Spatial cognition in bats and rats: from sensory acquisition to multiscale maps and navigation

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.

Unbiased analysis of spatial learning strategies in a modified Barnes maze using convolutional neural networks

Assessment of spatial learning abilities is central to behavioral neuroscience and a useful tool for animal model validation and drug development. However, biases introduced by the apparatus, environment, or experimentalist represent a critical challenge to the test validity. We have recently developed the Modified Barnes Maze (MBM) task, a spatial learning paradigm that overcomes inherent behavioral biases of animals in the classical Barnes maze. The specific combination of spatial strategies employed by mice is often considered representative of the level of cognitive resources used. Herein, we have developed a convolutional neural network-based classifier of exploration strategies in the MBM that can effectively provide researchers with enhanced insights into cognitive traits in mice. Following validation, we compared the learning performance of female and male C57BL/6J mice, as well as that of Ts65Dn mice, a model of Down syndrome, and 5xFAD mice, a model of Alzheimer's disease. Male mice exhibited more effective navigation abilities than female mice, reflected in higher utilization of effective spatial search strategies. Compared to wildtype controls, Ts65Dn mice exhibited delayed usage of spatial strategies despite similar success rates in completing this spatial task. 5xFAD mice showed increased usage of non-spatial strategies such as Circling that corresponded to higher latency to reach the target and lower success rate. These data exemplify the need for deeper strategy classification tools in dissecting complex cognitive traits. In sum, we provide a machine-learning-based strategy classifier that extends our understanding of mice's spatial learning capabilities while enabling a more accurate cognitive assessment.

Application of scaling to mouse spontaneous movement: Path curvature varies with speed and linear distance features isochrony

To conserve sequential behavior in relation to the topographic challenges of space, it is proposed that humans and nonhuman animals can organize behavior using different scaling principles. To deal with increases in linear distance, isochrony suggest that there is a corresponding increase in speed, whereas to deal with changes in curvature, speed is adjusted according to a power function. The present study investigates whether these principles provide a framework for describing the organization of mouse behavior in a variety of standard experimental tasks. The structure of movement was examined in ambulation during open field exploration; manipulation in a string-pulling task, in which a string is advanced hand over hand to retrieve food; and rung-walking, in which the limbs successively step from rung to rung on a horizontal ladder. Both principles were found to be conserved in the organization of mouse behavior across scales of movement. These principles provide novel measures of the temporal and geometric features of movement in the mouse and insights into how the temporal and geometric features of movement are conserved within different species.

The homogenous hippocampus: How hippocampal cells process available and potential goals

We present here a view of the firing patterns of hippocampal cells that is contrary, both functionally and anatomically, to conventional wisdom. We argue that the hippocampus responds to efference copies of goals encoded elsewhere; and that it uses these to detect and resolve conflict or interference between goals in general. While goals can involve space, hippocampal cells do not encode spatial (or other special types of) memory, as such. We also argue that the transverse circuits of the hippocampus operate in an essentially homogeneous way along its length. The apparently different functions of different parts (e.g. memory retrieval versus anxiety) result from the different (situational/motivational) inputs on which those parts perform the same fundamental computational operations. On this view, the key role of the hippocampus is the iterative adjustment, via Papez-like circuits, of synaptic weights in cell assemblies elsewhere.

Electrophysiological signatures of veridical head direction in humans

Information about heading direction is critical for navigation as it provides the means to orient ourselves in space. However, given that veridical head-direction signals require physical rotation of the head and most human neuroimaging experiments depend upon fixing the head in position, little is known about how the human brain is tuned to such heading signals. Here we adress this by asking 52 healthy participants undergoing simultaneous electroencephalography and motion tracking recordings (split into two experiments) and 10 patients undergoing simultaneous intracranial electroencephalography and motion tracking recordings to complete a series of orientation tasks in which they made physical head rotations to target positions. We then used a series of forward encoding models and linear mixed-effects models to isolate electrophysiological activity that was specifically tuned to heading direction. We identified a robust posterior central signature that predicts changes in veridical head orientation after regressing out confounds including sensory input and muscular activity. Both source localization and intracranial analysis implicated the medial temporal lobe as the origin of this effect. Subsequent analyses disentangled head-direction signatures from signals relating to head rotation and those reflecting location-specific effects. Lastly, when directly comparing head direction and eye-gaze-related tuning, we found that the brain maintains both codes while actively navigating, with stronger tuning to head direction in the medial temporal lobe. Together, these results reveal a taxonomy of population-level head-direction signals within the human brain that is reminiscent of those reported in the single units of rodents.

Spindle-locked ripples mediate memory reactivation during human NREM sleep

Memory consolidation relies in part on the reactivation of previous experiences during sleep. The precise interplay of sleep-related oscillations (slow oscillations, spindles and ripples) is thought to coordinate the information flow between relevant brain areas, with ripples mediating memory reactivation. However, in humans empirical evidence for a role of ripples in memory reactivation is lacking. Here, we investigated the relevance of sleep oscillations and specifically ripples for memory reactivation during human sleep using targeted memory reactivation. Intracranial electrophysiology in epilepsy patients and scalp EEG in healthy participants revealed that elevated levels of slow oscillation - spindle activity coincided with the read-out of experimentally induced memory reactivation. Importantly, spindle-locked ripples recorded intracranially from the medial temporal lobe were found to be correlated with the identification of memory reactivation during non-rapid eye movement sleep. Our findings establish ripples as key-oscillation for sleep-related memory reactivation in humans and emphasize the importance of the coordinated interplay of the cardinal sleep oscillations.

Clutter resilience via auditory stream segregation in echolocating greater mouse-eared bats

Bats use echolocation to navigate and hunt in darkness, and must in that process segregate target echoes from unwanted clutter echoes. Bats may do this by approaching a target at steep angles relative to the plane of the background, utilizing their directional transmission and receiving systems to minimize clutter from background objects, but it remains unknown how bats negotiate clutter that cannot be spatially avoided. Here, we tested the hypothesis that when movement no longer offers spatial release, echolocating bats mitigate clutter by calling at lower source levels and longer call intervals to ease auditory streaming. We trained five greater mouse-eared bats (Myotis myotis) to land on a spherical loudspeaker with two microphones attached. We used a phantom-echo setup, where the loudspeaker/target transmitted phantom clutter echoes by playing back the bats' own calls at time delays of 1, 3 and 5 ms with a virtual target strength 7 dB higher than the physical target. We show that the bats successfully landed on the target, irrespective of the clutter echo delays. Rather than decreasing their source levels, the bats used similar source level distributions in clutter and control trials. Similarly, the bats did not increase their call intervals, but instead used the same distribution of call intervals across control and clutter trials. These observations reject our hypothesis, leading us to conclude that bats display great resilience to clutter via short auditory integration times and acute auditory stream segregation rather than via biosonar adjustments.

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.

A perspective on neuroethology: what the past teaches us about the future of neuroethology

For 100 years, the Journal of Comparative Physiology-A has significantly supported research in the field of neuroethology. The celebration of the journal's centennial is a great time point to appreciate the recent progress in neuroethology and to discuss possible avenues of the field. Animal behavior is the main source of inspiration for neuroethologists. This is illustrated by the huge diversity of investigated behaviors and species. To explain behavior at a mechanistic level, neuroethologists combine neuroscientific approaches with sophisticated behavioral analysis. The rapid technological progress in neuroscience makes neuroethology a highly dynamic and exciting field of research. To summarize the recent scientific progress in neuroethology, I went through all abstracts of the last six International Congresses for Neuroethology (ICNs 2010-2022) and categorized them based on the sensory modalities, experimental model species, and research topics. This highlights the diversity of neuroethology and gives us a perspective on the field's scientific future. At the end, I highlight three research topics that may, among others, influence the future of neuroethology. I hope that sharing my roots may inspire other scientists to follow neuroethological approaches.

Parametric Amplification of Acoustically Actuated Micro Beams Using Fringing Electrostatic Fields

We report on theoretical and experimental investigation of parametric amplification of acoustically excited vibrations in micromachined single-crystal silicon cantilevers electrostatically actuated by fringing fields. The device dynamics are analyzed using the Mathieu-Duffing equation, obtained using the Galerkin order reduction technique. Our experimental results show that omnidirectional acoustic pressure used as a noncontact source for linear harmonic driving is a convenient and versatile tool for the mechanical dynamic characterization of unpackaged, nonintegrated microstructures. The fringing field's electrostatic actuation allows for efficient parametric amplification of an acoustic signal. The suggested amplification approach may have applications in a wide variety of micromechanical devices, including resonant sensors, microphones and microphone arrays, and hearing aids. It can be used also for upward frequency tuning.

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.

Active oscillations in microscale navigation

Living organisms routinely navigate their surroundings in search of better conditions, more food, or to avoid predators. Typically, animals do so by integrating sensory cues from the environment with their locomotor apparatuses. For single cells or small organisms that possess motility, fundamental physical constraints imposed by their small size have led to alternative navigation strategies that are specific to the microscopic world. Intriguingly, underlying these myriad exploratory behaviours or sensory functions is the onset of periodic activity at multiple scales, such as the undulations of cilia and flagella, the vibrations of hair cells, or the oscillatory shape modes of migrating neutrophils. Here, I explore oscillatory dynamics in basal microeukaryotes and hypothesize that these active oscillations play a critical role in enhancing the fidelity of adaptive sensorimotor integration.

Neural representation of goal direction in the monarch butterfly brain

Neural processing of a desired moving direction requires the continuous comparison between the current heading and the goal direction. While the neural basis underlying the current heading is well-studied, the coding of the goal direction remains unclear in insects. Here, we used tetrode recordings in tethered flying monarch butterflies to unravel how a goal direction is represented in the insect brain. While recording, the butterflies maintained robust goal directions relative to a virtual sun. By resetting their goal directions, we found neurons whose spatial tuning was tightly linked to the goal directions. Importantly, their tuning was unaffected when the butterflies changed their heading after compass perturbations, showing that these neurons specifically encode the goal direction. Overall, we here discovered invertebrate goal-direction neurons that share functional similarities to goal-direction cells reported in mammals. Our results give insights into the evolutionarily conserved principles of goal-directed spatial orientation in animals.

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.

Using multi-task experiments to test principles of hippocampal function

Investigations of hippocampal functions have revealed a dizzying array of findings, from lesion-based behavioral deficits, to a diverse range of characterized neural activations, to computational models of putative functionality. Across these findings, there remains an ongoing debate about the core function of the hippocampus and the generality of its representation. Researchers have debated whether the hippocampus's primary role relates to the representation of space, the neural basis of (episodic) memory, or some more general computation that generalizes across various cognitive domains. Within these different perspectives, there is much debate about the nature of feature encodings. Here, we suggest that in order to evaluate hippocampal responses-investigating, for example, whether neuronal representations are narrowly targeted to particular tasks or if they subserve domain-general purposes-a promising research strategy may be the use of multi-task experiments, or more generally switching between multiple task contexts while recording from the same neurons in a given session. We argue that this strategy-when combined with explicitly defined theoretical motivations that guide experiment design-could be a fruitful approach to better understand how hippocampal representations support different behaviors. In doing so, we briefly review key open questions in the field, as exemplified by articles in this special issue, as well as previous work using multi-task experiments, and extrapolate to consider how this strategy could be further applied to probe fundamental questions about hippocampal function.

Neuronal circuits within the homing pigeon hippocampal formation

The current study aimed to reveal in detail patterns of intrahippocampal connectivity in homing pigeons (Columba livia). In light of recent physiological evidence suggesting differences between dorsomedial and ventrolateral hippocampal regions and a hitherto unknown laminar organization along the transverse axis, we also aimed to gain a higher-resolution understanding of the proposed pathway segregation. Both in vivo and high-resolution in vitro tracing techniques were employed and revealed a complex connectivity pattern along the subdivisions of the avian hippocampus. We uncovered connectivity pathways along the transverse axis that started in the dorsolateral hippocampus and continued to the dorsomedial subdivision, from where information was relayed to the triangular region either directly or indirectly via the V-shaped layers. The often-reciprocal connectivity along these subdivisions displayed an intriguing topographical arrangement such that two parallel pathways could be discerned along the ventrolateral (deep) and dorsomedial (superficial) aspects of the avian hippocampus. The segregation along the transverse axis was further supported by expression patterns of the glial fibrillary acidic protein and calbindin. Moreover, we found strong expression of Ca²⁺ /calmodulin-dependent kinase IIα and doublecortin in the lateral but not medial V-shape layer, indicating a difference between the two V-shaped layers. Overall, our findings provide an unprecedented, detailed description of avian intrahippocampal pathway connectivity, and confirm the recently proposed segregation of the avian hippocampus along the transverse axis. We also provide further support for the hypothesized homology of the lateral V-shape layer and the dorsomedial hippocampus with the dentate gyrus and Ammon's horn of mammals, respectively.

Generalization of navigation memory in honeybees

Flying insects like the honeybee learn multiple features of the environment for efficient navigation. Here we introduce a novel paradigm in the natural habitat, and ask whether the memory of such features is generalized to novel test conditions. Foraging bees from colonies located in 5 different home areas were tested in a common area for their search flights. The home areas differed in the arrangements of rising natural objects or their lack, and in the existence or lack of elongated ground structures. The test area resembled partly or not at all the layout of landmarks in the respective home areas. In particular, the test area lacked rising objects. The search flights were tracked with harmonic radar and quantified by multiples procedures, extracting their differences on an individual basis. Random search as the only guide for searching was excluded by two model calculations. The frequencies of directions of flight sectors differed from both model calculations and between the home areas in a graded fashion. Densities of search flight fixes were used to create heat maps and classified by a partial least squares regression analysis. Classification was performed with a support vector machine in order to account for optimal hyperplanes. A rank order of well separated clusters was found that partly resemble the graded differences between the ground structures of the home areas and the test area. The guiding effect of elongated ground structures was quantified with respect to the sequence, angle and distance from these ground structures. We conclude that foragers generalize their specific landscape memory in a graded way to the landscape features in the test area, and argue that both the existence and absences of landmarks are taken into account. The conclusion is discussed in the context of the learning and generalization process in an insect, the honeybee, with an emphasis on exploratory learning in the context of navigation.

Effects of neuromodulation-inspired mechanisms on the performance of deep neural networks in a spatial learning task

In recent years, the biological underpinnings of adaptive learning have been modeled, leading to faster model convergence and various behavioral benefits in tasks including spatial navigation and cue-reward association. Furthermore, studies have investigated how the neuromodulatory system, a major driver of synaptic plasticity and state-dependent changes in the brain neuronal activities, plays a role in training deep neural networks (DNNs). In this study, we extended previous studies on neuromodulation-inspired DNNs and explored the effects of neuromodulatory components on learning and single unit activities in a spatial learning task. Under the multiscale neuromodulatory framework, plastic components, dropout probability modulation, and learning rate decay were added to the single unit, layer, and whole network levels of DNN models, respectively. We observed behavioral benefits including faster learning and smaller error of ambulation. We then concluded that neuromodulatory components can affect learning trajectories, outcomes, and single unit activities, in a component- and hyperparameter-dependent manner.

Modularity in Nervous Systems—a Key to Efficient Adaptivity for Deep Reinforcement Learning

Modularity as observed in biological systems has proven valuable for guiding classical motor theories towards good answers about action selection and execution. New challenges arise when we turn to learning: Trying to scale current computational models, such as deep reinforcement learning (DRL), to action spaces, input dimensions, and time horizons seen in biological systems still faces severe obstacles unless vast amounts of training data are available. This leads to the question: does biological modularity also hold an important key for better answers to obtain efficient adaptivity for deep reinforcement learning? We review biological experimental work on modularity in biological motor control and link this with current examples of (deep) RL approaches. Analyzing outcomes of simulation studies, we show that these approaches benefit from forms of modularization as found in biological systems. We identify three different strands of modularity exhibited in biological control systems. Two of them—modularity in state (i) and in action (ii) spaces—appear as a consequence of local interconnectivity (as in reflexes) and are often modulated by higher levels in a control hierarchy. A third strand arises from chunking of action elements along a (iii) temporal dimension. Usually interacting in an overarching spatio-temporal hierarchy of the overall system, the three strands offer major “factors” decomposing the entire modularity structure. We conclude that modularity with its above strands can provide an effective prior for DRL approaches to speed up learning considerably and making learned controllers more robust and adaptive.

A brainstem integrator for self-location memory and positional homeostasis in zebrafish

To track and control self-location, animals integrate their movements through space. Representations of self-location are observed in the mammalian hippocampal formation, but it is unknown if positional representations exist in more ancient brain regions, how they arise from integrated self-motion, and by what pathways they control locomotion. Here, in a head-fixed, fictive-swimming, virtual-reality preparation, we exposed larval zebrafish to a variety of involuntary displacements. They tracked these displacements and, many seconds later, moved toward their earlier location through corrective swimming ("positional homeostasis"). Whole-brain functional imaging revealed a network in the medulla that stores a memory of location and induces an error signal in the inferior olive to drive future corrective swimming. Optogenetically manipulating medullary integrator cells evoked displacement-memory behavior. Ablating them, or downstream olivary neurons, abolished displacement corrections. These results reveal a multiregional hindbrain circuit in vertebrates that integrates self-motion and stores self-location to control locomotor behavior.

Frames of reference in small-scale spatial tasks in wild bumblebees

Spatial cognitive abilities are fundamental to foraging animal species. In particular, being able to encode the location of an object in relation to another object (i.e., spatial relationships) is critical for successful foraging. Whether egocentric (i.e., viewer-dependent) or allocentric (i.e., dependent on external environment or cues) representations underlie these behaviours is still a highly debated question in vertebrates and invertebrates. Previous research shows that bees encode spatial information largely using egocentric information. However, no research has investigated this question in the context of relational similarity. To test this, a spatial matching task previously used with humans and great apes was adapted for use with wild-caught bumblebees. In a series of experiments, bees first experienced a rewarded object and then had to spontaneously (Experiment 1) find or learn (Experiments 2 and 3) to find a second one, based on the location of first one. The results showed that bumblebees predominantly exhibited an allocentric strategy in the three experiments. These findings suggest that egocentric representations alone might not be evolutionary ancestral and clearly indicate similarities between vertebrates and invertebrates when encoding spatial information.

Cognition of the manatee: past research and future developments

In this paper, we present a review of the current knowledge related to the cognitive abilities of the manatee, with a focus on the Antillean manatee in situ and ex situ. Following a biocentric approach, we consider the animals' ecology, perception and sociality and we introduce future perspectives on their cognition. Scientific literature on the cognitive abilities of Antillean manatees' is limited and mainly linked to medical training and veterinary manipulations. To perceive and to interact with their social and natural environment (e.g. social interactions, foraging and traveling), manatees use visual, acoustic and tactile modalities that may be involved in a large range of cognitive abilities. Research on stimuli perception in manatees is scarce; however, these animals demonstrate abilities to learn and appear to show long-term memory. For example, to mate and/or to forage manatees travel at medium and large geographical scales; without doubt their movements entail the use of a set of stimuli and learning processes. Furthermore, their social skills (e.g. social organization, tactile and acoustic communications) are also poorly understood although their social interactions appear to be more complex than previously thought. Finally, as for many animals, temperament/personality may play a key role during their interactions with conspecifics and the environment. These aspects on manatee behavior and cognition are important for management and conservation purposes and help us understand the evolution of these marine mammals.

Single-neuron detection of place cells remapping in short-term memory using motion microelectrode arrays

Place cells establish rapid mapping relationships between the external environment and themselves in a new context. However, the mapping relationships of environmental cues to place cells in short-term memory is still completely unknown. In this work, we designed a silicon-based motion microelectrode array (mMEA) and an implantation device to record electrophysiological signals of place cells in CA1, CA3, and DG regions in the hippocampus of ten mice in motion, and investigated the corresponding place fields under distal or local cues in just a few minutes. The mMEA can expand the detection area and greatly lower the motion noise. Finding and recording place cells of moving mice in short-term memory is made possible by the mMEA. The place-related cells were found for the first time. Unlike place cells, which only fire in a particular position of the environment, place-related cells fire in numerous areas of the environment. Furthermore, place cells in the CA1 and CA3 have the most stable place memory for time-preferred single cues, and they fire in concert with place-related cells during short-term memory dynamics, whereas place cells in the DG regions have overlapping and unstable place memory in a multi-cue context. These results demonstrate the consistency of place cells in CA1 and CA3 and reflect their different roles in spatial memory processing during familiarization with new environments. The mMEA provides a platform for studying the place cells of short-term memory.

Age-related changes in the organization of spontaneously occurring behaviors

Age-related changes in spatial and temporal processing have been documented across a range of species. Rodent studies typically investigate differences in performance between adult and senescent animals; however, progressive loss of neurons in the hippocampus and cortex has been observed to occur as early as after adolescence. Therefore, the current study evaluated the effects of age in three- and ten-month-old female rats on the organization of movement in open field and food protection behaviors, two tasks that have previously dissociated hippocampal and cortical pathology. Age-related differences were observed in general measures of locomotion, spatial orientation, and attentional processing. The results of the current study are consistent with age-related changes in the processing of spatial information and motivation that occur earlier in life than previously anticipated. These observations establish a foundation for future studies evaluating interventions that influence these age-related differences in performance.

Natural switches in behaviour rapidly modulate hippocampal coding

Throughout their daily lives, animals and humans often switch between different behaviours. However, neuroscience research typically studies the brain while the animal is performing one behavioural task at a time, and little is known about how brain circuits represent switches between different behaviours. Here we tested this question using an ethological setting: two bats flew together in a long 135 m tunnel, and switched between navigation when flying alone (solo) and collision avoidance as they flew past each other (cross-over). Bats increased their echolocation click rate before each cross-over, indicating attention to the other bat^1–9. Hippocampal CA1 neurons represented the bat’s own position when flying alone (place coding^10–14). Notably, during cross-overs, neurons switched rapidly to jointly represent the interbat distance by self-position. This neuronal switch was very fast—as fast as 100 ms—which could be revealed owing to the very rapid natural behavioural switch. The neuronal switch correlated with the attention signal, as indexed by echolocation. Interestingly, the different place fields of the same neuron often exhibited very different tuning to interbat distance, creating a complex non-separable coding of position by distance. Theoretical analysis showed that this complex representation yields more efficient coding. Overall, our results suggest that during dynamic natural behaviour, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.

During rapid behavioural switches in flying bats, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.

Encore: Behavioural animal models of stress, depression and mood disorders

Animal studies over the past two decades have led to extensive advances in our understanding of pathogenesis of depressive and mood disorders. Among these, rodent behavioural models proved to be of highest informative value. Here, we present a comprehensive overview of the most popular behavioural models with respect to physiological, circuit, and molecular biological correlates. Behavioural stress paradigms and behavioural tests are assessed in terms of outcomes, strengths, weaknesses, and translational value, especially in the domain of pharmacological studies.

Neural network based successor representations to form cognitive maps of space and language

How does the mind organize thoughts? The hippocampal-entorhinal complex is thought to support domain-general representation and processing of structural knowledge of arbitrary state, feature and concept spaces. In particular, it enables the formation of cognitive maps, and navigation on these maps, thereby broadly contributing to cognition. It has been proposed that the concept of multi-scale successor representations provides an explanation of the underlying computations performed by place and grid cells. Here, we present a neural network based approach to learn such representations, and its application to different scenarios: a spatial exploration task based on supervised learning, a spatial navigation task based on reinforcement learning, and a non-spatial task where linguistic constructions have to be inferred by observing sample sentences. In all scenarios, the neural network correctly learns and approximates the underlying structure by building successor representations. Furthermore, the resulting neural firing patterns are strikingly similar to experimentally observed place and grid cell firing patterns. We conclude that cognitive maps and neural network-based successor representations of structured knowledge provide a promising way to overcome some of the short comings of deep learning towards artificial general intelligence.

Unexpected Consequences of Noise-Induced Hearing Loss: Impaired Hippocampal Neurogenesis, Memory, and Stress

Noise-induced hearing loss (NIHL), caused by direct damage to the cochlea, reduces the flow of auditory information to the central nervous system, depriving higher order structures, such as the hippocampus with vital sensory information needed to carry out complex, higher order functions. Although the hippocampus lies outside the classical auditory pathway, it nevertheless receives acoustic information that influence its activity. Here we review recent results that illustrate how NIHL and other types of cochlear hearing loss disrupt hippocampal function. The hippocampus, which continues to generate new neurons (neurogenesis) in adulthood, plays an important role in spatial navigation, memory, and emotion. The hippocampus, which contains place cells that respond when a subject enters a specific location in the environment, integrates information from multiple sensory systems, including the auditory system, to develop cognitive spatial maps to aid in navigation. Acute exposure to intense noise disrupts the place-specific firing patterns of hippocampal neurons, "spatially disorienting" the cells for days. More traumatic sound exposures that result in permanent NIHL chronically suppresses cell proliferation and neurogenesis in the hippocampus; these structural changes are associated with long-term spatial memory deficits. Hippocampal neurons, which contain numerous glucocorticoid hormone receptors, are part of a complex feedback network connected to the hypothalamic-pituitary (HPA) axis. Chronic exposure to intense intermittent noise results in prolonged stress which can cause a persistent increase in corticosterone, a rodent stress hormone known to suppress neurogenesis. In contrast, a single intense noise exposure sufficient to cause permanent hearing loss produces only a transient increase in corticosterone hormone. Although basal corticosterone levels return to normal after the noise exposure, glucocorticoid receptors (GRs) in the hippocampus remain chronically elevated. Thus, NIHL disrupts negative feedback from the hippocampus to the HPA axis which regulates the release of corticosterone. Preclinical studies suggest that the noise-induced changes in hippocampal place cells, neurogenesis, spatial memory, and glucocorticoid receptors may be ameliorated by therapeutic interventions that reduce oxidative stress and inflammation. These experimental results may provide new insights on why hearing loss is a risk factor for cognitive decline and suggest methods for preventing this decline.

A stable hippocampal code in freely flying bats

Neural activity in the hippocampus is known to reflect how animals move through an environment1,2. Although navigational behaviour may show considerable stability3-6, the tuning stability of individual hippocampal neurons remains unclear7-12. Here we used wireless calcium imaging to longitudinally monitor the activity of dorsal CA1 hippocampal neurons in freely flying bats performing highly reproducible flights in a familiar environment. We find that both the participation and the spatial selectivity of most neurons remain stable over days and weeks. We also find that apparent changes in tuning can be largely attributed to variations in the flight behaviour of the bats. Finally, we show that bats navigating in the same environment under different room lighting conditions (lights on versus lights off) exhibit substantial changes in flight behaviour that can give the illusion of neuronal instability. However, when similar flight paths are compared across conditions, the stability of the hippocampal code persists. Taken together, we show that the underlying hippocampal code is highly stable over days and across contexts if behaviour is taken into account.

Running away or running to? Do prey make decisions solely based on the landscape of fear or do they also include stimuli from a landscape of safety?

Predator-prey interactions are a key part of ecosystem function, and non-consumptive effects fall under the landscape of fear theory. Under the landscape of fear, the antipredator responses of prey are based on the spatial and temporal distribution of predatory cues in the environment. However, the aversive stimuli (fear) are not the only stimuli prey can utilize when making behavioral decisions. Prey might also be using attractive stimuli that represent safety to guide decision making. Using a novel, orthogonal design, we were able to spatially separate aversive and attractive stimuli to determine whether prey are utilizing safety cues to navigate their environment. Crayfish Faxonius rusticus were placed in the center of a behavioral arena. Aversive stimuli of either predatory bass Micropterus salmoides cues or conspecific alarm cues increased along the x-axis of the behavioral arena. Safety cues (shelters) increased along the y-axis by decreasing the number of shelter openings in this direction. Crayfish were allowed two phases to explore the arena: one without the fearful stimuli and one with the stimuli. Linear mixed models were conducted to determine whether movement behaviors and habitat utilization were affected by the phase of the trial and the type of aversive stimuli. Crayfish responded more strongly to alarm cues than to fear cues, with only alarm cues significantly impacting habitat utilization. When responding to alarm cues, crayfish used safety cues as well as fear cues to relocate themselves within the arena. Based on these results, we argue that crayfish utilize a landscape of safety in conjunction with a landscape of fear when navigating their environment.

Using your nose to find your way: Ethological comparisons between human and non-human species

Olfaction is arguably the least valued among our sensory systems, and its significance for human behavior is often neglected. Spatial navigation represents no exception to the rule: humans are often characterized as purely visual navigators, a view that undermines the contribution of olfactory cues. Accordingly, research investigating whether and how humans use olfaction to navigate space is rare. In comparison, research on olfactory navigation in non-human species is abundant, and identifies behavioral strategies along with neural mechanisms characterizing the use of olfactory cues during spatial tasks. Using an ethological approach, our review draws from studies on olfactory navigation across species to describe the adaptation of strategies under the influence of selective pressure. Mammals interact with spatial environments by abstracting multisensory information into cognitive maps. We thus argue that olfactory cues, alongside inputs from other sensory modalities, play a crucial role in spatial navigation for mammalian species, including humans; that is, odors constitute one of the many building blocks in the formation of cognitive maps.

Bio-Inspired Approach for Long-Range Underwater Navigation Using Model Predictive Control

Lots of evidence has indicated that many kinds of animals can achieve goal-oriented navigation by spatial cognition and dead reckoning. The geomagnetic field (GF) is a ubiquitous cue for navigation by these animals. Inspired by the goal-oriented navigation of animals, a novel long-distance underwater geomagnetic navigation (LDUGN) method is presented in this article, which only utilizes the declination component ( D ) and inclination component ( I ) of GF for underwater navigation without any prior knowledge of the geographical location or geomagnetic map. The D and I measured by high-precision geomagnetic sensors are compared periodically with that of the destination to determine the velocity and direction in the next step. A model predictive control (MPC) algorithm with control and state constraints is proposed to achieve the control and optimization of navigation trajectory. Because the optimal control is recalculated at each sampling instant, the MPC algorithm can overcome interferences of geomagnetic daily fluctuation, geomagnetic storms, ocean current, and geomagnetic local anomaly. The simulation results validate the feasibility and accuracy of the proposed algorithm.

Spatial information transfer in hippocampal place cells depends on trial-to-trial variability, symmetry of place-field firing, and biophysical heterogeneities

The relationship between the feature-tuning curve and information transfer profile of individual neurons provides vital insights about neural encoding. However, the relationship between the spatial tuning curve and spatial information transfer of hippocampal place cells remains unexplored. Here, employing a stochastic search procedure spanning thousands of models, we arrived at 127 conductance-based place-cell models that exhibited signature electrophysiological characteristics and sharp spatial tuning, with parametric values that exhibited neither clustering nor strong pairwise correlations. We introduced trial-to-trial variability in responses and computed model tuning curves and information transfer profiles, using stimulus-specific (SSI) and mutual (MI) information metrics, across locations within the place field. We found spatial information transfer to be heterogeneous across models, but to reduce consistently with increasing levels of variability. Importantly, whereas reliable low-variability responses implied that maximal information transfer occurred at high-slope regions of the tuning curve, increase in variability resulted in maximal transfer occurring at the peak-firing location in a subset of models. Moreover, experience-dependent asymmetry in place-field firing introduced asymmetries in the information transfer computed through MI, but not SSI, and the impact of activity-dependent variability on information transfer was minimal compared to activity-independent variability. We unveiled ion-channel degeneracy in the regulation of spatial information transfer, and demonstrated critical roles for N-methyl-d-aspartate receptors, transient potassium and dendritic sodium channels in regulating information transfer. Our results demonstrate that trial-to-trial variability, tuning-curve shape and biological heterogeneities critically regulate the relationship between the spatial tuning curve and spatial information transfer in hippocampal place cells.

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.

NLM-HS: Navigation Learning Model Based on a Hippocampal-Striatal Circuit for Explaining Navigation Mechanisms in Animal Brains

Neurophysiological studies have shown that the hippocampus, striatum, and prefrontal cortex play different roles in animal navigation, but it is still less clear how these structures work together. In this paper, we establish a navigation learning model based on the hippocampal-striatal circuit (NLM-HS), which provides a possible explanation for the navigation mechanism in the animal brain. The hippocampal model generates a cognitive map of the environment and performs goal-directed navigation by using a place cell sequence planning algorithm. The striatal model performs reward-related habitual navigation by using the classic temporal difference learning algorithm. Since the two models may produce inconsistent behavioral decisions, the prefrontal cortex model chooses the most appropriate strategies by using a strategy arbitration mechanism. The cognitive and learning mechanism of the NLM-HS works in two stages of exploration and navigation. First, the agent uses a hippocampal model to construct the cognitive map of the unknown environment. Then, the agent uses the strategy arbitration mechanism in the prefrontal cortex model to directly decide which strategy to choose. To test the validity of the NLM-HS, the classical Tolman detour experiment was reproduced. The results show that the NLM-HS not only makes agents show environmental cognition and navigation behavior similar to animals, but also makes behavioral decisions faster and achieves better adaptivity than hippocampal or striatal models alone.

Multiscale representation of very large environments in the hippocampus of flying bats

Hippocampal place cells encode the animal's location. Place cells were traditionally studied in small environments, and nothing is known about large ethologically relevant spatial scales. We wirelessly recorded from hippocampal dorsal CA1 neurons of wild-born bats flying in a long tunnel (200 meters). The size of place fields ranged from 0.6 to 32 meters. Individual place cells exhibited multiple fields and a multiscale representation: Place fields of the same neuron differed up to 20-fold in size. This multiscale coding was observed from the first day of exposure to the environment, and also in laboratory-born bats that never experienced large environments. Theoretical decoding analysis showed that the multiscale code allows representation of very large environments with much higher precision than that of other codes. Together, by increasing the spatial scale, we discovered a neural code that is radically different from classical place codes.

Avian navigation: Head direction cells in the quail hippocampus

Birds are experts in many behaviors akin to those in mammals that are known to involve the hippocampus, yet the avian hippocampus is still poorly understood. A new study finds head-direction cells, but not place cells, in the hippocampal formation of quails.

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.

Directional tuning in the hippocampal formation of birds

Birds strongly rely on spatial memory and navigation. Therefore, it is of utmost interest to reveal how space is represented in the avian brain. Here we used tetrodes to record neurons from the hippocampal formation of Japanese quails-a ground-dwelling species-while the quails roamed in an open-field arena. Whereas spatially modulated cells (place cells, grid cells, border cells) were generally not encountered, the firing rate of about 12% of the neurons was unimodally and significantly modulated by the head azimuth-i.e., these were head-direction cells (HD cells). Typically, HD cells were maximally active at one preferred direction and minimally at the opposite null direction, with preferred directions spanning all 360° across the population. The preferred direction was independent of the animal's position and speed and was stable during the recording session. The HD tuning was broader compared to that of HD cells in rodents, and most cells had non-zero baseline firing in all directions. However, similar to findings in rodents, the HD tuning usually rotated with the rotation of a salient visual cue in the arena. Thus, these findings support the existence of an allocentric HD representation in the quail hippocampal formation and provide the first demonstration of HD cells in birds.

In situ novel environment assay reveals acoustic exploration as a repeatable behavioral response in migratory bats

Integrating information on species-specific sensory perception with spatial activity provides a high-resolution understanding of how animals explore environments, yet frequently used exploration assays commonly ignore sensory acquisition as a measure for exploration. Echolocation is an active sensing system used by hundreds of mammal species, primarily bats. As echolocation call activity can be reliably quantified, bats present an excellent model system to investigate intraspecific variation in environmental cue sampling. Here, we developed an in situ roost-like novel environment assay for tree-roosting bats. We repeatedly tested 52 individuals of the migratory bat species, Pipistrellus nathusii, across 24 h, to examine the role of echolocation when crawling through a maze-type arena and test for consistent intraspecific variation in sensory-based exploration. We reveal a strong correlation between echolocation call activity and spatial activity. Moreover, we show that during the exploration of the maze, individuals consistently differed in spatial activity as well as echolocation call activity, given their spatial activity, a behavioral response we term 'acoustic exploration'. Acoustic exploration was correlated with other exploratory behaviors, but not with emergence latency. We here present a relevant new measure for exploration behavior and provide evidence for consistent (short-term) intra-specific variation in the level at which wild bats collect information from a novel environment.

What are grid-like responses doing in the orbitofrontal cortex?

In 2005, the Moser group identified a new type of cell in the entorhinal cortex (ERC): the grid cell (Hafting, Nature, 436, 2005, pp. 801-806). A landmark series of studies from these investigators showed that grid cells support spatial navigation by encoding position, direction as well as distance information, and they subsequently found grid cells in pre- and para-subiculum areas adjacent to the ERC (Boccara, Nature Neuroscience, 13, 2010, pp. 987-994). Fast forward to 2010, when some clever investigators developed fMRI analysis methods to document grid-like responses in the human ERC (Doeller, Nature, 463, 2010, pp. 657-661). What was not at all expected was the co-identification of grid-like fMRI responses outside of the ERC, in particular, the orbitofrontal cortex (OFC) and the ventromedial prefrontal cortex (vmPFC). Here we provide a compact overview of the burgeoning literature on grid cells in both rodent and human species, while considering the intriguing question: what are grid-like responses doing in the OFC and vmPFC? (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Place Cells in Head-Fixed Mice Navigating a Floating Real-World Environment

The hippocampal place cell system in rodents has provided a major paradigm for the scientific investigation of memory function and dysfunction. Place cells have been observed in area CA1 of the hippocampus of both freely moving animals, and of head-fixed animals navigating in virtual reality environments. However, spatial coding in virtual reality preparations has been observed to be impaired. Here we show that the use of a real-world environment system for head-fixed mice, consisting of an air-floating track with proximal cues, provides some advantages over virtual reality systems for the study of spatial memory. We imaged the hippocampus of head-fixed mice injected with the genetically encoded calcium indicator GCaMP6s while they navigated circularly constrained or open environments on the floating platform. We observed consistent place tuning in a substantial fraction of cells despite the absence of distal visual cues. Place fields remapped when animals entered a different environment. When animals re-entered the same environment, place fields typically remapped over a time period of multiple days, faster than in freely moving preparations, but comparable with virtual reality. Spatial information rates were within the range observed in freely moving mice. Manifold analysis indicated that spatial information could be extracted from a low-dimensional subspace of the neural population dynamics. This is the first demonstration of place cells in head-fixed mice navigating on an air-lifted real-world platform, validating its use for the study of brain circuits involved in memory and affected by neurodegenerative disorders.

The fully automated bat (FAB) flight room: A human-free environment for studying navigation in flying bats and its initial application to the retrosplenial cortex

BACKGROUND

Bats can offer important insight into the neural computations underlying complex forms of navigation. Up to now, this had been done with the confound of the human experimenter being present in the same environment the bat was navigating in.

NEW METHOD

We, therefore, developed a novel behavioral setup, the fully automated bat (FAB) flight room, to obtain a detailed and quantitative understanding of bat navigation flight behavior while studying its relevant neural circuits, but importantly without human intervention. As a demonstration of the FAB flight room utility we trained bats on a four-target, visually-guided, foraging task and recorded neural activity from the retrosplenial cortex (RSC).

RESULTS

We find that bats can be efficiently trained and engaged in complex, multi-target, visuospatial behavior in the FAB flight room. Wireless neural recordings from the bat RSC during the task confirm the multiplexed characteristics of single RSC neurons encoding spatial positional information, target selection, reward obtainment and the intensity of visual cues used to guide navigation.

COMPARISON WITH EXISTING METHODS

In contrast to the methods introduced in previous studies, we now can investigate spatial navigation in bats without potential experimental biases that can be easily introduced by active physical involvement and presence of experimenters in the room.

CONCLUSIONS

Combined, we describe a novel experimental approach for studying spatial navigation in freely flying bats and provide support for the involvement of bat RSC in aerial visuospatial foraging behavior.

Multi-Scale Extension in an Entorhinal-Hippocampal Model for Cognitive Map Building

Neuroscience research shows that, by relying on internal spatial representations provided by the hippocampus and entorhinal cortex, mammals are able to build topological maps of environments and navigate. Taking inspiration from mammals' spatial cognition mechanism, entorhinal-hippocampal cognitive systems have been proposed for robots to build cognitive maps. However, path integration and vision processing are time-consuming, and the existing model of grid cells is hard to achieve in terms of adaptive multi-scale extension for different environments, resulting in the lack of viability for real environments. In this work, an optimized dynamical model of grid cells is built for path integration in which recurrent weight connections between grid cells are parameterized in a more optimized way and the non-linearity of sigmoidal neural transfer function is utilized to enhance grid cell activity packets. Grid firing patterns with specific spatial scales can thus be accurately achieved for the multi-scale extension of grid cells. In addition, a hierarchical vision processing mechanism is proposed for speeding up loop closure detection. Experiment results on the robotic platform demonstrate that our proposed entorhinal-hippocampal model can successfully build cognitive maps, reflecting the robot's spatial experience and environmental topological structures.

Navigating in a challenging semiarid environment: the use of a route-based mental map by a small-bodied neotropical primate

To increase efficiency in the search for resources, many animals rely on their spatial abilities. Specifically, primates have been reported to use mostly topological and rarely Euclidean maps when navigating in large-scale space. Here, we aimed to investigate if the navigation of wild common marmosets inhabiting a semiarid environment is consistent with a topological representation and how environmental factors affect navigation. We collected 497 h of direct behavioral and GPS information on a group of marmosets using a 2-min instantaneous focal animal sampling technique. We found that our study group reused not only long-route segments (mean of 1007 m) but entire daily routes, a pattern that is not commonly seen in primates. The most frequently reused route segments were the ones closer to feeding sites, distant to resting sites, and in areas sparse in tree vegetation. We also identified a total of 56 clustered direction change points indicating that the group modified their direction of travel. These changes in direction were influenced by their close proximity to resting and feeding sites. Despite our small sample size, the obtained results are important and consistent with the contention that common marmosets navigate using a topological map that seems to benefit these animals in response to the exploitation of clustered exudate trees. Based on our findings, we hypothesize that the Caatinga landscape imposes physical restrictions in our group's navigation such as gaps in vegetation, small trees and xerophytic plants. This study, based on preliminary evidence, raises the question of whether navigation patterns are an intrinsic characteristic of a species or are ecologically dependent and change according to the environment.

Echo View Cells From Bio-Inspired Sonar

Place recognition is naturally informed by the mosaic of sensations we remember from previously visiting a location and general knowledge of our location in the world. Neurons in the mammalian brain (specifically in the hippocampus formation) named “place cells” are thought to reflect this recognition of place and are involved in implementing a spatial map that can be used for path planning and memory recall. In this research, we use bat-inspired sonar to mimic how bats might sense objects in the environment and recognize the views associated with different places. These “echo view cells” may contribute (along with odometry) to the creation of place cell representations observed in bats. Although detailed sensory template matching is straightforward, it is quite unlikely that a flying animal or robot will return to the exact 3-D position and pose where the original memory was captured. Instead, we strive to recognize views over extended regions that are many body lengths in size, reducing the number of places to be remembered for a map. We have successfully demonstrated some of this spatial invariance by training feed-forward neural networks (traditional neural networks and spiking neural networks) to recognize 66 distinct places in a laboratory environment over a limited range of translations and rotations. We further show how the echo view cells respond between known views and how their outputs can be combined over time for continuity.