Field repetition and local mapping in the hippocampus and medial entorhinal cortex

Hippocampal place cells support spatial cognition and are thought to form the neural substrate of a global 'cognitive map'. A widely held view is that parts of the hippocampus also underlie the ability to separate patterns, or to provide different neural codes for distinct environments. However, a number of studies have shown that in environments composed of multiple, repeating compartments, place cells and other spatially modulated neurons show the same activity in each local area. This repetition of firing fields may reflect pattern completion, and may make it difficult for animals to distinguish similar local environments. In this review we will (a) highlight some of the navigation difficulties encountered by humans in repetitive environments, (b) summarise literature demonstrating that place and grid cells represent local and not global space, and (c) attempt to explain the origin of these phenomena. We argue that the repetition of firing fields can be a useful tool for understanding of the relationship between grid cells in the entorhinal cortex and place cells in the hippocampus, the spatial inputs shared by these cells, and the propagation of spatially-related signals through these structures

Irregular distribution of grid cell firing fields in rats exploring a 3D volumetric space

We investigated how entorhinal grid cells encode volumetric space. On a horizontal surface, grid cells usually produce multiple, spatially focal, approximately circular firing fields that are evenly sized and spaced to form a regular, close-packed, hexagonal array. This spatial regularity has been suggested to underlie navigational computations. In three dimensions, theoretically the equivalent firing pattern would be a regular, hexagonal close packing of evenly sized spherical fields. In the present study, we report that, in rats foraging in a cubic lattice, grid cells maintained normal temporal firing characteristics and produced spatially stable firing fields. However, although most grid fields were ellipsoid, they were sparser, larger, more variably sized and irregularly arranged, even when only fields abutting the lower surface (equivalent to the floor) were considered. Thus, grid self-organization is shaped by the environment’s structure and/or movement affordances, and grids may not need to be regular to support spatial computations

Predictive maps in rats and humans for spatial navigation

Much of our understanding of navigation comes from the study of individual species, often with specific tasks tailored to those species. Here, we provide a novel experimental and analytic framework integrating across humans, rats, and simulated reinforcement learning (RL) agents to interrogate the dynamics of behavior during spatial navigation. We developed a novel open-field navigation task ("Tartarus maze") requiring dynamic adaptation (shortcuts and detours) to frequently changing obstructions on the path to a hidden goal. Humans and rats were remarkably similar in their trajectories. Both species showed the greatest similarity to RL agents utilizing a "successor representation," which creates a predictive map. Humans also displayed trajectory features similar to model-based RL agents, which implemented an optimal tree-search planning procedure. Our results help refine models seeking to explain mammalian navigation in dynamic environments and highlight the utility of modeling the behavior of different species to uncover the shared mechanisms that support behavior

Hippocampal place cells encode global location but not changes in environmental connectivity in a 4-room navigation task

Flexible navigation relies on a cognitive map of space, thought to be implemented by hippocampal place cells: neurons that exhibit location-specific firing. In connected environments, optimal navigation requires keeping track of one’s location and of the available connections between subspaces. We examined whether the dorsal CA1 place cells of rats encode environmental connectivity in four geometrically identical boxes arranged in a square. Rats moved between boxes by pushing saloon-type doors that could be locked in one or both directions. Although rats demonstrated knowledge of environmental connectivity, their place cells did not respond to connectivity changes, nor did they represent doorways differently from other locations. Place cells coded location in a global reference frame, with a different map for each box and minimal repetitive fields despite the repetitive geometry. These results suggest that CA1 place cells provide a spatial map that does not explicitly include connectivity

Contribution of Cerebellar Sensorimotor Adaptation to Hippocampal Spatial Memory

Complementing its primary role in motor control, cerebellar learning has also a bottom-up influence on cognitive functions, where high-level representations build up from elementary sensorimotor memories. In this paper we examine the cerebellar contribution to both procedural and declarative components of spatial cognition. To do so, we model a functional interplay between the cerebellum and the hippocampal formation during goal-oriented navigation. We reinterpret and complete existing genetic behavioural observations by means of quantitative accounts that cross-link synaptic plasticity mechanisms, single cell and population coding properties, and behavioural responses. In contrast to earlier hypotheses positing only a purely procedural impact of cerebellar adaptation deficits, our results suggest a cerebellar involvement in high-level aspects of behaviour. In particular, we propose that cerebellar learning mechanisms may influence hippocampal place fields, by contributing to the path integration process. Our simulations predict differences in place-cell discharge properties between normal mice and L7-PKCI mutant mice lacking long-term depression at cerebellar parallel fibre-Purkinje cell synapses. On the behavioural level, these results suggest that, by influencing the accuracy of hippocampal spatial codes, cerebellar deficits may impact the exploration-exploitation balance during spatial navigation

Spatial goal coding in the hippocampal formation

The mammalian hippocampal formation contains several distinct populations of neurons involved in representing self-position and orientation. These neurons, which include place, grid, head direction, and boundary-vector cells, are thought to collectively instantiate cognitive maps supporting flexible navigation. However, to flexibly navigate, it is necessary to also maintain internal representations of goal locations, such that goal-directed routes can be planned and executed. Although it has remained unclear how the mammalian brain represents goal locations, multiple neural candidates have recently been uncovered during different phases of navigation. For example, during planning, sequential activation of spatial cells may enable simulation of future routes toward the goal. During travel, modulation of spatial cells by the prospective route, or by distance and direction to the goal, may allow maintenance of route and goal-location information, supporting navigation on an ongoing basis. As the goal is approached, an increased activation of spatial cells may enable the goal location to become distinctly represented within cognitive maps, aiding goal localization. Lastly, after arrival at the goal, sequential activation of spatial cells may represent the just-taken route, enabling route learning and evaluation. Here, we review and synthesize these and other evidence for goal coding in mammalian brains, relate the experimental findings to predictions from computational models, and discuss outstanding questions and future challenges

Cerebellar adaptation deficits reduce the rate of acquisition and the accuracy of hippocampal place field representations in the MWM.

<p><b>A–C.</b> Time course and accuracy of the hippocampal spatial map (measured in the whole environment) in simulated controls and mutants. The bar diagram in C shows the grand mean of the spatial code accuracy averaged over the entire training. <b>D–I.</b> Time course and accuracy of spatial map in the peripheral area (D–F) and the central region (G–I) of the MWM.</p

Cerebellar adaptation deficits impact the exploratory behaviour of simulated L7-PKCI mice.

<p>Time course of the spatial representation accuracy as a function of exploration time for both simulated controls and mutants undertaking a free-exploration task.</p

Population place coding is suboptimal in simulated L7-PKCI mice compared to controls.

<p><b>A.</b> Information content of the spatial code encoded by the population of hippocampal place cells in controls and mutants. <b>B.</b> Redundancy of the hippocampal spatial code in both simulated groups. <b>C.</b> Spatial density of hippocampal place fields in both groups. <b>Unitary hippocampal place fields in simulated L7-PKCI mice are not impaired, relative to controls, in terms of size, spatial coherence and information content. D.</b> Mean size of place fields in simulated controls and mutants. <b>E.</b> Mean spatial coherence (local smoothness) of place fields in both groups. <b>F.</b> Mean spatial information content of unitary place fields in both groups.</p

The hypothesis of a cerebellar influence on path integration, and hence on hippocampal place coding, accounts for all L7-PKCIs' spatial navigation impairments observed experimentally.

<p><b>Results in the MWM: </b><b>A.</b> Mean escape latency over training (left y-axis) and score (right y-axis) of simulated controls and mutants. <b>B.</b> Correlation between searching score and escape latency for control (top) and mutant (bottom) simulated mice. <b>C.</b> Mean angular deviation between ideal and actual trajectory to the goal. <b>D.</b> Ratio between the time spent in the platform quadrant and the total duration of a trial. <b>E.</b> Mean distance of the simulated mouse to the platform. <b>F.</b> Mean circling time. <b>Results in the Starmaze: </b><b>G.</b> Mean number of visited alleys. <b>H.</b> Mean distance swum in the Starmaze.</p