Integration of grid maps in merged environments

Abstract

Natural environments are represented by local maps of grid cells and place cells that are stitched together. The manner by which transitions between map fragments are generated is unknown. We recorded grid cells while rats were trained in two rectangular compartments, A and B (each 1 m × 2 m), separated by a wall. Once distinct grid maps were established in each environment, we removed the partition and allowed the rat to explore the merged environment (2 m × 2 m). The grid patterns were largely retained along the distal walls of the box. Nearer the former partition line, individual grid fields changed location, resulting almost immediately in local spatial periodicity and continuity between the two original maps. Grid cells belonging to the same grid module retained phase relationships during the transformation. Thus, when environments are merged, grid fields reorganize rapidly to establish spatial periodicity in the area where the environments meet.

Grid pattern development, distortions and topological defects may depend on distributed anchoring

“…D. The grid did not shear if there was no anisotropic behavior (left) or if there was no compression distortions because of a homogenous place cell ring rates and a low (right). A dataset where animals had been subjected to a merging of two 1x2 m familiar environments was also investigated (Wernle et al 2018). From 13 animals, three grid modules had more than 3 cells with a grid spacing less than 60 cm.…”

“…1.24, F(4, 434) = 13, p = 0.0008 and F(3, 295) = 73, p = 1.9 × 10 -35 ; Wilcoxon's test for pentagons and 352 heptagons vs hexagons, p = 2.1 × 10 -6 and p = 1.0 × 10 -20 for modules 4 and 5 respectively). The local 353 gridness score and Voronoi analyses were also applied to a data set of three modules from animals 354 running in a geometrically manipulated environment from a previous study (Wernle et al 2018). 2 out 355 of 3 modules also displayed negative/absent local gridness scores and had a higher ratio of heptagons 356 and pentagons (supplementary Figure 4).…”

“…However, compression distortions lead to a gradual 44 2 contortion of the pattern across the environment which may necessitate resetting to occur at multiple 45 locations distal to local cues and borders to keep the pattern stable. Anchoring further implies learning 46 which has been observed where the grid has been locally altered by local changes in the 47 environment (Boccara et al 2019; Sanguinetti-Scheck 2019; Wernle et al 2018). Thus, effects of 48…”

Coding advantage of grid cell orientation under noisy conditions

“…For example, how does the activity of place cells in the hippocampus relate to the orientation of grid cells [47][48][49][50]? How do grid cells modulate the coding scheme for two separate spaces when the two spaces are being merged into a single space [51][52]? Our modeling approach consisting of a spatial encoding scheme, a method to characterize encoding capacity, geometrical analyses for both ideal and realistic situations, and a reinforcement learning model offers tools for addressing these issues to unravel the mysteries of the navigation ability of the mammalian brain.…”

Transition scale-spaces: A computational theory for the discretized entorhinal cortex

“…Embedded in an inhibitory local recurrent circuit (Couey et al, 2013), they interact with several other spatially modulated cells of the EC, for instance head direction (Ranck, 1984;Sargolini et al, 2006), border (Lever et al, 2009;Savelli et al, 2008), or speed cells (Hinman et al, 2016;Kropff et al, 2015). Moreover, they are influenced by the geometry of an animal's surrounding (Krupic et al, 2014;Wernle et al, 2017), and project to place cells ; E. I. Moser and M.-B.…”