animal navigation
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AbstractIn addition to providing animals with a source of directional or ‘compass’ information, Earth’s magnetic field also provides a potential source of positional or ‘map’ information that animals might exploit to assess location. In less than a generation, the idea that animals use Earth’s magnetic field as a kind of map has gone from a contentious hypothesis to a well-established tenet of animal navigation. Diverse animals ranging from lobsters to birds are now known to use magnetic positional information for a variety of purposes, including staying on track along migratory pathways, adjusting food intake at appropriate points in a migration, remaining within a suitable oceanic region, and navigating toward specific goals. Recent findings also indicate that sea turtles, salmon, and at least some birds imprint on the magnetic field of their natal area when young and use this information to facilitate return as adults, a process that may underlie long-distance natal homing (a.k.a. natal philopatry) in many species. Despite recent progress, much remains to be learned about the organization of magnetic maps, how they develop, and how animals use them in navigation.

The detection of visual motion enables sophisticated animal navigation, and studies in flies have provided profound insights into the cellular and circuit basis of this neural computation. The fly's directionally selective T4 and T5 neurons respectively encode ON and OFF motion. Their axons terminate in one of four retinotopic layers in the lobula plate, where each layer encodes one of four cardinal directions of motion. While the input circuitry of the directionally selective neurons has been studied in detail, the synaptic connectivity of circuits integrating T4/T5 motion signals is largely unknown. Here we report a 3D electron microscopy reconstruction, wherein we comprehensively identified T4/T5's synaptic partners in the lobula plate, revealing a diverse set of new cell types and attributing new connectivity patterns to known cell types. Our reconstruction explains how the ON and OFF motion pathways converge. T4 and T5 cells that project to the same layer, connect to common synaptic partners symmetrically, that is with similar weights, and also comprise a core motif together with bilayer interneurons, detailing the circuit basis for computing motion opponency. We discovered pathways that likely encode new directions of motion by integrating vertical and horizontal motion signals from upstream T4/T5 neurons. Finally, we identify substantial projections into the lobula, extending the known motion pathways and suggesting that directionally selective signals shape feature detection there. The circuits we describe enrich the anatomical basis for experimental and computations analyses of motion vision and bring us closer to understanding complete sensory-motor pathways.

The whiskers of rodents are a key sensory organ that provides critical tactile information for animal navigation and object exploration throughout life. Previous work has explored the developmental sensory-driven activation of the primary sensory cortex processing whisker information (wS1), also called barrel cortex. This body of work has shown that the barrel cortex is already activated by sensory stimuli during the first post-natal week. However, it is currently unknown when over the course of development these stimuli begin being processed by higher order cortical areas, such as secondary whisker somatosensory area (wS2). Here we investigate for the first time the developmental engagement of wS2 by sensory stimuli and the emergence of cortico-cortical communication from wS1 to wS2. Using in vivo wide-field imaging and electrophysiological recordings in control and conditional knock-out mice we find that wS1 and wS2 are able to process bottom-up information coming from the thalamus already right after birth. We identify that it is only at the end of the first post-natal week that wS1 begins to provide excitation into wS2, a connection which begins to acquire feed-forward inhibition characteristics after the second post-natal week. Therefore, we have uncovered a developmental window during which excitatory versus inhibitory functional connectivity between wS1 and wS2 takes place.

Insects have a sophisticated ability to navigate real environments. Virtual reality (VR) is a powerful tool for analyzing animal navigation in laboratory studies and is the most successful when used in the study of visually guided behaviors. However, the use of VR with non-visual sensory information, such as sound, on which nocturnal insects rely, for analyzing animal navigation has not been fully studied. We developed an auditory VR for the study of auditory navigation in crickets, Gryllus bimaculatus. The system consisted of a spherical treadmill on which a tethered female cricket walked. Sixteen speakers were placed around the cricket for auditory stimuli. The two optical mice attached to the treadmill measured the cricket’s locomotion, and the sound pressure and direction of the auditory stimuli were controlled at 100 Hz based on the position and heading of the cricket relative to a sound source in a virtual arena. We demonstrated that tethered female crickets selectively responded to the conspecific male calling song and localized the sound source in a virtual arena, which was similar to the behavior of freely walking crickets. Further combinations of our system with neurophysiological techniques will help understand the neural mechanisms for insect auditory navigation.

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.

One persistent question in animal navigation is how animals follow habitual routes between their home and a food source. Our current understanding of insect navigation suggests an interplay between visual memories, collision avoidance and path integration, the continuous integration of distance and direction travelled. However, these behavioural modules have to be continuously updated with instantaneous visual information. In order to alleviate this need, the insect could learn and replicate habitual movements (“movement memories”) around objects (e.g. a bent trajectory around an object) to reach its destination. We investigated whether bumblebees, Bombus terrestris, learn and use movement memories en route to their home. Using a novel experimental paradigm, we habituated bumblebees to establish a habitual route in a flight tunnel containing “invisible” obstacles. We then confronted them with conflicting cues leading to different choice directions depending on whether they rely on movement or visual memories. The results suggest that they use movement memories to navigate, but also rely on visual memories to solve conflicting situations. We investigated whether the observed behaviour was due to other guidance systems, such as path integration or optic flow-based flight control, and found that neither of these systems was sufficient to explain the behaviour.

Diverse taxa use Earth’s magnetic field in combination with other sensory modalities to accomplish navigation tasks ranging from local homing to long-distance migration across continents and ocean basins. Several animals have the ability to use the inclination or tilt of magnetic field lines as a component of a magnetic compass sense that can be used to maintain migratory headings. In addition, a few animals are able to distinguish among different inclination angles and, in effect, exploit inclination as a surrogate for latitude. Little is known, however, about the role that magnetic inclination plays in guiding long-distance migrations. In this paper, we use an agent-based modelling approach to investigate whether an artificial agent can successfully execute a series of transequatorial migrations by using sequential measurements of magnetic inclination. The agent was tested with multiple navigation strategies in both present-day and reversed magnetic fields. The findings (i) demonstrate that sequential inclination measurements can enable migrations between the northern and southern hemispheres, and (ii) demonstrate that an inclination-based strategy can tolerate a reversed magnetic field, which could be useful in the development of autonomous engineered systems that must be robust to magnetic field changes. The findings also appear to be consistent with the results of some animal navigation experiments, although whether any animal exploits a strategy of using sequential measurements of inclination remains unknown.

Abstract Collective behavior refers to the group-level organization arising from interaction among individuals. To exchange information the individuals rely on their sensing modalities. Experimental studies provide evidence that the integration of information from multiple sensory modalities can influence animal navigation and social communication. In this paper, we present a modified Vicsek model with a composite sensing scheme that combines both auditory and visual sensing cues through the set of sensory neighbors. We investigate the combined effect of auditory and visual sensing on the group behavior compared to pure vision and audition using numerical simulation. We observe that taking the advantage of composite modality, the particles get access to more information that enables them to form a single large, cohesive, and perfectly aligned group using a narrow sensing region, which is possible in either vision or audition only using a wider sensing region.