Individual learning phenotypes drive collective behavior

Reinforcement expectation in the honeybee (Apis mellifera): Can downshifts in reinforcement show conditioned inhibition?

When animals learn the association of a conditioned stimulus (CS) with an unconditioned stimulus (US), later presentation of the CS invokes a representation of the US. When the expected US fails to occur, theoretical accounts predict that conditioned inhibition can accrue to any other stimuli that are associated with this change in the US. Empirical work with mammals has confirmed the existence of conditioned inhibition. But the way it is manifested, the conditions that produce it, and determining whether it is the opposite of excitatory conditioning are important considerations. Invertebrates can make valuable contributions to this literature because of the well-established conditioning protocols and access to the central nervous system (CNS) for studying neural underpinnings of behavior. Nevertheless, although conditioned inhibition has been reported, it has yet to be thoroughly investigated in invertebrates. Here, we evaluate the role of the US in producing conditioned inhibition by using proboscis extension response conditioning of the honeybee (Apis mellifera). Specifically, using variations of a "feature-negative" experimental design, we use downshifts in US intensity relative to US intensity used during initial excitatory conditioning to show that an odorant in an odor-odor mixture can become a conditioned inhibitor. We argue that some alternative interpretations to conditioned inhibition are unlikely. However, we show variation across individuals in how strongly they show conditioned inhibition, with some individuals possibly revealing a different means of learning about changes in reinforcement. We discuss how the resolution of these differences is needed to fully understand whether and how conditioned inhibition is manifested in the honeybee, and whether it can be extended to investigate how it is encoded in the CNS. It is also important for extension to other insect models. In particular, work like this will be important as more is revealed of the complexity of the insect brain from connectome projects.

Regulation of division of labor in insects: a colony-level perspective

Studies of division of labor have focused mainly on individual workers performing tasks. Here I propose a shift in perspective: colonies perform tasks, and task performance should be evaluated at the colony level. I then review studies from the recent literature from this perspective, on topics including evaluating task performance; specialization and efficiency; flexibility and task performance; response threshold models; and variation in behavior arising from diverse sensory experiences and learning. The use of specialized workers is only one of a variety of strategies that colonies may follow in performing tasks. The ability of colonies to produce consistent responses and to compensate for changes in the labor pool supports the idea of a task allocation system that precedes specialization. The colony-level perspective raises new questions about how tasks are done and the strategies used to improve colony task performance.

The buzz within: the role of the gut microbiome in honeybee social behavior

Gut symbionts influence the physiology and behavior of their host, but the extent to which these effects scale to social behaviors is an emerging area of research. The use of the western honeybee (Apis mellifera) as a model enables researchers to investigate the gut microbiome and behavior at several levels of social organization. Insight into gut microbial effects at the societal level is critical for our understanding of how involved microbial symbionts are in host biology. In this Commentary, we discuss recent findings in honeybee gut microbiome research and synthesize these with knowledge of the physiology and behavior of other model organisms to hypothesize how host-microbe interactions at the individual level could shape societal dynamics and evolution.

A predisposed motor bias shapes individuality in vocal learning

The development of individuality during learned behavior is a common trait observed across animal species; however, the underlying biological mechanisms remain understood. Similar to human speech, songbirds develop individually unique songs with species-specific traits through vocal learning. In this study, we investigate the developmental and molecular mechanisms underlying individuality in vocal learning by utilizing F1 hybrid songbirds (Taeniopygia guttata cross with Taeniopygia bichenovii), taking an integrating approach combining experimentally controlled systematic song tutoring, unbiased discriminant analysis of song features, and single-cell transcriptomics. When tutoring with songs from both parental species, F1 hybrid individuals exhibit evident diversity in their acquired songs. Approximately 30% of F1 hybrids selectively learn either song of the two parental species, while others develop merged songs that combine traits from both species. Vocal acoustic biases during vocal babbling initially appear as individual differences in songs among F1 juveniles and are maintained through the sensitive period of song vocal learning. These vocal acoustic biases emerge independently of the initial auditory experience of hearing the biological father's and passive tutored songs. We identify individual differences in transcriptional signatures in a subset of cell types, including the glutamatergic neurons projecting from the cortical vocal output nucleus to the hypoglossal nuclei, which are associated with variations of vocal acoustic features. These findings suggest that a genetically predisposed vocal motor bias serves as the initial origin of individual variation in vocal learning, influencing learning constraints and preferences.

A modeling framework for adaptive collective defense: crisis response in social-insect colonies

Living systems, from cells to superorganismic insect colonies, have an organizational boundary between inside and outside and allocate resources to defend it. Whereas the micro-scale dynamics of cell walls can be difficult to study, the adaptive allocation of workers to defense in social-insect colonies is more conspicuous. This is particularly the case for Tetragonisca angustula stingless bees, which combine different defensive mechanisms found across other colonial animals: (1) morphological specialization (distinct soldiers (majors) are produced over weeks); (2) age-based polyethism (young majors transition to guarding tasks over days); and (3) task switching (small workers (minors) replace soldiers within minutes under crisis). To better understand how these timescales of reproduction, development, and behavior integrate to balance defensive demands with other colony needs, we developed a demographic Filippov ODE system to study the effect of these processes on task allocation and colony size. Our results show that colony size peaks at low proportions of majors, but colonies die if minors are too plastic or defensive demands are too high or if there is a high proportion of quickly developing majors. For fast maturation, increasing major production may decrease defenses. This model elucidates the demographic factors constraining collective defense regulation in social insects while also suggesting new explanations for variation in defensive allocation at smaller scales where the mechanisms underlying defensive processes are not easily observable. Moreover, our work helps to establish social insects as model organisms for understanding other systems where the transaction costs for component turnover are nontrivial, as in manufacturing systems and just-in-time supply chains.

Tyramine and its Amtyr1 receptor modulate attention in honey bees (Apis mellifera)

Animals must learn to ignore stimuli that are irrelevant to survival and attend to ones that enhance survival. When a stimulus regularly fails to be associated with an important consequence, subsequent excitatory learning about that stimulus can be delayed, which is a form of nonassociative conditioning called 'latent inhibition'. Honey bees show latent inhibition toward an odor they have experienced without association with food reinforcement. Moreover, individual honey bees from the same colony differ in the degree to which they show latent inhibition, and these individual differences have a genetic basis. To investigate the mechanisms that underly individual differences in latent inhibition, we selected two honey bee lines for high and low latent inhibition, respectively. We crossed those lines and mapped a Quantitative Trait Locus for latent inhibition to a region of the genome that contains the tyramine receptor gene Amtyr1 [We use Amtyr1 to denote the gene and AmTYR1 the receptor throughout the text.]. We then show that disruption of Amtyr1 signaling either pharmacologically or through RNAi qualitatively changes the expression of latent inhibition but has little or slight effects on appetitive conditioning, and these results suggest that AmTYR1 modulates inhibitory processing in the CNS. Electrophysiological recordings from the brain during pharmacological blockade are consistent with a model that AmTYR1 indirectly regulates at inhibitory synapses in the CNS. Our results therefore identify a distinct Amtyr1-based modulatory pathway for this type of nonassociative learning, and we propose a model for how Amtyr1 acts as a gain control to modulate hebbian plasticity at defined synapses in the CNS. We have shown elsewhere how this modulation also underlies potentially adaptive intracolonial learning differences among individuals that benefit colony survival. Finally, our neural model suggests a mechanism for the broad pleiotropy this gene has on several different behaviors.

NAPS: Integrating pose estimation and tag-based tracking

1. Significant advances in computational ethology have allowed the quantification of behaviour in unprecedented detail. Tracking animals in social groups, however, remains challenging as most existing methods can either capture pose or robustly retain individual identity over time but not both. 2. To capture finely resolved behaviours while maintaining individual identity, we built NAPS (NAPS is ArUco Plus SLEAP), a hybrid tracking framework that combines state-of-the-art, deep learning-based methods for pose estimation (SLEAP) with unique markers for identity persistence (ArUco). We show that this framework allows the exploration of the social dynamics of the common eastern bumblebee (Bombus impatiens). 3. We provide a stand-alone Python package for implementing this framework along with detailed documentation to allow for easy utilization and expansion. We show that NAPS can scale to long timescale experiments at a high frame rate and that it enables the investigation of detailed behavioural variation within individuals in a group. 4. Expanding the toolkit for capturing the constituent behaviours of social groups is essential for understanding the structure and dynamics of social networks. NAPS provides a key tool for capturing these behaviours and can provide critical data for understanding how individual variation influences collective dynamics.

Colonies of ants allocate exploratory individuals to where they are ecologically needed

Individual differences in behavior have large consequences for the way in which ecology impacts fitness. Individuals differ in how they explore their environment and how exploratory behavior benefits them. In group-living animals, behavioral heterogeneity can be beneficial because different individuals perform different tasks. For example, exploratory individuals may discover new food sources and recruit group members to exploit the food, while less exploratory individuals forgo the risks of exploration. Here we ask how individual variation in exploratory behavior affects the ability of Argentine ant Linepithema humile colonies to (1) locate novel food sources, (2) exploit known food resources, and (3) respond to disruptions while foraging. To address these questions, we conducted field experiments on L. humile foraging trails in which we manipulated food availability near and at the foraging trails and disrupted the foraging trails. We sampled individuals based on their response to the perturbations in the field and tested their exploratory behavior in the lab. We found that exploratory individuals benefit the colony by locating novel foods and increasing resource exploitation, but they do not play an important role in the recovery of a foraging trail after disruption. Thus, the benefits of behavioral heterogeneity to the group, specifically in exploratory behavior, differ across ecological contexts.

Diverse communication strategies in bees as a window into adaptations to an unpredictable world

Communication is a fundamental feature of animal societies and helps their members to solve the challenges they encounter, from exploiting food sources to fighting enemies or finding a new home. Eusocial bees inhabit a wide range of environments and they have evolved a multitude of communication signals that help them exploit resources in their environment efficiently. We highlight recent advances in our understanding of bee communication strategies and discuss how variation in social biology, such as colony size or nesting habits, and ecological conditions are important drivers of variation in communication strategies. Anthropogenic factors, such as habitat conversion, climate change, or the use of agrochemicals, are changing the world bees inhabit, and it is becoming clear that this affects communication both directly and indirectly, for example by affecting food source availability, social interactions among nestmates, and cognitive functions. Whether and how bees adapt their foraging and communication strategies to these changes represents a new frontier in bee behavioral and conservation research.

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'.

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.

Predicting the impacts of chemical pollutants on animal groups

Chemical pollution is among the fastest-growing agents of global change. Synthetic chemicals with diverse modes-of-action are being detected in the tissues of wildlife and pervade entire food webs. Although such pollutants can elicit a range of sublethal effects on individual organisms, research on how chemical pollutants affect animal groups is severely lacking. Here we synthesise research from two related, but largely segregated fields - ecotoxicology and behavioural ecology - to examine pathways by which chemical contaminants could disrupt processes that govern the emergence, self-organisation, and collective function of animal groups. Our review provides a roadmap for prioritising the study of chemical pollutants within the context of sociality and highlights important methodological advancements for future research.

Slow-Fast Cognitive Phenotypes and Their Significance for Social Behavior: What Can We Learn From Honeybees?

Cognitive variation is proposed to be the fundamental underlying factor that drives behavioral variation, yet it is still to be fully integrated with the observed variation at other phenotypic levels that has recently been unified under the common pace-of-life framework. This cognitive and the resulting behavioral diversity is especially significant in the context of a social group, the performance of which is a collective outcome of this diversity. In this review, we argue about the utility of classifying cognitive traits along a slow-fast continuum in the larger context of the pace-of-life framework. Using Tinbergen’s explanatory framework for different levels of analyses and drawing from the large body of knowledge about honeybee behavior, we discuss the observed interindividual variation in cognitive traits and slow-fast cognitive phenotypes from an adaptive, evolutionary, mechanistic and developmental perspective. We discuss the challenges in this endeavor and suggest possible next steps in terms of methodological, statistical and theoretical approaches to move the field forward for an integrative understanding of how slow-fast cognitive differences, by influencing collective behavior, impact social evolution.

Gut microbiome drives individual memory variation in bumblebees

The potential of the gut microbiome as a driver of individual cognitive differences in natural populations of animals remains unexplored. Here, using metagenomic sequencing of individual bumblebee hindguts, we find a positive correlation between the abundance of Lactobacillus Firm-5 cluster and memory retention on a visual discrimination task. Supplementation with the Firm-5 species Lactobacillus apis, but not other non-Firm-5 bacterial species, enhances bees' memory. Untargeted metabolomics after L. apis supplementation show increased LPA (14:0) glycerophospholipid in the haemolymph. Oral administration of the LPA increases long-term memory significantly. Based on our findings and metagenomic/metabolomic analyses, we propose a molecular pathway for this gut-brain interaction. Our results provide insights into proximate and ultimate causes of cognitive differences in natural bumblebee populations.

Heritable Cognitive Phenotypes Influence Appetitive Learning but not Extinction in Honey Bees

Learning and attention allow animals to better navigate complex environments. While foraging, honey bees (Apis mellifera L.) learn several aspects of their foraging environment, such as color and odor of flowers, which likely begins to happen before they evaluate the quality of the food. If bees begin to evaluate quality before they taste food, and then learn the food is depleted, this may create a conflict in what the bee learns and remembers. Individual honey bees differ in their sensitivity to information, thus creating variation in how they learn or do not learn certain environmental stimuli. For example, foraging honey bees exhibit differences in latent inhibition (LI), a learning process through which regular encounter with a stimulus without a consequence such as food can later reduce conditioning to that stimulus. Here, we test whether bees from distinct selected LI genotypes learn differently if reinforced via just antennae or via both antennae + proboscis. We also evaluate whether learned information goes extinct at different rates in these distinct LI genetic lines. We find that high LI bees learned significantly better when they were reinforced both antenna + proboscis, while low LI and control bees learned similarly with the two reinforcement pathways. We also find no differences in the acquisition and extinction of learned information in high LI and low LI bees. Our work provides insight into how underlying cognition may influence how honey bees learn and value information, which may lead to differences in how individuals and colonies make foraging decisions.

Understanding Drivers of Variation and Predicting Variability Across Levels of Biological Organization

Differences within a biological system are ubiquitous, creating variation in nature. Variation underlies all evolutionary processes and allows persistence and resilience in changing environments; thus, uncovering the drivers of variation is critical. The growing recognition that variation is central to biology presents a timely opportunity for determining unifying principles that drive variation across biological levels of organization. Currently, most studies that consider variation are focused at a single biological level and not integrated into a broader perspective. Here we explain what variation is and how it can be measured. We then discuss the importance of variation in natural systems, and briefly describe the biological research that has focused on variation. We outline some of the barriers and solutions to studying variation and its drivers in biological systems. Finally, we detail the challenges and opportunities that may arise when studying the drivers of variation due to the multi-level nature of biological systems. Examining the drivers of variation will lead to a reintegration of biology. It will further forge interdisciplinary collaborations and open opportunities for training diverse quantitative biologists. We anticipate that these insights will inspire new questions and new analytic tools to study the fundamental questions of what drives variation in biological systems and how variation has shaped life.

Ants’ Personality and Its Dependence on Foraging Styles: Research Perspectives

The paper is devoted to analyzing consistent individual differences in behavior, also known as “personalities,” in the context of a vital ant task—the detection and transportation of food. I am trying to elucidate the extent to which collective cognition is individual-based and whether a single individual’s actions can suffice to direct the entire colony or colony units. The review analyzes personalities in various insects with different life cycles and provides new insights into the role of individuals in directing group actions in ants. Although it is widely accepted that, in eusocial insects, colony personality emerges from the workers’ personalities, there are only a few examples of investigations of personality at the individual level. The central question of the review is how the distribution of behavioral types and cognitive responsibilities within ant colonies depends on a species’ foraging style. In the context of how workers’ behavioral traits display during foraging, a crucial question is what makes an ant a scout that discovers a new food source and mobilizes its nestmates. In mass recruiting, tandem-running, and even in group-recruiting species displaying leadership, the division of labor between scouts and recruits appears to be ephemeral. There is only little, if any, evidence of ants’ careers and behavioral consistency as leaders. Personal traits characterize groups of individuals at the colony level but not performers of functional roles during foraging. The leader-scouting seems to be the only known system that is based on a consistent personal difference between scouting and foraging individuals.

Artificial selection for schooling behaviour and its effects on associative learning abilities

The evolution of collective behaviour has been proposed to have important effects on individual cognitive abilities. Yet, in what way they are related remains enigmatic. In this context, the 'distributed cognition' hypothesis suggests that reliance on other group members relaxes selection for individual cognitive abilities. Here, we tested how cognitive processes respond to evolutionary changes in collective motion using replicate lines of guppies (Poecilia reticulata) artificially selected for the degree of schooling behaviour (group polarization) with >15% difference in schooling propensity. We assessed associative learning in females of these selection lines in a series of cognitive assays: colour associative learning, reversal learning, social associative learning, and individual and collective spatial associative learning. We found that control females were faster than polarization-selected females at fulfilling a learning criterion only in the colour associative learning assay, but they were also less likely to reach a learning criterion in the individual spatial associative learning assay. Hence, although testing several cognitive domains, we found weak support for the distributed cognition hypothesis. We propose that any cognitive implications of selection for collective behaviour lie outside of the cognitive abilities included in food-motivated associative learning for visual and spatial cues.

Early olfactory, but not gustatory processing, is affected by the selection of heritable cognitive phenotypes in honey bee

Associative learning enables animals to predict rewards or punishments by their associations with predictive stimuli, while non-associative learning occurs without reinforcement. The latter includes latent inhibition (LI), whereby animals learn to ignore an inconsequential 'familiar' stimulus. Individual honey bees display heritable differences in expression of LI. We examined the behavioral and neuronal responses between honey bee genetic lines exhibiting high and low LI. We observed, as in previous studies, that high LI lines learned a familiar odor more slowly than low LI bees. By measuring gustatory responses to sucrose, we determined that perception of sucrose reward was similar between both lines, thereby not contributing to the LI phenotype. We then used extracellular electrophysiology to determine differences in neural responses of the antennal lobe (AL) to familiar and novel odors between the lines. Low LI bees responded significantly more strongly to both familiar and novel odors than the high LI bees, but the lines showed equivalent differences in response to the novel and familiar odors. This work suggests that some effects of genotype are present in early olfactory processing, and those effects could complement how LI is manifested at later stages of processing in brains of bees in the different lines.

Individual learning phenotypes drive collective behavior

Individual differences in learning can influence how animals respond to and communicate about their environment, which may nonlinearly shape how a social group accomplishes a collective task. There are few empirical examples of how differences in collective dynamics emerge from variation among individuals in cognition. Here, we use a naturally variable and heritable learning behavior called latent inhibition (LI) to show that interactions among individuals that differ in this cognitive ability drive collective foraging behavior in honey bee colonies. We artificially selected two distinct phenotypes: high-LI bees that ignore previously familiar stimuli in favor of novel ones and low-LI bees that learn familiar and novel stimuli equally well. We then provided colonies differentially composed of different ratios of these phenotypes with a choice between familiar and novel feeders. Colonies of predominantly high-LI individuals preferred to visit familiar food locations, while low-LI colonies visited novel and familiar food locations equally. Interestingly, in colonies of mixed learning phenotypes, the low-LI individuals showed a preference to visiting familiar feeders, which contrasts with their behavior when in a uniform low-LI group. We show that the shift in feeder preference of low-LI bees is driven by foragers of the high-LI phenotype dancing more intensely and attracting more followers. Our results reveal that cognitive abilities of individuals and their social interactions, which we argue relate to differences in attention, drive emergent collective outcomes.