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.

Parvalbumin and Somatostatin Interneurons Control Different Space-Coding Networks in the Medial Entorhinal Cortex.

The medial entorhinal cortex (MEC) contains several discrete classes of GABAergic interneurons, but their specific contributions to spatial pattern formation in this area remain elusive. We employed a pharmacogenetic approach to silence either parvalbumin (PV)- or somatostatin (SOM)-expressing interneurons while MEC cells were recorded in freely moving mice. PV-cell silencing antagonized the hexagonally patterned spatial selectivity of grid cells, especially in layer II of MEC. The impairment was accompanied by reduced speed modulation in colocalized speed cells. Silencing SOM cells, in contrast, had no impact on grid cells or speed cells but instead decreased the spatial selectivity of cells with discrete aperiodic firing fields. Border cells and head direction cells were not affected by either intervention. The findings point to distinct roles for PV and SOM interneurons in the local dynamics underlying periodic and aperiodic firing in spatially modulated cells of the MEC. VIDEO ABSTRACT.

Neural Networks for Navigation: From Connections to Computations.

Many animals can navigate toward a goal they cannot see based on an internal representation of that goal in the brain's spatial maps. These maps are organized around networks with stable fixed-point dynamics (attractors), anchored to landmarks, and reciprocally connected to motor control. This review summarizes recent progress in understanding these networks, focusing on studies in arthropods. One factor driving recent progress is the availability of the Drosophila connectome; however, it is increasingly clear that navigation depends on ongoing synaptic plasticity in these networks. Functional synapses appear to be continually reselected from the set of anatomical potential synapses based on the interaction of Hebbian learning rules, sensory feedback, attractor dynamics, and neuromodulation. This can explain how the brain's maps of space are rapidly updated; it may also explain how the brain can initialize goals as stable fixed points for navigation.

Mechanisms Underlying the Neural Computation of Head Direction.

Many animals use an internal sense of direction to guide their movements through the world. Neurons selective to head direction are thought to support this directional sense and have been found in a diverse range of species, from insects to primates, highlighting their evolutionary importance. Across species, most head-direction networks share four key properties: a unique representation of direction at all times, persistent activity in the absence of movement, integration of angular velocity to update the representation, and the use of directional cues to correct drift. The dynamics of theorized network structures called ring attractors elegantly account for these properties, but their relationship to brain circuits is unclear. Here, we review experiments in rodents and flies that offer insights into potential neural implementations of ring attractor networks. We suggest that a theory-guided search across model systems for biological mechanisms that enable such dynamics would uncover general principles underlying head-direction circuit function.

Parallel vector memories in the brain of a bee as foundation for flexible navigation.

Insects rely on path integration (vector-based navigation) and landmark guidance to perform sophisticated navigational feats, rivaling those seen in mammals. Bees in particular exhibit complex navigation behaviors including creating optimal routes and novel shortcuts between locations, an ability historically indicative of the presence of a cognitive map. A mammalian cognitive map has been widely accepted. However, in insects, the existence of a centralized cognitive map is highly contentious. Using a controlled laboratory assay that condenses foraging behaviors to short distances in walking bumblebees, we reveal that vectors learned during path integration can be transferred to long-term memory, that multiple such vectors can be stored in parallel, and that these vectors can be recalled at a familiar location and used for homeward navigation. These findings demonstrate that bees meet the two fundamental requirements of a vector-based analog of a decentralized cognitive map: Home vectors need to be stored in long-term memory and need to be recalled from remembered locations. Thus, our data demonstrate that bees possess the foundational elements for a vector-based map. By utilizing this relatively simple strategy for spatial organization, insects may achieve high-level navigation behaviors seen in vertebrates with the limited number of neurons in their brains, circumventing the computational requirements associated with the cognitive maps of mammals.

Formalising the role of behaviour in neuroscience.

We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbers ℕ $$ \mathrm{\mathbb{N}} $$ . We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two-dimensional coordinates under addition. We also study a system for processing a n b n $$ {a}^n{b}^n $$ strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost.

The influence of travel time on perceived traveled distance varies by spatiotemporal scale.

The influence of travel time on perceived traveled distance has often been studied, but the results are inconsistent regarding the relationship between the two magnitudes. We argue that this is due to differences in the lengths of investigated travel distances and hypothesize that the influence of travel time differs for rather short compared to rather long traveled distances. We tested this hypothesis in a virtual environment presented on a desktop as well as through a head-mounted display. Our results show that, for longer distances, more travel time leads to longer perceived distance, while we do not find an influence of travel time on shorter distances. The presentation through an HMD vs. desktop only influenced distance judgments in the short distance condition. These results are in line with the idea that the influence of travel time varies by the length of the traveled distance, and provide insights on the question of how distance perception in path integration studies is affected by travel time, thereby resolving inconsistencies reported in previous studies.

Effect of repetition of vertical and horizontal routes on navigation performance in Australian bull ants.

Solitarily foraging ant species differ in their reliance on their two primary navigational systems- path integration and visual learning. Despite many species of Australian bull ants spending most of their foraging time on their foraging tree, little is known about the use of these systems while climbing. "Rewinding" displacements are commonly used to understand navigational system usage, and work by introducing a mismatch between these navigational systems, by displacing foragers after they have run-down their path integration vector. We used rewinding to test the role of path integration on the arboreal and terrestrial navigation of M. midas. We rewound foragers along either the vertical portion, the ground surface portion, or across both portions of their homing trip. Since rewinding involves repeatedly capturing and releasing foragers, we included a nondisplacement, capture-and-release control, in which the path integration vector is unchanged. We found that rewound foragers do not seem to accumulate path integration vector, although a limited effect of vertical rewinding was found, suggesting a potential higher sensitivity while descending the foraging tree. However, the decrease in navigational efficiency due to capture was larger than the vertical rewinding effect, which along with the negative impact of the vertical surface, and an interaction between capture and rewinding, may suggest aversion rather than path integration caused the vertical rewinding response. Together these results add to the evidence that M. midas makes minimal use of path integration while foraging, and the growing evidence that they are capable of quickly learning from aversive stimulus.

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

INTRODUCTION: Entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimer's disease (AD), associated with EC grid cell dysfunction. Given the role of grid cells in path integration (PI)-based spatial behaviors, we predicted that PI impairment would represent the first behavioral change in adults at risk of AD. METHODS: We compared immersive virtual reality (VR) PI ability to other cognitive domains in 100 asymptomatic midlife adults stratified by hereditary and physiological AD risk factors. In some participants, behavioral data were compared to 7T magnetic resonance imaging (MRI) measures of brain structure and function. RESULTS: Midlife PI impairments predicted both hereditary and physiological AD risk, with no corresponding multi-risk impairment in episodic memory or other spatial behaviors. Impairments associated with altered functional MRI signal in the posterior-medial EC. DISCUSSION: Altered PI may represent the transition point from at-risk state to disease manifestation in AD, prior to impairment in other cognitive domains.

Comparative biology of spatial navigation in three arachnid orders (Amblypygi, Araneae, and Scorpiones).

From both comparative biology and translational research perspectives, there is escalating interest in understanding how animals navigate their environments. Considerable work is being directed towards understanding the sensory transduction and neural processing of environmental stimuli that guide animals to, for example, food and shelter. While much has been learned about the spatial orientation behavior, sensory cues, and neurophysiology of champion navigators such as bees and ants, many other, often overlooked animal species possess extraordinary sensory and spatial capabilities that can broaden our understanding of the behavioral and neural mechanisms of animal navigation. For example, arachnids are predators that often return to retreats after hunting excursions. Many of these arachnid central-place foragers are large and highly conducive to scientific investigation. In this review we highlight research on three orders within the Class Arachnida: Amblypygi (whip spiders), Araneae (spiders), and Scorpiones (scorpions). For each, we describe (I) their natural history and spatial navigation, (II) how they sense the world, (III) what information they use to navigate, and (IV) how they process information for navigation. We discuss similarities and differences among the groups and highlight potential avenues for future research.

Parallel motion vision pathways in the brain of a tropical bee.

Spatial orientation is a prerequisite for most behaviors. In insects, the underlying neural computations take place in the central complex (CX), the brain's navigational center. In this region different streams of sensory information converge to enable context-dependent navigational decisions. Accordingly, a variety of CX input neurons deliver information about different navigation-relevant cues. In bees, direction encoding polarized light signals converge with translational optic flow signals that are suited to encode the flight speed of the animals. The continuous integration of speed and directions in the CX can be used to generate a vector memory of the bee's current position in space in relation to its nest, i.e., perform path integration. This process depends on specific, complex features of the optic flow encoding CX input neurons, but it is unknown how this information is derived from the visual periphery. Here, we thus aimed at gaining insight into how simple motion signals are reshaped upstream of the speed encoding CX input neurons to generate their complex features. Using electrophysiology and anatomical analyses of the halictic bees Megalopta genalis and Megalopta centralis, we identified a wide range of motion-sensitive neurons connecting the optic lobes with the central brain. While most neurons formed pathways with characteristics incompatible with CX speed neurons, we showed that one group of lobula projection neurons possess some physiological and anatomical features required to generate the visual responses of CX optic-flow encoding neurons. However, as these neurons cannot explain all features of CX speed cells, local interneurons of the central brain or alternative input cells from the optic lobe are additionally required to construct inputs with sufficient complexity to deliver speed signals suited for path integration in bees.

Temporal effects of sugar intake on fly local search and honey bee dance behaviour.

Honey bees communicate flight navigational information of profitable food to nestmates via their dance, a small-scale walking pattern, inside the nest. Hungry flies and honey bee foragers exhibit a sugar-elicited search involving path integration that bears a resemblance to dance behaviour. This study aimed to investigate the temporal dynamics of the initiation of sugar-elicited search and dance behaviour, using a comparative approach. Passive displacement experiments showed that feeding and the initiation of search could be spatially and temporally dissociated. Sugar intake increased the probability of initiating a search but the actual onset of walking triggers the path integration system to guide the search. When prevented from walking after feeding, flies and bees maintained their motivation for a path integration-based search for a duration of 3 min. In flies, turning and associated characters were significantly reduced during this period but remained higher than in flies without sugar stimulus. These results suggest that sugar elicits two independent behavioural responses: path integration and increased turning, with the initiation and duration of path integration system being temporally restricted. Honey bee dance experiments demonstrated that the motivation of foragers to initiate dance persisted for 15 min, while the number of circuits declined after 3 min following sugar ingestion. Based on these findings, we propose that food intake during foraging increases the probability to initiate locomotor behaviours involving the path integration system in both flies and honey bees, and this ancestral connection might have been co-opted and elaborated during the evolution of dance communication by honey bees.

An 'instinct for learning': the learning flights and walks of bees, wasps and ants from the 1850s to now.

The learning flights and walks of bees, wasps and ants are precisely coordinated movements that enable insects to memorise the visual surroundings of their nest or other significant places such as foraging sites. These movements occur on the first few occasions that an insect leaves its nest. They are of special interest because their discovery in the middle of the 19th century provided perhaps the first evidence that insects can learn and are not solely governed by instinct. Here, we recount the history of research on learning flights from their discovery to the present day. The first studies were conducted by skilled naturalists and then, over the following 50 years, by neuroethologists examining the insects' learning behaviour in the context of experiments on insect navigation and its underlying neural mechanisms. The most important property of these movements is that insects repeatedly fixate their nest and look in other favoured directions, either in a preferred compass direction, such as North, or towards preferred objects close to the nest. Nest facing is accomplished through path integration. Memories of views along a favoured direction can later guide an insect's return to its nest. In some ant species, the favoured direction is adjusted to future foraging needs. These memories can then guide both the outward and homeward legs of a foraging trip. Current studies of central areas of the insect brain indicate what regions implement the behavioural manoeuvres underlying learning flights and the resulting visual memories.

Homing tasks performed using variations of crawling gait patterns reveal a role for attention in podokinetic path integration.

Self-motion can be perceived via podokinetic information, that is, based upon the movements of the legs during legged locomotion. This information can be integrated in order to perceive a path of travel through the environment (i.e., via podokinetic path integration). Two types of podokinetic information have been distinguished by analyzing the patterns of bias that result from manipulating the gait patterns used in direct-route homing tasks. Each type of podokinetic information has been associated specific groupings of gaits that support equivalent perceptual measurements of self-motion. Specifically, gaits are grouped if they can be varied across the outbound and inbound phases of a homing task (e.g., walking outbound and jogging inbound) and the accuracy of homing task performances does not differ from matched-gait control conditions. Recently, it was theorized that different types of podokinetic information are related to the differences in the kinematic form of limb motions in these groupings of gaits. Here we test an alternative hypothesis, namely that attention plays a role in selecting the type of podokinetic information. In three experiments, we manipulated the crawling gait patterns used in direct-route homing tasks. Consistent with our hypotheses, we observe that self-motion is equivalently measured via crawling movement patterns that (1) have distinct kinematic forms, but that similarly direct participants' attention onto controlling the swing phase trajectories of their arms, and (2) have distinct inter-limb coordination patterns (i.e., pace vs. trot), but do not require attention to be specifically focused upon swing phase arm trajectories.

Empowering episodic memory through a model-based egocentric navigational training.

Recent works have proposed that spatial mechanisms in the hippocampal-entorhinal system might have originally developed to represent distances and positions in the physical space and successively evolved to represent experience and memory in the mental space (Bellmund et al. 2018; Bottini and Doeller 2020). Within this phylogenetic continuity hypothesis (Buzsáki and Moser 2013), mechanisms supporting episodic and semantic memory would have evolved from egocentric and allocentric spatial navigation mechanisms, respectively. Recent studies have described a specific relationship between human performance in egocentric navigation and episodic memory (Committeri et al. 2020; Fragueiro et al. 2021), representing the first behavioral support to this hypothesis. Here, we tested the causal relationship among egocentric navigation and both episodic and semantic components of declarative memory. We conducted two experiments on healthy young adults: in the first experiment, participants were submitted to a navigational training based on path integration, while in the second experiment, participants completed a control training based on visual-perceptual learning. Performance in a set of memory tasks assessing episodic, semantic and short-term memory was compared among the pre- vs. post-training sessions. The results indicated a significant improvement of the episodic memory but not of the semantic or the short-term memory performance following the navigational training. In addition, no modulations of performance across the three memory tasks were observed following the control perceptual training. Our findings provide brand-new evidence of a potential causal association between mechanisms of egocentric navigation and episodic memory, thereby further supporting the phylogenetic continuity hypothesis between navigation and memory mechanisms as well as offering new insights about possible clinical applications of navigational trainings for memory functions/dysfunctions.

Increased variability but intact integration during visual navigation in Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disturbance afflicting a variety of functions. The recent computational focus suggesting aberrant Bayesian inference in ASD has yielded promising but conflicting results in attempting to explain a wide variety of phenotypes by canonical computations. Here, we used a naturalistic visual path integration task that combines continuous action with active sensing and allows tracking of subjects' dynamic belief states. Both groups showed a previously documented bias pattern by overshooting the radial distance and angular eccentricity of targets. For both control and ASD groups, these errors were driven by misestimated velocity signals due to a nonuniform speed prior rather than imperfect integration. We tracked participants' beliefs and found no difference in the speed prior, but there was heightened variability in the ASD group. Both end point variance and trajectory irregularities correlated with ASD symptom severity. With feedback, variance was reduced, and ASD performance approached that of controls. These findings highlight the need for both more naturalistic tasks and a broader computational perspective to understand the ASD phenotype and pathology.

On the 'cognitive map debate' in insect navigation.

In a historical account recently published in this journal Dhein argues that the current debate whether insects like bees and ants use cognitive maps (centralized map hypothesis) or other means of navigation (decentralized network hypothesis) largely reflects the classical debate between American experimental psychologists à la Tolman and German ethologists à la Lorenz, respectively. In this dichotomy we, i.e., the proponents of the network hypothesis, are inappropriately placed on the Lorenzian line. In particular, we argue that in contrast to Dhein's claim our concepts are not based on merely instinctive or peripheral modes of information processing. In general, on the one side our approaches have largely been motivated by the early biocybernetics way of thinking. On the other side they are deeply rooted in studies on the insect's behavioral ecology, i.e., in the ecological setting within which the navigational strategies have evolved and within which the animal now operates. Following such a bottom-up approach we are not "anti-cognitive map researchers" but argue that the results we have obtained in ants, and also the results of some decisive experiments in bees, can be explained and simulated without the need of invoking metric maps.

Magnetosensation during re-learning walks in desert ants (Cataglyphis nodus).

At the beginning of their foraging careers, Cataglyphis desert ants calibrate their compass systems and learn the visual panorama surrounding the nest entrance. For that, they perform well-structured initial learning walks. During rotational body movements (pirouettes), naïve ants (novices) gaze back to the nest entrance to memorize their way back to the nest. To align their gaze directions, they rely on the geomagnetic field as a compass cue. In contrast, experienced ants (foragers) use celestial compass cues for path integration during food search. If the panorama at the nest entrance is changed, foragers perform re-learning walks prior to heading out on new foraging excursions. Here, we show that initial learning walks and re-learning walks are structurally different. During re-learning walks, foragers circle around the nest entrance before leaving the nest area to search for food. During pirouettes, they do not gaze back to the nest entrance. In addition, foragers do not use the magnetic field as a compass cue to align their gaze directions during re-learning walk pirouettes. Nevertheless, magnetic alterations during re-learning walks under manipulated panoramic conditions induce changes in nest-directed views indicating that foragers are still magnetosensitive in a cue conflict situation.

Finding food in the dark: how trajectories of a gymnotiform fish change with spatial learning.

We analyzed the trajectories of freely foraging Gymnotus sp., a pulse-type gymnotiform weakly electric fish, swimming in a dark arena. For each fish, we compared the its initial behavior as it learned the relative location of landmarks and food with its behavior after learning was complete, i.e. after time/distance to locate food had reached a minimal asymptotic level. During initial exploration when the fish did not know the arena layout, trajectories included many sharp angle head turns that occurred at nearly completely random intervals. After spatial learning was complete, head turns became far smoother. Interestingly, the fish still did not take a stereotyped direct route to the food but instead took smooth but variable curved trajectories. We also measured the fish's heading angle error (heading angle - heading angle towards food). After spatial learning, the fish's initial heading angle errors were strongly biased to zero, i.e. the fish mostly turned towards the food. As the fish approached closer to the food, they switched to a random search strategy with a more uniform distribution of heading angle errors.

Wood ants learn the magnetic direction of a route but express uncertainty because of competing directional cues.

Wood ants were trained indoors to follow a magnetically specified route that went from the centre of an arena to a drop of sucrose at the edge. The arena, placed in a white cylinder, was in the centre of a 3D coil system generating an inclined Earth-strength magnetic field in any horizontal direction. The specified direction was rotated between each trial. The ants' knowledge of the route was tested in trials without food. Tests given early in the day, before any training, show that ants remember the magnetic route direction overnight. During the first 2 s of a test, ants mostly faced in the specified direction, but thereafter were often misdirected, with a tendency to face briefly in the opposite direction. Uncertainty about the correct path to take may stem in part from competing directional cues linked to the room. In addition to facing along the route, there is evidence that ants develop magnetically directed home and food vectors dependent upon path integration. A second experiment asked whether ants can use magnetic information contextually. In contrast to honeybees given a similar task, ants failed this test. Overall, we conclude that magnetic directional cues can be sufficient for route learning.