensive? Neuroscientist Kate Jeffery explains why the rat navigation system appears to favor flat maps stitched together into a mosaic , and what this reveals about the evolutionary trade-offs shaping spatial cognition. Subscribe for more from the Convergent Science Network podcast series. Kate Jeffery joins Paul Verschure and Tony Prescott at the BCBT summer school to discuss her research on how place cells, grid cells, and head direction cells handle the vertical dimension. Her laboratory has found that grid cells, which fire in periodic hexagonal patterns on flat surfaces, do not produce the same metric structure in the vertical plane. On a pegboard where rats move horizontally at different heights, grid fields extend into strips rather than grids. On a climbing wall where the body is parallel to the surface, something more grid-like appears. The implication is that the system maps space relative to the plane of the animal's body rather than constructing a universal three-dimensional coordinate frame. The discussion addresses what this means for models of spatial cognition. Jeffery proposes a multi-planar model in which the brain tiles complex three-dimensional environments with locally two-dimensional map fragments, linked by some coarser three-dimensional information. She explains why this is an efficient evolutionary solution: a full 3D map would require vastly more neural resources, while a patchwork of flat maps supplemented with elevation cues handles most real-world navigation demands. The conversation also explores how the head direction system might cope with three dimensions , whether through a spherical attractor, three orthogonal ring attractors, or a simpler scheme that just tracks yaw on whatever surface the animal occupies. Key topics include the relationship between grid cells and contextual cues, the developmental sequence of spatial cell types, the influence of deep learning on thinking about modularity in the brain, and the practical constraints that ecology imposes on neural representations of space. Part of the Convergent Science Network podcast series from the BCBT Summer School.