Grid Cells Form a Global Representation of Connected Environments.

The firing patterns of grid cells in medial entorhinal cortex (mEC) and associated brain areas form triangular arrays that tessellate the environment [1, 2] and maintain constant spatial offsets to each other between environments [3, 4]. These cells are thought to provide an efficient metric for navigation in large-scale space [5-8]. However, an accurate and universal metric requires grid cell firing patterns to uniformly cover the space to be navigated, in contrast to recent demonstrations that environmental features such as boundaries can distort [9-11] and fragment [12] grid patterns. To establish whether grid firing is determined by local environmental cues, or provides a coherent global representation, we recorded mEC grid cells in rats foraging in an environment containing two perceptually identical compartments connected via a corridor. During initial exposures to the multicompartment environment, grid firing patterns were dominated by local environmental cues, replicating between the two compartments. However, with prolonged experience, grid cell firing patterns formed a single, continuous representation that spanned both compartments. Thus, we provide the first evidence that in a complex environment, grid cell firing can form the coherent global pattern necessary for them to act as a metric capable of supporting large-scale spatial navigation

How environment and self-motion combine in neural representations of space

Estimates of location or orientation can be constructed solely from sensory information representing environmental cues. In unfamiliar or sensory-poor environments, these estimates can also be maintained and updated by integrating self-motion information. However, the accumulation of error dictates that updated representations of heading direction and location become progressively less reliable over time, and must be corrected by environmental sensory inputs when available. Anatomical, electrophysiological and behavioural evidence indicates that angular and translational path integration contributes to the firing of head direction cells and grid cells. We discuss how sensory inputs may be combined with self-motion information in the firing patterns of these cells. For head direction cells, direct projections from egocentric sensory representations of distal cues can help to correct cumulative errors. Grid cells may benefit from sensory inputs via boundary vector cells and place cells. However, the allocentric code of boundary vector cells and place cells requires consistent head-direction information in order to translate the sensory signal of egocentric boundary distance into allocentric boundary vector cell firing, suggesting that the different spatial representations found in and around the hippocampal formation are interdependent. We conclude that, rather than representing pure path integration, the firing of head-direction cells and grid cells reflects the interface between self-motion and environmental sensory information. Together with place cells and boundary vector cells they can support a coherent unitary representation of space based on both environmental sensory inputs and path integration signals

Memory Structure and Cognitive Maps

A common way to understand memory structures in the cognitive sciences is as a cognitive map​. Cognitive maps are representational systems organized by dimensions shared with physical space. The appeal to these maps begins literally: as an account of how spatial information is represented and used to inform spatial navigation. Invocations of cognitive maps, however, are often more ambitious; cognitive maps are meant to scale up and provide the basis for our more sophisticated memory capacities. The extension is not meant to be metaphorical, but the way in which these richer mental structures are supposed to remain map-like is rarely made explicit. Here we investigate this missing link, asking: how do cognitive maps represent non-spatial information?​ We begin with a survey of foundational work on spatial cognitive maps and then provide a comparative review of alternative, non-spatial representational structures. We then turn to several cutting-edge projects that are engaged in the task of scaling up cognitive maps so as to accommodate non-spatial information: first, on the spatial-isometric approach​ , encoding content that is non-spatial but in some sense isomorphic to spatial content; second, on the ​ abstraction approach​ , encoding content that is an abstraction over first-order spatial information; and third, on the ​ embedding approach​ , embedding non-spatial information within a spatial context, a prominent example being the Method-of-Loci. Putting these cases alongside one another reveals the variety of options available for building cognitive maps, and the distinctive limitations of each. We conclude by reflecting on where these results take us in terms of understanding the place of cognitive maps in memory

Distorting the metric fabric of the cognitive map

Grid cells are neurons whose regularly spaced firing fields form apparently symmetric arrays, or grids, that are thought to collectively provide an environment-independent metric framework for the brain's cognitive map of space. However, two recent studies show that grids are naturally distorted, revealing greater local environment-specific effects than previously recognized

How environmental movement constraints shape the neural code for space

Study of the neural code for space in rodents has many insights to offer for how mammals, including humans, construct a mental representation of space. This code is centered on the hippocampal place cells, which are active in particular places in the environment. Place cells are informed by numerous other spatial cell types including grid cells, which provide a signal for distance and direction and are thought to help anchor the place cell signal. These neurons combine self-motion and environmental information to create and update their map-like representation. Study of their activity patterns in complex environments of varying structure has revealed that this "cognitive map" of space is not a fixed and rigid entity that permeates space, but rather is variably affected by the movement constraints of the environment. These findings are pointing toward a more flexible spatial code in which the map is adapted to the movement possibilities of the space. An as-yet-unanswered question is whether these different forms of representation have functional consequences, as suggested by an enactivist view of spatial cognition