Collective gradient sensing in fish schools

Origin stories: how does learned migratory behaviour arise in populations?

Although decades of research have deepened our understanding of the proximate triggers and ultimate drivers of migrations for a range of taxa, how populations establish migrations remains a mystery. However, recent studies have begun to illuminate the interplay between genetically inherited and learned migrations, opening the door to the evaluation of how migration may be learned, established, and maintained. Nevertheless, for migratory species where the role of learning is evident, we lack a comprehensive framework for understanding how populations learn specific routes and refine migratory movements over time (i.e., their origins). This review draws on advances in behavioural and movement ecology to offer a comprehensive framework for how populations could transition from resident to migratory by connecting cognitive research on fine-scale perceptual cues and movement decisions with literature on learning and cultural transmission, to the emergent pattern of migration. We synthesize the multiple cognitive mechanisms and processes that allow a population to respond to seasonal resource limitation, then encode spatial and environmental information about resource availability in memory and engage in social learning to navigate their landscapes and track resources better. A rise in global reintroduction efforts, along with human-induced rapid shifts in environmental cues and changing landscapes make evaluating the origins of this threatened behaviour more urgent than ever.

Conditioning a collective avoidance response in rummy-nose tetra

Escape waves in animal groups, such as bird flocks and fish schools, have attracted a lot of attention, as they provide the opportunity to better understand how information can efficiently propagate in moving groups, and how individuals can coordinate their actions under the threat of predators. There is a lack of appropriate experimental protocols to study escape waves in highly social fish, in which the number of individuals initiating the escape and the identity of the initiators are controlled. Indeed, highly social fish or obligate schoolers have a tendency to not respond well or to freeze when tested in experimental setups designed for single individuals. In this manuscript, we report the results of a pilot experiment with limited sample size using an aversive conditioning protocol to trigger a collective escape response to a green light in a group of rummy-nose tetra (Hemigrammus rhodostomus). Our experimental results suggest that aversive conditioning can (i) be successfully used in this schooling species, (ii) trigger collective escape responses, and (iii) be transferred from the training setup to a new environment. We also introduce metrics to characterize learning and forgetting at group level. These results nurture promising future empirical research on the cognitive and behavioral mechanisms of escape responses in schools of fish, both at the individual and collective scales.

Shortest path choice in zebrafish (Danio rerio)

Many animals regularly move between different locations within their home range. During these journeys, individuals are expected to use the shortest path, because this strategy minimizes energy expenditure and reduces exposure to adverse conditions, such as predation. The ability to find the shortest distance route has been demonstrated in ants, migrating birds and a few mammals. We investigated whether a freshwater fish, Danio rerio, exhibits this ability. Small groups of zebrafish were allowed to move between the two compartments of their tank using two paths differing in length. They developed a preference for the shorter path gradually over the six days of the experiment. Subjects' accuracy in choosing the shorter path varied from below 60%, with a 20% length disparity, to 80% when one path was twice as long as the other. In a second experiment, zebrafish were initially allowed to practice in groups and then tested individually. We found evidence of individual and sex differences in performance, with males performing more accurately than females. However, due to our experimental design, we cannot conclusively determine whether these differences are indeed cognitive or influenced by confounding factors during the group phase of the experiment.

Mechanisms of group-hunting in vertebrates

Group-hunting is ubiquitous across animal taxa and has received considerable attention in the context of its functions. By contrast much less is known about the mechanisms by which grouping predators hunt their prey. This is primarily due to a lack of experimental manipulation alongside logistical difficulties quantifying the behaviour of multiple predators at high spatiotemporal resolution as they search, select, and capture wild prey. However, the use of new remote-sensing technologies and a broadening of the focal taxa beyond apex predators provides researchers with a great opportunity to discern accurately how multiple predators hunt together and not just whether doing so provides hunters with a per capita benefit. We incorporate many ideas from collective behaviour and locomotion throughout this review to make testable predictions for future researchers and pay particular attention to the role that computer simulation can play in a feedback loop with empirical data collection. Our review of the literature showed that the breadth of predator:prey size ratios among the taxa that can be considered to hunt as a group is very large (<100 to >102 ). We therefore synthesised the literature with respect to these predator:prey ratios and found that they promoted different hunting mechanisms. Additionally, these different hunting mechanisms are also related to particular stages of the hunt (search, selection, capture) and thus we structure our review in accordance with these two factors (stage of the hunt and predator:prey size ratio). We identify several novel group-hunting mechanisms which are largely untested, particularly under field conditions, and we also highlight a range of potential study organisms that are amenable to experimental testing of these mechanisms in connection with tracking technology. We believe that a combination of new hypotheses, study systems and methodological approaches should help push the field of group-hunting in new directions.

Illuminance-tuned collective motion in fish

We experimentally investigate the role of illumination on the collective dynamics of a large school (ca. 50 individuals) of Hemigrammus rhodostomus. The structure of the group, defined using two order parameters, is quantified while progressively altering the visual range of the fish through controlled cycles of ambient light intensity. We show that, at low light levels, the individuals within the group are unable to form a cohesive group, while at higher illuminance the degree of alignment of the school correlates with the light intensity. When increasing the illuminance, the school structure is successively characterized by a polarized state followed by a highly regular and stable rotational configuration (milling). Our study shows that vision is necessary to achieve cohesive collective motion for free swimming fish schools, while the short-range lateral line sensing is insufficient in this situation. The present experiment therefore provides new insights into the interaction mechanisms that govern the emergence and intensity of collective motion in biological systems.

Collective gradient perception with a flying robot swarm

In this paper, we study the problem of collective and emergent sensing with a flying robot swarm in which social interactions among individuals lead to following the gradient of a scalar field in the environment without the need of any gradient sensing capability. We proposed two methods—desired distance modulation and speed modulation—with and without alignment control. In the former, individuals modulate their desired distance to their neighbors and in the latter, they modulate their speed depending on the social interactions with their neighbors and measurements from the environment. Methods are systematically tested using two metrics with different scalar field models, swarm sizes and swarm densities. Experiments are conducted using: (1) a kinematic simulator, (2) a physics-based simulator, and (3) real nano-drone swarm. Results show that using the proposed methods, a swarm—composed of individuals lacking gradient sensing ability—is able to follow the gradient in a scalar field successfully. Results show that when individuals modulate their desired distances, alignment control is not needed but it still increases the performance. However, when individuals modulate their speed, alignment control is needed for collective motion. Real nano-drone experiments reveal that the proposed methods are applicable in real-life scenarios.

The impact of individual perceptual and cognitive factors on collective states in a data-driven fish school model

In moving animal groups, social interactions play a key role in the ability of individuals to achieve coordinated motion. However, a large number of environmental and cognitive factors are able to modulate the expression of these interactions and the characteristics of the collective movements that result from these interactions. Here, we use a data-driven fish school model to quantitatively investigate the impact of perceptual and cognitive factors on coordination and collective swimming patterns. The model describes the interactions involved in the coordination of burst-and-coast swimming in groups of Hemigrammus rhodostomus. We perform a comprehensive investigation of the respective impacts of two interactions strategies between fish based on the selection of the most or the two most influential neighbors, of the range and intensity of social interactions, of the intensity of individual random behavioral fluctuations, and of the group size, on the ability of groups of fish to coordinate their movements. We find that fish are able to coordinate their movements when they interact with their most or two most influential neighbors, provided that a minimal level of attraction between fish exist to maintain group cohesion. A minimal level of alignment is also required to allow the formation of schooling and milling. However, increasing the strength of social interactions does not necessarily enhance group cohesion and coordination. When attraction and alignment strengths are too high, or when the heading random fluctuations are too large, schooling and milling can no longer be maintained and the school switches to a swarming phase. Increasing the interaction range between fish has a similar impact on collective dynamics as increasing the strengths of attraction and alignment. Finally, we find that coordination and schooling occurs for a wider range of attraction and alignment strength in small group sizes.

Hydrodynamical Fingerprint of a Neighbour in a Fish Lateral Line

For fish, swimming in group may be favorable to individuals. Several works reported that in a fish school, individuals sense and adjust their relative position to prevent collisions and maintain the group formation. Also, from a hydrodynamic perspective, relative-position and kinematic synchronisation between adjacent fish may considerably influence their swimming performance. Fish may sense the relative-position and tail-beat phase difference with their neighbors using both vision and the lateral-line system, however, when swimming in dark or turbid environments, visual information may become unavailable. To understand how lateral-line sensing can enable fish to judge the relative-position and phase-difference with their neighbors, in this study, based on a verified three-dimensional computational fluid dynamics approach, we simulated two fish swimming adjacently with various configurations. The lateral-line signal was obtained by sampling the surface hydrodynamic stress. The sensed signal was processed by Fast Fourier Transform (FFT), which is robust to turbulence and environmental flow. By examining the lateral-line pressure and shear-stress signals in the frequency domain, various states of the neighboring fish were parametrically identified. Our results reveal that the FFT-processed lateral-line signals in one fish may potentially reflect the relative-position, phase-differences, and the tail-beat frequency of its neighbor. Our results shed light on the fluid dynamical aspects of the lateral-line sensing mechanism used by fish. Furthermore, the presented approach based on FFT is especially suitable for applications in bioinspired swimming robotics. We provide suggestions for the design of artificial systems consisting of multiple stress sensors for robotic fish to improve their performance in collective operation.

Dominating lengthscales of zebrafish collective behaviour

Collective behaviour in living systems is observed across many scales, from bacteria to insects, to fish shoals. Zebrafish have emerged as a model system amenable to laboratory study. Here we report a three-dimensional study of the collective dynamics of fifty zebrafish. We observed the emergence of collective behaviour changing between ordered to randomised, upon adaptation to new environmental conditions. We quantify the spatial and temporal correlation functions of the fish and identify two length scales, the persistence length and the nearest neighbour distance, that capture the essence of the behavioural changes. The ratio of the two length scales correlates robustly with the polarisation of collective motion that we explain with a reductionist model of self-propelled particles with alignment interactions.

The Cognitive Ecology of Animal Movement: Evidence From Birds and Mammals

Cognition, defined as the processes concerned with the acquisition, retention and use of information, underlies animals’ abilities to navigate their local surroundings, embark on long-distance seasonal migrations, and socially learn information relevant to movement. Hence, in order to fully understand and predict animal movement, researchers must know the cognitive mechanisms that generate such movement. Work on a few model systems indicates that most animals possess excellent spatial learning and memory abilities, meaning that they can acquire and later recall information about distances and directions among relevant objects. Similarly, field work on several species has revealed some of the mechanisms that enable them to navigate over distances of up to several thousand kilometers. Key behaviors related to movement such as the choice of nest location, home range location and migration route are often affected by parents and other conspecifics. In some species, such social influence leads to the formation of aggregations, which in turn may lead to further social learning about food locations or other resources. Throughout the review, we note a variety of topics at the interface of cognition and movement that invite further investigation. These include the use of social information embedded in trails, the likely important roles of soundscapes and smellscapes, the mechanisms that large mammals rely on for long-distance migration, and the effects of expertise acquired over extended periods.

Modeling multi-sensory feedback control of zebrafish in a flow

Understanding how animals navigate complex environments is a fundamental challenge in biology and a source of inspiration for the design of autonomous systems in engineering. Animal orientation and navigation is a complex process that integrates multiple senses, whose function and contribution are yet to be fully clarified. Here, we propose a data-driven mathematical model of adult zebrafish engaging in counter-flow swimming, an innate behavior known as rheotaxis. Zebrafish locomotion in a two-dimensional fluid flow is described within the finite-dipole model, which consists of a pair of vortices separated by a constant distance. The strength of these vortices is adjusted in real time by the fish to afford orientation and navigation control, in response to of the multi-sensory input from vision, lateral line, and touch. Model parameters for the resulting stochastic differential equations are calibrated through a series of experiments, in which zebrafish swam in a water channel under different illumination conditions. The accuracy of the model is validated through the study of a series of measures of rheotactic behavior, contrasting results of real and in-silico experiments. Our results point at a critical role of hydromechanical feedback during rheotaxis, in the form of a gradient-following strategy.

The sensory basis of schooling by intermittent swimming in the rummy-nose tetra (Hemigrammus rhodostomus)

Schooling is a collective behaviour that enhances the ability of a fish to sense and respond to its environment. Although schooling is essential to the biology of a diversity of fishes, it is generally unclear how this behaviour is coordinated by different sensory modalities. We used experimental manipulation and kinematic measurements to test the role of vision and flow sensing in the rummy-nose tetra (Hemigrammus rhodostomus), which swims with intermittent phases of bursts and coasts. Groups of five fish required a minimum level of illuminance (greater than 1.5 lx) to achieve the necessary close nearest-neighbour distance and high polarization for schooling. Compromising the lateral line system with an antibiotic treatment caused tetras to swim with greater nearest-neighbour distance and lower polarization. Therefore, vision is both necessary and sufficient for schooling in H. rhodostomus, and both sensory modalities aid in attraction. These results can serve as a basis for understanding the individual roles of sensory modalities in schooling for some fish species.

Testing a thermodynamic approach to collective animal behavior in laboratory fish schools

Collective behaviors displayed by groups of social animals are observed frequently in nature. Understanding and predicting the behavior of complex biological systems is dependent on developing effective descriptions and models. While collective animal systems are characteristically nonequilibrium, we can employ concepts from equilibrium statistical mechanics to motivate the measurement of material-like properties in laboratory animal aggregates. Here, we present results from a new set of experiments that utilize high speed footage of two-dimensional schooling events, particle tracking, and projected static and dynamic light fields to observe and control the behavior of negatively phototaxic fish schools (Hemigrammus bleheri). First, we use static light fields consisting of dark circular regions to produce visual stimuli that confine the schools to a range of areas. We find that schools have a maximum density which is independent of group size, and that a swim pressurelike quantity, Π increases linearly with number density, suggesting that unperturbed schools exist on an isotherm. Next, we use dynamic light fields where the radius of the dark region shrinks linearly with time to compress the schools. We find that an effective temperature parameter depends on the compression time and our results are thus consistent with the school having a constant heat flux. These findings further evidence the utility of effective thermodynamic descriptions of nonequilibrium systems in collective animal behavior.

Optimal Flow Sensing for Schooling Swimmers

Fish schooling implies an awareness of the swimmers for their companions. In flow mediated environments, in addition to visual cues, pressure and shear sensors on the fish body are critical for providing quantitative information that assists the quantification of proximity to other fish. Here we examine the distribution of sensors on the surface of an artificial swimmer so that it can optimally identify a leading group of swimmers. We employ Bayesian experimental design coupled with numerical simulations of the two-dimensional Navier Stokes equations for multiple self-propelled swimmers. The follower tracks the school using information from its own surface pressure and shear stress. We demonstrate that the optimal sensor distribution of the follower is qualitatively similar to the distribution of neuromasts on fish. Our results show that it is possible to identify accurately the center of mass and the number of the leading swimmers using surface only information.