Understanding how animal groups achieve coordinated movement

Hydrodynamics-driven phase-locking and collective motility of sessile active dumbbells

Collective motion is a phenomenon observed across length scales in nature - from bacterial swarming and tissue migration to the flocking of animals. The mechanisms underlying this behavior vary significantly depending on the biological system, ranging from hydrodynamic and chemical interactions in bacteria to mechanical forces in epithelial tissues and social alignment in animal groups. While collective motion often arises from the coordinated activity of independently motile agents, this work explores a novel context: the emergence of collective motion in systems of non-motile active agents. Inspired by the oscillatory shape dynamics observed in suspended cells such as neutrophils and fibroblasts, we model active dumbbells exhibiting limit-cycle oscillations in shape as a minimal representation of such systems. Through computational simulations, we demonstrate that hydrodynamic interactions between these dumbbells lead to three key phenomena - a density-dependent transition from sessile to collective motion, hydrodynamics-induced phase separation, and synchronization of oscillatory shape changes. We have explored the role of hydrodynamic interactions on these emergent properties of sessile active dumbbells. These results underscore the critical role of hydrodynamic coupling in enabling and organizing collective behaviors in systems lacking intrinsic motility. This study lays the groundwork for future investigations into the emergent behavior of active matter and its implications for understanding cell motility, tissue dynamics, and the development of bio-inspired materials.

Collective phases and long-term dynamics in a fish school model with burst-and-coast swimming

Intermittent and asynchronous burst-and-coast swimming is widely adopted by various species of fish as an energy-efficient mode of locomotion. This swimming mode significantly influences how fish integrate information and make decisions in a social context. Here, we introduce a simplified fish school model in which individuals have an asynchronous burst-and-coast swimming mode and selectively interact only with one or two neighbours that exert the largest influence on their behaviour over a limited spatial range. The interactions consist of a fish that is attracted to and aligned with these neighbours. We show that, by adjusting the interactions between individuals above a sufficiently high level, depending on the relative strength of attraction and alignment, the model can produce a cohesive fish school that replicates the main collective phases observed in nature: schooling, milling and swarming when each individual interacts with only one neighbour; and schooling and swarming when each individual interacts with two neighbours. Moreover, the model showed that these patterns can be maintained over long simulations. However, with the exception of swarming, these patterns do not persist indefinitely, and fish lose cohesion and progressively disperse. We further identified the mechanisms that lead to group dispersion.

Collective properties of Petitella georgiae in tube environments

The movement of biological swarms is widespread in nature, and collective behavior enhances a swarm's adaptability to its environment. However, most research focuses on free swarm movement, overlooking the impact of environmental constraints such as tubes. This study examines the swimming behavior of Petitella georgiae through a tube. Observations of position, speed, and direction reveal that each fish is influenced by the swarm's distribution in its field of view. The speed ratio between the middle region and edge region positively correlates with tube angles, and higher speeds are associated with higher densities within specific angle ranges.

Collective responses of flocking sheep (Ovis aries) to a herding dog (border collie)

Group-living organisms commonly exhibit collective escape responses, yet how information flows among group members in these events remains an open question. Here, we study the collective responses of a sheep flock (Ovis aries) to a shepherd dog (border collie) in a driving task between two well-defined target points. We collected high-resolution spatiotemporal data from 14 sheep and the dog, using Ultra-Wide-Band tags attached to each individual. We find that the spatial positions of sheep along the front-back axis of the group's velocity strongly correlate with their impact on the collective movement. Our analyses reveal that, even though the dog chases the sheep flock from behind, directional information on shorter time scales propagates from the front of the group towards the rear; further, the dog adjusts its movement in response to the flock's dynamics. We introduce an agent-based model that captures key data features. Specifically, in response to chasing, the sheep change their spatial relative positions less frequently and exhibit a transfer of directional information flow from front to back; this pattern disappears in the absence of chasing. Our study reveals some general insights into how directional information propagates in escaping animal groups.

Effects of Starve and Shelter Availability on the Group Behavior of Two Freshwater Fish Species (Chindongo demasoni and Spinibarbus sinensis)

In complex environments, fish often suffer from reduced physiological functioning due to starvation, which may have a significant effect on their behavioral adaptive strategies to predator attacks. We selected qingbo (Spinibarbus sinensis, which prefers flowing water habitats) and demasone cichlid (Chindongo demasoni, which prefers still water habitats), to investigate the differences in group distribution and dynamics between the two species when faced with a simulated predation attack under different trophic states (fasted for 2 weeks or fed). We chose to conduct our experiments in a six-arm maze that included a central area and six arms of equal length and width and to obtain evidence of how the fish used the various areas of the maze to respond to simulated predation attacks. We found that the two fish species differed in their responses to simulated predation attacks under different trophic states. The group structure of the two species was relatively stable, and the effect of fasting on the qingbo group was not significant, whereas the demasone cichlid group was more susceptible to the effects of fasting, shelter and a simulated predation attack. In an environment with shelter, both species had the same anti-predator strategy and tended to enter the shelter arm to hide after encountering a simulated predation attack. However, differences in the anti-predator strategies of the two species emerged in the no-shelter environment, with the qingbo tending to enter the arm to hide, whereas the demasone cichlid group chose to enter the central area to congregate, and this phenomenon was more pronounced in the fasted group. In conclusion, our research shows that even group-stable fish may shift their anti-predation strategies (i.e., entering a shelter to hide shifts to aggregating in situ into a shoal) when starved and that the worse the swimming ability of the fish, the more affected they are by starvation.

Relative telencephalon size does not affect collective motion in the guppy (Poecilia reticulata)

Collective motion is common across all animal taxa, from swarming insects to schools of fish. The collective motion requires intricate behavioral integration among individuals, yet little is known about how evolutionary changes in brain morphology influence the ability for individuals to coordinate behavior in groups. In this study, we utilized guppies that were selectively bred for relative telencephalon size, an aspect of brain morphology that is normally associated with advanced cognitive functions, to examine its role in collective motion using an open-field assay. We analyzed high-resolution tracking data of same-sex shoals consisting of 8 individuals to assess different aspects of collective motion, such as alignment, attraction to nearby shoal members, and swimming speed. Our findings indicate that variation in collective motion in guppy shoals might not be strongly affected by variation in relative telencephalon size. Our study suggests that group dynamics in collectively moving animals are likely not driven by advanced cognitive functions but rather by fundamental cognitive processes stemming from relatively simple rules among neighboring individuals.

Data-driven exploration of swarmalators with second-order harmonics

We explore the dynamics of a swarmalator population comprising second-order harmonics in phase interaction. A key observation in our study is the emergence of the active asynchronous state in swarmalators with second-order harmonics, mirroring findings in the one-dimensional analog of the model, accompanied by the formation of clustered states. Particularly, we observe a transition from the static asynchronous state to the active phase wave state via the active asynchronous state. We have successfully delineated and quantified the stability boundary of the active asynchronous state through a completely data-driven method. This was achieved by utilizing the enhanced image processing capabilities of convolutional neural networks, specifically, the U-Net architecture. Complementing this data-driven analysis, our study also incorporates an analytical stability of the clustered states, providing a multifaceted perspective on the system's behavior. Our investigation not only sheds light on the nuanced behavior of swarmalators under second-order harmonics, but also demonstrates the efficacy of convolutional neural networks in analyzing complex dynamical systems.

The role of vision and lateral line sensing for schooling in giant danios (Devario aequipinnatus)

Schooling is a collective behavior that relies on a fish's ability to sense and respond to the other fish around it. Previous work has identified 'rules' of schooling - attraction to neighbors that are far away, repulsion from neighbors that are too close and alignment with neighbors at the correct distance - but we do not understand well how these rules emerge from the sensory physiology and behavior of individual fish. In particular, fish use both vision and their lateral lines to sense each other, but it is unclear how much they rely on information from these sensory modalities to coordinate schooling behavior. To address this question, we studied how the schooling of giant danios (Devario aequipinnatus) changes when they are unable to see or use their lateral lines. We found that giant danios were able to school without their lateral lines but did not school in darkness. Surprisingly, giant danios in darkness had the same attraction properties as fish in light when they were in close proximity, indicating that they could sense nearby fish with their lateral lines. However, they were not attracted to more distant fish, suggesting that long-distance attraction through vision is important for maintaining a cohesive school. These results help us expand our understanding of the roles that vision and the lateral line play in the schooling of some fish species.

Selective social interactions and speed-induced leadership in schooling fish

Animals moving together in groups are believed to interact among each other with effective social forces, such as attraction, repulsion, and alignment. Such forces can be inferred using "force maps," i.e., by analyzing the dependency of the acceleration of a focal individual on relevant variables. Here, we introduce a force map technique suitable for the analysis of the alignment forces experienced by individuals. After validating it using an agent-based model, we apply the force map to experimental data of schooling fish. We observe signatures of an effective alignment force with faster neighbors and an unexpected antialignment with slower neighbors. Instead of an explicit antialignment behavior, we suggest that the observed pattern is the result of a selective attention mechanism, where fish pay less attention to slower neighbors. This mechanism implies the existence of temporal leadership interactions based on relative speeds between neighbors. We present support for this hypothesis both from agent-based modeling as well as from exploring leader-follower relationships in the experimental data.

Extinct and extant termites reveal the fidelity of behavior fossilization in amber

Fossils encompassing multiple individuals provide rare direct evidence of behavioral interactions among extinct organisms. However, the fossilization process can alter the spatial relationship between individuals and hinder behavioral reconstruction. Here, we report a Baltic amber inclusion preserving a female-male pair of the extinct termite species Electrotermes affinis. The head-to-abdomen contact in the fossilized pair resembles the tandem courtship behavior of extant termites, although their parallel body alignment differs from the linear alignment typical of tandem runs. To solve this inconsistency, we simulated the first stage of amber formation, the immobilization of captured organisms, by exposing living termite tandems to sticky surfaces. We found that the posture of the fossilized pair matches trapped tandems and differs from untrapped tandems. Thus, the fossilized pair likely is a tandem running pair, representing the direct evidence of the mating behavior of extinct termites. Furthermore, by comparing the postures of partners on a sticky surface and in the amber inclusion, we estimated that the male likely performed the leader role in the fossilized tandem. Our results demonstrate that past behavioral interactions can be reconstructed despite the spatial distortion of body poses during fossilization. Our taphonomic approach demonstrates how certain behaviors can be inferred from fossil occurrences.

Rushing for "burned" food: Why and how does a group of patas monkeys (Erythrocebus patas) reach freshly burned areas?

Recently, considerable attention has been paid to animal adaptations to anthropogenic environments, such as foraging in burned areas where plants are promoted to regenerate by anthropogenic burning. However, among primates, reports on the utilization of resources that are available immediately after burning have been limited to a few primate species. In this study, we investigated and compared the activity budgets and food categories of a group of patas monkeys (Erythrocebus patas) in freshly burned areas by comparing them with those in previously burned areas and unburned areas. We also assessed the proportion of time spent in the freshly burned area before and after the fire: GPS collars were fitted to five of the six adults in the group, and their patterns when they traveled toward freshly burned and unburned feeding areas were compared. Patas monkeys spent more time in freshly burned areas after the fire, and they visited such areas mostly for feeding, particularly on roasted seeds of Cissus populnea. Furthermore, patas monkeys traveled faster and in a more synchronized way toward freshly burned areas. This "apparent goal-directed" travel began at least 1 h before arriving. Results indicate that the group recognized freshly burned areas as valuable, and the monkeys were able to travel in a goal-directed manner to them despite their variable locations. We suggest that smoke from freshly burned areas provides a visual cue with which to orient to the burned areas. Our results also support the notion that some primates are flexible enough to adapt to and benefit from anthropogenic environmental changes.

Predicting the long-term collective behaviour of fish pairs with deep learning

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social interactions in the fish species Hemigrammus rhodostomus. We compare the results of our deep learning approach with experiments and with the results of a state-of-the-art analytical model. To that end, we propose a systematic methodology to assess the faithfulness of a collective motion model, exploiting a set of stringent individual and collective spatio-temporal observables. We demonstrate that machine learning (ML) models of social interactions can directly compete with their analytical counterparts in reproducing subtle experimental observables. Moreover, this work emphasizes the need for consistent validation across different timescales, and identifies key design aspects that enable our deep learning approach to capture both short- and long-term dynamics. We also show that our approach can be extended to larger groups without any retraining, and to other fish species, while retaining the same architecture of the deep learning network. Finally, we discuss the added value of ML in the context of the study of collective motion in animal groups and its potential as a complementary approach to analytical models.

Pausing to swarm: locust intermittent motion is instrumental for swarming-related visual processing

Intermittent motion is prevalent in animal locomotion. Of special interest is the case of collective motion, in which social and environmental information must be processed in order to establish coordinated movement. We explored this nexus in locust, focusing on how intermittent motion interacts with swarming-related visual-based decision-making. Using a novel approach, we compared individual locust behaviour in response to continuously moving stimuli, with their response in semi-closed-loop conditions, in which the stimuli moved either in phase with the locust walking, or out of phase, i.e. only during the locust's pauses. Our findings clearly indicate the greater tendency of a locust to respond and 'join the swarming motion' when the visual stimuli were presented during its pauses. Hence, the current study strongly confirms previous indications of the dominant role of pauses in the collective motion-related decision-making of locusts. The presented insights contribute to a deeper general understanding of how intermittent motion contributes to group cohesion and coordination in animal swarms.

Swarmalators on a ring with uncorrelated pinning

We present a case study of swarmalators (mobile oscillators) that move on a 1D ring and are subject to pinning. Previous work considered the special case where the pinning in space and the pinning in the phase dimension were correlated. Here, we study the general case where the space and phase pinning are uncorrelated, both being chosen uniformly at random. This induces several new effects, such as pinned async, mixed states, and a first-order phase transition. These phenomena may be found in real world swarmalators, such as systems of vinegar eels, Janus matchsticks, electrorotated Quincke rollers, or Japanese tree frogs.

Shoaling behaviour in response to turbidity in three-spined sticklebacks

Many fresh and coastal waters are becoming increasingly turbid because of human activities, which may disrupt the visually mediated behaviours of aquatic organisms. Shoaling fish typically depend on vision to maintain collective behaviour, which has a range of benefits including protection from predators, enhanced foraging efficiency and access to mates. Previous studies of the effects of turbidity on shoaling behaviour have focussed on changes to nearest neighbour distance and average group-level behaviours. Here, we investigated whether and how experimental shoals of three-spined sticklebacks (Gasterosteus aculeatus) in clear (<10 Nephelometric Turbidity Units [NTU]) and turbid (~35 NTU) conditions differed in five local-level behaviours of individuals (nearest and furthest neighbour distance, heading difference with nearest neighbour, bearing angle to nearest neighbour and swimming speed). These variables are important for the emergent group-level properties of shoaling behaviour. We found an indirect effect of turbidity on nearest neighbour distances driven by a reduction in swimming speed, and a direct effect of turbidity which increased variability in furthest neighbour distances. In contrast, the alignment and relative position of individuals was not significantly altered in turbid compared to clear conditions. Overall, our results suggest that the shoals were usually robust to adverse effects of turbidity on collective behaviour, but group cohesion was occasionally lost during periods of instability.

Tuning social interactions' strength drives collective response to light intensity in schooling fish

Schooling fish heavily rely on visual cues to interact with neighbors and avoid obstacles. The availability of sensory information is influenced by environmental conditions and changes in the physical environment that can alter the sensory environment of the fish, which in turn affects individual and group movements. In this study, we combine experiments and data-driven modeling to investigate the impact of varying levels of light intensity on social interactions and collective behavior in rummy-nose tetra fish. The trajectories of single fish and groups of fish swimming in a tank under different lighting conditions were analyzed to quantify their movements and spatial distribution. Interaction functions between two individuals and the fish interaction with the tank wall were reconstructed and modeled for each light condition. Our results demonstrate that light intensity strongly modulates social interactions between fish and their reactions to obstacles, which then impact collective motion patterns that emerge at the group level.

Energetics of collective movement in vertebrates

The collective directional movement of animals occurs over both short distances and longer migrations, and is a critical aspect of feeding, reproduction and the ecology of many species. Despite the implications of collective motion for lifetime fitness, we know remarkably little about its energetics. It is commonly thought that collective animal motion saves energy: moving alone against fluid flow is expected to be more energetically expensive than moving in a group. Energetic conservation resulting from collective movement is most often inferred from kinematic metrics or from computational models. However, the direct measurement of total metabolic energy savings during collective motion compared with solitary movement over a range of speeds has yet to be documented. In particular, longer duration and higher speed collective motion must involve both aerobic and non-aerobic (high-energy phosphate stores and substrate-level phosphorylation) metabolic energy contributions, and yet no study to date has quantified both types of metabolic contribution in comparison to locomotion by solitary individuals. There are multiple challenging questions regarding the energetics of collective motion in aquatic, aerial and terrestrial environments that remain to be answered. We focus on aquatic locomotion as a model system to demonstrate that understanding the energetics and total cost of collective movement requires the integration of biomechanics, fluid dynamics and bioenergetics to unveil the hydrodynamic and physiological phenomena involved and their underlying mechanisms.

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.

Nearest Neighbour Node Deployment Algorithm for Mobile Sensor Networks

Many animal aggregations display remarkable collective coordinated movements on a large scale, which emerge as a result of distributed local decision-making by individuals. The recent advances in modelling the collective motion of animals through the utilisation of Nearest Neighbour rules, without the need for centralised coordination, resulted in the development of self-deployment algorithms in Mobile Sensor Networks (MSNs) to achieve various types of coverage essential for different applications. However, the energy consumption associated with sensor movement to achieve the desired coverage remains a significant concern for the majority of algorithms reported in the literature. In this paper, the Nearest Neighbour Node Deployment (NNND) algorithm is proposed to efficiently provide blanket coverage across a given area while minimising energy consumption and enhancing fault tolerance. In contrast to other algorithms that sequentially move sensors, NNND leverages the power of parallelism by employing multiple streams of sensor motions, each directed towards a distinct section of the area. The cohesion of each stream is maintained by adaptively choosing a leader for each stream while collision avoidance is also ensured. These properties contribute to minimising the travel distance within each stream, resulting in decreased energy consumption. Additionally, the utilisation of multiple leaders in NNND eliminates the presence of a single point of failure, hence enhancing the fault tolerance of the area coverage. The results of our extensive simulation study demonstrate that NNND not only achieves lower energy consumption but also a higher percentage of k-coverage.

Simulating individual movement in fish

Accurately quantifying an animal's movement is crucial for developing a greater empirical and theoretical understanding of its behaviour, and for simulating biologically plausible movement patterns. However, we have a relatively poor understanding of how animals move at fine temporal scales and in three-dimensional environments. Here, we collected high temporal resolution data on the three-dimensional spatial positions of individual three-spined sticklebacks (Gasterosteus aculeatus), allowing us to derive statistics describing key geometric characteristics of their movement and to quantify the extent to which this varies between individuals. We then used these statistics to develop a simple model of fish movement and evaluated the biological plausibility of simulated movement paths using a Turing-type test, which quantified the association preferences of live fish towards animated conspecifics following either 'real' (i.e., based on empirical measurements) or simulated movements. Live fish showed no difference in their response to 'real' movement compared to movement simulated by the model, although significantly preferred modelled movement over putatively unnatural movement patterns. The model therefore has the potential to facilitate a greater understanding of the causes and consequences of individual variation in movement, as well as enabling the construction of agent-based models or real-time computer animations in which individual fish move in biologically feasible ways.

Using neuronal models to capture burst-and-glide motion and leadership in fish

While mathematical models, in particular self-propelled particle models, capture many properties of large fish schools, they do not always capture the interactions of smaller shoals. Nor do these models tend to account for the use of intermittent locomotion, often referred to as burst-and-glide, by many species. In this paper, we propose a model of social burst-and-glide motion by combining a well-studied model of neuronal dynamics, the FitzHugh-Nagumo model, with a model of fish motion. We first show that our model can capture the motion of a single fish swimming down a channel. Extending to a two-fish model, where visual stimulus of a neighbour affects the internal burst or glide state of the fish, we observe a rich set of dynamics found in many species. These include: leader-follower behaviour; periodic changes in leadership; apparently random (i.e. chaotic) leadership change; and tit-for-tat turn taking. Moreover, unlike previous studies where a randomness is required for leadership switching to occur, we show that this can instead be the result of deterministic interactions. We give several empirically testable predictions for how bursting fish interact and discuss our results in light of recently established correlations between fish locomotion and brain activity.

Individual variation in spawning migration timing in a salmonid fish-Exploring roles of environmental and social cues

Describing and explaining patterns of individual animal behaviors in situ, and their repeatability over the annual cycle, is an emerging field in ecology owing largely to advances in tagging technology. We describe individual movements of adult Sakhalin taimen Parahucho perryi, an endangered salmonid fish, in the headwaters of a river in northern Japan during the spring spawning season over 2 years. Migration timing, separated into stages prior to, during, and following the spawning period, was found to be more consistent and repeatable for females than males. We hypothesized that the observed coordinated movement within seasons, and repeatability in migration timing across seasons, could result from (1) individual-specific responsiveness resulting from endogenous, biological traits that are mediated by environmental factors, or (2) social interactions among comigrating individuals. We found that water temperature and water level experienced by fish near the river mouth approximately a week before arrival at the spawning ground explained variability in run timing between years for females but not males. We found no evidence of conspecific attraction or repulsion resulting from social interactions among the spawners and post-spawners. We conclude that individual-specific responsiveness to environmental cues was the likely mechanism underpinning the observed migration timing and movement patterns.

Dynamics of collective motion across time and species

Most studies of collective animal behaviour rely on short-term observations, and comparisons of collective behaviour across different species and contexts are rare. We therefore have a limited understanding of intra- and interspecific variation in collective behaviour over time, which is crucial if we are to understand the ecological and evolutionary processes that shape collective behaviour. Here, we study the collective motion of four species: shoals of stickleback fish (Gasterosteus aculeatus), flocks of homing pigeons (Columba livia), a herd of goats (Capra aegagrus hircus) and a troop of chacma baboons (Papio ursinus). First, we describe how local patterns (inter-neighbour distances and positions), and group patterns (group shape, speed and polarization) during collective motion differ across each system. Based on these, we place data from each species within a 'swarm space', affording comparisons and generating predictions about the collective motion across species and contexts. We encourage researchers to add their own data to update the 'swarm space' for future comparative work. Second, we investigate intraspecific variation in collective motion over time and provide guidance for researchers on when observations made over different time scales can result in confident inferences regarding species collective motion. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Inferring social influence in animal groups across multiple timescales

Many animal behaviours exhibit complex temporal dynamics, suggesting there are multiple timescales at which they should be studied. However, researchers often focus on behaviours that occur over relatively restricted temporal scales, typically ones that are more accessible to human observation. The situation becomes even more complex when considering multiple animals interacting, where behavioural coupling can introduce new timescales of importance. Here, we present a technique to study the time-varying nature of social influence in mobile animal groups across multiple temporal scales. As case studies, we analyse golden shiner fish and homing pigeons, which move in different media. By analysing pairwise interactions among individuals, we show that predictive power of the factors affecting social influence depends on the timescale of analysis. Over short timescales the relative position of a neighbour best predicts its influence and the distribution of influence across group members is relatively linear, with a small slope. At longer timescales, however, both relative position and kinematics are found to predict influence, and nonlinearity in the influence distribution increases, with a small number of individuals being disproportionately influential. Our results demonstrate that different interpretations of social influence arise from analysing behaviour at different timescales, highlighting the importance of considering its multiscale nature. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Lekking as collective behaviour

Lekking is a spectacular mating system in which males maintain tightly organized clustering of territories during the mating season, and females visit these leks for mating. Various hypotheses-ranging from predation dilution to mate choice and mating benefit-offer potential explanations for the evolution of this peculiar mating system. However, many of these classic hypotheses rarely consider the spatial dynamics that produce and maintain the lek. In this article, we propose to view lekking through the perspective of collective behaviour, in which simple local interactions between organisms, as well as habitat, likely produce and maintain lekking. Further, we argue that interactions within the leks change over time, typically over a breeding season, to produce many broad-level as well as specific collective patterns. To test these ideas at both proximate and ultimate levels, we argue that the concepts and tools from the literature on collective animal behaviour, such as agent-based models and high-resolution video tracking that enables capturing fine-scale spatio-temporal interactions, could be useful. To demonstrate the promise of these ideas, we develop a spatially explicit agent-based model and show how simple rules such as spatial fidelity, local social interactions and repulsion among males can potentially explain the formation of lek and synchronous departures of males for foraging from the lek. On the empirical side, we discuss the promise of applying the collective behaviour approach to blackbuck (Antilope cervicapra) leks-using high-resolution recordings via a camera fitted to unmanned aerial vehicles and subsequent tracking of animal movements. Broadly, we suggest that a lens of collective behaviour may provide novel insights into understanding both the proximate and ultimate factors that shape leks. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Social Synchronization of Conditioned Fear in Mice Requires Ventral Hippocampus Input to the Amygdala

BACKGROUND

Social organisms synchronize behaviors as an evolutionary-conserved means of thriving. Synchronization under threat, in particular, benefits survival and occurs across species, including humans, but the underlying mechanisms remain unknown because of the scarcity of relevant animal models. Here, we developed a rodent paradigm in which mice synchronized a classically conditioned fear response and identified an underlying neuronal circuit.

METHODS

Male and female mice were trained individually using auditory fear conditioning and then tested 24 hours later as dyads while allowing unrestricted social interaction during exposure to the conditioned stimulus under visible or infrared illumination to eliminate visual cues. The synchronization of the immobility or freezing bouts was quantified by calculating the effect size Cohen's d for the difference between the actual freezing time overlap and the overlap by chance. The inactivation of the dorsomedial prefrontal cortex, dorsal hippocampus, or ventral hippocampus was achieved by local infusions of muscimol. The chemogenetic disconnection of the hippocampus-amygdala pathway was performed by expressing hM4D(Gi) in the ventral hippocampal neurons and infusing clozapine N-oxide in the amygdala.

RESULTS

Mice synchronized cued but not contextual fear. It was higher in males than in females and attenuated in the absence of visible light. Inactivation of the ventral but not dorsal hippocampus or dorsomedial prefrontal cortex abolished fear synchronization. Finally, the disconnection of the hippocampus-amygdala pathway diminished fear synchronization.

CONCLUSIONS

Mice synchronize expression of conditioned fear relying on the ventral hippocampus-amygdala pathway, suggesting that the hippocampus transmits social information to the amygdala to synchronize threat response.

Visual processing and collective motion-related decision-making in desert locusts

Collectively moving groups of animals rely on the decision-making of locally interacting individuals in order to maintain swarm cohesion. However, the complex and noisy visual environment poses a major challenge to the extraction and processing of relevant information. We addressed this challenge by studying swarming-related decision-making in desert locust last-instar nymphs. Controlled visual stimuli, in the form of random dot kinematograms, were presented to tethered locust nymphs in a trackball set-up, while monitoring movement trajectory and walking parameters. In a complementary set of experiments, the neurophysiological basis of the observed behavioural responses was explored. Our results suggest that locusts use filtering and discrimination upon encountering multiple stimuli simultaneously. Specifically, we show that locusts are sensitive to differences in speed at the individual conspecific level, and to movement coherence at the group level, and may use these to filter out non-relevant stimuli. The locusts also discriminate and assign different weights to different stimuli, with an observed interactive effect of stimulus size, relative abundance and motion direction. Our findings provide insights into the cognitive abilities of locusts in the domain of decision-making and visual-based collective motion, and support locusts as a model for investigating sensory-motor integration and motion-related decision-making in the intricate swarm environment.

Long-range connections are crucial for synchronization transition in a computational model of Drosophila brain dynamics

The synchronization transition type has been the focus of attention in recent years because it is associated with many functional characteristics of the brain. In this paper, the synchronization transition in neural networks with sleep-related biological drives in Drosophila is investigated. An electrical synaptic neural network is established to research the difference between the synchronization transition of the network during sleep and wake, in which neurons regularly spike during sleep and chaotically spike during wake. The synchronization transition curves are calculated mainly using the global instantaneous order parameters S. The underlying mechanisms and types of synchronization transition during sleep are different from those during wake. During sleep, regardless of the network structure, a frustrated (discontinuous) transition can be observed. Moreover, the phenomenon of quasi periodic partial synchronization is observed in ring-shaped regular network with and without random long-range connections. As the network becomes dense, the synchronization of the network only needs to slightly increase the coupling strength g. While during wake, the synchronization transition of the neural network is very dependent on the network structure, and three mechanisms of synchronization transition have emerged: discontinuous synchronization (explosive synchronization and frustrated synchronization), and continuous synchronization. The random long-range connections is the main topological factor that plays an important role in the resulting synchronization transition. Furthermore, similarities and differences are found by comparing synchronization transition research for the Hodgkin-Huxley neural network in the beta-band and gammma-band, which can further improve the synchronization phase transition research of biologically motivated neural networks. A complete research framework can also be used to study coupled nervous systems, which can be extended to general coupled dynamic systems.

The structure inference of flocking systems based on the trajectories

The interaction between the swarm individuals affects the dynamic behavior of the swarm, but it is difficult to obtain directly from outside observation. Therefore, the problem we focus on is inferring the structure of the interactions in the swarm from the individual behavior trajectories. Similar inference problems that existed in network science are named network reconstruction or network inference. It is a fundamental problem pervading research on complex systems. In this paper, a new method, called Motion Trajectory Similarity, is developed for inferring direct interactions from the motion state of individuals in the swarm. It constructs correlations by combining the similarity of the motion trajectories of each cross section of the time series, in which individuals with highly similar motion states are more likely to interact with each other. Experiments on the flocking systems demonstrate that our method can produce a reliable interaction inference and outperform traditional network inference methods. It can withstand a high level of noise and time delay introduced into flocking models, as well as parameter variation in the flocking system, to achieve robust reconstruction. The proposed method provides a new perspective for inferring the interaction structure of a swarm, which helps us to explore the mechanisms of collective movement in swarms and paves the way for developing the flocking models that can be quantified and predicted.

Braitenberg Vehicles as Developmental Neurosimulation

Connecting brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. As is standard among models of artificial and biological neural networks, an analogue of the fully mature brain is presented as a blank slate. However, this does not consider the realities of biological development and developmental learning. Our purpose is to model the development of an artificial organism that exhibits complex behaviors. We introduce three alternate approaches to demonstrate how developmental embodied agents can be implemented. The resulting developmental Braitenberg vehicles (dBVs) will generate behaviors ranging from stimulus responses to group behavior that resembles collective motion. We will situate this work in the domain of artificial brain networks along with broader themes such as embodied cognition, feedback, and emergence. Our perspective is exemplified by three software instantiations that demonstrate how a BV-genetic algorithm hybrid model, a multisensory Hebbian learning model, and multi-agent approaches can be used to approach BV development. We introduce use cases such as optimized spatial cognition (vehicle-genetic algorithm hybrid model), hinges connecting behavioral and neural models (multisensory Hebbian learning model), and cumulative classification (multi-agent approaches). In conclusion, we consider future applications of the developmental neurosimulation approach.

Does a roosting flock of migratory birds also echelon in high winds?

The organized aerial manoeuvres of birds in “V” and “J” flock echelons have always captivated onlookers and several of these aspects are still a matter of ongoing research. However, we could not find any published evidence or report on echeloning in a roosting flock of birds in high wind conditions. Here, we provide first evidence of an echelon in a roosting flock of the Eurasian oystercatcher (Haematopus ostralegus ostralegus) at the onset of Storm Malik in Scotland on the morning of the 29th of January 2022, under ~ 11 ms−1 winds. This observation opens-up several new research questions on if, how, and why birds position themselves in a flock while roosting in high winds.

The social transmission of stress in animal collectives

The stress systems are powerful mediators between the organism's systemic dynamic equilibrium and changes in its environment beyond the level of anticipated fluctuations. Over- or under-activation of the stress systems' responses can impact an animal's health, survival and reproductive success. While physiological stress responses and their influence on behaviour and performance are well understood at the individual level, it remains largely unknown whether-and how-stressed individuals can affect the stress systems of other group members, and consequently their collective behaviour. Stressed individuals could directly signal the presence of a stressor (e.g. via an alarm call or pheromones), or an acute or chronic activation of the stress systems could be perceived by others (as an indirect cue) and spread via social contagion. Such social transmission of stress responses could then amplify the effects of stressors by impacting social interactions, social dynamics and the collective performance of groups. As the neuroendocrine pathways of the stress response are highly conserved among vertebrates, transmission of physiological stress states could be more widespread among non-human animals than previously thought. We therefore suggest that identifying the extent to which stress transmission modulates animal collectives represents an important research avenue.

The limits of convergence in the collective behavior of competing marine taxa

Collective behaviors in biological systems such as coordinated movements have important ecological and evolutionary consequences. While many studies examine within-species variation in collective behavior, explicit comparisons between functionally similar species from different taxonomic groups are rare. Therefore, a fundamental question remains: how do collective behaviors compare between taxa with morphological and physiological convergence, and how might this relate to functional ecology and niche partitioning? We examined the collective motion of two ecologically similar species from unrelated clades that have competed for pelagic predatory niches for over 500 million years-California market squid, Doryteuthis opalescens (Mollusca) and Pacific sardine, Sardinops sagax (Chordata). We (1) found similarities in how groups of individuals from each species collectively aligned, measured by angular deviation, the difference between individual orientation and average group heading. We also (2) show that conspecific attraction, which we approximated using nearest neighbor distance, was greater in sardine than squid. Finally, we (3) found that individuals of each species explicitly matched the orientation of groupmates, but that these matching responses were less rapid in squid than sardine. Based on these results, we hypothesize that information sharing is a comparably important function of social grouping for both taxa. On the other hand, some capabilities, including hydrodynamically conferred energy savings and defense against predators, could stem from taxon-specific biology.

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.

Flexible group cohesion and coordination, but robust leader-follower roles, in a wild social primate using urban space

Collective behaviour has a critical influence on group social structure and organization, individual fitness and social evolution, but we know little about whether and how it changes in anthropogenic environments. Here, we show multiple and varying effects of urban space-use upon group-level processes in a primate generalist-the chacma baboon (Papio ursinus)-within a managed wild population living at the urban edge in the City of Cape Town, South Africa. In natural space, we observe baboon-typical patterns of collective behaviour. By contrast, in urban space (where there are increased risks, but increased potential for high-quality food rewards), baboons show extreme flexibility in collective behaviour, with changes in spatial cohesion and association networks, travel speeds and group coordination. However, leader-follower roles remain robust across natural and urban space, with adult males having a disproportionate influence on the movement of group members. Their important role in the group's collective behaviour complements existing research and supports the management tactic employed by field rangers of curbing the movements of adult males, which indirectly deters the majority of the group from urban space. Our findings highlight both flexibility and robustness in collective behaviour when groups are presented with novel resources and heightened risks.

The Energy Homeostasis Principle: A Naturalistic Approach to Explain the Emergence of Behavior

It is still elusive to explain the emergence of behavior and understanding based on its neural mechanisms. One renowned proposal is the Free Energy Principle (FEP), which uses an information-theoretic framework derived from thermodynamic considerations to describe how behavior and understanding emerge. FEP starts from a whole-organism approach, based on mental states and phenomena, mapping them into the neuronal substrate. An alternative approach, the Energy Homeostasis Principle (EHP), initiates a similar explanatory effort but starts from single-neuron phenomena and builds up to whole-organism behavior and understanding. In this work, we further develop the EHP as a distinct but complementary vision to FEP and try to explain how behavior and understanding would emerge from the local requirements of the neurons. Based on EHP and a strict naturalist approach that sees living beings as physical and deterministic systems, we explain scenarios where learning would emerge without the need for volition or goals. Given these starting points, we state several considerations of how we see the nervous system, particularly the role of the function, purpose, and conception of goal-oriented behavior. We problematize these conceptions, giving an alternative teleology-free framework in which behavior and, ultimately, understanding would still emerge. We reinterpret neural processing by explaining basic learning scenarios up to simple anticipatory behavior. Finally, we end the article with an evolutionary perspective of how this non-goal-oriented behavior appeared. We acknowledge that our proposal, in its current form, is still far from explaining the emergence of understanding. Nonetheless, we set the ground for an alternative neuron-based framework to ultimately explain understanding.

Emergence and repeatability of leadership and coordinated motion in fish shoals

Studies of self-organizing groups like schools of fish or flocks of birds have sought to uncover the behavioral rules individuals use (local-level interactions) to coordinate their motion (global-level patterns). However, empirical studies tend to focus on short-term or one-off observations where coordination has already been established or describe transitions between different coordinated states. As a result, we have a poor understanding of how behavioral rules develop and are maintained in groups. Here, we study the emergence and repeatability of coordinated motion in shoals of stickleback fish (Gasterosteus aculeatus). Shoals were introduced to a simple environment, where their spatio-temporal position was deduced via video analysis. Using directional correlation between fish velocities and wavelet analysis of fish positions, we demonstrate how shoals that are initially uncoordinated in their motion quickly transition to a coordinated state with defined individual leader-follower roles. The identities of leaders and followers were repeatable across two trials, and coordination was reached more quickly during the second trial and by groups of fish with higher activity levels (tested before trials). The rapid emergence of coordinated motion and repeatability of social roles in stickleback fish shoals may act to reduce uncertainty of social interactions in the wild, where individuals live in a system with high fission-fusion dynamics and non-random patterns of association.

Unveiling social distancing mechanisms via a fish-robot hybrid interaction

Pathogen transmission is a major limit of social species. Social distancing, a behavioural-based response to diseases, has been regularly reported in nature. However, the identification of distinctive stimuli associated with an infectious disease represents a challenging task for host species, whose cognitive mechanisms are still poorly understood. Herein, the social fish Paracheirodon innesi, was selected as model organism to investigate animal abilities in exploiting visual information to identify and promote social distancing towards potentially infected conspecifics. To address this, a robotic fish replica mimicking a healthy P. innesi subject, and another mimicking P. innesi with morphological and/or locomotion anomalies were developed. P. innesi individuals were attracted by the healthy fish replica, while they avoided the fish replica with morphological abnormalities, as well as the fish replica with an intact appearance, but performing locomotion anomalies (both symptoms associated with a microsporidian parasite infesting P. innesi and other fish). Furthermore, the fish replica presenting both morphology and locomotion anomalies in conjunction, triggered a significantly stronger social distancing response. This confirms the hypothesis that group living animals overgeneralize cues that can be related with a disease to minimize transmission, and highlights the important role of visual cues in infection risk contexts. This study prompts more attention on the role of behavioural-based strategies to avoid pathogen/parasite diffusion, and can be used to optimize computational approaches to model disease dynamics.

Synchronization of nonlinearly coupled networks based on circle criterion

The problem of synchronization in networks of linear systems with nonlinear diffusive coupling and a connected undirected graph is studied. By means of a coordinate transformation, the system is reduced to the form of mean-field dynamics and a synchronization-error system. The network synchronization conditions are established based on the stability conditions of the synchronization-error system obtained using the circle criterion, and the results are used to derive the condition for synchronization in a network of neural-mass-model populations with a connected undirected graph. Simulation examples are presented to illustrate the obtained results.

Pedestrian flow in two dimensions: Optimal psychological stress leads to less evacuation time and decongestion

Collective motion is an innate ability of all living systems, which depends on physiological and psychosocial factors in the case of humans. Such a collective organization is becoming of great interest in collective motion in human crowds. Using a cellular automaton (CA) simulation model, we demonstrate that emergency egress from a two-dimensional corridor with optimal stress leads to less evacuation time and efficient mass evacuations. We study how three types of stress (i.e., mild stress, optimal stress, and anxiety) described in the literature have a significant impact on the collective dynamics. We found that low-stress levels could decrease the evacuation time in an entire occupied room since agents choose alternative routes rather than the shortest path to the exit and display cooperative behavior. Therefore, the combination of mild and optimal stress can lead to efficient evacuations. Also CA simulations may be used to find safer and more efficient ways to conduct mass evacuation procedures.

Coordination of movement via complementary interactions of leaders and followers in termite mating pairs

In collective animal motion, coordination is often achieved by feedback between leaders and followers. For stable coordination, a leader's signals and a follower's responses are hypothesized to be attuned to each other. However, their roles are difficult to disentangle in species with highly coordinated movements, hiding potential diversity of behavioural mechanisms for collective behaviour. Here, we show that two Coptotermes termite species achieve a similar level of coordination via distinct sets of complementary leader-follower interactions. Even though C. gestroi females produce less pheromone than C. formosanus, tandem runs of both species were stable. Heterospecific pairs with C. gestroi males were also stable, but not those with C. formosanus males. We attributed this to the males' adaptation to the conspecific females; C. gestroi males have a unique capacity to follow females with small amounts of pheromone, while C. formosanus males reject C. gestroi females as unsuitable but are competitive over females with large amounts of pheromone. An information-theoretic analysis supported this conclusion by detecting information flow from female to male only in stable tandems. Our study highlights cryptic interspecific variation in movement coordination, a source of novelty for the evolution of social interactions.

Honeybee communication during collective defence is shaped by predation

BACKGROUND

Social insect colonies routinely face large vertebrate predators, against which they need to mount a collective defence. To do so, honeybees use an alarm pheromone that recruits nearby bees into mass stinging of the perceived threat. This alarm pheromone is carried directly on the stinger; hence, its concentration builds up during the course of the attack. We investigate how bees react to different alarm pheromone concentrations and how this evolved response pattern leads to better coordination at the group level.

RESULTS

We first present a dose-response curve to the alarm pheromone, obtained experimentally. This data reveals two phases in the bees' response: initially, bees become more likely to sting as the alarm pheromone concentration increases, but aggressiveness drops back when very high concentrations are reached. Second, we apply Projective Simulation to model each bee as an artificial learning agent that relies on the pheromone concentration to decide whether to sting or not. Individuals are rewarded based on the collective performance, thus emulating natural selection in these complex societies. By also modelling predators in a detailed way, we are able to identify the main selection pressures that shaped the response pattern observed experimentally. In particular, the likelihood to sting in the absence of alarm pheromone (starting point of the dose-response curve) is inversely related to the rate of false alarms, such that bees in environments with low predator density are less likely to waste efforts responding to irrelevant stimuli. This is compensated for by a steep increase in aggressiveness when the alarm pheromone concentration starts rising. The later decay in aggressiveness may be explained as a curbing mechanism preventing worker loss.

CONCLUSIONS

Our work provides a detailed understanding of alarm pheromone responses in honeybees and sheds light on the selection pressures that brought them about. In addition, it establishes our approach as a powerful tool to explore how selection based on a collective outcome shapes individual responses, which remains a challenging issue in the field of evolutionary biology.