Reverse social contagion as a mechanism for regulating mass behaviors in highly integrated social systems.

Mass behavior is the rapid adoption of similar conduct by all group members, with potentially catastrophic outcomes such as mass panic. Yet, these negative consequences are rare in integrated social systems such as social insect colonies, thanks to mechanisms of social regulation. Here, we test the hypothesis that behavioral deactivation between active individuals is a powerful social regulator that reduces energetic spending in groups. Borrowing from scaling theories for human settlements and using behavioral data on harvester ants, we derive ties between the hypermetric scaling of the interaction network and the hypometric scaling of activity levels, both relative to the colony size. We use elements of economics theory and metabolic measurements collected with the behavioral data to link activity and metabolic scalings with group size. Our results support the idea that metabolic scaling across social systems is the product of different balances between their social regulation mechanisms.

Motile Living Biobots Self-Construct from Adult Human Somatic Progenitor Seed Cells.

Fundamental knowledge gaps exist about the plasticity of cells from adult soma and the potential diversity of body shape and behavior in living constructs derived from genetically wild-type cells. Here anthrobots are introduced, a spheroid-shaped multicellular biological robot (biobot) platform with diameters ranging from 30 to 500 microns and cilia-powered locomotive abilities. Each Anthrobot begins as a single cell, derived from the adult human lung, and self-constructs into a multicellular motile biobot after being cultured in extra cellular matrix for 2 weeks and transferred into a minimally viscous habitat. Anthrobots exhibit diverse behaviors with motility patterns ranging from tight loops to straight lines and speeds ranging from 5-50 microns s-1 . The anatomical investigations reveal that this behavioral diversity is significantly correlated with their morphological diversity. Anthrobots can assume morphologies with fully polarized or wholly ciliated bodies and spherical or ellipsoidal shapes, each related to a distinct movement type. Anthrobots are found to be capable of traversing, and inducing rapid repair of scratches in, cultured human neural cell sheets in vitro. By controlling microenvironmental cues in bulk, novel structures, with new and unexpected behavior and biomedically-relevant capabilities, can be discovered in morphogenetic processes without direct genetic editing or manual sculpting.

A simple mechanism for collective decision-making in the absence of payoff information.

Animals are often faced with time-critical decisions without prior information about their actions' outcomes. In such scenarios, individuals budget their investment into the task to cut their losses in case of an adverse outcome. In animal groups, this may be challenging because group members can only access local information, and consensus can only be achieved through distributed interactions among individuals. Here, we combined experimental analyses with theoretical modeling to investigate how groups modulate their investment into tasks in uncertain conditions. Workers of the arboreal weaver ant Oecophylla smaragdina form three-dimensional chains using their own bodies to bridge vertical gaps between existing trails and new areas to explore. The cost of a chain increases with its length because ants participating in the structure are prevented from performing other tasks. The payoffs of chain formation, however, remain unknown to the ants until the chain is complete and they can explore the new area. We demonstrate that weaver ants cap their investment into chains, and do not form complete chains when the gap is taller than 90 mm. We show that individual ants budget the time they spend in chains depending on their distance to the ground, and propose a distance-based model of chain formation that explains the emergence of this tradeoff without the need to invoke complex cognition. Our study provides insights into the proximate mechanisms that lead individuals to engage (or not) in collective actions and furthers our knowledge of how decentralized groups make adaptive decisions in uncertain conditions.

Steering self-organisation through confinement.

Self-organisation is the spontaneous emergence of spatio-temporal structures and patterns from the interaction of smaller individual units. Examples are found across many scales in very different systems and scientific disciplines, from physics, materials science and robotics to biology, geophysics and astronomy. Recent research has highlighted how self-organisation can be both mediated and controlled by confinement. Confinement is an action over a system that limits its units' translational and rotational degrees of freedom, thus also influencing the system's phase space probability density; it can function as either a catalyst or inhibitor of self-organisation. Confinement can then become a means to actively steer the emergence or suppression of collective phenomena in space and time. Here, to provide a common framework and perspective for future research, we examine the role of confinement in the self-organisation of soft-matter systems and identify overarching scientific challenges that need to be addressed to harness its full scientific and technological potential in soft matter and related fields. By drawing analogies with other disciplines, this framework will accelerate a common deeper understanding of self-organisation and trigger the development of innovative strategies to steer it using confinement, with impact on, e.g., the design of smarter materials, tissue engineering for biomedicine and in guiding active matter.

Ontogeny of collective behaviour.

During their lifetime, superorganisms, like unitary organisms, undergo transformations that change the machinery of their collective behaviour. Here, we suggest that these transformations are largely understudied and propose that more systematic research into the ontogeny of collective behaviours is needed if we hope to better understand the link between proximate behavioural mechanisms and the development of collective adaptive functions. In particular, certain social insects engage in self-assemblage, forming dynamic and physically connected architectures with striking similarities to developing multicellular organisms, making them good model systems for ontogenetic studies of collective behaviour. However, exhaustive time series and three-dimensional data are required to thoroughly characterize the different life stages of the collective structures and the transitions between these stages. The well-established fields of embryology and developmental biology offer practical tools and theoretical frameworks that could speed up the acquisition of new knowledge about the formation, development, maturity and dissolution of social insect self-assemblages and, by extension, other superorganismal behaviours. We hope that this review will encourage an expansion of the ontogenetic perspective in the field of collective behaviour and, in particular, in self-assemblage research, which has far-reaching applications in robotics, computer science and regenerative medicine. This article is part of a discussion meeting issue 'Collective behaviour through time'.

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'.

Hysteresis stabilizes dynamic control of self-assembled army ant constructions.

Biological systems must adjust to changing external conditions, and their resilience depends on their control mechanisms. How is dynamic control implemented in noisy, decentralized systems? Army ants' self-assembled bridges are built on unstable features, like leaves, which frequently move. Using field experiments and simulations, we characterize the bridges' response as the gaps they span change in size, identify the control mechanism, and explore how this emerges from individuals' decisions. For a given gap size, bridges were larger after the gap increased rather than decreased. This hysteresis was best explained by an accumulator model, in which individual decisions to join or leave a bridge depend on the difference between its current and equilibrium state. This produces robust collective structures that adjust to lasting perturbations while ignoring small, momentary shifts. Our field data support separate joining and leaving cues; joining is prompted by high bridge performance and leaving by an excess of ants. This leads to stabilizing hysteresis, an important feature of many biological and engineered systems.

Simulated poaching affects global connectivity and efficiency in social networks of African savanna elephants-An exemplar of how human disturbance impacts group-living species.

Selective harvest, such as poaching, impacts group-living animals directly through mortality of individuals with desirable traits, and indirectly by altering the structure of their social networks. Understanding the relationship between disturbance-induced, structural network changes and group performance in wild animals remains an outstanding problem. To address this problem, we evaluated the immediate effect of disturbance on group sociality in African savanna elephants-an example, group-living species threatened by poaching. Drawing on static association data from ten free-ranging groups, we constructed one empirically based, population-wide network and 100 virtual networks; performed a series of experiments 'poaching' the oldest, socially central or random individuals; and quantified the immediate change in the theoretical indices of network connectivity and efficiency of social diffusion. Although the social networks never broke down, targeted elimination of the socially central conspecifics, regardless of age, decreased network connectivity and efficiency. These findings hint at the need to further study resilience by modeling network reorganization and interaction-mediated socioecological learning, empirical data permitting. The main contribution of our work is in quantifying connectivity together with global efficiency in multiple social networks that feature the sociodemographic diversity likely found in wild elephant populations. The basic design of our simulation makes it adaptable for hypothesis testing about the consequences of anthropogenic disturbance or lethal management on social interactions in a variety of group-living species with limited, real-world data.

A cellular platform for the development of synthetic living machines.

Robot swarms have, to date, been constructed from artificial materials. Motile biological constructs have been created from muscle cells grown on precisely shaped scaffolds. However, the exploitation of emergent self-organization and functional plasticity into a self-directed living machine has remained a major challenge. We report here a method for generation of in vitro biological robots from frog (Xenopus laevis) cells. These xenobots exhibit coordinated locomotion via cilia present on their surface. These cilia arise through normal tissue patterning and do not require complicated construction methods or genomic editing, making production amenable to high-throughput projects. The biological robots arise by cellular self-organization and do not require scaffolds or microprinting; the amphibian cells are highly amenable to surgical, genetic, chemical, and optical stimulation during the self-assembly process. We show that the xenobots can navigate aqueous environments in diverse ways, heal after damage, and show emergent group behaviors. We constructed a computational model to predict useful collective behaviors that can be elicited from a xenobot swarm. In addition, we provide proof of principle for a writable molecular memory using a photoconvertible protein that can record exposure to a specific wavelength of light. Together, these results introduce a platform that can be used to study many aspects of self-assembly, swarm behavior, and synthetic bioengineering, as well as provide versatile, soft-body living machines for numerous practical applications in biomedicine and the environment.

Individual error correction drives responsive self-assembly of army ant scaffolds.

An inherent strength of evolved collective systems is their ability to rapidly adapt to dynamic environmental conditions, offering resilience in the face of disruption. This is thought to arise when individual sensory inputs are filtered through local interactions, producing an adaptive response at the group level. To understand how simple rules encoded at the individual level can lead to the emergence of robust group-level (or distributed) control, we examined structures we call "scaffolds," self-assembled by Eciton burchellii army ants on inclined surfaces that aid travel during foraging and migration. We conducted field experiments with wild E. burchellii colonies, manipulating the slope over which ants traversed, to examine the formation of scaffolds and their effects on foraging traffic. Our results show that scaffolds regularly form on inclined surfaces and that they reduce losses of foragers and prey, by reducing slipping and/or falling of ants, thus facilitating traffic flow. We describe the relative effects of environmental geometry and traffic on their growth and present a theoretical model to examine how the individual behaviors underlying scaffold formation drive group-level effects. Our model describes scaffold growth as a control response at the collective level that can emerge from individual error correction, requiring no complex communication among ants. We show that this model captures the dynamics observed in our experiments and is able to predict the growth-and final size-of scaffolds, and we show how the analytical solution allows for estimation of these dynamics.

Ant Collective Behavior Is Heritable and Shaped by Selection.

AbstractCollective behaviors are widespread in nature and usually assumed to be strongly shaped by natural selection. However, the degree to which variation in collective behavior is heritable and has fitness consequences-the two prerequisites for evolution by natural selection-is largely unknown. We used a new pharaoh ant (Monomorium pharaonis) mapping population to estimate the heritability, genetic correlations, and fitness consequences of three collective behaviors (foraging, aggression, and exploration), as well as of body size, sex ratio, and caste ratio. Heritability estimates for the collective behaviors were moderate, ranging from 0.17 to 0.32, but lower than our estimates for the heritability of caste ratio, sex ratio, and body size of new workers, queens, and males. Moreover, variation in collective behaviors among colonies was phenotypically correlated, suggesting that selection may shape multiple colony collective behaviors simultaneously. Finally, we found evidence for directional selection that was similar in strength to estimates of selection in natural populations. Altogether, our study begins to elucidate the genetic architecture of collective behavior and is one of the first studies to demonstrate that it is shaped by selection.

Collective Pulsing in Xeniid Corals: Part I-Using Computer Vision and Information Theory to Search for Coordination.

Xeniid corals (Cnidaria: Alcyonacea), a family of soft corals, include species displaying a characteristic pulsing behavior. This behavior has been shown to increase oxygen diffusion away from the coral tissue, resulting in higher photosynthetic rates from mutualistic symbionts. Maintaining such a pulsing behavior comes at a high energetic cost, and it has been proposed that coordinating the pulse of individual polyps within a colony might enhance the efficiency of fluid transport. In this paper, we test whether patterns of collective pulsing emerge in coral colonies and investigate possible interactions between polyps within a colony. We video recorded different colonies of Heteroxenia sp. in a laboratory environment. Our methodology is based on the systematic integration of a computer vision algorithm (ISOMAP) and an information-theoretic approach (transfer entropy), offering a vantage point to assess coordination in collective pulsing. Perhaps surprisingly, we did not detect any form of collective pulsing behavior in the colonies. Using artificial data sets, however, we do demonstrate that our methodology is capable of detecting even weak information transfer. The lack of a coordination is consistent with previous work on many cnidarians where coordination between actively pulsing polyps and medusa has not been observed. In our companion paper, we show that there is no fluid dynamic benefit of coordinated pulsing, supporting this result. The lack of coordination coupled with no obvious fluid dynamic benefit to grouping suggests that there may be non-fluid mechanical advantages to forming colonies, such as predator avoidance and defense.

Genetic lineage tracing of targeted cell populations during enthesis healing.

Rotator cuff supraspinatus tendon injuries are clinically challenging due to the high rates of failure after surgical repair. One key limitation to functional healing is the failure to regenerate the enthesis transition between tendon and bone, which heals by disorganized scar formation. Using two models of supraspinatus tendon injury in mouse (partial tear and full detachment/repair), the purpose of the study was to determine functional gait outcomes and identify the origin of the cells that mediate healing. Consistent with previous reports, enthesis injuries did not regenerate; partial tear resulted in a localized scar defect adjacent to intact enthesis, while full detachment with repair resulted in full disruption of enthesis alignment and massive scar formation between tendon and enthesis fibrocartilage. Although gait after partial tear injury was largely normal, gait was permanently impaired after full detachment/repair. Genetic lineage tracing of intrinsic tendon and cartilage/fibrocartilage cells (ScxCreERT2 and Sox9CreERT2 , respectively), myofibroblasts (αSMACreERT2 ), and Wnt-responsive stem cells (Axin2CreERT2 ) failed to identify scar-forming cells in partial tear injury. Unmineralized enthesis fibrocartilage was strongly labeled by Sox9CreERT2 while Axin2CrERT2 labeled a subset of tendon cells away from the skeletal insertion site. In contrast to the partial tear model, Axin2CreERT2 labeling showed considerable contribution of Axin2lin cells to the scar after full detachment/repair. Clinical Significance: Clinically relevant models of rotator cuff tendon injuries in mouse enable the use of genetic tools; lineage tracing suggests that distinct mechanisms of healing are activated with full detachment/repair injuries versus partial tear. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:3275-3284, 2018.

Architecture, space and information in constructions built by humans and social insects: a conceptual review.

The similarities between the structures built by social insects and by humans have led to a convergence of interests between biologists and architects. This new, de facto interdisciplinary community of scholars needs a common terminology and theoretical framework in which to ground its work. In this conceptually oriented review paper, we review the terms 'information', 'space' and 'architecture' to provide definitions that span biology and architecture. A framework is proposed on which interdisciplinary exchange may be better served, with the view that this will aid better cross-fertilization between disciplines, working in the areas of collective behaviour and analysis of the structures and edifices constructed by non-humans; and to facilitate how this area of study may better contribute to the field of architecture. We then use these definitions to discuss the informational content of constructions built by organisms and the influence these have on behaviour, and vice versa. We review how spatial constraints inform and influence interaction between an organism and its environment, and examine the reciprocity of space and information on construction and the behaviour of humans and social insects.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'.

Methods for the effective study of collective behavior in a radial arm maze.

Collective behaviors are observed throughout nature, from bacterial colonies to human societies. Important theoretical breakthroughs have recently been made in understanding why animals produce group behaviors and how they coordinate their activities, build collective structures, and make decisions. However, standardized experimental methods to test these findings have been lacking. Notably, easily and unambiguously determining the membership of a group and the responses of an individual within that group is still a challenge. The radial arm maze is presented here as a new standardized method to investigate collective exploration and decision-making in animal groups. This paradigm gives individuals within animal groups the opportunity to make choices among a set of discrete alternatives, and these choices can easily be tracked over long periods of time. We demonstrate the usefulness of this paradigm by performing a set of refuge-site selection experiments with groups of fish. Using an open-source, robust custom image-processing algorithm, we automatically counted the number of animals in each arm of the maze to identify the majority choice. We also propose a new index to quantify the degree of group cohesion in this context. The radial arm maze paradigm provides an easy way to categorize and quantify the choices made by animals. It makes it possible to readily apply the traditional uses of the radial arm maze with single animals to the study of animal groups. Moreover, it opens up the possibility of studying questions specifically related to collective behaviors.

Optimal construction of army ant living bridges.

Integrating the costs and benefits of collective behaviors is a fundamental challenge to understanding the evolution of group living. These costs and benefits can rarely be quantified simultaneously due to the complexity of the interactions within the group, or even compared to each other because of the absence of common metrics between them. The construction of 'living bridges' by New World army ants - which they use to shorten their foraging trails - is a unique example of a collective behavior where costs and benefits have been experimentally measured and related to each other. As a result, it is possible to make quantitative predictions about when and how the behavior will be observed. In this paper, we extend a previous mathematical model of these costs and benefits to much broader domain of applicability. Specifically, we exhibit a procedure for analyzing the optimal formation, and final configuration, of army ant living bridges given a means to express the geometrical configuration of foraging path obstructions. Using this procedure, we provide experimentally testable predictions of the final bridge position, as well as the optimal formation process for certain cases, for a wide range of scenarios, which more closely resemble common terrain obstacles that ants encounter in nature. As such, our framework offers a rare benchmark for determining the evolutionary pressures governing the evolution of a naturally occurring collective animal behavior.

The adaptive significance of phasic colony cycles in army ants.

Army ants are top arthropod predators in tropical forests around the world. The colonies of many army ant species undergo stereotypical behavioral and reproductive cycles, alternating between brood care and reproductive phases. In the brood care phase, colonies contain a cohort of larvae that are synchronized in their development and have to be fed. In the reproductive phase larvae are absent and oviposition takes place. Despite these colony cycles being a striking feature of army ant biology, their adaptive significance is unclear. Here we use a modeling approach to show that cyclic reproduction is favored under conditions where per capita foraging costs decrease with the number of larvae in a colony ("High Cost of Entry" scenario), while continuous reproduction is favored under conditions where per capita foraging costs increase with the number of larvae ("Resource Exhaustion" scenario). We argue that the former scenario specifically applies to army ants, because large raiding parties are required to overpower prey colonies. However, once raiding is successful it provides abundant food for a large cohort of larvae. The latter scenario, on the other hand, will apply to non-army ants, because in those species local resource depletion will force workers to forage over larger distances to feed large larval cohorts. Our model provides a quantitative framework for understanding the adaptive value of phasic colony cycles in ants.

Decision-making without a brain: how an amoeboid organism solves the two-armed bandit.

Several recent studies hint at shared patterns in decision-making between taxonomically distant organisms, yet few studies demonstrate and dissect mechanisms of decision-making in simpler organisms. We examine decision-making in the unicellular slime mould Physarum polycephalum using a classical decision problem adapted from human and animal decision-making studies: the two-armed bandit problem. This problem has previously only been used to study organisms with brains, yet here we demonstrate that a brainless unicellular organism compares the relative qualities of multiple options, integrates over repeated samplings to perform well in random environments, and combines information on reward frequency and magnitude in order to make correct and adaptive decisions. We extend our inquiry by using Bayesian model selection to determine the most likely algorithm used by the cell when making decisions. We deduce that this algorithm centres around a tendency to exploit environments in proportion to their reward experienced through past sampling. The algorithm is intermediate in computational complexity between simple, reactionary heuristics and calculation-intensive optimal performance algorithms, yet it has very good relative performance. Our study provides insight into ancestral mechanisms of decision-making and suggests that fundamental principles of decision-making, information processing and even cognition are shared among diverse biological systems.