Environmental boundaries as an error correction mechanism for grid cells

A memory model of rodent spatial navigation in which place cells are memories arranged in a grid and grid cells are non-spatial

A theory and neurocomputational model are presented that explain grid cell responses as the byproduct of equally dissimilar hippocampal memories. On this account, place and grid cells are best understood as the natural consequence of memory encoding and retrieval; a precise hexagonal grid is the exception rather than the rule, emerging when the animal explores a large surface that is devoid of landmarks and objects. In the proposed memory model, place cells represent memories that are conjunctions of both spatial and non-spatial attributes, and grid cells primarily represent the non-spatial attributes (e.g. sounds, surface texture, etc.) found throughout the two-dimensional recording enclosure. Place cells support memories of the locations where non-spatial attributes can be found (e.g. positions with a particular sound), which are arranged in a hexagonal lattice owing to memory encoding and consolidation processes (pattern separation) as applied to situations in which the non-spatial attributes are found at all locations of a two-dimensional surface. Grid cells exhibit their spatial firing pattern owing to feedback from hippocampal place cells (i.e. a hexagonal pattern of remembered locations for the non-spatial attribute represented by a grid cell). Model simulations explain a wide variety of results in the rodent spatial navigation literature.

Flexible hippocampal representation of abstract boundaries supports memory-guided choice

Hippocampal cognitive maps encode the relative locations of spatial cues in an environment and adapt their representation when boundaries geometrically change. Hippocampal cognitive maps can represent abstract knowledge, yet it's unclear whether the hippocampus is sensitive to changes to the extreme coordinates, boundaries, of abstract spaces. We create a memory-guided choice task to test whether the human hippocampus and medial prefrontal cortex (mPFC) flexibly learn abstract boundary representations in distinct two-dimensional (2D) knowledge spaces. Participants build up a 2D map-like representation of abstract boundaries, where the hippocampus and mPFC represent a decision cue's Euclidean distance to the closest boundary. Notably, mPFC distance representations selectively reflect individual performance improvements during the task. Testing for neural sensitivity to boundary-defined contextual changes, only the hippocampus flexibly represents abstract boundaries, which relates to choice behavior. These findings suggest that abstract knowledge retrieval within dynamically changing contexts is facilitated by generalized mPFC and flexible hippocampal boundary representations.

Tiling of large-scaled environments by grid cells requires experience

Grid cells in the medial entorhinal cortex are widely believed to provide a universal spatial metric supporting vector-based navigation irrespective of the spatial scale of an environment. However, using single unit recordings in freely behaving mice, we demonstrate that spatial periodicity in grid cell firing is substantially disrupted when transitioning from a small to a large-scale arena when the scale ratio is larger than the scale ratio of successive grid modules. Remarkably, grid patterns reemerge with experience in the large-scale arena, suggesting that grid cells can learn to represent large-scale spaces with experience.

Rotation errors in path integration are associated with Alzheimer's disease tau pathology: a cross-sectional study

BACKGROUND

Early Alzheimer's disease diagnosis is crucial for preventive therapy development. Standard neuropsychological evaluation does not identify clinically normal individuals with brain amyloidosis, the first stage of the pathology, defined as preclinical Alzheimer's disease. Spatial navigation assessment, in particular path integration, appears promising to detect preclinical symptoms, as the medial temporal lobe plays a key role in navigation and is the first cortical region affected by tau pathology.

METHODS

We have conducted a cross-sectional study. We related the path integration performance of 102 individuals without dementia, aged over 50, to amyloid and tau pathologies, measured using positron emission tomography. We included 75 clinically normal individuals (19 with brain amyloidosis, 56 without) and 27 individuals with mild cognitive impairment (18 with brain amyloidosis, 9 without). We fitted linear mixed models to predict the path integration performances according to amyloid status or tau pathology in the medial temporal lobal, adjusting for age, gender, cognitive status, education, and video game experience. We decomposed the error into rotation and distance errors.

RESULTS

We observed that clinically normal adults with brain amyloidosis (preclinical Alzheimer's disease) had spatial navigation deficits when relying only on self-motion cues. However, they were able to use a landmark to reduce their errors. Individuals with mild cognitive impairment had deficits in path integration that did not improve when a landmark was added in the environment. The amyloid status did not influence performance among individuals with mild cognitive impairment. Among all individuals, rotation, but not distance, errors increased with the level of tau pathology in the medial temporal lobe.

CONCLUSION

Our results suggest that path integration performance in an environment without external cues allows identifying individuals with preclinical Alzheimer's disease, before overt episodic memory impairment is noticeable. Specifically, we demonstrated that poor angular estimation is an early cognitive marker of tau pathology, whereas distance estimation relates to older ages, not to Alzheimer's disease.

TRIAL REGISTRATION

Eudra-CT 2018-003473-94.

Episodic and associative memory from spatial scaffolds in the hippocampus

Hippocampal circuits in the brain enable two distinct cognitive functions: the construction of spatial maps for navigation, and the storage of sequential episodic memories1-5. Although there have been advances in modelling spatial representations in the hippocampus6-10, we lack good models of its role in episodic memory. Here we present a neocortical-entorhinal-hippocampal network model that implements a high-capacity general associative memory, spatial memory and episodic memory. By factoring content storage from the dynamics of generating error-correcting stable states, the circuit (which we call vector hippocampal scaffolded heteroassociative memory (Vector-HaSH)) avoids the memory cliff of prior memory models11,12, and instead exhibits a graceful trade-off between number of stored items and recall detail. A pre-structured internal scaffold based on grid cell states is essential for constructing even non-spatial episodic memory: it enables high-capacity sequence memorization by abstracting the chaining problem into one of learning low-dimensional transitions. Vector-HaSH reproduces several hippocampal experiments on spatial mapping and context-based representations, and provides a circuit model of the 'memory palaces' used by memory athletes13. Thus, this work provides a unified understanding of the spatial mapping and associative and episodic memory roles of the hippocampus.

Vector coding and place coding in hippocampus share a common directional signal

Vector coding is a major mechanism by which neural systems represent an animal's location in both global and local, item-based reference frames. Landmark vector cells (LVCs) in the hippocampus complement classic place cells by encoding vector relationships between the organism and specific landmarks. How these place- and vector-coding properties interact is not known. We recorded place cells and LVCs using calcium imaging of the CA1 region of freely moving rats during cue-card rotation studies. Place fields rotated around the center of the platform to follow the cue rotation, whereas the fields of simultaneously recorded LVCs rotated by the same amount around the nearby landmarks. Some neurons demonstrated conjunctive coding of both classic place field properties and LVC properties. These results demonstrate that CA1 neurons employ a common directional input, presumably provided by the head direction cell system, to encode animals' locations in both world-centered and landmark-centered reference frames.

Improved Navigation Performance Through Memory Triggering Maps: A Neurocartographic Approach

When using navigation devices the "cognitive map" created in the user's mind is much more fragmented, incomplete and inaccurate, compared to the mental model of space created when reading a conventional printed map. As users become more dependent on digital devices that reduce orientation skills, there is an urgent need to develop more efficient navigation systems that promote orientation skills. This paper proposes to consider brain processes for creating more efficient maps that use a network of optimally located cardinal lines and landmarks organized to support and stabilize the neurocognitive structures in the brain that promote spatial orientation. This new approach combines neurocognitive insights with classical research on the efficiency of cartographic visualizations. Recent neuroscientific findings show that spatially tuned neurons could be linked to navigation processes. In particular, the activity of grid cells, which appear to be used to process metric information about space, can be influenced by environmental stimuli such as walls or boundaries. Grid cell activity could be used to create a new framework for map-based interfaces that primarily considers the brain structures associated with the encoding and retrieval of spatial information. The new framework proposed in this paper suggests to arrange map symbols in a specific way that the map design helps to stabilize grid cell firing in the brain and by this improve spatial orientation and navigational performance. Spatially oriented cells are active in humans not only when moving in space, but also when imagining moving through an area-such as when reading a map. It seems likely that the activity of grid cells can be stabilized simply by map symbols that are perceived when reading a map.

Impaired spatial coding and neuronal hyperactivity in the medial entorhinal cortex of aged App NL-G-F mice

The progressive accumulation of amyloid beta (Aβ) pathology in the brain has been associated with aberrant neuronal network activity and poor cognitive performance in preclinical mouse models of Alzheimer's disease (AD). Presently, our understanding of the mechanisms driving pathology-associated neuronal dysfunction and impaired information processing in the brain remains incomplete. Here, we assessed the impact of advanced Aβ pathology on spatial information processing in the medial entorhinal cortex (MEC) of 18-month App NL-G-F/NL- G-F knock-in (APP KI) mice as they explored contextually novel and familiar open field arenas in a two-day, four-session recording paradigm. We tracked single unit firing activity across all sessions and found that spatial information scores were decreased in MEC neurons from APP KI mice versus those in age-matched C57BL/6J controls. MEC single unit spatial representations were also impacted in APP KI mice. Border cell firing preferences were unstable across sessions and spatial periodicity in putative grid cells was disrupted. In contrast, MEC border cells and grid cells in Control mice were intact and stable across sessions. We then quantified the stability of MEC spatial maps across sessions by utilizing a metric based on the Earth Mover's Distance (EMD). We found evidence for increased instability in spatially-tuned APP KI MEC neurons versus Controls when mice were re-exposed to familiar environments and exposed to a novel environment. Additionally, spatial decoding analysis of MEC single units revealed deficits in position and speed coding in APP KI mice in all session comparisons. Finally, MEC single unit analysis revealed a mild hyperactive phenotype in APP KI mice that appeared to be driven by narrow-spiking units (putative interneurons). These findings tie Aβ-associated dysregulation in neuronal firing to disruptions in spatial information processing that may underlie certain cognitive deficits associated with AD.

Modeling Grid Cell Distortions with a Grid Cell Calibration Mechanism

The medial entorhinal cortex of rodents is known to contain grid cells that exhibit precise periodic firing patterns based on the animal's position, resulting in a distinct hexagonal pattern in space. These cells have been extensively studied due to their potential to unveil the navigational computations that occur within the mammalian brain and interesting phenomena such as so-called grid cell distortions have been observed. Previous neuronal models of grid cells assumed their firing fields were independent of environmental boundaries. However, more recent research has revealed that the grid pattern is, in fact, dependent on the environment's boundaries. When rodents are placed in nonsquare cages, the hexagonal pattern tends to become disrupted and adopts different shapes. We believe that these grid cell distortions can provide insights into the underlying neural circuitry involved in grid cell firing. To this end, a calibration circuit for grid cells is proposed. Our simulations demonstrate that this circuit is capable of reproducing grid distortions observed in several previous studies. Our model also reproduces distortions in place cells and incorporates experimentally observed distortions of speed cells, which present further opportunities for exploration. It generates several experimentally testable predictions, including an alternative behavioral description of boundary vector cells that predicts behaviors in nonsquare environments different from the current model of boundary vector cells. In summary, our study proposes a calibration circuit that reproduces observed grid distortions and generates experimentally testable predictions, aiming to provide insights into the neural mechanisms governing spatial computations in mammals.

Learning to use landmarks for navigation amplifies their representation in retrosplenial cortex

Visual landmarks provide powerful reference signals for efficient navigation by altering the activity of spatially tuned neurons, such as place cells, head direction cells, and grid cells. To understand the neural mechanism by which landmarks exert such strong influence, it is necessary to identify how these visual features gain spatial meaning. In this study, we characterized visual landmark representations in mouse retrosplenial cortex (RSC) using chronic two-photon imaging of the same neuronal ensembles over the course of spatial learning. We found a pronounced increase in landmark-referenced activity in RSC neurons that, once established, remained stable across days. Changing behavioral context by uncoupling treadmill motion from visual feedback systematically altered neuronal responses associated with the coherence between visual scene flow speed and self-motion. To explore potential underlying mechanisms, we modeled how burst firing, mediated by supralinear somatodendritic interactions, could efficiently mediate context- and coherence-dependent integration of landmark information. Our results show that visual encoding shifts to landmark-referenced and context-dependent codes as these cues take on spatial meaning during learning.

Grid Cells in Cognition: Mechanisms and Function

The activity patterns of grid cells form distinctively regular triangular lattices over the explored spatial environment and are largely invariant to visual stimuli, animal movement, and environment geometry. These neurons present numerous fascinating challenges to the curious (neuro)scientist: What are the circuit mechanisms responsible for creating spatially periodic activity patterns from the monotonic input-output responses of single neurons? How and why does the brain encode a local, nonperiodic variable-the allocentric position of the animal-with a periodic, nonlocal code? And, are grid cells truly specialized for spatial computations? Otherwise, what is their role in general cognition more broadly? We review efforts in uncovering the mechanisms and functional properties of grid cells, highlighting recent progress in the experimental validation of mechanistic grid cell models, and discuss the coding properties and functional advantages of the grid code as suggested by continuous attractor network models of grid cells.

Human navigation strategies and their errors result from dynamic interactions of spatial uncertainties

Goal-directed navigation requires continuously integrating uncertain self-motion and landmark cues into an internal sense of location and direction, concurrently planning future paths, and sequentially executing motor actions. Here, we provide a unified account of these processes with a computational model of probabilistic path planning in the framework of optimal feedback control under uncertainty. This model gives rise to diverse human navigational strategies previously believed to be distinct behaviors and predicts quantitatively both the errors and the variability of navigation across numerous experiments. This furthermore explains how sequential egocentric landmark observations form an uncertain allocentric cognitive map, how this internal map is used both in route planning and during execution of movements, and reconciles seemingly contradictory results about cue-integration behavior in navigation. Taken together, the present work provides a parsimonious explanation of how patterns of human goal-directed navigation behavior arise from the continuous and dynamic interactions of spatial uncertainties in perception, cognition, and action.

Mental navigation in the primate entorhinal cortex

A cognitive map is a suitably structured representation that enables novel computations using previous experience; for example, planning a new route in a familiar space1. Work in mammals has found direct evidence for such representations in the presence of exogenous sensory inputs in both spatial2,3 and non-spatial domains4-10. Here we tested a foundational postulate of the original cognitive map theory1,11: that cognitive maps support endogenous computations without external input. We recorded from the entorhinal cortex of monkeys in a mental navigation task that required the monkeys to use a joystick to produce one-dimensional vectors between pairs of visual landmarks without seeing the intermediate landmarks. The ability of the monkeys to perform the task and generalize to new pairs indicated that they relied on a structured representation of the landmarks. Task-modulated neurons exhibited periodicity and ramping that matched the temporal structure of the landmarks and showed signatures of continuous attractor networks12,13. A continuous attractor network model of path integration14 augmented with a Hebbian-like learning mechanism provided an explanation of how the system could endogenously recall landmarks. The model also made an unexpected prediction that endogenous landmarks transiently slow path integration, reset the dynamics and thereby reduce variability. This prediction was borne out in a reanalysis of firing rate variability and behaviour. Our findings link the structured patterns of activity in the entorhinal cortex to the endogenous recruitment of a cognitive map during mental navigation.

Visual boundary cues suffice to anchor place and grid cells in virtual reality

The hippocampal formation contains neurons responsive to an animal's current location and orientation, which together provide the organism with a neural map of space.1,2,3 Spatially tuned neurons rely on external landmark cues and internally generated movement information to estimate position.4,5 An important class of landmark cue are the boundaries delimiting an environment, which can define place cell field position6,7 and stabilize grid cell firing.8 However, the precise nature of the sensory information used to detect boundaries remains unknown. We used 2-dimensional virtual reality (VR)9 to show that visual cues from elevated walls surrounding the environment are both sufficient and necessary to stabilize place and grid cell responses in VR, when only visual and self-motion cues are available. By contrast, flat boundaries formed by the edges of a textured floor did not stabilize place and grid cells, indicating only specific forms of visual boundary stabilize hippocampal spatial firing. Unstable grid cells retain internally coherent, hexagonally arranged firing fields, but these fields "drift" with respect to the virtual environment over periods >5 s. Optic flow from a virtual floor does not slow drift dynamics, emphasizing the importance of boundary-related visual information. Surprisingly, place fields are more stable close to boundaries even with floor and wall cues removed, suggesting invisible boundaries are inferred using the motion of a discrete, separate cue (a beacon signaling reward location). Subsets of place cells show allocentric directional tuning toward the beacon, with strength of tuning correlating with place field stability when boundaries are removed.

Entorhinal-based path integration selectively predicts midlife risk of Alzheimer's disease

INTRODUCTION

Entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimer's disease (AD), associated with EC grid cell dysfunction. Given the role of grid cells in path integration (PI)-based spatial behaviors, we predicted that PI impairment would represent the first behavioral change in adults at risk of AD.

METHODS

We compared immersive virtual reality (VR) PI ability to other cognitive domains in 100 asymptomatic midlife adults stratified by hereditary and physiological AD risk factors. In some participants, behavioral data were compared to 7T magnetic resonance imaging (MRI) measures of brain structure and function.

RESULTS

Midlife PI impairments predicted both hereditary and physiological AD risk, with no corresponding multi-risk impairment in episodic memory or other spatial behaviors. Impairments associated with altered functional MRI signal in the posterior-medial EC.

DISCUSSION

Altered PI may represent the transition point from at-risk state to disease manifestation in AD, prior to impairment in other cognitive domains.

The mosaic structure of the mammalian cognitive map

The cognitive map, proposed by Tolman in the 1940s, is a hypothetical internal representation of space constructed by the brain to enable an animal to undertake flexible spatial behaviors such as navigation. The subsequent discovery of place cells in the hippocampus of rats suggested that such a map-like representation does exist, and also provided a tool with which to explore its properties. Single-neuron studies in rodents conducted in small singular spaces have suggested that the map is founded on a metric framework, preserving distances and directions in an abstract representational format. An open question is whether this metric structure pertains over extended, often complexly structured real-world space. The data reviewed here suggest that this is not the case. The emerging picture is that instead of being a single, unified construct, the map is a mosaic of fragments that are heterogeneous, variably metric, multiply scaled, and sometimes laid on top of each other. Important organizing factors within and between fragments include boundaries, context, compass direction, and gravity. The map functions not to provide a comprehensive and precise rendering of the environment but rather to support adaptive behavior, tailored to the species and situation.

Subicular neurons encode concave and convex geometries

Animals in the natural world constantly encounter geometrically complex landscapes. Successful navigation requires that they understand geometric features of these landscapes, including boundaries, landmarks, corners and curved areas, all of which collectively define the geometry of the environment1-12. Crucial to the reconstruction of the geometric layout of natural environments are concave and convex features, such as corners and protrusions. However, the neural substrates that could underlie the perception of concavity and convexity in the environment remain elusive. Here we show that the dorsal subiculum contains neurons that encode corners across environmental geometries in an allocentric reference frame. Using longitudinal calcium imaging in freely behaving mice, we find that corner cells tune their activity to reflect the geometric properties of corners, including corner angles, wall height and the degree of wall intersection. A separate population of subicular neurons encode convex corners of both larger environments and discrete objects. Both corner cells are non-overlapping with the population of subicular neurons that encode environmental boundaries. Furthermore, corner cells that encode concave or convex corners generalize their activity such that they respond, respectively, to concave or convex curvatures within an environment. Together, our findings suggest that the subiculum contains the geometric information needed to reconstruct the shape and layout of naturalistic spatial environments.

Grid cells: the missing link in understanding Parkinson's disease?

The mechanisms underlying Parkinson's disease (PD) are complex and not fully understood, and the box-and-arrow model among other current models present significant challenges. This paper explores the potential role of the allocentric brain and especially its grid cells in several PD motor symptoms, including bradykinesia, kinesia paradoxa, freezing of gait, the bottleneck phenomenon, and their dependency on cueing. It is argued that central hubs, like the locus coeruleus and the pedunculopontine nucleus, often narrowly interpreted in the context of PD, play an equally important role in governing the allocentric brain as the basal ganglia. Consequently, the motor and secondary motor (e.g., spatially related) symptoms of PD linked with dopamine depletion may be more closely tied to erroneous computation by grid cells than to the basal ganglia alone. Because grid cells and their associated central hubs introduce both spatial and temporal information to the brain influencing velocity perception they may cause bradykinesia or hyperkinesia as well. In summary, PD motor symptoms may primarily be an allocentric disturbance resulting from virtual faulty computation by grid cells revealed by dopamine depletion in PD.

Environment geometry alters subiculum boundary vector cell receptive fields in adulthood and early development

Boundaries to movement form a specific class of landmark information used for navigation: Boundary Vector Cells (BVCs) are neurons which encode an animal's location as a vector displacement from boundaries. Here we characterise the prevalence and spatial tuning of subiculum BVCs in adult and developing male rats, and investigate the relationship between BVC spatial firing and boundary geometry. BVC directional tunings align with environment walls in squares, but are uniformly distributed in circles, demonstrating that environmental geometry alters BVC receptive fields. Inserted barriers uncover both excitatory and inhibitory components to BVC receptive fields, demonstrating that inhibitory inputs contribute to BVC field formation. During post-natal development, subiculum BVCs mature slowly, contrasting with the earlier maturation of boundary-responsive cells in upstream Entorhinal Cortex. However, Subiculum and Entorhinal BVC receptive fields are altered by boundary geometry as early as tested, suggesting this is an inherent feature of the hippocampal representation of space.

Grid codes underlie multiple cognitive maps in the human brain

Grid cells fire at multiple positions that organize the vertices of equilateral triangles tiling a 2D space and are well studied in rodents. The last decade witnessed rapid progress in two other research lines on grid codes-empirical studies on distributed human grid-like representations in physical and multiple non-physical spaces, and cognitive computational models addressing the function of grid cells based on principles of efficient and predictive coding. Here, we review the progress in these fields and integrate these lines into a systematic organization. We also discuss the coordinate mechanisms of grid codes in the human entorhinal cortex and medial prefrontal cortex and their role in neurological and psychiatric diseases.

Hippocampal firing fields anchored to a moving object predict homing direction during path-integration-based behavior

Homing based on path integration (H-PI) is a form of navigation in which an animal uses self-motion cues to keep track of its position and return to a starting point. Despite evidence for a role of the hippocampus in homing behavior, the hippocampal spatial representations associated with H-PI are largely unknown. Here we developed a homing task (AutoPI task) that required a mouse to find a randomly placed lever on an arena before returning to its home base. Recordings from the CA1 area in male mice showed that hippocampal neurons remap between random foraging and AutoPI task, between trials in light and dark conditions, and between search and homing behavior. During the AutoPI task, approximately 25% of the firing fields were anchored to the lever position. The activity of 24% of the cells with a lever-anchored field predicted the homing direction of the animal on each trial. Our results demonstrate that the activity of hippocampal neurons with object-anchored firing fields predicts homing behavior.

Dissociating effects of aging and genetic risk of sporadic Alzheimer's disease on path integration

Path integration is a spatial navigation ability that requires the integration of information derived from self-motion cues and stable landmarks, when available, to return to a previous location. Path integration declines with age and Alzheimer's disease (AD). Here, we sought to separate the effects of age and AD risk on path integration, with and without a landmark. Overall, 279 people participated, aged between 18 and 80 years old. Advanced age impaired the appropriate use of a landmark. Older participants furthermore remembered the location of the goal relative to their starting location and reproduced this initial view without considering that they had moved in the environment. This lack of adaptative behavior was not associated with AD risk. In contrast, participants at genetic risk of AD (apolipoprotein E ε4 carriers) exhibited a pure path integration deficit, corresponding to difficulty in performing path integration in the absence of a landmark. Our results show that advanced-age impacts landmark-supported path integration, and that this age effect is dissociable from the effects of AD risk impacting pure path integration.

Theta oscillations as a substrate for medial prefrontal-hippocampal assembly interactions

The execution of cognitive functions requires coordinated circuit activity across different brain areas that involves the associated firing of neuronal assemblies. Here, we tested the circuit mechanism behind assembly interactions between the hippocampus and the medial prefrontal cortex (mPFC) of adult rats by recording neuronal populations during a rule-switching task. We identified functionally coupled CA1-mPFC cells that synchronized their activity beyond that expected from common spatial coding or oscillatory firing. When such cell pairs fired together, the mPFC cell strongly phase locked to CA1 theta oscillations and maintained consistent theta firing phases, independent of the theta timing of their CA1 counterpart. These functionally connected CA1-mPFC cells formed interconnected assemblies. While firing together with their CA1 assembly partners, mPFC cells fired along specific theta sequences. Our results suggest that upregulated theta oscillatory firing of mPFC cells can signal transient interactions with specific CA1 assemblies, thus enabling distributed computations.

Acute stress impairs visual path integration

Acute stress exerts substantial effects on episodic memory, which are often mediated by glucocorticoids, the end-product of the hypothalamic-pituitary-adrenal axis. Surprisingly little is known, however, about the influence of acute stress on human spatial navigation. One specific navigational strategy is path integration, which is linked to the medial entorhinal cortex, a region harboring glucocorticoid receptors and thus susceptible for stress effects. Here, we investigated effects of acute stress on path integration performance using a virtual homing task. We divided a sample of healthy young male participants into a stress group (nstress = 32) and a control group (ncontrol = 34). The stress group underwent the socially evaluated cold-pressor test, while the control group underwent a non-stressful control procedure. Stress induction was confirmed via physiological and subjective markers, including an increase of salivary cortisol concentrations. We applied linear mixed models to investigate the effect of acute stress on path integration depending on task difficulty and the presence or absence of spatial cues. These analyses revealed that stress impaired path integration especially in trials with high difficulty and led to greater decline of performance upon removal of spatial cues. Stress-induced deficits were strongly related to impaired distance estimation, and to a lesser extent to compromised rotation estimation. These behavioral findings are in accordance with the hypothesis that acute stress impairs path integration processes, potentially by affecting the entorhinal grid cell system. More generally, the current data suggests acute stress to impair cognitive functions mediated by medial temporal lobe regions outside the hippocampus.

A map of spatial navigation for neuroscience

Spatial navigation has received much attention from neuroscientists, leading to the identification of key brain areas and the discovery of numerous spatially selective cells. Despite this progress, our understanding of how the pieces fit together to drive behavior is generally lacking. We argue that this is partly caused by insufficient communication between behavioral and neuroscientific researchers. This has led the latter to under-appreciate the relevance and complexity of spatial behavior, and to focus too narrowly on characterizing neural representations of space-disconnected from the computations these representations are meant to enable. We therefore propose a taxonomy of navigation processes in mammals that can serve as a common framework for structuring and facilitating interdisciplinary research in the field. Using the taxonomy as a guide, we review behavioral and neural studies of spatial navigation. In doing so, we validate the taxonomy and showcase its usefulness in identifying potential issues with common experimental approaches, designing experiments that adequately target particular behaviors, correctly interpreting neural activity, and pointing to new avenues of research.

How Do You Build a Cognitive Map? The Development of Circuits and Computations for the Representation of Space in the Brain

In mammals, the activity of neurons in the entorhinal-hippocampal network is modulated by the animal's position and its movement through space. At multiple stages of this distributed circuit, distinct populations of neurons can represent a rich repertoire of navigation-related variables like the animal's location, the speed and direction of its movements, or the presence of borders and objects. Working together, spatially tuned neurons give rise to an internal representation of space, a cognitive map that supports an animal's ability to navigate the world and to encode and consolidate memories from experience. The mechanisms by which, during development, the brain acquires the ability to create an internal representation of space are just beginning to be elucidated. In this review, we examine recent work that has begun to investigate the ontogeny of circuitry, firing patterns, and computations underpinning the representation of space in the mammalian brain.

Simultaneous representation of multiple time horizons by entorhinal grid cells and CA1 place cells

Grid cells and place cells represent the spatiotemporal continuum of an animal's past, present, and future locations. However, their spatiotemporal relationship is unclear. Here, we co-record grid and place cells in freely foraging rats. We show that average time shifts in grid cells tend to be prospective and are proportional to their spatial scale, providing a nearly instantaneous readout of a spectrum of progressively increasing time horizons ranging hundreds of milliseconds. Average time shifts of place cells are generally larger compared to grid cells and also increase with place field sizes. Moreover, time horizons display nonlinear modulation by the animal's trajectories in relation to the local boundaries and locomotion cues. Finally, long and short time horizons occur at different parts of the theta cycle, which may facilitate their readout. Together, these findings suggest that population activity of grid and place cells may represent local trajectories essential for goal-directed navigation and planning.

Are grid cells used for navigation? On local metrics, subjective spaces, and black holes

The symmetric, lattice-like spatial pattern of grid-cell activity is thought to provide a neuronal global metric for space. This view is compatible with grid cells recorded in empty boxes but inconsistent with data from more naturalistic settings. We review evidence arguing against the global-metric notion, including the distortion and disintegration of the grid pattern in complex and three-dimensional environments. We argue that deviations from lattice symmetry are key for understanding grid-cell function. We propose three possible functions for grid cells, which treat real-world grid distortions as a feature rather than a bug. First, grid cells may constitute a local metric for proximal space rather than a global metric for all space. Second, grid cells could form a metric for subjective action-relevant space rather than physical space. Third, distortions may represent salient locations. Finally, we discuss mechanisms that can underlie these functions. These ideas may transform our thinking about grid cells.

Mobile cognition: imaging the human brain in the 'real world'

Cognitive neuroscience studies in humans have enabled decades of impactful discoveries but have primarily been limited to recording the brain activity of immobile participants in a laboratory setting. In recent years, advances in neuroimaging technologies have enabled recordings of human brain activity to be obtained during freely moving behaviours in the real world. Here, we propose that these mobile neuroimaging methods can provide unique insights into the neural mechanisms of human cognition and contribute to the development of novel treatments for neurological and psychiatric disorders. We further discuss the challenges associated with studying naturalistic human behaviours in complex real-world settings as well as strategies for overcoming them. We conclude that mobile neuroimaging methods have the potential to bring about a new era of cognitive neuroscience in which neural mechanisms can be studied with increased ecological validity and with the ability to address questions about natural behaviour and cognitive processes in humans engaged in dynamic real-world experiences.

Superficial-layer versus deep-layer lateral entorhinal cortex: Coding of allocentric space, egocentric space, speed, boundaries, and corners

Entorhinal cortex is the major gateway between the neocortex and the hippocampus and thus plays an essential role in subserving episodic memory and spatial navigation. It can be divided into the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC), which are commonly theorized to be critical for spatial (context) and non-spatial (content) inputs, respectively. Consistent with this theory, LEC neurons are found to carry little information about allocentric self-location, even in cue-rich environments, but they exhibit egocentric spatial information about external items in the environment. The superficial and deep layers of LEC are believed to mediate the input to and output from the hippocampus, respectively. As earlier studies mainly examined the spatial firing properties of superficial-layer LEC neurons, here we characterized the deep-layer LEC neurons and made direct comparisons with their superficial counterparts in single unit recordings from behaving rats. Because deep-layer LEC cells received inputs from hippocampal regions, which have strong selectivity for self-location, we hypothesized that deep-layer LEC neurons would be more informative about allocentric position than superficial-layer LEC neurons. We found that deep-layer LEC cells showed only slightly more allocentric spatial information and higher spatial consistency than superficial-layer LEC cells. Egocentric coding properties were comparable between these two subregions. In addition, LEC neurons demonstrated preferential firing at lower speeds, as well as at the boundary or corners of the environment. These results suggest that allocentric spatial outputs from the hippocampus are transformed in deep-layer LEC into the egocentric coding dimensions of LEC, rather than maintaining the allocentric spatial tuning of the CA1 place fields.

Gated transformations from egocentric to allocentric reference frames involving retrosplenial cortex, entorhinal cortex, and hippocampus

This paper reviews the recent experimental finding that neurons in behaving rodents show egocentric coding of the environment in a number of structures associated with the hippocampus. Many animals generating behavior on the basis of sensory input must deal with the transformation of coordinates from the egocentric position of sensory input relative to the animal, into an allocentric framework concerning the position of multiple goals and objects relative to each other in the environment. Neurons in retrosplenial cortex show egocentric coding of the position of boundaries in relation to an animal. These neuronal responses are discussed in relation to existing models of the transformation from egocentric to allocentric coordinates using gain fields and a new model proposing transformations of phase coding that differ from current models. The same type of transformations could allow hierarchical representations of complex scenes. The responses in rodents are also discussed in comparison to work on coordinate transformations in humans and non-human primates.

Chronic stress is associated with specific path integration deficits

Repeated exposure to stress (chronic stress) can cause excess levels of circulating cortisol and has detrimental influences on various cognitive functions including long-term memory and navigation. However, it remains an open question whether chronic stress affects path integration, a navigational strategy that presumably relies on the functioning of grid cells in the medial entorhinal cortex. The entorhinal cortex is a brain region in the medial temporal lobe, which contains multiple cell types involved in spatial navigation (and episodic memory), and a high number of corticosteroid receptors, predisposing it as a potential target of cortisol effects. Here, our goal was to investigate the association between chronic stress and path integration performance. We assessed chronic stress via hair cortisol concentration (physiological measure) and the Perceived Stress Questionnaire (subjective measure) in 52 female participants aged 22-65 years. Path integration was measured using a virtual homing task. Linear mixed models revealed selective impairments associated with chronic stress that depended on error type and environmental features. When focusing on distance estimations in the path integration task, we observed a significant relationship to hair cortisol concentrations indicating impaired path integration particularly during trials with higher difficulty in participants with high hair cortisol concentrations. This relationship especially emerged in the absence of spatial cues (a boundary or a landmark), and particularly in participants who reported high levels of subjectively experienced chronic stress. The findings are in line with the hypothesis that chronic stress compromises path integration, possibly via an effect on the entorhinal grid cell system.

Path integration selectively predicts midlife risk of Alzheimer's disease

The entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimer's disease (AD), associated with EC grid cell dysfunction. Given the role of grid cells in path integration, we predicted that path integration impairment would represent the first behavioural change in adults at-risk of AD. Using immersive virtual reality, we found that midlife path integration impairments predicted both hereditary and physiological AD risk, with no corresponding impairment on tests of episodic memory or other spatial behaviours. Impairments related to poorer angular estimation and were associated with hexadirectional grid-like fMRI signal in the posterior-medial EC. These results indicate that altered path integration may represent the transition point from at-risk state to disease onset in AD, prior to impairment in other cognitive domains.

Navigational roots of spatial and temporal memory structure

Our minds are constantly in transit, from the present to the past to the future, across places we have and have not directly experienced. Nevertheless, memories of our mental time travel are not organized continuously and are adaptively chunked into contexts and episodes. In this paper, I will review evidence that suggests that spatial boundary representations play a critical role in providing structure to both our spatial and temporal memories. I will illustrate the intimate connection between hippocampal spatial mapping and temporal sequencing of episodic memory to propose that high-level cognitive processes like mental time travel and conceptual mapping are rooted in basic navigational mechanisms that we humans and nonhuman animals share. Our neuroscientific understanding of hippocampal function across species may provide new insight into the origins of even the most uniquely human cognitive abilities.

Place cells dynamically refine grid cell activities to reduce error accumulation during path integration in a continuous attractor model

Navigation is one of the most fundamental skills of animals. During spatial navigation, grid cells in the medial entorhinal cortex process speed and direction of the animal to map the environment. Hippocampal place cells, in turn, encode place using sensory signals and reduce the accumulated error of grid cells for path integration. Although both cell types are part of the path integration system, the dynamic relationship between place and grid cells and the error reduction mechanism is yet to be understood. We implemented a realistic model of grid cells based on a continuous attractor model. The grid cell model was coupled to a place cell model to address their dynamic relationship during a simulated animal's exploration of a square arena. The grid cell model processed the animal's velocity and place field information from place cells. Place cells incorporated salient visual features and proximity information with input from grid cells to define their place fields. Grid cells had similar spatial phases but a diversity of spacings and orientations. To determine the role of place cells in error reduction for path integration, the animal's position estimates were decoded from grid cell activities with and without the place field input. We found that the accumulated error was reduced as place fields emerged during the exploration. Place fields closer to the animal's current location contributed more to the error reduction than remote place fields. Place cells' fields encoding space could function as spatial anchoring signals for precise path integration by grid cells.

Multiple bumps can enhance robustness to noise in continuous attractor networks

A central function of continuous attractor networks is encoding coordinates and accurately updating their values through path integration. To do so, these networks produce localized bumps of activity that move coherently in response to velocity inputs. In the brain, continuous attractors are believed to underlie grid cells and head direction cells, which maintain periodic representations of position and orientation, respectively. These representations can be achieved with any number of activity bumps, and the consequences of having more or fewer bumps are unclear. We address this knowledge gap by constructing 1D ring attractor networks with different bump numbers and characterizing their responses to three types of noise: fluctuating inputs, spiking noise, and deviations in connectivity away from ideal attractor configurations. Across all three types, networks with more bumps experience less noise-driven deviations in bump motion. This translates to more robust encodings of linear coordinates, like position, assuming that each neuron represents a fixed length no matter the bump number. Alternatively, we consider encoding a circular coordinate, like orientation, such that the network distance between adjacent bumps always maps onto 360 degrees. Under this mapping, bump number does not significantly affect the amount of error in the coordinate readout. Our simulation results are intuitively explained and quantitatively matched by a unified theory for path integration and noise in multi-bump networks. Thus, to suppress the effects of biologically relevant noise, continuous attractor networks can employ more bumps when encoding linear coordinates; this advantage disappears when encoding circular coordinates. Our findings provide motivation for multiple bumps in the mammalian grid network.

State transitions in the statistically stable place cell population correspond to rate of perceptual change

The hippocampus occupies a central role in mammalian navigation and memory. Yet an understanding of the rules that govern the statistics and granularity of the spatial code, as well as its interactions with perceptual stimuli, is lacking. We analyzed CA1 place cell activity recorded while rats foraged in different large-scale environments. We found that place cell activity was subject to an unexpected but precise homeostasis—the distribution of activity in the population as a whole being constant at all locations within and between environments. Using a virtual reconstruction of the largest environment, we showed that the rate of transition through this statistically stable population matches the rate of change in the animals’ visual scene. Thus, place fields near boundaries were small but numerous, while in the environment’s interior, they were larger but more dispersed. These results indicate that hippocampal spatial activity is governed by a small number of simple laws and, in particular, suggest the presence of an information-theoretic bound imposed by perception on the fidelity of the spatial memory system.

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Neural activity in rodent CA1 place cell populations is homeostatically balanced

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Hippocampal place field size and frequency are governed by proximity to boundaries

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Transition rate through place cell population matches rate of change in visual scene

Microcircuits for spatial coding in the medial entorhinal cortex

The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism's spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.

Grid-cell modules remain coordinated when neural activity is dissociated from external sensory cues

The representation of an animal’s position in the medial entorhinal cortex (MEC) is distributed across several modules of grid cells, each characterized by a distinct spatial scale. The population activity within each module is tightly coordinated and preserved across environments and behavioral states. Little is known, however, about the coordination of activity patterns across modules. We analyzed the joint activity patterns of hundreds of grid cells simultaneously recorded in animals that were foraging either in the light, when sensory cues could stabilize the representation, or in darkness, when such stabilization was disrupted. We found that the states of different modules are tightly coordinated, even in darkness, when the internal representation of position within the MEC deviates substantially from the true position of the animal. These findings suggest that internal brain mechanisms dynamically coordinate the representation of position in different modules, ensuring that they jointly encode a coherent and smooth trajectory.

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Hundreds of grid cells were recorded simultaneously from multiple grid modules

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Coordination between grid modules was assessed in rats that foraged in darkness

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Coordination persists despite relative drift of the represented versus true position

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This suggests that internal network mechanisms maintain inter-module coordination

Place cells may simply be memory cells: Memory compression leads to spatial tuning and history dependence

The observation of place cells has suggested that the hippocampus plays a special role in encoding spatial information. However, place cell responses are modulated by several nonspatial variables and reported to be rather unstable. Here, we propose a memory model of the hippocampus that provides an interpretation of place cells consistent with these observations. We hypothesize that the hippocampus is a memory device that takes advantage of the correlations between sensory experiences to generate compressed representations of the episodes that are stored in memory. A simple neural network model that can efficiently compress information naturally produces place cells that are similar to those observed in experiments. It predicts that the activity of these cells is variable and that the fluctuations of the place fields encode information about the recent history of sensory experiences. Place cells may simply be a consequence of a memory compression process implemented in the hippocampus.

Effect of reward on electrophysiological signatures of grid cell population activity in human spatial navigation

The regular equilateral triangular periodic firing pattern of grid cells in the entorhinal cortex is considered a regular metric for the spatial world, and the grid-like representation correlates with hexadirectional modulation of theta (4-8 Hz) power in the entorhinal cortex relative to the moving direction. However, researchers have not clearly determined whether grid cells provide only simple spatial measures in human behavior-related navigation strategies or include other factors such as goal rewards to encode information in multiple patterns. By analysing the hexadirectional modulation of EEG signals in the theta band in the entorhinal cortex of patients with epilepsy performing spatial target navigation tasks, we found that this modulation presents a grid pattern that carries target-related reward information. This grid-like representation is influenced by explicit goals and is related to the local characteristics of the environment. This study provides evidence that human grid cell population activity is influenced by reward information at the level of neural oscillations.

Olfactory landmarks and path integration converge to form a cognitive spatial map

The convergence of internal path integration and external sensory landmarks generates a cognitive spatial map in the hippocampus. We studied how localized odor cues are recognized as landmarks by recording the activity of neurons in CA1 during a virtual navigation task. We found that odor cues enriched place cell representations, dramatically improving navigation. Presentation of the same odor at different locations generated distinct place cell representations. An odor cue at a proximal location enhanced the local place cell density and also led to the formation of place cells beyond the cue. This resulted in the recognition of a second, more distal odor cue as a distinct landmark, suggesting an iterative mechanism for extending spatial representations into unknown territory. Our results establish that odors can serve as landmarks, motivating a model in which path integration and odor landmarks interact sequentially and iteratively to generate cognitive spatial maps over long distances.

Dynamical self-organization and efficient representation of space by grid cells

To plan trajectories and navigate, animals must maintain a mental representation of the environment and their own position within it. This "cognitive map" is thought to be supported in part by the entorhinal cortex, where grid cells are active when an animal occupies the vertices of a scaling hierarchy of periodic lattices of locations in an enclosure. Here, we review computational developments which suggest that the grid cell network is: (a) efficient, providing required spatial resolution with a minimum number of neurons, (b) self-organizing, dynamically coordinating the structure and scale of the responses, and (c) adaptive, re-organizing in response to changes in landmarks and the structure of the boundaries of spaces. We consider these ideas in light of recent discoveries of similar structures in the mental representation of abstract spaces of shapes and smells, and in other brain areas, and highlight promising directions for future research.

The grid code for ordered experience

Entorhinal cortical grid cells fire in a periodic pattern that tiles space, which is suggestive of a spatial coordinate system. However, irregularities in the grid pattern as well as responses of grid cells in contexts other than spatial navigation have presented a challenge to existing models of entorhinal function. In this Perspective, we propose that hippocampal input provides a key informative drive to the grid network in both spatial and non-spatial circumstances, particularly around salient events. We build on previous models in which neural activity propagates through the entorhinal-hippocampal network in time. This temporal contiguity in network activity points to temporal order as a necessary characteristic of representations generated by the hippocampal formation. We advocate that interactions in the entorhinal-hippocampal loop build a topological representation that is rooted in the temporal order of experience. In this way, the structure of grid cell firing supports a learned topology rather than a rigid coordinate frame that is bound to measurements of the physical world.

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.

Behavior determines the hippocampal spatial mapping of a multisensory environment

Animals behave in multisensory environments guided by various modalities of spatial information. Mammalian navigation engages a cognitive map of space in the hippocampus. Yet it is unknown whether and how this map incorporates multiple modalities of spatial information. Here, we establish two behavioral tasks in which mice navigate the same multisensory virtual environment by either pursuing a visual landmark or tracking an odor gradient. These tasks engage different proportions of visuo-spatial and olfacto-spatial mapping CA1 neurons and different population-level representations of each sensory-spatial coordinate. Switching between tasks results in global remapping. In a third task, mice pursue a target of varying sensory modality, and this engages modality-invariant neurons mapping the abstract behaviorally relevant coordinate irrespective of its physical modality. These findings demonstrate that the hippocampus does not necessarily map space as one coherent physical variable but as a combination of sensory and abstract reference frames determined by the subject's behavioral goal.

Crucial role for CA2 inputs in the sequential organization of CA1 time cells supporting memory

There is considerable evidence for hippocampal time cells that briefly activate in succession to represent the temporal structure of memories. Previous studies have shown that time cells can be disrupted while leaving place cells intact, indicating that spatial and temporal information can be coded in parallel. However, the circuits in which spatial and temporal information are coded have not been clearly identified. Here we investigated temporal and spatial coding by dorsal hippocampal CA1 (dCA1) neurons in mice trained on a classic spatial working-memory task. On each trial, the mice approached the same choice point on a maze but were trained to alternate between traversing one of two distinct spatial routes (spatial coding phase). In between trials, there was a 10-s mnemonic delay during which the mouse continuously ran in a fixed location (temporal coding phase). Using cell-type-specific optogenetic methods, we found that inhibiting dorsal CA2 (dCA2) inputs into dCA1 degraded time cell coding during the mnemonic delay and impaired the mouse's subsequent memory-guided choice. Conversely, inhibiting dCA2 inputs during the spatial coding phase had a negligible effect on place cell activity in dCA1 and no effect on behavior. Collectively, our work demonstrates that spatial and temporal coding in dCA1 is largely segregated with respect to the dCA2-dCA1 circuit and suggests that CA2 plays a critical role in representing the flow of time in memory within the hippocampal network.