Visual landmarks sharpen grid cell metric and confer context specificity to neurons of the medial entorhinal cortex

Abstract

Neurons of the medial entorhinal cortex (MEC) provide spatial representations critical for navigation. In this network, the periodic firing fields of grid cells act as a metric element for position. The location of the grid firing fields depends on interactions between self-motion information, geometrical properties of the environment and nonmetric contextual cues. Here, we test whether visual information, including nonmetric contextual cues, also regulates the firing rate of MEC neurons. Removal of visual landmarks caused a profound impairment in grid cell periodicity. Moreover, the speed code of MEC neurons changed in darkness and the activity of border cells became less confined to environmental boundaries. Half of the MEC neurons changed their firing rate in darkness. Manipulations of nonmetric visual cues that left the boundaries of a 1D environment in place caused rate changes in grid cells. These findings reveal context specificity in the rate code of MEC neurons.DOI: http://dx.doi.org/10.7554/eLife.16937.001

Grid and Nongrid Cells in Medial Entorhinal Cortex Represent Spatial Location and Environmental Features with Complementary Coding Schemes

“…For mEC recordings, classification has previously been performed by first calculating descriptive values for each cell class (grid score, border score, spatial information, HD mean resultant length) and by then comparing the values to those calculated from the shuffled data of all recorded mEC cells pooled together (Figure S2A) (Barry et al, 2012; Bjerknes et al, 2015; Boccara et al, 2010; Koenig et al, 2011; Kropff et al, 2015; Krupic et al, 2015; Langston et al, 2010; Latuske et al, 2015; Perez-Escobar et al, 2016; Stensola et al, 2012; Tang et al, 2014; Wills et al, 2010; Winter et al, 2015; Zhang et al, 2013). However, pooling shuffled data across all cells fails to account for the firing statistics of individual cells, most notably the relationship between a cell’s firing rate and its spatial information (Figure S2B) (Rolls et al, 1997).…”

“…For the entire mEC cell population the reorganization of firing patterns is generally more pronounced in response to larger differences [with the exception of layer II pyramidal cells (Kitamura et al, 2015)], but more limited in response to minor differences between environments (Hargreaves et al, 2007; Keene et al, 2016; Kitamura et al, 2015; Perez-Escobar et al, 2016). This pattern is consistent with findings from only grid cells, for which large contextual changes elicit distinct spatial firing patterns and for which more minor manipulations of environmental features, such as the shape of its exterior or the color of its walls, do not alter the spatial firing patterns (Fyhn et al, 2007).…”

Principles governing the integration of landmark and self-motion cues in entorhinal cortical codes for navigation

“…These inputs are presumably important for processing visual stimuli during running, and could be most highly activated during gain increase conditions. While it is unlikely that vision provides the primary source of speed information to MEC, as speed cells retain their basic tuning features in the absence of visual cues 16 , visual cortex remains a likely substrate for modulating the strength of speed responses to changes in optic flow, an idea that future experiments could more directly assess. In addition, at the behavioral level, we show that mice can accurately integrate optic flow to estimate distance traveled.…”

“…In MEC, speed cells retain their general coding features in complete darkness, but firing rates and the slopes of linear fits between firing rate and running speed decrease 16 , suggesting that visual inputs calibrate their response features. Visual inputs could provide a measure of self-motion in the form of optic flow 20 , which must be combined with other multisensory signals to generate a unified self-motion percept 21 .…”

Spatial representation in the hippocampal formation: a history

“…However, these distortions of the grid pattern were recorded when the environment was changed after the animal was already familiar with it, suggesting that grid maps might be formed by path integration but linked to external cues in such a way that the latter can override the path-integration dynamics 90 . Yet under grid fields have not yet been identified in darkness in mice 147,148 . The reason for the possible species difference is not known.…”