The Psychology of Superorganisms: Collective Decision Making by Insect Societies

The Physics of Sensing and Decision-Making by Animal Groups

To ensure survival and reproduction, individual animals navigating the world must regularly sense their surroundings and use this information for important decision-making. The same is true for animals living in groups, where the roles of sensing, information propagation, and decision-making are distributed on the basis of individual knowledge, spatial position within the group, and more. This review highlights key examples of temporal and spatiotemporal dynamics in animal group decision-making, emphasizing strong connections between mathematical models and experimental observations. We start with models of temporal dynamics, such as reaching consensus and the time dynamics of excitation-inhibition networks. For spatiotemporal dynamics in sparse groups, we explore the propagation of information and synchronization of movement in animal groups with models of self-propelled particles, where interactions are typically parameterized by length and timescales. In dense groups, we examine crowding effects using a soft condensed matter approach, where interactions are parameterized by physical potentials and forces. While focusing on invertebrates, we also demonstrate the applicability of these results to a wide range of organisms, aiming to provide an overview of group behavior dynamics and identify new areas for exploration.

The evolution of division of labour: preconditions and evolutionary feedback

Division of Labour (DoL) among group members reflects the pinnacle of social complexity. The synergistic effects created by task specialization and the sharing of duties benefitting the group raise the efficiency of the acquisition, use, management and defence of resources by a fundamental step above the potential of individual agents. At the same time, it may stabilize societies because of the involved interdependence among collaborators. Here, I review the conditions associated with the emergence of DoL, which include the existence of (i) sizeable groups with enduring membership; (ii) individual specialization improving the efficiency of task performance; and (iii) low conflict of interest among group members owing to correlated payoffs. This results in (iv) a combination of intra-individual consistency with inter-individual variance in carrying out different tasks, which creates (v) some degree of mutual interdependence among group members. DoL typically evolves 'bottom-up' without external regulatory forces, but the latter may gain importance at a later stage of the evolution of social complexity. Owing to the involved feedback processes, cause and effect are often difficult to disentangle in the evolutionary trajectory towards structured societies with well-developed DoL among their members. Nevertheless, the emergence of task specialization and DoL may entail a one-way street towards social complexity, with retrogression getting increasingly difficult the more individual agents depend on each other at progressing stages of social evolution.This article is part of the theme issue 'Division of labour as key driver of social evolution'.

An associative account of collective learning

Associative learning is an important adaptive mechanism that is well conserved among a broad range of species. Although it is typically studied in isolated animals, associative learning can occur in the presence of conspecifics in nature. Although many social aspects of individual learning have received much attention, the study of collective learning-the acquisition of knowledge in groups of animals through shared experience-has a much shorter history. Consequently, the conditions under which collective learning emerges and the mechanisms that underlie such emergence are still largely unexplored. Here, we develop a parsimonious model of collective learning based on the complementary integration of associative learning and collective intelligence. The model assumes (i) a simple associative learning rule, based on the Rescorla-Wagner model, in which the actions of conspecifics serve as cues and (ii) a horse-race action selection rule. Simulations of this model show no benefit of group training over individual training in a simple discrimination task (A+/B-). However, a group-training advantage emerges after the discrimination task is reversed (A-/B+). Model predictions suggest that, in a dynamic environment, tracking the actions of conspecifics that are solving the same problem can yield superior learning to individual animals and enhanced performance to the group.

Collective decision-making during reproduction in social insects: a conceptual model for queen supersedure in honey bees (Apis mellifera)

Insect societies have served as excellent examples for co-ordinated decision-making. The production of sexuals is the most important group decision that social insects face since it affects both direct and indirect fitness. The behavioral processes by which queens are selected have been of particular interest since they are the primary egg layers that enable colony function. As a model system, previous research on honey bee reproduction has focused on swarming behavior and nest site selection. One significant gap in our knowledge of the collective decision-making process over reproduction is how daughter queens simply replace old or failing queens (=supersedure) rather than being reared for the purposes of colony fission (=swarming) or queen loss (=emergency queen rearing). Here, I present a conceptual model that provides a framework for understanding the collective decisions by colonies to supersede their mother queens, as well as provide some key recommendations on future empirical work.

Paint marking using CO2 anaesthetization does not affect exploratory and recruitment behaviours in the rock ant, Temnothorax rugatulus

The study of animal behaviour sometimes requires unique identification of individuals, especially in the study of social behaviours involving the interactions of multiple individuals. To this end, researchers have developed many different methods of marking individuals. For small animals like insects, paint marks are often applied to their bodies by anaesthetizing them using low temperature or carbon dioxide. Despite this procedure being ubiquitous when studying social insects, the effect of paint and anaesthetics on their behaviour has not been well investigated, especially their effect on performance during a collective task. In our study, we investigate how paint marks and anaesthetics affect the movement and recruitment behaviours of the ant Temnothorax rugatulus in a house hunting context. We painted two thirds of colony members, half of them using CO2 and the other half using low temperature as methods of anaesthetization, and left the one third unpainted as a control group. We then measured their exploratory behaviour prior to house hunting and their recruitment behaviours during house hunting. We found that neither paint marks nor anaesthetics reduce activity levels of these behaviours. However, low-temperature anaesthetized ants performed a higher number of recruitment behaviours than control ants. Because CO2 anaesthetized ants performed all tasks at the same level as control ants, our data suggest that this is a good technique for paint marking ants, especially T. rugatulus. This is the first study empirically testing negative effects of paint marking on individual and collective outcomes in social insects. Our study represents an important step towards routine validation of individual identification methods used in the study of animal behaviour.

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.

The effect of experience on collective decision-making

Social groups repeatedly solving a complex task can improve their collective performance. To study the mechanisms of collective improvement, we tested the effect of experience on collective decision-making using acorn ants (Temnothorax ambiguus). During a six-emigration training phase, colonies in the choice treatment gained experience choosing to move into one of two nests varying in quality, while colonies in the no-choice treatment had only a single available nest. Both treatments were tested in a subsequent test with two nests of varying quality. We found that experience improved decision-making speed, regardless of treatment. We also found that colonies of the choice treatment were more proficient by carrying a larger proportion of individuals directly into the better-quality nest. However, there was no steady improvement in proficiency throughout their training. Using social network analysis, we quantified changes in group performance over successive emigrations. We found that network density, our measure for social connectedness, and the coefficient of variation of out-strength distribution, our measure for workload distribution, did not differ between treatments and remained stable over successive emigrations. We conclude that collective experience with decision-making may improve subsequent group performance, but the mechanisms of improvement remain unclear. Further research on decision-making in house-hunting ants will advance our understanding of the mechanisms underpinning collective improvement.

Inhibitory signaling in collective social insect networks, is it indeed uncommon?

Individual entities across levels of biological organization interact to reach collective decisions. In centralized neuronal networks, competing neural populations commonly accumulate information over time while increasing their own activity, and cross-inhibiting other populations until one group passes a given threshold. In social insects, there is good evidence for decisions mediated by positive feedbacks, but we found evidence for similar inhibitory signals only in honey bee (Apis mellifera) stop signals, and Pharaoh's ant- (Monomorium pharaonic) repellent pheromones, with only the former occasionally being used as cross-inhibition. We discuss whether these differences stem from insufficient research effort or represent genuine differences across levels of biological organization.

Emergence and retention of a collective memory in cockroaches

The stability of collective decisions-making in social systems is crucial as it can lead to counterintuitive phenomena such as collective memories, where an initial choice is challenged by environmental changes. Many social species face the challenge to perform collective decisions under variable conditions. In this study, we focused on situations where isolated individuals and groups of the American cockroach (Periplaneta americana) had to choose between two shelters with different luminosities that were inverted during the experiment. The darker shelter was initially preferred, but only groups that reached a consensus within that shelter maintain their choice after the light inversion, while isolated individuals and small groups lacked site fidelity. Our mathematical model, incorporating deterministic and probabilistic elements, sheds light on the significance interactions and their stochasticity in the emergence and retention of a collective memory.

Neuromodulatory control of complex adaptive dynamics in the brain

How is the massive dimensionality and complexity of the microscopic constituents of the nervous system brought under sufficiently tight control so as to coordinate adaptive behaviour? A powerful means for striking this balance is to poise neurons close to the critical point of a phase transition, at which a small change in neuronal excitability can manifest a nonlinear augmentation in neuronal activity. How the brain could mediate this critical transition is a key open question in neuroscience. Here, I propose that the different arms of the ascending arousal system provide the brain with a diverse set of heterogeneous control parameters that can be used to modulate the excitability and receptivity of target neurons-in other words, to act as control parameters for mediating critical neuronal order. Through a series of worked examples, I demonstrate how the neuromodulatory arousal system can interact with the inherent topological complexity of neuronal subsystems in the brain to mediate complex adaptive behaviour.

Mechanisms of collective learning: how can animal groups improve collective performance when repeating a task?

Learning is ubiquitous in animals: individuals can use their experience to fine-tune behaviour and thus to better adapt to the environment during their lifetime. Observations have accumulated that, at the collective level, groups can also use their experience to improve collective performance. Yet, despite apparent simplicity, the links between individual learning capacities and a collective's performance can be extremely complex. Here we propose a centralized and broadly applicable framework to begin classifying this complexity. Focusing principally on groups with stable composition, we first identify three distinct ways through which groups can improve their collective performance when repeating a task: each member learning to better solve the task on its own, members learning about each other to better respond to one another and members learning to improve their complementarity. We show through selected empirical examples, simulations and theoretical treatments that these three categories identify distinct mechanisms with distinct consequences and predictions. These mechanisms extend well beyond current social learning and collective decision-making theories in explaining collective learning. Finally, our approach, definitions and categories help generate new empirical and theoretical research avenues, including charting the expected distribution of collective learning capacities across taxa and its links to social stability and evolution. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Is collective nest site selection in ants influenced by the anchoring effect?

Evolutionary theory predicts that animals make decisions that maximize fitness. If so, they are expected to adhere to principles of rational choice, which a decision-maker must follow to reliably maximize net benefit. For example, evaluation of an option should not be influenced by the quality of other unchosen options. However, humans and other animals are known to evaluate a mediocre option more favorably after encountering poor options than after encountering no options, a phenomenon known as the 'anchoring effect'. Rationality is also expected in the consensus decisions of animal societies, but the anchoring effect has not previously been tested in that context. Here we show that colonies of the rock ant, Temnothorax rugatulus, demonstrate the anchoring effect during nest site selection - colonies moved more readily from a mediocre nest to a good nest when exposed to poor nests than when exposed to mediocre nests. This effect depended on both current conditions and past experience; movement probability was affected only when colonies were exposed to surrounding nests before and during the emigration. The effect was small, reaching statistical significance in only one of two experimental replicates. We discuss possible mechanisms and ultimate explanations for why colonies show this seemingly suboptimal behavior.

Interpersonal synchrony when singing in a choir

Singing in a choir has long been known to enhance well-being and protect mental health. Clearly, the experience of a uniquely harmonious social activity is very satisfying for the singers. How might this come about? One of the important factors positively associated with well-being is interpersonal action coordination allowing the choir to function as a whole. This review focuses on temporal coordination dynamics of physiological systems and/or subsystems forming part or the core of the functional substrate of choir singing. These coordination dynamics will be evaluated with respect to the concept of a superordinate system, or superorganism, based on the principles of self-organization and circular causality. We conclude that choral singing is a dynamic process requiring tight interpersonal action coordination that is characterized by coupled physiological systems and specific network topology dynamics, representing a potent biomarker for social interaction.

Social complexity and brain evolution: insights from ant neuroarchitecture and genomics

Brain evolution is hypothesized to be driven by requirements to adaptively respond to environmental cues and social signals. Diverse models describe how sociality may have influenced eusocial insect-brain evolution, but specific impacts of social organization and other selective forces on brain architecture have been difficult to distinguish. Here, we evaluate predictions derived from and/or inferences made by models of social organization concerning the effects of individual and collective behavior on brain size, structure, and function using results of neuroanatomical and genomic studies. In contrast to the predictions of some models, we find that worker brains in socially complex species have great behavioral and cognitive capacity. We also find that colony size, the evolution of worker physical castes, and task specialization affect brain size and mosaicism, supporting the idea that sensory, processing and motor requirements for behavioral performance select for adaptive allometries of functionally specialized brain centers. We review available transcriptomic and comparative genomic studies seeking to elucidate the molecular pathways functionally associated with social life and the genetic changes that occurred during the evolution of social complexity. We discuss ways forward, using comparative neuroanatomy, transcriptomics, and comparative genomics, to distinguish among multiple alternative explanations for the relationship between the evolution of neural systems and social complexity.

Drug effect and addiction research with insects - From Drosophila to collective reward in honeybees

Animals and humans share similar reactions to the effects of addictive substances, including those of their brain networks to drugs. Our review focuses on simple invertebrate models, particularly the honeybee (Apis mellifera), and on the effects of drugs on bee behaviour and brain functions. The drug effects in bees are very similar to those described in humans. Furthermore, the honeybee community is a superorganism in which many collective functions outperform the simple sum of individual functions. The distribution of reward functions in this superorganism is unique - although sublimated at the individual level, community reward functions are of higher quality. This phenomenon of collective reward may be extrapolated to other animal species living in close and strictly organised societies, i.e. humans. The relationship between sociality and reward, based on use of similar parts of the neural network (social decision-making network in mammals, mushroom body in bees), suggests a functional continuum of reward and sociality in animals.

Alternative model systems for cognitive variation: eusocial-insect colonies

Understanding the origins and maintenance of cognitive variation in animal populations is central to the study of the evolution of cognition. However, the brain is itself a complex, hierarchical network of heterogeneous components, from diverse cell types to diverse neuropils, each of which may be of limited use to study in isolation or prohibitively challenging to manipulate in situ. Consequently, highly tractable alternative model systems may be valuable tools. Eusocial-insect colonies display emergent cognitive-like properties from relatively simple social interactions between diverse subunits that can be observed and manipulated while operating collectively. Here, we review the individual-scale mechanisms that cause group-level variation in how colonies solve problems analogous to cognitive challenges faced by brains, like decision-making, attention, and search.

Distinct and enhanced hygienic responses of a leaf-cutting ant toward repeated fungi exposures

Leaf-cutting ants and their fungal crops are a textbook example of a long-term obligatory mutualism. Many microbes continuously enter their nest containing the fungal cultivars, destabilizing the symbiosis and, in some cases, outcompeting the mutualistic partners. Preferably, the ant workers should distinguish between different microorganisms to respond according to their threat level and recurrence in the colony. To address these assumptions, we investigated how workers of Atta sexdens sanitize their fungal crop toward five different fungi commonly isolated from the fungus gardens: Escovopsis sp., Fusarium oxysporum, Metarhizium anisopliae, Trichoderma spirale, and Syncephalastrum sp. Also, to investigate the plasticity of these responses toward recurrences of these fungi, we exposed the colonies with each fungus three times fourteen days apart. As expected, intensities in sanitization differed according to the fungal species. Ants significantly groom their fungal crop more toward F. oxysporum, M. anisopliae, and Syncephalastrum sp. than toward Escovopsis sp. and T. spirale. Weeding, self-, and allogrooming were observed in less frequency than fungus grooming in all cases. Moreover, we detected a significant increase in the overall responses after repeated exposures for each fungus, except for Escovopsis sp. Our results indicate that A. sexdens workers are able to distinguish between different fungi and apply distinct responses to remove these from the fungus gardens. Our findings also suggest that successive exposures to the same antagonist increase hygiene, indicating plasticity of ant colonies' defenses to previously encountered pathogens.

The emergence of a collective sensory response threshold in ant colonies

SignificanceIn this study, we ask how ant colonies integrate information about the external environment with internal state parameters to produce adaptive, system-level responses. First, we show that colonies collectively evacuate the nest when the ground temperature becomes too warm. The threshold temperature for this response is a function of colony size, with larger colonies evacuating the nest at higher temperatures. The underlying dynamics can thus be interpreted as a decision-making process that takes both temperature (external environment) and colony size (internal state) into account. Using mathematical modeling, we show that these dynamics can emerge from a balance between local excitatory and global inhibitory forces acting between the ants. Our findings in ants parallel other complex biological systems like neural circuits.

Social Brain Energetics: Ergonomic Efficiency, Neurometabolic Scaling, and Metabolic Polyphenism in Ants

Metabolism, a metric of the energy cost of behavior, plays a significant role in social evolution. Body size and metabolic scaling are coupled, and a socioecological pattern of increased body size is associated with dietary change and the formation of larger and more complex groups. These consequences of the adaptive radiation of animal societies beg questions concerning energy expenses, a substantial portion of which may involve the metabolic rates of brains that process social information. Brain size scales with body size, but little is understood about brain metabolic scaling. Social insects such as ants show wide variation in worker body size and morphology that correlates with brain size, structure, and worker task performance, which is dependent on sensory inputs and information-processing ability to generate behavior. Elevated production and maintenance costs in workers may impose energetic constraints on body size and brain size that are reflected in patterns of metabolic scaling. Models of brain evolution do not clearly predict patterns of brain metabolic scaling, nor do they specify its relationship to task performance and worker ergonomic efficiency, two key elements of social evolution in ants. Brain metabolic rate is rarely recorded and therefore the conditions under which brain metabolism influences the evolution of brain size are unclear. We propose that studies of morphological evolution, colony social organization, and worker ergonomic efficiency should be integrated with analyses of species-specific patterns of brain metabolic scaling to advance our understanding of brain evolution in ants.

Semi-automatic detection of honeybee brood hygiene—an example of artificial learning to facilitate ethological studies on social insects

Machine-learning techniques are shifting the boundaries of feasibility in many fields of ethological research. Here, we describe an application of machine learning to the detection/measurement of hygienic behaviour, an important breeding trait in the honey bee (Apis mellifera). Hygienic worker bees are able to detect and destroy diseased brood, thereby reducing the reproduction of economically important pathogens and parasites such as the Varroa mite (Varroa destructor). Video observation of this behaviour on infested combs has many advantages over other methods of measurement, but analysing the recorded material is extremely time-consuming. We approached this problem by combining automatic tracking of bees in the video recordings, extracting relevant features, and training a multi-layer discriminator on positive and negative examples of the behaviour of interest. Including expert knowledge into the design of the features lead to an efficient model for identifying the uninteresting parts of the video which can be safely skipped. This algorithm was then used to semiautomatically identify individual worker bees involved in the behaviour. Application of the machine-learning method allowed to save 70% of the time required for manual analysis, and substantially increased the number of cell openings correctly identified. It thereby turns video-observation of individual cell opening events into an economically competitive method for selecting potentially resistant bees. This method presents an example of how machine learning can be used to boost ethological research, and how it can generate new knowledge by explaining the learned decision rule in form of meaningful parameters.

Ants resort to majority concession to reach democratic consensus in the presence of a persistent minority

Social groups often need to overcome differences in individual interests and knowledge to reach consensus decisions. Here, we combine experiments and modeling to study conflict resolution in emigrating ant colonies during binary nest selection. We find that cohesive emigration, without fragmentation, is achieved only by intermediate-sized colonies. We then impose a conflict regarding the desired emigration target between colony subgroups. This is achieved using an automated selective gate system that manipulates the information accessible to each ant. Under this conflict, we find that individuals concede their potential benefit to promote social consensus. In particular, colonies resolve the conflict imposed by a persistent minority through "majority concession," wherein a majority of ants that hold first-hand knowledge regarding the superior quality nest choose to reside in the inferior one. This outcome is unlikely in social groups of selfish individuals and emphasizes the importance of group cohesion in eusocial societies.

When and Why Did Human Brains Decrease in Size? A New Change-Point Analysis and Insights From Brain Evolution in Ants

Human brain size nearly quadrupled in the six million years since Homo last shared a common ancestor with chimpanzees, but human brains are thought to have decreased in volume since the end of the last Ice Age. The timing and reason for this decrease is enigmatic. Here we use change-point analysis to estimate the timing of changes in the rate of hominin brain evolution. We find that hominin brains experienced positive rate changes at 2.1 and 1.5 million years ago, coincident with the early evolution of Homo and technological innovations evident in the archeological record. But we also find that human brain size reduction was surprisingly recent, occurring in the last 3,000 years. Our dating does not support hypotheses concerning brain size reduction as a by-product of body size reduction, a result of a shift to an agricultural diet, or a consequence of self-domestication. We suggest our analysis supports the hypothesis that the recent decrease in brain size may instead result from the externalization of knowledge and advantages of group-level decision-making due in part to the advent of social systems of distributed cognition and the storage and sharing of information. Humans live in social groups in which multiple brains contribute to the emergence of collective intelligence. Although difficult to study in the deep history of Homo, the impacts of group size, social organization, collective intelligence and other potential selective forces on brain evolution can be elucidated using ants as models. The remarkable ecological diversity of ants and their species richness encompasses forms convergent in aspects of human sociality, including large group size, agrarian life histories, division of labor, and collective cognition. Ants provide a wide range of social systems to generate and test hypotheses concerning brain size enlargement or reduction and aid in interpreting patterns of brain evolution identified in humans. Although humans and ants represent very different routes in social and cognitive evolution, the insights ants offer can broadly inform us of the selective forces that influence brain size.

No coordination required for resources allocation during colony fission in a social insect? An individual-based model reproduces empirical patterns

Social insects are classic examples of cooperation and coordination. For instance, laboratory studies of colony relocation, or house-hunting, have investigated how workers coordinate their efforts to swiftly move the colony to the best nesting site available while preserving colony integrity, i.e. avoiding a split. However, several studies have shown that, in some other contexts, individuals may use private rather than social information and may act solitarily rather than in a coordinated way. Here, we study resource allocation by a mature ant colony when it reproduces by fissioning into several colonies. This is a very different task than house hunting in that colony fission seeks the split of the colony. We develop a simple individual-based model to test if colony fission and resource allocation may be carried out by workers acting solitarily with no coordination. Our model reproduces well the pattern of allocation observed in nature (number and size of new colonies). This does not show that workers do not communicate nor coordinate. Rather, it suggests that independent decision making may be an important component of the process of resource allocation.

Hive geometry shapes the recruitment rate of honeybee colonies

Honey bees make decisions regarding foraging and nest-site selection in groups ranging from hundreds to thousands of individuals. To effectively make these decisions, bees need to communicate within a spatially distributed group. However, the spatiotemporal dynamics of honey bee communication have been mostly overlooked in models of collective decisions, focusing primarily on mean field models of opinion dynamics. We analyze how the spatial properties of the nest or hive, and the movement of individuals with different belief states (uncommitted or committed) therein affect the rate of information transmission using spatially-extended models of collective decision-making within a hive. Honeybees waggle-dance to recruit conspecifics with an intensity that is a threshold nonlinear function of the waggler concentration. Our models range from treating the hive as a chain of discrete patches to a continuous line (long narrow hive). The combination of population-thresholded recruitment and compartmentalized populations generates tradeoffs between rapid information propagation with strong population dispersal and recruitment failures resulting from excessive population diffusion and also creates an effective colony-level signal-detection mechanism whereby recruitment to low quality objectives is blocked.

Irrational risk aversion in an ant

Animals must often decide between exploiting safe options or risky options with a chance for large gains. Both proximate theories based on perceptual mechanisms, and evolutionary ones based on fitness benefits, have been proposed to explain decisions under risk. Eusocial insects represent a special case of risk sensitivity, as they must often make collective decisions based on resource evaluations from many individuals. Previously, colonies of the ant Lasius niger were found to be risk-neutral, but the risk preference of individual foragers was unknown. Here, we tested individual L. niger in a risk sensitivity paradigm. Ants were trained to associate one scent with 0.55 M sucrose solution and another with an equal chance of either 0.1 or 1.0 M sucrose. Preference was tested in a Y-maze. Ants were extremely risk-averse, with 91% choosing the safe option. Based on the psychophysical Weber-Fechner law, we predicted that ants evaluate resources depending on their logarithmic difference. To test this hypothesis, we designed 4 more experiments by varying the relative differences between the alternatives, making the risky option less, equally or more valuable than the safe one. Our results support the logarithmic origin of risk aversion in ants, and demonstrate that the behaviour of individual foragers can be a very poor predictor of colony-level behaviour.

Minimal Organizational Requirements for the Ascription of Animal Personality to Social Groups

Recently, psychological phenomena have been expanded to new domains, crisscrossing boundaries of organizational levels, with the emergence of areas such as social personality and ecosystem learning. In this contribution, we analyze the ascription of an individual-based concept (personality) to the social level. Although justified boundary crossings can boost new approaches and applications, the indiscriminate misuse of concepts refrains the growth of scientific areas. The concept of social personality is based mainly on the detection of repeated group differences across a population, in a direct transposition of personality concepts from the individual to the social level. We show that this direct transposition is problematic for avowing the nonsensical ascription of personality even to simple electronic devices. To go beyond a metaphoric use of social personality, we apply the organizational approach to a review of social insect communication networks. Our conceptual analysis shows that socially self-organized systems, such as isolated ant trails and bee's recruitment groups, are too simple to have social personality. The situation is more nuanced when measuring the collective choice between nest sites or foraging patches: some species show positive and negative feedbacks between two or more self-organized social structures so that these co-dependent structures are inter-related by second-order, social information systems, complying with a formal requirement for having social personality: the social closure of constraints. Other requirements include the decoupling between individual and social dynamics, and the self-regulation of collective decision processes. Social personality results to be sometimes a metaphorical transposition of a psychological concept to a social phenomenon. The application of this organizational approach to cases of learning ecosystems, or evolutionary learning, could help to ground theoretically the ascription of psychological properties to levels of analysis beyond the individual, up to meta-populations or ecological communities.

Occupancy patterns in superorganisms: a spin-glass approach to ant exploration

Emergence of collective, as well as superorganism-like, behaviour in biological populations requires the existence of rules of communication, either direct or indirect, between organisms. Because reaching an understanding of such rules at the individual level can be often difficult, approaches carried out at higher, or effective, levels of description can represent a useful alternative. In the present work, we show how a spin-glass approach characteristic of statistical physics can be used as a tool to characterize the properties of the spatial occupancy patterns of a biological population. We exploit the presence of pairwise interactions in spin-glass models for detecting correlations between occupancies at different sites in the media. Such correlations, we claim, represent a proxy to the existence of planned and/or social strategies in the spatial organization of the population. Our spin-glass approach does not only identify those correlations but produces a statistical replica of the system (at the level of occupancy patterns) that can be subsequently used for testing alternative conditions/hypothesis. Here, this methodology is presented and illustrated for a particular case of study: we analyse occupancy patterns of Aphaenogaster senilis ants during foraging through a simplified environment consisting of a discrete (tree-like) artificial lattice. Our spin-glass approach consistently reproduces the experimental occupancy patterns across time, and besides, an intuitive biological interpretation of the parameters is attainable. Likewise, we prove that pairwise correlations are important for reproducing these dynamics by showing how a null model, where such correlations are neglected, would perform much worse; this provides a solid evidence to the existence of superorganism-like strategies in the colony.

Trail Pheromone Does Not Modulate Subjective Reward Evaluation in Lasius niger Ants

Comparing the value of options is at the heart of economic decision-making. While an option may have an absolute quality (e.g. a food source has a fixed energy content), the perceived value of the option may be malleable. The factors affecting the perceived value of an option may thus strongly influence which option is ultimately chosen. Expectations have been shown to be a strong driver of perceived value in both humans and social insects, causing an undervaluation of a given option if a better option was expected, and an overvaluation if a poorer one was expected. In humans, perceived value can be strongly affected by social information. Value perception in some insects has also been shown to be affected by social information, showing conformism as in humans and other animals. Here, over a series of experiments, we tested whether pheromone trail presence, a social information source, influenced the perceived value of a food source in the ant Lasius niger. We found that the presence of pheromone trails leading to a sucrose solution does not influence food acceptance, pheromone deposition when returning from a food source, drinking time, or frequency of U-turns on return from the food. Two further assays for measuring changes in food acceptance, designed to increase sensitivity by avoiding ceiling effects, also showed no effect of pheromone presence on food acceptance. In a separate study, L. niger have also been found to show no preference for, or avoidance of, odors associated with foods found in the presence of pheromone. We are thus confident that trail pheromone presence does not affect the perceived value of a food source in these ants.

Physical and social cues shape nest-site preference and prey capture behavior in social spiders

Animals often face conflicting demands when making movement decisions. To examine the decision process of social animals, we evaluated nest-site preferences of the social spider Stegodyphus dumicola. Colonies engage in collective web building, constructing 3D nests and 2D capture webs on trees and fences. We examined how individuals and groups decide where to construct a nest based on habitat structure and conspecific presence. Individuals had a strong preference for 3D substrates and conspecific presence. Groups were then provided with conflicting options of 3D substrates versus 2D substrates with a conspecific. Groups preferred the 3D structures without presettled conspecifics over a 2D substrate with conspecifics. When a group fragmented and individuals settled on both substrates, the minority group eventually joined the majority. Before rejoining, the collective prey capture behavior of divided groups improved with the size of the majority fragment. The costs of slow responses to prey for split groups and weak conspecific attraction may explain why dispersal is rare in these spiders.

Computational and robotic modeling reveal parsimonious combinations of interactions between individuals in schooling fish

Coordinated motion and collective decision-making in fish schools result from complex interactions by which individuals integrate information about the behavior of their neighbors. However, little is known about how individuals integrate this information to take decisions and control their motion. Here, we combine experiments with computational and robotic approaches to investigate the impact of different strategies for a fish to interact with its neighbors on collective swimming in groups of rummy-nose tetra (Hemigrammus rhodostomus). By means of a data-based agent model describing the interactions between pairs of H. rhodostomus (Calovi et al., 2018), we show that the simple addition of the pairwise interactions with two neighbors quantitatively reproduces the collective behavior observed in groups of five fish. Increasing the number of interacting neighbors does not significantly improve the simulation results. Remarkably, and even without confinement, we find that groups remain cohesive and polarized when each agent interacts with only one of its neighbors: the one that has the strongest contribution to the heading variation of the focal agent, dubbed as the "most influential neighbor". However, group cohesion is lost when each agent only interacts with its nearest neighbor. We then investigate by means of a robotic platform the collective motion in groups of five robots. Our platform combines the implementation of the fish behavioral model and a control system to deal with real-world physical constraints. A better agreement with experimental results for fish is obtained for groups of robots only interacting with their most influential neighbor, than for robots interacting with one or even two nearest neighbors. Finally, we discuss the biological and cognitive relevance of the notion of "most influential neighbors". Overall, our results suggest that fish have to acquire only a minimal amount of information about their environment to coordinate their movements when swimming in groups.

Conflictual influence of humidity during shelter selection of the American cockroach (Periplaneta americana)

In collective decision-making, when confronted with different options, groups usually show a more marked preference for one of the options than do isolated individuals. This results from the amplification of individual preferences by social interactions within the group. We show, in an unusual counter-example, that when facing a binary choice between shelters with different relative humidities, isolated cockroaches of the species Periplaneta americana select the wettest shelter, while groups select the driest one. This inversion of selection results from a conflictual influence of humidity on the probabilities of entering and leaving each shelter. It is shown that the individual probability of entering the wettest shelter is higher than the group probability and is increased by previous entries and exits. The probability of leaving each shelter decreases in the population due to social interactions, but this decrease is less pronounced in the wettest shelter, suggesting weaker social interactions. A theoretical model is developed and highlights the existence of tipping points dependent on population size, beyond which an inversion of selection of a resting place is observed.

Measuring collective behavior: an ecological approach

Collective behavior is ubiquitous throughout nature. Many systems, from brains to ant colonies, work without central control. Collective behavior is regulated by interactions among the individual participants such as neurons or ants. Interactions create feedback that produce the outcome, the behavior that we observe: Brains think and remember, ant colonies collect food or move nests, flocks of birds turn, human societies develop new forms of social organization. But the processes by which interactions produce outcomes are as diverse as the behavior itself. Just as convergent evolution has led to organs, such as the eye, that are similar in function but are based on different physiological processes, so it has led to forms of collective behavior that appear similar but arise from different social processes. An ecological perspective can help us to understand the dynamics of collective behavior and how it works.

Social Complexity and Brain Evolution: Comparative Analysis of Modularity and Integration in Ant Brain Organization

The behavioral demands of living in social groups have been linked to the evolution of brain size and structure, but how social organization shapes investment and connectivity within and among functionally specialized brain regions remains unclear. To understand the influence of sociality on brain evolution in ants, a premier clade of eusocial insects, we statistically analyzed patterns of brain region size covariation as a proxy for brain region connectivity. We investigated brain structure covariance in young and old workers of two formicine ants, the Australasian weaver ant Oecophylla smaragdina, a pinnacle of social complexity in insects, and its socially basic sister clade Formica subsericea. As previously identified in other ant species, we predicted that our analysis would recognize in both species an olfaction-related brain module underpinning social information processing in the brain, and a second neuroanatomical cluster involved in nonolfactory sensorimotor processes, thus reflecting conservation of compartmental connectivity. Furthermore, we hypothesized that covariance patterns would reflect divergence in social organization and life histories either within this species pair or compared to other ant species. Contrary to our predictions, our covariance analyses revealed a weakly defined visual, rather than olfactory, sensory processing cluster in both species. This pattern may be linked to the reliance on vision for worker behavioral performance outside of the nest and the correlated expansion of the optic lobes to meet navigational demands in both species. Additionally, we found that colony size and social organization, key measures of social complexity, were only weakly correlated with brain modularity in these formicine ants. Worker age also contributed to variance in brain organization, though in different ways in each species. These findings suggest that brain organization may be shaped by the divergent life histories of the two study species. We compare our findings with patterns of brain organization of other eusocial insects.

The Neglected Pieces of Designing Collective Decision-Making Processes

Autonomous decision-making is a fundamental requirement for the intelligent behavior of individual agents and systems. For artificial systems, one of the key design prerequisites is providing the system with the ability to make proper decisions. Current literature on collective artificial systems designs decision-making mechanisms inspired mostly by the successful natural systems. Nevertheless, most of the approaches focus on voting mechanisms and miss other fundamental aspects. In this paper, we aim to draw attention to the missed pieces for the design of efficient collective decision-making, mainly information processes in its two types of stimuli and options set.

Food-burying behavior in red imported fire ants (Hymenoptera: Formicidae)

The food-burying behavior has been reported in many mammals and birds, but was rarely observed in invertebrates. The red imported fire ants, Solenopsis invicta Buren, is an invasive pest in many areas of the world that usually performing food-burying during the foraging processes. However, the impacted factors and measureable patterns of this behavior is largely unknown. In the present study, food-burying vs food-transport behaviors of Solenopsis invicta were observed under laboratory and field conditions. When starved (no food was provided for 37 days) in the laboratory, food (sausage) was consumed by large numbers of ants, and few burying behaviors were observed. However, when food was provided until satiation of the colonies, food-transport was suppressed and significantly more soil particles were relocated on the food and graph paper square (where the food was placed) when compared with these colonies exposed to starved conditions. Videotapes showed that soil particles (1.47 ± 0.09 mm²) were preferentially placed adjacent to (in contact with) the food items at the beginning; and after the edges were covered, ants transported significantly smaller soil particles (1.13 ± 0.06 mm²) to cover the food. Meanwhile, larger particles (1.96 ± 0.08 mm²) were pulled/dragged around (but not in contact with) the food. Interestingly, only a small number of ants, mainly the small workers, were involved in food-burying, and the ants tended to repeatedly transport soil particles. A total of 12 patterns of particle transport were identified, and soil particles were most frequently picked from the foraging arena and subsequently placed adjacent to the food. In the field, almost all released food was actively transported by Solenopsis invicta workers, and no burying behavior was observed. Our results show that the food-burying behavior of Solenopsis invicta may be associated with the suppressed foraging activity, and the burying task may be carried out by certain groups of workers.

The Ecology of Collective Behavior in Ants

Nest choice in Temnothorax spp.; task allocation and the regulation of activity in Pheidole dentata, Pogonomyrmex barbatus, and Atta spp.; and trail networks in Monomorium pharaonis and Cephalotes goniodontus all provide examples of correspondences between the dynamics of the environment and the dynamics of collective behavior. Some important aspects of the dynamics of the environment include stability, the threat of rupture or disturbance, the ratio of inflow and outflow of resources or energy, and the distribution of resources. These correspond to the dynamics of collective behavior, including the extent of amplification, how feedback instigates and inhibits activity, and the extent to which the interactions that provide the information to regulate behavior are local or spatially centralized.

Parallel vs. comparative evaluation of alternative options by colonies and individuals of the ant Temnothorax rugatulus

Both a single ant and the colony to which it belongs can make decisions, but the underlying mechanisms may differ. Colonies are known to be less susceptible than lone ants to “choice overload”, whereby decision quality deteriorates with increasing number of options. We probed the basis of this difference, using the model system of nest-site selection by the ant Temnothorax rugatulus. We tested the applicability of two competing models originally developed to explain information-processing mechanisms in vertebrates. The Tug of War model states that concurrent alternatives are directly compared, so that choosing between two alternatives takes longer than accepting a single one. In contrast, the Sequential Choice Model assumes that options are examined in parallel, and action takes place once any option reaches a decision criterion, so that adding more options shortens time to act. We found that single ants matched the Tug of War model while colonies fitted the Sequential Choice model. Our study shows that algorithmic models for decision-making can serve to investigate vastly different domains, from vertebrate individuals to both individuals and colonies of social insects.

Information sharing for a coordination game in fluctuating environments

Collective action dilemmas pervade the social and biological sciences - from human decision-making to bacterial quorum sensing. In these scenarios, individuals sense cues from the environment to adopt a suitable phenotype or change in behavior. However, when cues include signals from other individuals, then the appropriate behavior of each individual is linked. Here, we develop a framework to quantify the influence of information sharing on individual behavior in the context of two player coordination games. In this framework, the environment stochastically switches between two states, and the state determines which one of two actions players must coordinate on. Given a stochastically switching environment, we then consider two versions of the game that differ in the way players acquire information. In the first model, players independently sense private environmental cues, but do not communicate with each other. We find there are two types of strategies that emerge as Nash equilibria and fitness maximizers - players prefer to commit to one particular action when private information is poor, or prefer to employ phenotypic plasticity when it is good. The second model adds an additional layer of communication, where players share social cues as well. When the quality of social information is high, we find the socially optimal strategy is a novel "majority logic" strategy that bases decision-making on social cues. Our game-theoretic approach offers a principled way of investigating the role of communication in group decision-making under uncertain conditions.