Hippocampal Spatial Mapping As Fast Graph Learning

The hippocampal formation has been shown to be involved in spatial mapping (O'Keefe and Dostrovsky, 1971; Taube et al., 1990; Hafting et al., 2005). Analogies to geographic maps or computer graphics suggest that spatial mapping should involve associating a Euclidean space of unique location representations, for example Cartesian coordinates, with a set of locations in the real world. In neuroscience, such a Euclidean space is often theorized to be provided by entorhinal grid cells (Hafting et al., 2005). A single grid cell module can represent Euclidean space ambiguously, while an array of grid cells can theoretically create unique location representations (Fiete et al., 2008). In models that simulate spatial mapping of the brain at a low level, the population activity of multiple grid cell modules is often used in this way (Lewis et al., 2019; Whittington et al., 2020), or they use a single grid cell module to complement traditional Cartesian coordinates (Milford and Wyeth, 2008). These models imply that the brain maps space in a way that is fundamentally similar to metrical geographic maps or computer graphics.