The place-cell representation of volumetric space in rats

Formation of cognitive maps in large-scale environments by sensorimotor integration

Hippocampus in the mammalian brain supports navigation by building a cognitive map of the environment. However, only a few studies have investigated cognitive maps in large-scale arenas. To reveal the computational mechanisms underlying the formation of cognitive maps in large-scale environments, we propose a neural network model of the entorhinal-hippocampal neural circuit that integrates both spatial and non-spatial information. Spatial information is relayed from the grid units in medial entorhinal cortex (MEC) by integrating multimodal sensory-motor signals. Non-spatial, such as object, information is imparted from the visual units in lateral entorhinal cortex (LEC) by encoding visual scenes through a deep neural network. The synaptic weights from the grid units and the visual units to the place units in the hippocampus are learned by a competitive learning rule. We simulated the model in a large box maze. The place units in the model form irregularly-spaced multiple fields across the environment. When the strength of visual inputs is dominant, the responses of place units become conjunctive and egocentric. These results point to the key role of the hippocampus in balancing spatial and non-spatial information relayed via LEC and MEC.

The 3D Vertical Maze: A new model system for studying the interactions between social and spatial cognition

BACKGROUND

Evolutionary biology and neuroscience evidence supports the theory that spatial cognition and social cognition share neural mechanisms. Although rodent models are widely used to study either spatial or social cognition, few studies have explored the interactions between these domains, possibly because measures across tasks differ.

NEW METHOD

We introduce the automated 3-dimensional Vertical Maze (VM), a new model system designed to measure multiple aspects of spatial and social behavior and cognition. The VM features a standard 3-chamber maze positioned above three-level columns allowing for presentation of conspecifics as either demonstrators or discriminative stimuli at different spatial distances and different social familiarity levels. The presentation of demonstrators below the perforated floors of the 3-chamber level encourages rats to use multisensory cues to judge distance, direction, and social identity of conspecifics.

RESULTS

Using the VM, we found that rats showed normal social preferences whether demonstrators were presented at the near, middle, or far distance. In an operant spatial distance discrimination task, rats readily learned to associate a reward with the spatial distance of a demonstrator.

COMPARISON WITH EXISTING METHODS

This new paradigm advances the field by permitting the presentation of social information (conspecifics) at different spatial distances allowing more direct comparison of behavioral measures across social and spatial information domains.

CONCLUSIONS

The VM is an effective tool for studying both spatial and social cognition opening new avenues for investigating the neural and cognitive foundations of spatial and social behavior and for exploring the possibility of shared mechanisms across these cognitive domains.

Hippocampal Interneurons Shape Spatial Coding Alterations in Neurological Disorders

Hippocampal interneurons (INs) play a fundamental role in regulating neural oscillations, modulating excitatory circuits, and shaping spatial representation. While historically overshadowed by excitatory pyramidal cells in spatial coding research, recent advances have demonstrated that inhibitory INs not only coordinate network dynamics but also contribute directly to spatial information processing. This review aims to provide a novel integrative perspective on how distinct IN subtypes participate in spatial coding and how their dysfunction contributes to cognitive deficits in neurological disorders such as epilepsy, Alzheimer's disease (AD), traumatic brain injury (TBI), and cerebral hypoxia-ischemia. We synthesize recent findings demonstrating that different IN classes-including parvalbumin (PV)-, somatostatin (SST)-, cholecystokinin (CCK)-, and calretinin (CR)-expressing neurons-exhibit spatially selective activity, challenging traditional views of spatial representation, and influence memory consolidation through network-level interactions. By leveraging cutting-edge techniques such as in vivo calcium imaging and optogenetics, new evidence suggests that INs encode spatial information with a level of specificity previously attributed only to pyramidal cells. Furthermore, we investigate the impact of inhibitory circuit dysfunction in neurological disorders, examining how disruptions in interneuronal activity lead to impaired theta-gamma coupling, altered sharp wave ripples, and destabilized place cell representations, ultimately resulting in spatial memory deficits. This review advances the field by shifting the focus from pyramidal-centered models to a more nuanced understanding of the hippocampal network, emphasizing the active role of INs in spatial coding. By highlighting the translational potential of targeting inhibitory circuits for therapeutic interventions, we propose novel strategies for restoring hippocampal network function in neurological conditions. Readers will gain a comprehensive understanding of the emerging role of INs in spatial representation and the critical implications of their dysfunction, paving the way for future research on interneuron-targeted treatments for cognitive disorders.

Translational differentiation of vertically displaced surfaces by grid cells

Navigation is commonly associated with two-dimensional (2D) representations of space. Recordings from place and grid cells in the rodent and bat brain have largely upheld this association. Recent studies have investigated how these 2D representations might extend into the three-dimensional (3D) world. One unexplored question is whether grid cells represent vertically separated horizontal surfaces as a single 3D space or distinct planar environments. To address this issue, we recorded grid cells as rats foraged in both an open-field environment and one with a transparent floor suspended directly above the open-field environment. Rats either actively locomoted up a ramp to the elevated environment, or they were passively moved between the two environments, to test how differences in path integration may affect grid cell firing. We found that grid cell firing patterns in the elevated environment were translated (but not rotated) relative to those in the floor environment and were consistent across active and passive sessions. The translation of the grid pattern on the elevated surface was consistent among co-recorded grid cells but differed between animals and between different groups of grid cells recorded from the same animal. Non-grid spatially modulated cells also rearranged their location preferences between the two surfaces. Overall, we did not observe any evidence that the two surfaces were represented with a single 3D representation but instead were treated as two distinct surfaces connected by a common orientation signal. These findings suggest that grid cell representations on visually distinct, vertically displaced horizontal surfaces are planar rather than volumetric.

Hand position fields of neurons in the premotor cortex of macaques during natural reaching

While hippocampus represents spatial information through place cells for body navigation, whether motor areas employ a similar framework to guide hand reaching remains unknown. Here, we investigate tuning properties in dorsal premotor cortex (PMd) during naturalistic reach-and-grasp tasks in four monkeys. We find that 22% (132/601) of PMd neurons increase firing rates when the monkey's hand occupies specific positions in space, forming the position fields. These cells represent the hand position highly efficiently, achieving ~80% accuracy for decoding hand trajectories with only 50 most dedicated position tuned cells ( ~ 10% of all recorded neurons). The hand position is co-represented with hand moving direction, speed, and reward location in the same population of PMd neurons, forming a mixed-selective framework to integrate positional and kinematic information. Our findings suggest field-like positional coding may be a mechanism shared across brain regions for spatial representation in goal-directed movements, including body navigation and forelimb reaching.

Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences

The vertebrate hippocampus is believed to use recurrent connectivity in area CA3 to support episodic memory recall from partial cues. This brain area also contains place cells, whose location-selective firing fields implement maps supporting spatial memory. Here we show that place cells emerge in networks trained to remember temporally continuous sensory episodes. We model CA3 as a recurrent autoencoder that recalls and reconstructs sensory experiences from noisy and partially occluded observations by agents traversing simulated arenas. The agents move in realistic trajectories modeled from rodents and environments are modeled as continuously varying, high-dimensional, sensory experience maps (spatially smoothed Gaussian random fields). Training our autoencoder to accurately pattern-complete and reconstruct sensory experiences with a constraint on total activity causes spatially localized firing fields, i.e., place cells, to emerge in the encoding layer. The emergent place fields reproduce key aspects of hippocampal phenomenology: a) remapping (maintenance of and reversion to distinct learned maps in different environments), implemented via repositioning of experience manifolds in the network's hidden layer, b) orthogonality of spatial representations in different arenas, c) robust place field emergence in differently shaped rooms, with single units showing multiple place fields in large or complex spaces, and d) slow representational drift of place fields. We argue that these results arise because continuous traversal of space makes sensory experience temporally continuous. We make testable predictions: a) rapidly changing sensory context will disrupt place fields, b) place fields will form even if recurrent connections are blocked, but reversion to previously learned representations upon remapping will be abolished, c) the dimension of temporally smooth experience sets the dimensionality of place fields, including during virtual navigation of abstract spaces. Code for our experiments is available at.

Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences

The vertebrate hippocampus is believed to use recurrent connectivity in area CA3 to support episodic memory recall from partial cues. This brain area also contains place cells, whose location-selective firing fields implement maps supporting spatial memory. Here we show that place cells emerge in networks trained to remember temporally continuous sensory episodes. We model CA3 as a recurrent autoencoder that recalls and reconstructs sensory experiences from noisy and partially occluded observations by agents traversing simulated arenas. The agents move in realistic trajectories modeled from rodents and environments are modeled as continuously varying, high-dimensional, sensory experience maps (spatially smoothed Gaussian random fields). Training our autoencoder to accurately pattern-complete and reconstruct sensory experiences with a constraint on total activity causes spatially localized firing fields, i.e., place cells, to emerge in the encoding layer. The emergent place fields reproduce key aspects of hippocampal phenomenology: a) remapping (maintenance of and reversion to distinct learned maps in different environments), implemented via repositioning of experience manifolds in the network's hidden layer, b) orthogonality of spatial representations in different arenas, c) robust place field emergence in differently shaped rooms, with single units showing multiple place fields in large or complex spaces, and d) slow representational drift of place fields. We argue that these results arise because continuous traversal of space makes sensory experience temporally continuous. We make testable predictions: a) rapidly changing sensory context will disrupt place fields, b) place fields will form even if recurrent connections are blocked, but reversion to previously learned representations upon remapping will be abolished, c) the dimension of temporally smooth experience sets the dimensionality of place fields, including during virtual navigation of abstract spaces. Code for our experiments is available at.

Unweaving the Cognitive Map: A Personal History

I have been incredibly fortunate to have worked in the field of hippocampal spatial coding during three of its most exciting decades, the 1990s, 2000s, and 2010s. During this time I had a ringside view of some of the foundational discoveries that were made which have transformed our understanding of the hippocampal system and its role in cognition (especially spatial cognition) and memory. These discoveries inspired me in my own lab over the years to pursue three broad lines of enquiry-3D spatial encoding, context and the sense of direction-which are outlined here. If some of my personal recollections are a little inaccurate (such is the nature of episodic memory!) I apologize in advance.

Information transfer from spatial to social distance in rats: implications for the role of the posterior parietal cortex in spatial-social integration

Humans and other social animals can represent and navigate complex networks of social relationships in ways that are suggestive of representation and navigation in space. There is some evidence that cortical regions initially required for processing space have been adapted to include processing of social information. One candidate region for supporting both spatial and social information processing is the posterior parietal cortex (PPC). We examined the hypothesis that rats can transfer or generalize distance information across spatial and social domains and that this phenomenon requires the PPC. In a novel apparatus, rats learned to discriminate two conspecifics positioned at different spatial distances (near vs. far) in a goal-driven paradigm. Following spatial learning, subjects were tested on probe trials in which spatial distance was replaced with social distance (cagemate vs. less familiar conspecific). The PPC was chemogenetically inactivated during a subset of probe sessions. We predicted that, in control probe trials, subjects would select conspecifics whose social distance matched the previously learned spatial distance. That is, if trained on the near distance, the rat would choose the highly familiar cagemate, and if trained on the far distance, the rat would choose the less familiar conspecific. Subjects learned to discriminate conspecifics based on spatial distance in our goal-driven paradigm. Moreover, choice for the appropriate social distance in the first probe session was significantly higher than chance. This result suggests that rats transferred learned spatial information to social contexts. Contrary to our predictions, PPC inactivation did not impair spatial to social information transfer. Possible reasons are discussed. To our knowledge, this is the first study to provide evidence that spatial and social distance are processed by shared cognitive mechanisms in the rat model.

Disruption of hippocampal-prefrontal neural dynamics and risky decision-making in a mouse model of Alzheimer's disease

This study investigates how amyloid pathology influences hippocampal-prefrontal neural dynamics and decision-making in Alzheimer's disease (AD) using 5XFAD mice, a well-established model system characterized by pronounced early amyloid pathology. Utilizing ecologically-relevant "approach food-avoid predator" foraging tasks, we observed that 5XFAD mice exhibited persistent risk-taking behaviors and reduced adaptability to changing threat conditions, indicative of impaired decision-making. Multi-regional neural recordings revealed rigid hippocampal CA1 place-cell fields, decreased sharp-wave ripple (SWR) frequencies, and disrupted medial prefrontal-hippocampal connectivity, all of which corresponded with deficits in behavioral flexibility during spatial risk scenarios. These findings highlight the critical role of SWR dynamics and corticolimbic circuit integrity in adaptive decision-making, with implications for understanding cognitive decline in AD in naturalistic contexts. By identifying specific neural disruptions underlying risky decision-making deficits, this work provides insights into the neural basis of cognitive dysfunction in AD and suggests potential targets for therapeutic intervention.

Cognitive Maps for a Non-Euclidean Environment: Path Integration and Spatial Memory on a Sphere

Humans build mental models of the world and utilize them for various cognitive tasks. The exact form of cognitive maps is not fully understood, especially for novel and complex environments beyond the flat Euclidean environment. To address this gap, we investigated path integration-a critical process underlying cognitive mapping-and spatial-memory capacity on the spherical (non-Euclidean) and planar (Euclidean) environments in young healthy adults (N = 20) using immersive virtual reality. We observed a strong Euclidean bias during the path-integration task on the spherical surface, even among participants who possessed knowledge of non-Euclidean geometry. Notably, despite this bias, participants demonstrated reasonable navigation ability on the sphere. This observation and simulation suggest that humans navigate nonflat surfaces by constructing locally confined Euclidean maps and flexibly combining them. This insight sheds light on potential neural mechanisms and behavioral strategies for solving complex cognitive tasks.

Encoding of 2D Self-Centered Plans and World-Centered Positions in the Rat Frontal Orienting Field

The neural mechanisms of motor planning have been extensively studied in rodents. Preparatory activity in the frontal cortex predicts upcoming choice, but limitations of typical tasks have made it challenging to determine whether the spatial information is in a self-centered direction reference frame or a world-centered position reference frame. Here, we trained male rats to make delayed visually guided orienting movements to six different directions, with four different target positions for each direction, which allowed us to disentangle direction versus position tuning in neural activity. We recorded single unit activity from the rat frontal orienting field (FOF) in the secondary motor cortex, a region involved in planning orienting movements. Population analyses revealed that the FOF encodes two separate 2D maps of space. First, a 2D map of the planned and ongoing movement in a self-centered direction reference frame. Second, a 2D map of the animal's current position on the port wall in a world-centered reference frame. Thus, preparatory activity in the FOF represents self-centered upcoming movement directions, but FOF neurons multiplex both self- and world-reference frame variables at the level of single neurons. Neural network model comparison supports the view that despite the presence of world-centered representations, the FOF receives the target information as self-centered input and generates self-centered planning signals.

Modeling hippocampal spatial cells in rodents navigating in 3D environments

Studies on the neural correlates of navigation in 3D environments are plagued by several issues that need to be solved. For example, experimental studies show markedly different place cell responses in rats and bats, both navigating in 3D environments. In this study, we focus on modelling the spatial cells in rodents in a 3D environment. We propose a deep autoencoder network to model the place and grid cells in a simulated agent navigating in a 3D environment. The input layer to the autoencoder network model is the HD layer, which encodes the agent's HD in terms of azimuth (θ) and pitch angles (ϕ). The output of this layer is given as input to the Path Integration (PI) layer, which computes displacement in all the preferred directions. The bottleneck layer of the autoencoder model encodes the spatial cell-like responses. Both grid cell and place cell-like responses are observed. The proposed model is verified using two experimental studies with two 3D environments. This model paves the way for a holistic approach using deep neural networks to model spatial cells in 3D navigation.

Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus

The role of the hippocampus in spatial navigation has been primarily studied in nocturnal mammals, such as rats, that lack many adaptations for daylight vision. Here we demonstrate that during 3D navigation, the common marmoset, a new world primate adapted to daylight, predominantly uses rapid head-gaze shifts for visual exploration while remaining stationary. During active locomotion marmosets stabilize the head, in contrast to rats that use low-velocity head movements to scan the environment as they locomote. Pyramidal neurons in the marmoset hippocampus CA3/CA1 regions predominantly show mixed selectivity for 3D spatial view, head direction, and place. Exclusive place selectivity is scarce. Inhibitory interneurons are predominantly mixed selective for angular head velocity and translation speed. Finally, we found theta phase resetting of local field potential oscillations triggered by head-gaze shifts. Our findings indicate that marmosets adapted to their daylight ecological niche by modifying exploration/navigation strategies and their corresponding hippocampal specializations.

Exploring the Remediation of Behavioral Disturbances of Spatial Cognition in Community-Dwelling Senior Citizens with Mild Cognitive Impairment via Innovative Technological Apparatus (BDSC-MCI Project): Protocol for a Prospective, Multi-Center Observational Study

Spatial navigation (SN) has been reported to be one of the first cognitive domains to be affected in Alzheimer's disease (AD), which occurs as a result of progressive neuropathology involving specific brain areas. Moreover, the epsilon 4 isoform of apolipoprotein-E (APOE-ε4) has been associated with both sporadic and familial late-onset AD, and patients with mild cognitive impairment (MCI) due to AD are more likely to progressively deteriorate. Spatial navigation performance will be examined on a sample of 76 community-dwelling senior citizens (25 healthy controls; 25 individuals with subjective cognitive decline (SCD); and 26 patients with MCI due to AD) via a virtual computer-based task (i.e., the AppleGame) and a naturalistic task (i.e., the Detour Navigation Test-modified version) for which a wearable device with sensors will be used for recording gait data and revealing physiological parameters that may be associated with spatial disorientation. We expect that patients with MCI due to AD and APOE-ε4 carriers will show altered SN performances compared to individuals with SCD and healthy controls in the experimental tasks, and that VR testing may predict ecological performance. Impaired SN performances in people at increased risk of developing AD may inform future cognitive rehabilitation protocols for counteracting spatial disorientation that may occur during elders' traveling to unfamiliar locations. The research protocol has been approved by the Ethics Committee of the Istituto Auxologico Italiano. Findings will be published in peer-reviewed medical journals and discussed in national and international congresses.

Estimating neuronal firing density: A quantitative analysis of firing rate map algorithms

The analysis of neurons that exhibit receptive fields dependent on an organism's spatial location, such as grid, place or boundary cells typically begins by mapping their activity in space using firing rate maps. However, mapping approaches are varied and depend on multiple tuning parameters that are usually chosen qualitatively by the experimenter and thus vary significantly across studies. Small changes in parameters such as these can impact results significantly, yet, to date a quantitative investigation of firing rate maps has not been attempted. Using simulated datasets, we examined how tuning parameters, recording duration and firing field size affect the accuracy of spatial maps generated using the most widely used approaches. For each approach we found a clear subset of parameters which yielded low-error firing rate maps and isolated the parameters yielding 1) the least error possible and 2) the Pareto-optimal parameter set which balanced error, computation time, place field detection accuracy and the extrapolation of missing values. Smoothed bivariate histograms and averaged shifted histograms were consistently associated with the fastest computation times while still providing accurate maps. Adaptive smoothing and binning approaches were found to compensate for low positional sampling the most effectively. Kernel smoothed density estimation also compensated for low sampling well and resulted in accurate maps, but it was also among the slowest methods tested. Overall, the bivariate histogram, coupled with spatial smoothing, is likely the most desirable method in the majority of cases.

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.

Convergence of location, direction, and theta in the rat anteroventral thalamic nucleus

The thalamus and cortex are anatomically interconnected, with the thalamus providing integral information for cortical functions. The anteroventral thalamic nucleus (AV) is reciprocally connected to retrosplenial cortex (RSC). Two distinct AV subfields, dorsomedial (AVDM) and ventrolateral (AVVL), project differentially to granular vs. dysgranular RSC, respectively. To probe if functional responses of AV neurons differ, we recorded single neurons and local field potentials from AVDM and AVVL in rats during foraging. We observed place cells (neurons modulated by spatial location) in both AVDM and AVVL. Additionally, we characterized neurons modulated by theta oscillations, heading direction, and a conjunction of these. Place cells and conjunctive Theta-by-Head direction cells were more prevalent in AVVL; more non-conjunctive theta and directional neurons were prevalent in AVDM. These findings add further evidence that there are two thalamocortical circuits connecting AV and RSC, and reveal that the signaling involves place information in addition to direction and theta.

Dissociating two aspects of human 3D spatial perception by studying fighter pilots

Human perception of 3D space has been investigated extensively, but there are conflicting reports regarding its distortions. A possible solution to these discrepancies is that 3D perception is in fact comprised of two different processes-perception of traveled space, and perception of surrounding space. Here we tested these two aspects on the same subjects, for the first time. To differentiate these two aspects and investigate whether they emerge from different processes, we asked whether these two aspects are affected differently by the individual's experience of 3D locomotion. Using an immersive high-grade flight-simulator with realistic virtual-reality, we compared these two aspects of 3D perception in fighter pilots-individuals highly experienced in 3D locomotion-and in control subjects. We found that the two aspects of 3D perception were affected differently by 3D locomotion experience: the perception of 3D traveled space was plastic and experience-dependent, differing dramatically between pilots and controls, while the perception of surrounding space was rigid and unaffected by experience. This dissociation suggests that these two aspects of 3D spatial perception emerge from two distinct processes.

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.

Boundary vector cells in the goldfish central telencephalon encode spatial information

Navigation is one of the most fundamental cognitive skills for the survival of fish, the largest vertebrate class, and almost all other animal classes. Space encoding in single neurons is a critical component of the neural basis of navigation. To study this fundamental cognitive component in fish, we recorded the activity of neurons in the central area of the goldfish telencephalon while the fish were freely navigating in a quasi-2D water tank embedded in a 3D environment. We found spatially modulated neurons with firing patterns that gradually decreased with the distance of the fish from a boundary in each cell's preferred direction, resembling the boundary vector cells found in the mammalian subiculum. Many of these cells exhibited beta rhythm oscillations. This type of spatial representation in fish brains is unique among space-encoding cells in vertebrates and provides insights into spatial cognition in this lineage.

Tracking neural activity from the same cells during the entire adult life of mice

Stably recording the electrical activity of the same neurons over the adult life of an animal is important to neuroscience research and biomedical applications. Current implantable devices cannot provide stable recording on this timescale. Here, we introduce a method to precisely implant electronics with an open, unfolded mesh structure across multiple brain regions in the mouse. The open mesh structure forms a stable interwoven structure with the neural network, preventing probe drifting and showing no immune response and neuron loss during the year-long implantation. Rigorous statistical analysis, visual stimulus-dependent measurement and unbiased, machine-learning-based analysis demonstrated that single-unit action potentials have been recorded from the same neurons of behaving mice in a very long-term stable manner. Leveraging this stable structure, we demonstrated that the same neurons can be recorded over the entire adult life of the mouse, revealing the aging-associated evolution of single-neuron activities.

Environment Symmetry Drives a Multidirectional Code in Rat Retrosplenial Cortex

We investigated how environment symmetry shapes the neural processing of direction by recording directionally tuned retrosplenial neurons in male Lister hooded rats exploring multicompartment environments that had different levels of global rotational symmetry. Our hypothesis built on prior observations of twofold symmetry in the directional tuning curves of rats in a globally twofold-symmetric environment. To test whether environment symmetry was the relevant factor shaping the directional responses, here we deployed the same apparatus (two connected rectangular boxes) plus one with fourfold symmetry (a 2 × 2 array of connected square boxes) and one with onefold symmetry (a circular open-field arena). Consistent with our hypothesis we found many neurons with tuning curve symmetries that mirrored these environment symmetries, having twofold, fourfold, or onefold symmetric tuning, respectively. Some cells expressed this pattern only globally (across the whole environment), maintaining singular tuning curves in each subcompartment. However, others also expressed it locally within each subcompartment. Because multidirectionality has not been reported in naive rats in single environmental compartments, this suggests an experience-dependent effect of global environment symmetry on local firing symmetry. An intermingled population of directional neurons were classic head direction cells with globally referenced directional tuning. These cells were electrophysiologically distinct, with narrower tuning curves and a burstier firing pattern. Thus, retrosplenial directional neurons can simultaneously encode overall head direction and local head direction (relative to compartment layout). Furthermore, they can learn about global environment symmetry and express this locally. This may be important for the encoding of environment structure beyond immediate perceptual reach.SIGNIFICANCE STATEMENT We investigated how environment symmetry shapes the neural code for space by recording directionally tuned neurons from the retrosplenial cortex of rats exploring single- or multicompartment environments having onefold, twofold, or fourfold rotational symmetry. We found that many cells expressed a symmetry in their head direction tuning curves that matched the corresponding global environment symmetry, indicating plasticity of their directional tuning. They were also electrophysiologically distinct from canonical head directional cells. Notably, following exploration of the global space, many multidirectionally tuned neurons encoded global environment symmetry, even in local subcompartments. Our results suggest that multidirectional head direction codes contribute to the cognitive mapping of the complex structure of multicompartmented spaces.

Neural Correlates of Spatial Navigation in Primate Hippocampus

The hippocampus has been extensively implicated in spatial navigation in rodents and more recently in bats. Numerous studies have revealed that various kinds of spatial information are encoded across hippocampal regions. In contrast, investigations of spatial behavioral correlates in the primate hippocampus are scarce and have been mostly limited to head-restrained subjects during virtual navigation. However, recent advances made in freely-moving primates suggest marked differences in spatial representations from rodents, albeit some similarities. Here, we review empirical studies examining the neural correlates of spatial navigation in the primate (including human) hippocampus at the levels of local field potentials and single units. The lower frequency theta oscillations are often intermittent. Single neuron responses are highly mixed and task-dependent. We also discuss neuronal selectivity in the eye and head coordinates. Finally, we propose that future studies should focus on investigating both intrinsic and extrinsic population activity and examining spatial coding properties in large-scale hippocampal-neocortical networks across tasks.

A Review of Neurologgers for Extracellular Recording of Neuronal Activity in the Brain of Freely Behaving Wild Animals

Simultaneous monitoring of animal behavior and neuronal activity in the brain enables us to examine the neural underpinnings of behaviors. Conventionally, the neural activity data are buffered, amplified, multiplexed, and then converted from analog to digital in the head-stage amplifier, following which they are transferred to a storage server via a cable. Such tethered recording systems, intended for indoor use, hamper the free movement of animals in three-dimensional (3D) space as well as in large spaces or underwater, making it difficult to target wild animals active under natural conditions; it also presents challenges in realizing its applications to humans, such as the Brain-Machine Interfaces (BMI). Recent advances in micromachine technology have established a wireless logging device called a neurologger, which directly stores neural activity on ultra-compact memory media. The advent of the neurologger has triggered the examination of the neural correlates of 3D flight, underwater swimming of wild animals, and translocation experiments in the wild. Examples of the use of neurologgers will provide an insight into understanding the neural underpinnings of behaviors in the natural environment and contribute to the practical application of BMI. Here we outline the monitoring of the neural underpinnings of flying and swimming behaviors using neurologgers. We then focus on neuroethological findings and end by discussing their future perspectives.

Neural Oscillations in Aversively Motivated Behavior

Fear and anxiety-based disorders are highly debilitating and among the most prevalent psychiatric disorders. These disorders are associated with abnormal network oscillations in the brain, yet a comprehensive understanding of the role of network oscillations in the regulation of aversively motivated behavior is lacking. In this review, we examine the oscillatory correlates of fear and anxiety with a particular focus on rhythms in the theta and gamma-range. First, we describe neural oscillations and their link to neural function by detailing the role of well-studied theta and gamma rhythms to spatial and memory functions of the hippocampus. We then describe how theta and gamma oscillations act to synchronize brain structures to guide adaptive fear and anxiety-like behavior. In short, that hippocampal network oscillations act to integrate spatial information with motivationally salient information from the amygdala during states of anxiety before routing this information via theta oscillations to appropriate target regions, such as the prefrontal cortex. Moreover, theta and gamma oscillations develop in the amygdala and neocortical areas during the encoding of fear memories, and interregional synchronization reflects the retrieval of both recent and remotely encoded fear memories. Finally, we argue that the thalamic nucleus reuniens represents a key node synchronizing prefrontal-hippocampal theta dynamics for the retrieval of episodic extinction memories in the hippocampus.

Adaptive cognitive maps for curved surfaces in the 3D world

Terrains in a 3D world can be undulating. Yet, most prior research has exclusively investigated spatial representations on a flat surface, leaving a 2D cognitive map as the dominant model in the field. Here, we investigated whether humans represent a curved surface by building a dimension-reduced flattened 2D map or a full 3D map. Participants learned the location of objects positioned on a flat and curved surface in a virtual environment by driving on the concave side of the surface (Experiment 1), driving and looking vertically (Experiment 2), or flying (Experiment 3). Subsequently, they were asked to retrieve either the path distance or the 3D Euclidean distance between the objects. Path distance estimation was good overall, but we found a significant underestimation bias for the path distance on the curve, suggesting an influence of potential 3D shortcuts, even though participants were only driving on the surface. Euclidean distance estimation was better when participants were exposed more to the global 3D structure of the environment by looking and flying. These results suggest that the representation of the 2D manifold, embedded in a 3D world, is neither purely 2D nor 3D. Rather, it is flexible and dependent on the behavioral experience and demand.

Juxtacellular opto-tagging of hippocampal CA1 neurons in freely moving mice

Neural circuits are made of a vast diversity of neuronal cell types. While immense progress has been made in classifying neurons based on morphological, molecular, and functional properties, understanding how this heterogeneity contributes to brain function during natural behavior has remained largely unresolved. In the present study, we combined the juxtacellular recording and labeling technique with optogenetics in freely moving mice. This allowed us to selectively target molecularly defined cell classes for in vivo single-cell recordings and morphological analysis. We validated this strategy in the CA1 region of the mouse hippocampus by restricting Channelrhodopsin expression to Calbindin-positive neurons. Directly versus indirectly light-activated neurons could be readily distinguished based on the latencies of light-evoked spikes, with juxtacellular labeling and post hoc histological analysis providing ‘ground-truth’ validation. Using these opto-juxtacellular procedures in freely moving mice, we found that Calbindin-positive CA1 pyramidal cells were weakly spatially modulated and conveyed less spatial information than Calbindin-negative neurons – pointing to pyramidal cell identity as a key determinant for neuronal recruitment into the hippocampal spatial map. Thus, our method complements current in vivo techniques by enabling optogenetic-assisted structure–function analysis of single neurons recorded during natural, unrestrained behavior.

The time, the path, its length and strenuousness in maze learning

Previous findings show that rats in a maze tend to choose the shortest path to reach food. But it is not clear whether this choice is based on path length solely, or some other factors. The aim of this experiment was to investigate which factor dominates the behavior in a maze: path (longer and shorter), time (longer and shorter), or effort (more or less strenuous). The experiment involved 40 mice (4 groups), learning a maze with two paths. Each group went through only one of the situations within which we kept one factor constant on two paths while the remaining two factors were varied. Only in the fourth situation all factors were equalized. The results show that there is a statistically significant difference in the maze path preference between four situations. Preference between the paths is such that mice always choose paths requiring less effort.

Spatial modulation of hippocampal activity in freely moving macaques

The hippocampal formation is linked to spatial navigation, but there is little corroboration from freely moving primates with concurrent monitoring of head and gaze stances. We recorded neural activity across hippocampal regions in rhesus macaques during free foraging in an open environment while tracking their head and eye. Theta activity was intermittently present at movement onset and modulated by saccades. Many neurons were phase-locked to theta, with few showing phase precession. Most neurons encoded a mixture of spatial variables beyond place and grid tuning. Spatial representations were dominated by facing location and allocentric direction, mostly in head, rather than gaze, coordinates. Importantly, eye movements strongly modulated neural activity in all regions. These findings reveal that the macaque hippocampal formation represents three-dimensional (3D) space using a multiplexed code, with head orientation and eye movement properties being dominant during free exploration.

Spatial representability of neuronal activity

A common approach to interpreting spiking activity is based on identifying the firing fields—regions in physical or configuration spaces that elicit responses of neurons. Common examples include hippocampal place cells that fire at preferred locations in the navigated environment, head direction cells that fire at preferred orientations of the animal’s head, view cells that respond to preferred spots in the visual field, etc. In all these cases, firing fields were discovered empirically, by trial and error. We argue that the existence and a number of properties of the firing fields can be established theoretically, through topological analyses of the neuronal spiking activity. In particular, we use Leray criterion powered by persistent homology theory, Eckhoff conditions and Region Connection Calculus to verify consistency of neuronal responses with a single coherent representation of space.

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.

Nonlocal spatiotemporal representation in the hippocampus of freely flying bats

Navigation occurs through a continuum of space and time. The hippocampus is known to encode the immediate position of moving animals. However, active navigation, especially at high speeds, may require representing navigational information beyond the present moment. Using wireless electrophysiological recordings in freely flying bats, we demonstrate that neural activity in area CA1 predominantly encodes nonlocal spatial information up to meters away from the bat's present position. This spatiotemporal representation extends both forward and backward in time, with an emphasis on future locations, and is found during both random exploration and goal-directed navigation. The representation of position thus extends along a continuum, with each moment containing information about past, present, and future, and may provide a key mechanism for navigating along self-selected and remembered paths.

Learning an Efficient Hippocampal Place Map from Entorhinal Inputs Using Non-Negative Sparse Coding

Cells in the entorhinal cortex (EC) contain rich spatial information and project strongly to the hippocampus where a cognitive map is supposedly created. These cells range from cells with structured spatial selectivity, such as grid cells in the medial EC (MEC) that are selective to an array of spatial locations that form a hexagonal grid, to weakly spatial cells, such as non-grid cells in the MEC and lateral EC (LEC) that contain spatial information but have no structured spatial selectivity. However, in a small environment, place cells in the hippocampus are generally selective to a single location of the environment, while granule cells in the dentate gyrus of the hippocampus have multiple discrete firing locations but lack spatial periodicity. Given the anatomic connection from the EC to the hippocampus, how the hippocampus retrieves information from upstream EC remains unclear. Here, we propose a unified learning model that can describe the spatial tuning properties of both hippocampal place cells and dentate gyrus granule cells based on non-negative sparse coding from EC inputs. Sparse coding plays an important role in many cortical areas and is proposed here to have a key role in the hippocampus. Our results show that the hexagonal patterns of MEC grid cells with various orientations, grid spacings and phases are necessary for the model to learn different place cells that efficiently tile the entire spatial environment. However, if there is a lack of diversity in any grid parameters or a lack of hippocampal cells in the network, this will lead to the emergence of hippocampal cells that have multiple firing locations. More surprisingly, the model can also learn hippocampal place cells even when weakly spatial cells, instead of grid cells, are used as the input to the hippocampus. This work suggests that sparse coding may be one of the underlying organizing principles for the navigational system of the brain.

Choice of method of place cell classification determines the population of cells identified

Place cells, spatially responsive hippocampal cells, provide the neural substrate supporting navigation and spatial memory. Historically most studies of these neurons have used electrophysiological recordings from implanted electrodes but optical methods, measuring intracellular calcium, are becoming increasingly common. Several methods have been proposed as a means to identify place cells based on their calcium activity but there is no common standard and it is unclear how reliable different approaches are. Here we tested four methods that have previously been applied to two-photon hippocampal imaging or electrophysiological data, using both model datasets and real imaging data. These methods use different parameters to identify place cells, including the peak activity in the place field, compared to other locations (the Peak method); the stability of cells' activity over repeated traversals of an environment (Stability method); a combination of these parameters with the size of the place field (Combination method); and the spatial information held by the cells (Information method). The methods performed differently from each other on both model and real data. In real datasets, vastly different numbers of place cells were identified using the four methods, with little overlap between the populations identified as place cells. Therefore, choice of place cell detection method dramatically affects the number and properties of identified cells. Ultimately, we recommend the Peak method be used in future studies to identify place cell populations, as this method is robust to moderate variations in place field within a session, and makes no inherent assumptions about the spatial information in place fields, unless there is an explicit theoretical reason for detecting cells with more narrowly defined properties.

Dorsal CA1 hippocampal place cells form a multi-scale representation of megaspace

Spatially firing "place cells" within the hippocampal CA1 region form internal maps of the environment necessary for navigation and memory. In rodents, these neurons have been almost exclusively studied in small environments (<4 m²). It remains unclear how place cells encode a very large open 2D environment that is commensurate with the natural environments experienced by rodents and other mammals. Such an ethologically realistic environment would require a complex spatial representation, capable of simultaneously representing space at multiple overlapping fine-to-coarse informational scales. Here, we show that in a "megaspace" (18.6 m²), the majority of dorsal CA1 place cells exhibited multiple place subfields of different sizes, akin to those observed along the septo-temporal axis. Furthermore, the total area covered by the subfields of each cell was not correlated with the number of subfields, and increased with the scale of the environment. The multiple different-sized subfields exhibited by place cells in the megaspace suggest that the ensemble population of subfields form a multi-scale representation of space within the dorsal hippocampus. Our findings point to a new dorsal hippocampus ensemble coding scheme that simultaneously supports navigational processes at both fine- and coarse-grained resolutions. VIDEO ABSTRACT.

Cross-species neuroscience: closing the explanatory gap

Neuroscience has seen substantial development in non-invasive methods available for investigating the living human brain. However, these tools are limited to coarse macroscopic measures of neural activity that aggregate the diverse responses of thousands of cells. To access neural activity at the cellular and circuit level, researchers instead rely on invasive recordings in animals. Recent advances in invasive methods now permit large-scale recording and circuit-level manipulations with exquisite spatio-temporal precision. Yet, there has been limited progress in relating these microcircuit measures to complex cognition and behaviour observed in humans. Contemporary neuroscience thus faces an explanatory gap between macroscopic descriptions of the human brain and microscopic descriptions in animal models. To close the explanatory gap, we propose adopting a cross-species approach. Despite dramatic differences in the size of mammalian brains, this approach is broadly justified by preserved homology. Here, we outline a three-armed approach for effective cross-species investigation that highlights the need to translate different measures of neural activity into a common space. We discuss how a cross-species approach has the potential to transform basic neuroscience while also benefiting neuropsychiatric drug development where clinical translation has, to date, seen minimal success. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

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.

Volumetric spatial behaviour in rats reveals the anisotropic organisation of navigation

We investigated how access to the vertical dimension influences the natural exploratory and foraging behaviour of rats. Using high-accuracy three-dimensional tracking of position in two- and three-dimensional environments, we sought to determine (i) how rats navigated through the environments with respect to gravity, (ii) where rats chose to form their home bases in volumetric space, and (iii) how they navigated to and from these home bases. To evaluate how horizontal biases may affect these behaviours, we compared a 3D maze where animals preferred to move horizontally to a different 3D configuration where all axes were equally energetically costly to traverse. Additionally, we compared home base formation in two-dimensional arenas with and without walls to the three-dimensional climbing mazes. We report that many behaviours exhibited by rats in horizontal spaces naturally extend to fully volumetric ones, such as home base formation and foraging excursions. We also provide further evidence for the strong differentiation of the horizontal and vertical axes: rats showed a horizontal movement bias, they formed home bases mainly in the bottom layers of both mazes and they generally solved the vertical component of return trajectories before and faster than the horizontal component. We explain the bias towards horizontal movements in terms of energy conservation, while the locations of home bases are explained from an information gathering view as a method for correcting self-localisation.

Knowledge Across Reference Frames: Cognitive Maps and Image Spaces

In human and non-human animals, conceptual knowledge is partially organized according to low-dimensional geometries that rely on brain structures and computations involved in spatial representations. Recently, two separate lines of research have investigated cognitive maps, that are associated with the hippocampal formation and are similar to world-centered representations of the environment, and image spaces, that are associated with the parietal cortex and are similar to self-centered spatial relationships. We review evidence supporting cognitive maps and image spaces, and we propose a hippocampal-parietal network that can account for the organization and retrieval of knowledge across multiple reference frames. We also suggest that cognitive maps and image spaces may be two manifestations of a more general propensity of the mind to create low-dimensional internal models.

On the absence or presence of 3D tuned head direction cells in rats: a review and rebuttal

A major question in the field of spatial cognition is how animals represent three-dimensional (3D) space. Different results have been obtained across various species and may depend on whether the species inhabits a 3D environment or is terrestrial (land dwelling). The head direction (HD) cell system is an attractive candidate to study in terms of 3D representations. HD cells fire as a function of the animal's directional heading in the horizontal plane, independent of the animal's location and on-going behavior. Another issue concerns whether HD cells are tuned in 3D space or tuned to the 2D horizontal plane. Shinder and Taube (Shinder ME, Taube JS. J Neurophysiol 121: 4-37, 2019) addressed this issue by manipulating a rat's orientation in 3D space while monitoring responses from classic HD cells in the rat anterodorsal thalamus. They reported that HD cells did not display conjunctive firing with pitch or roll orientations. Direction-specific firing was primarily derived from horizontal semicircular canal information and that the gravity vector played an important role in influencing the cell's firing rate and its preferred firing direction. Laurens and Angelaki (Laurens J, Angelaki DE. J Neurophysiol 122: 1274-1287, 2019) challenged this view by performing a mathematical analysis on the Shinder and Taube data and concluded that they would not have seen 3D tuning based on their experimental approach. We provide a historical review of these issues followed by a summary of the experiments, which includes additional analyses. We then define what it means for a HD cell to be tuned in 3D and finish by rebutting the reanalyses performed by Laurens and Angelaki.

Efficient and flexible representation of higher-dimensional cognitive variables with grid cells

We shed light on the potential of entorhinal grid cells to efficiently encode variables of dimension greater than two, while remaining faithful to empirical data on their low-dimensional structure. Our model constructs representations of high-dimensional inputs through a combination of low-dimensional random projections and "classical" low-dimensional hexagonal grid cell responses. Without reconfiguration of the recurrent circuit, the same system can flexibly encode multiple variables of different dimensions while maximizing the coding range (per dimension) by automatically trading-off dimension with an exponentially large coding range. It achieves high efficiency and flexibility by combining two powerful concepts, modularity and mixed selectivity, in what we call "mixed modular coding". In contrast to previously proposed schemes, the model does not require the formation of higher-dimensional grid responses, a cell-inefficient and rigid mechanism. The firing fields observed in flying bats or climbing rats can be generated by neurons that combine activity from multiple grid modules, each representing higher-dimensional spaces according to our model. The idea expands our understanding of grid cells, suggesting that they could implement a general circuit that generates on-demand coding and memory states for variables in high-dimensional vector spaces.

Commutative Properties of Head Direction Cells during Locomotion in 3D: Are All Routes Equal?

Navigation often requires movement in three-dimensional (3D) space. Recent studies have postulated two different models for how head direction (HD) cells encode 3D space: the rotational plane hypothesis and the dual-axis model. To distinguish these models, we recorded HD cells in female rats while they traveled different routes along both horizontal and vertical surfaces from an elevated platform to the top of a cuboidal apparatus. We compared HD cell preferred firing directions (PFDs) in different planes and addressed the issue of whether HD cell firing is commutative-does the order of the animal's route affect the final outcome of the cell's PFD? Rats locomoted a direct or indirect route from the floor to the cube top via one, two, or three vertical walls. Whereas the rotational plane hypothesis accounted for PFD shifts when the animal traversed horizontal corners, the cell's PFD was better explained by the dual-axis model when the animal traversed vertical corners. Responses also followed the dual-axis model (1) under dark conditions, (2) for passive movement of the rat, (3) following apparatus rotation, (4) for movement around inside vertical corners, and (5) across a 45° outside vertical corner. The order in which the animal traversed the different planes did not affect the outcome of the cell's PFD, indicating that responses were commutative. HD cell peak firing rates were generally equivalent along each surface. These findings indicate that the animal's orientation with respect to gravity plays an important role in determining a cell's PFD, and that vestibular and proprioceptive cues drive these computations.SIGNIFICANCE STATEMENT Navigating in a three-dimensional (3D) world is a complex task that requires one to maintain a proper sense of orientation relative to both local and global cues. Rodent head direction (HD) cells have been suggested to subserve this sense of orientation, but most HD cell studies have focused on navigation in 2D environments. We investigated the responses of HD cells as rats moved between multiple vertically and horizontally oriented planar surfaces, demonstrating that HD cells align their directional representations to both local (current plane of locomotion) and global (gravity) cues across several experimental conditions, including darkness and passive movement. These findings offer critical insights into the processing of 3D space in the mammalian brain.