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Pollutants can have severe detrimental effects on insects, even at sublethal doses. Agrochemicals have been identified as important causes of pollinator declines, but the impacts of other anthropogenic compounds, such as metallic trace elements contaminating soils and waters, have received considerably less attention. Here, we exposed honey bee colonies to chronic field-realistic concentrations of lead in food and demonstrate that consumption of this single trace element impaired bee cognition and morphological development. Honey bees exposed to the highest lead concentration had reduced olfactory learning performances and developed smaller heads, which may have constrained their cognitive functions. Our results show that lead pollutants can have dramatic effects on honey bee health and may contribute to the widespread decline of pollinators.

We examined how bees solve a visual discrimination task that uses stimuli commonly found in numerical cognition studies. Bees performed well on the task, but additional tests showed that they had learned continuous (non-numerical) cues. A network model using biologically plausible visual feature filtering and a simple associative rule was capable of learning the task using only continuous cues inherent in the training stimuli, with no numerical processing. This model was also able to reproduce behaviours that have been considered in other studies indicative of numerical cognition. Our results support the idea that a sense of magnitude may be more primitive and basic than a sense of number. Our findings highlight how problematic inadvertent continuous cues can be for studies of numerical cognition. This remains a deep issue within the field that requires increased vigilance and cleverness from the experimenter. We suggest ways of better assessing numerical cognition in non-speaking animals, including assessing the use of all alternative cues in one test, using cross-modal cues, analysing behavioural responses to detect underlying strategies and finding the neural substrate.

International audience; Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit several patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in details, how populations of individuals exploit resources in a common area is an open question difficult to address experimentally. Here we explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of route segments leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, a negative reinforcement of route segments leading to unrewarding flowers is necessary when flowers are patchily distributed. In these more complex environments, the negative experiences of individual bees favour the spatial segregation of foragers and high levels of collective foraging efficiency.

Honeybees forage on diverse flowers which vary in the amount and type of rewards they offer, and bees are challenged with maximizing the resources they gather for their colony. That bees are effective foragers is clear, but how bees solve this type of complex multi-choice task is unknown. Here, we set bees a five-comparison choice task in which five colours differed in their probability of offering reward and punishment. The colours were ranked such that high ranked colours were more likely to offer reward, and the ranking was unambiguous. Bees' choices in unrewarded tests matched their individual experiences of reward and punishment of each colour, indicating bees solved this test not by comparing or ranking colours but by basing their colour choices on their history of reinforcement for each colour. Computational modelling suggests a structure like the honeybee mushroom body with reinforcement-related plasticity at both input and output can be sufficient for this cognitive strategy. We discuss how probability matching enables effective choices to be made without a need to compare any stimuli directly, and the utility and limitations of this simple cognitive strategy for foraging animals.

International audience; Workers of social insects, such as bees, ants and wasps, show some degree of inter-individual variability in decision-making, learning and memory. Whether these natural cognitive differences translate into distinct adaptive behavioural strategies is virtually unknown. Here we examined variability in the movement patterns of bumblebee foragers establishing routes between artificial flowers. We recorded all flower visitation sequences performed by 29 bees tested for 20 consecutive foraging bouts in three experimental arrays, each characterised by a unique spatial configuration of artificial flowers and three-dimensional landmarks. All bees started to develop efficient routes as they accumulated foraging experience in each array, and showed consistent inter-individual differences in their levels of route fidelity and foraging performance, as measured by travel speed and the frequency of revisits to flowers. While the tendency of bees to repeat the same route was influenced by their colony origin, foraging performance was correlated to body size. The largest foragers travelled faster and made less revisits to empty flowers. We discuss the possible adaptive value of such inter-individual variability within the forager caste for optimisation of colony-level foraging performances in social pollinators.

Division of labor is a hallmark of social insects. In the honeybee (Apis mellifera) each sterile female worker performs a series of social tasks. The most drastic changes in behavior occur when a nurse bee, who takes care of the brood and the queen in the hive, transitions to foraging behavior. Foragers provision the colony with pollen, nectar or water. Nurse bees and foragers differ in numerous behaviors, including responsiveness to gustatory stimuli. Differences in gustatory responsiveness, in turn, might be involved in regulating division of labor through differential sensory response thresholds. Biogenic amines are important modulators of behavior. Tyramine and octopamine have been shown to increase gustatory responsiveness in honeybees when injected into the thorax, thereby possibly triggering social organization. So far, most of the experiments investigating the role of amines on gustatory responsiveness have focused on the brain. The potential role of the fat body in regulating sensory responsiveness and division of labor has large been neglected. We here investigated the role of the fat body in modulating gustatory responsiveness through tyramine signaling in different social roles of honeybees. We quantified levels of tyramine, tyramine receptor gene expression and the effect of elevating fat body tyramine titers on gustatory responsiveness in both nurse bees and foragers. Our data suggest that elevating the tyramine titer in the fat body pharmacologically increases gustatory responsiveness in foragers, but not in nurse bees. This differential effect of tyramine on gustatory responsiveness correlates with a higher natural gustatory responsiveness of foragers, with a higher tyramine receptor (Amtar1) mRNA expression in fat bodies of foragers and with lower baseline tyramine titers in fat bodies of foragers compared to those of nurse bees. We suggest that differential tyramine signaling in the fat body has an important role in the plasticity of division of labor through changing gustatory responsiveness.

Members of the natural resistance-associated macrophage protein (NRAMP) family are evolutionarily conserved metal ion transporters that play an essential role in regulating intracellular divalent cation homeostasis in both prokaryotes and eukaryotes. Malvolio (Mvl), the sole NRAMP family member in insects, plays a role in food choice behaviors in Drosophila and other species. However, the specific physiological and cellular processes that require the action of Mvl for appropriate feeding decisions remain elusive. Here, we show that normal food choice requires Mvl function specifically in the dopaminergic system, and can be rescued by supplementing food with manganese. Collectively, our data indicate that the action of the Mvl transporter affects food choice behavior via the regulation of dopaminergic innervation of the mushroom bodies, a principle brain region associated with decision-making in insects. Our studies suggest that the homeostatic regulation of the intraneuronal levels of divalent cations plays an important role in the development and function of the dopaminergic system and associated behaviors.

The insect central complex (CX) is an enigmatic structure whose computational function has evaded inquiry, but has been implicated in a wide range of behaviours. Recent experimental evidence from the fruit fly (Drosophila melanogaster) and the cockroach (Blaberus discoidalis) has demonstrated the existence of neural activity corresponding to the animal's orientation within a virtual arena (a neural 'compass'), and this provides an insight into one component of the CX structure. There are two key features of the compass activity: an offset between the angle represented by the compass and the true angular position of visual features in the arena, and the remapping of the 270° visual arena onto an entire circle of neurons in the compass. Here we present a computational model which can reproduce this experimental evidence in detail, and predicts the computational mechanisms that underlie the data. We predict that both the offset and remapping of the fly's orientation onto the neural compass can be explained by plasticity in the synaptic weights between segments of the visual field and the neurons representing orientation. Furthermore, we predict that this learning is reliant on the existence of neural pathways that detect rotational motion across the whole visual field and uses this rotation signal to drive the rotation of activity in a neural ring attractor. Our model also reproduces the 'transitioning' between visual landmarks seen when rotationally symmetric landmarks are presented. This model can provide the basis for further investigation into the role of the central complex, which promises to be a key structure for understanding insect behaviour, as well as suggesting approaches towards creating fully autonomous robotic agents.