GABAergic feedback signaling into the calyces of the mushroom bodies enables olfactory reversal learning in honey bees

GABA in the honey bee mushroom bodies - is inhibition the wellspring of plasticity?

Structural plasticity is the hallmark of the protocerebral mushroom bodies of adult insects. This plasticity is especially well-studied in social hymenopterans. In adult worker honey bees, phenomena such as increased neuropil volume, increased dendritic branching, and changes in the details of synaptic microcircuitry are associated with both the onset of foraging and the accumulation of foraging experience. Prior models of the drivers of these changes have focused on differences between the sensory environment of the hive and the world outside the hive, leading to enhanced excitatory (cholinergic) inputs to the intrinsic neurons of the mushroom bodies (Kenyon cells). This article proposes experimental and bioinformatics-based approaches for exploration of a role for changes in the inhibitory (GABAergic) innervation of the mushroom bodies as a driver of sensitive periods for structural plasticity in the honey bee brain.

Learning performance and GABAergic pathway link to deformed wing virus in the mushroom bodies of naturally infected honey bees

Viral infections can be detrimental to the foraging ability of the western honey bee, Apis mellifera. The deformed wing virus (DWV) is the most common honey bee virus and has been proposed as a possible cause of learning and memory impairment. However, evidence for this phenomenon so far has come from artificially infected bees, while less is known about the implications of natural infections with the virus. Using the proboscis extension reflex (PER), we uncovered no significant association between a simple associative learning task and natural DWV load. However, when assessed through a reversal associative learning assay, bees with higher DWV load performed better in the reversal learning phase. DWV is able to replicate in the honey bee mushroom bodies, where the GABAergic signalling pathway has an antagonistic effect on associative learning but is crucial for reversal learning. Hence, we assessed the pattern of expression of several GABA-related genes in bees with different learning responses. Intriguingly, mushroom body expression of selected genes was positively correlated with DWV load, but only for bees with good reversal learning performance. We hypothesise that DWV might improve olfactory learning performance by enhancing the GABAergic inhibition of responses to unrewarded stimuli, which is consistent with the behavioural patterns that we observed. However, at higher disease burdens, which might be induced by an artificial infection or by a severe, natural Varroa infestation, this DWV-associated increase in GABA signalling could impair associative learning as previously reported by other studies.

Acute exposure to caffeine improves foraging in an invasive ant

Argentine ants, Linepithema humile, are a particularly concerning invasive species. Control efforts often fall short likely due to a lack of sustained bait consumption. Using neuroactives, such as caffeine, to improve ant learning and navigation could increase recruitment and consumption of toxic baits. Here, we exposed L. humile to a range of caffeine concentrations and a complex ecologically relevant task: an open landscape foraging experiment. Without caffeine, we found no effect of consecutive foraging visits on the time the ants take to reach a reward, suggesting a failure to learn the reward's location. However, under low to intermediate caffeine concentrations ants were 38% faster with each consecutive visit, implying that caffeine boosts learning. Interestingly, such improvements were lost at high doses. In contrast, caffeine had no impact on the ants' homing behavior. Adding moderate levels of caffeine to baits could improve ant's ability to learn its location, improving bait efficacy.

Investigating visual navigation using spiking neural network models of the insect mushroom bodies

Ants are capable of learning long visually guided foraging routes with limited neural resources. The visual scene memory needed for this behaviour is mediated by the mushroom bodies; an insect brain region important for learning and memory. In a visual navigation context, the mushroom bodies are theorised to act as familiarity detectors, guiding ants to views that are similar to those previously learned when first travelling along a foraging route. Evidence from behavioural experiments, computational studies and brain lesions all support this idea. Here we further investigate the role of mushroom bodies in visual navigation with a spiking neural network model learning complex natural scenes. By implementing these networks in GeNN-a library for building GPU accelerated spiking neural networks-we were able to test these models offline on an image database representing navigation through a complex outdoor natural environment, and also online embodied on a robot. The mushroom body model successfully learnt a large series of visual scenes (400 scenes corresponding to a 27 m route) and used these memories to choose accurate heading directions during route recapitulation in both complex environments. Through analysing our model's Kenyon cell (KC) activity, we were able to demonstrate that KC activity is directly related to the respective novelty of input images. Through conducting a parameter search we found that there is a non-linear dependence between optimal KC to visual projection neuron (VPN) connection sparsity and the length of time the model is presented with an image stimulus. The parameter search also showed training the model on lower proportions of a route generally produced better accuracy when testing on the entire route. We embodied the mushroom body model and comparator visual navigation algorithms on a Quanser Q-car robot with all processing running on an Nvidia Jetson TX2. On a 6.5 m route, the mushroom body model had a mean distance to training route (error) of 0.144 ± 0.088 m over 5 trials, which was performance comparable to standard visual-only navigation algorithms. Thus, we have demonstrated that a biologically plausible model of the ant mushroom body can navigate complex environments both in simulation and the real world. Understanding the neural basis of this behaviour will provide insight into how neural circuits are tuned to rapidly learn behaviourally relevant information from complex environments and provide inspiration for creating bio-mimetic computer/robotic systems that can learn rapidly with low energy requirements.

Cognitive limits of larval Drosophila: testing for conditioned inhibition, sensory preconditioning, and second-order conditioning

Drosophila larvae are an established model system for studying the mechanisms of innate and simple forms of learned behavior. They have about 10 times fewer neurons than adult flies, and it was the low total number of their neurons that allowed for an electron microscopic reconstruction of their brain at synaptic resolution. Regarding the mushroom body, a central brain structure for many forms of associative learning in insects, it turned out that more than half of the classes of synaptic connection had previously escaped attention. Understanding the function of these circuit motifs, subsequently confirmed in adult flies, is an important current research topic. In this context, we test larval Drosophila for their cognitive abilities in three tasks that are characteristically more complex than those previously studied. Our data provide evidence for (i) conditioned inhibition, as has previously been reported for adult flies and honeybees. Unlike what is described for adult flies and honeybees, however, our data do not provide evidence for (ii) sensory preconditioning or (iii) second-order conditioning in Drosophila larvae. We discuss the methodological features of our experiments as well as four specific aspects of the organization of the larval brain that may explain why these two forms of learning are observed in adult flies and honeybees, but not in larval Drosophila.

The Relationship between Cognition and Brain Size or Neuron Number

The comparative approach is a powerful way to explore the relationship between brain structure and cognitive function. Thus far, the field has been dominated by the assumption that a bigger brain somehow means better cognition. Correlations between differences in brain size or neuron number between species and differences in specific cognitive abilities exist, but these correlations are very noisy. Extreme differences exist between clades in the relationship between either brain size or neuron number and specific cognitive abilities. This means that correlations become weaker, not stronger, as the taxonomic diversity of sampled groups increases. Cognition is the outcome of neural networks. Here we propose that considering plausible neural network models will advance our understanding of the complex relationships between neuron number and different aspects of cognition. Computational modelling of networks suggests that adding pathways, or layers, or changing patterns of connectivity in a network can all have different specific consequences for cognition. Consequently, models of computational architecture can help us hypothesise how and why differences in neuron number might be related to differences in cognition. As methods in connectomics continue to improve and more structural information on animal brains becomes available, we are learning more about natural network structures in brains, and we can develop more biologically plausible models of cognitive architecture. Natural animal diversity then becomes a powerful resource to both test the assumptions of these models and explore hypotheses for how neural network structure and network size might delimit cognitive function.

Differential Brain Expression Patterns of microRNAs Related to Olfactory Performance in Honey Bees (Apis mellifera)

MicroRNAs (miRNAs) play a vital role in the nerve regulation of honey bees (Apis mellifera). This study aims to investigate the differences in expression of miRNAs in a honey bee's brain for olfactory learning tasks and to explore their potential role in a honey bee's olfactory learning and memory. In this study, 12 day old honey bees with strong and weak olfactory performances were utilized to investigate the influence of miRNAs on olfactory learning behavior. The honey bee brains were dissected, and a small RNA-seq technique was used for high-throughput sequencing. The data analysis of the miRNA sequences revealed that 14 differentially expressed miRNAs (DEmiRNAs) between the two groups, strong (S) and weak (W), for olfactory performance in honey bees were identified, which included seven up-regulated and seven down-regulated. The qPCR verification results of the 14 miRNAs showed that four miRNAs (miR-184-3p, miR-276-3p, miR-87-3p, and miR-124-3p) were significantly associated with olfactory learning and memory. The target genes of these DEmiRNAs were subjected to the GO database annotation and KEGG pathway enrichment analyses. The functional annotation and pathway analysis showed that the neuroactive ligand-receptor interaction pathway, oxidative phosphorylation, biosynthesis of amino acids, pentose phosphate pathway, carbon metabolism, and terpenoid backbone biosynthesis may be a great important pathway related to olfactory learning and memory in honey bees. Our findings together further explained the relationship between olfactory performance and the brain function of honey bees at the molecular level and provides a basis for further study on miRNAs related to olfactory learning and memory in honey bees.

What is really social about social insect cognition?

It is often assumed that social life imposes specific cognitive demands for animals to communicate, cooperate and compete, ultimately requiring larger brains. The “social brain” hypothesis is supported by data in primates and some other vertebrates, but doubts have been raised over its applicability to other taxa, and in particular insects. Here, we review recent advances in insect cognition research and ask whether we can identify cognitive capacities that are specific to social species. One difficulty involved in testing the social brain hypothesis in insects is that many of the model species used in cognition studies are highly social (eusocial), and comparatively little work has been done in insects that live in less integrated social structures or that are solitary. As more species are studied, it is becoming clear that insects share a rich cognitive repertoire and that these abilities are not directly related to their level of social complexity. Moreover, some of the cognitive mechanisms involved in many social interactions may not differ from those involved in non-social behaviors. We discuss the need for a more comparative and neurobiologically grounded research agenda to better understand the evolution of insect brains and cognition.

Individual consistency in the learning abilities of honey bees: cognitive specialization within sensory and reinforcement modalities

The question of whether individuals perform consistently across a variety of cognitive tasks is relevant for studies of comparative cognition. The honey bee (Apis mellifera) is an appropriate model to study cognitive consistency as its learning can be studied in multiple elemental and non-elemental learning tasks. We took advantage of this possibility and studied if the ability of honey bees to learn a simple discrimination correlates with their ability to solve two tasks of higher complexity, reversal learning and negative patterning. We performed four experiments in which we varied the sensory modality of the stimuli (visual or olfactory) and the type (Pavlovian or operant) and complexity (elemental or non-elemental) of conditioning to examine if stable correlated performances could be observed across experiments. Across all experiments, an individual's proficiency to learn the simple discrimination task was positively and significantly correlated with performance in both reversal learning and negative patterning, while the performances in reversal learning and negative patterning were positively, yet not significantly correlated. These results suggest that correlated performances across learning paradigms represent a distinct cognitive characteristic of bees. Further research is necessary to examine if individual cognitive consistency can be found in other insect species as a common characteristic of insect brains.

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.

The gut parasite Nosema ceranae impairs olfactory learning in bumblebees

Pollinators are exposed to numerous parasites and pathogens when foraging on flowers. These biological stressors may affect critical cognitive abilities required for foraging. Here, we tested whether exposure to Nosema ceranae, one of the most widespread parasites of honey bees also found in wild pollinators, impacts cognition in bumblebees. We investigated different forms of olfactory learning and memory using conditioning of the proboscis extension reflex. Seven days after feeding parasite spores, bumblebees showed lower performances in absolute, differential, and reversal learning than controls. The consistent observations across different types of olfactory learning indicates a general negative effect of N. ceranae exposure that did not specifically target particular brain areas or neural processes. We discuss the potential mechanisms by which N. ceranae impairs bumblebee cognition and the broader consequences for populations of pollinators.

The Neural Signature of Visual Learning Under Restrictive Virtual-Reality Conditions

Honey bees are reputed for their remarkable visual learning and navigation capabilities. These capacities can be studied in virtual reality (VR) environments, which allow studying performances of tethered animals in stationary flight or walk under full control of the sensory environment. Here, we used a 2D VR setup in which a tethered bee walking stationary under restrictive closed-loop conditions learned to discriminate vertical rectangles differing in color and reinforcing outcome. Closed-loop conditions restricted stimulus control to lateral displacements. Consistently with prior VR analyses, bees learned to discriminate the trained stimuli. Ex vivo analyses on the brains of learners and non-learners showed that successful learning led to a downregulation of three immediate early genes in the main regions of the visual circuit, the optic lobes (OLs) and the calyces of the mushroom bodies (MBs). While Egr1 was downregulated in the OLs, Hr38 and kakusei were coincidently downregulated in the calyces of the MBs. Our work thus reveals that color discrimination learning induced a neural signature distributed along the sequential pathway of color processing that is consistent with an inhibitory trace. This trace may relate to the motor patterns required to solve the discrimination task, which are different from those underlying pathfinding in 3D VR scenarios allowing for navigation and exploratory learning and which lead to IEG upregulation.

Evidence of cognitive specialization in an insect: proficiency is maintained across elemental and higher-order visual learning but not between sensory modalities in honey bees

Individuals differing in their cognitive abilities and foraging strategies may confer a valuable benefit to their social groups as variability may help responding flexibly in scenarios with different resource availability. Individual learning proficiency may either be absolute or vary with the complexity or the nature of the problem considered. Determining if learning abilities correlate between tasks of different complexity or between sensory modalities has a high interest for research on brain modularity and task-dependent specialisation of neural circuits. The honeybee Apis mellifera constitutes an attractive model to address this question due to its capacity to successfully learn a large range of tasks in various sensory domains. Here we studied whether the performance of individual bees in a simple visual discrimination task (a discrimination between two visual shapes) is stable over time and correlates with their capacity to solve either a higher-order visual task (a conceptual discrimination based on spatial relations between objects) or an elemental olfactory task (a discrimination between two odorants). We found that individual learning proficiency within a given task was maintained over time and that some individuals performed consistently better than others within the visual modality, thus showing consistent aptitude across visual tasks of different complexity. By contrast, performance in the elemental visual-learning task did not predict performance in the equivalent elemental olfactory task. Overall, our results suggest the existence of cognitive specialisation within the hive, which may contribute to ecological social success.

Chronic exposure to trace lead impairs honey bee learning

Pollutants can have severe detrimental effects on insects, even at sublethal doses, damaging developmental and cognitive processes involved in crucial behaviours. Agrochemicals have been identified as important causes of pollinator declines, but the impacts of other anthropogenic compounds, such as metallic trace elements in soils and waters, have received considerably less attention. Here, we exposed colonies of the European honey bee Apis mellifera to chronic field-realistic concentrations of lead in food and demonstrated that consumption of this trace element impaired bee cognition and morphological development. Honey bees exposed to the highest of these low concentrations had reduced olfactory learning performances. These honey bees also developed smaller heads, which may have constrained their cognitive functions as we show a general relationship between head size and learning performance. Our results demonstrate that lead pollutants, even at trace levels, can have dramatic effects on honey bee cognitive abilities, potentially altering key colony functions and the pollination service.

Fruit flies can learn non-elemental olfactory discriminations

Associative learning allows animals to establish links between stimuli based on their concomitance. In the case of Pavlovian conditioning, a single stimulus A (the conditional stimulus, CS) is reinforced unambiguously with an unconditional stimulus (US) eliciting an innate response. This conditioning constitutes an 'elemental' association to elicit a learnt response from A+ without US presentation after learning. However, associative learning may involve a 'complex' CS composed of several components. In that case, the compound may predict a different outcome than the components taken separately, leading to ambiguity and requiring the animal to perform so-called non-elemental discrimination. Here, we focus on such a non-elemental task, the negative patterning (NP) problem, and provide the first evidence of NP solving in Drosophila. We show that Drosophila learn to discriminate a simple component (A or B) associated with electric shocks (+) from an odour mixture composed either partly (called 'feature-negative discrimination' A+ versus AB-) or entirely (called 'NP' A+B+ versus AB-) of the shock-associated components. Furthermore, we show that conditioning repetition results in a transition from an elemental to a configural representation of the mixture required to solve the NP task, highlighting the cognitive flexibility of Drosophila.

Honeybees solve a multi-comparison ranking task by probability matching

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 use and limitations of this simple cognitive strategy for foraging animals.

In Situ Metabolomics of the Honeybee Brain: The Metabolism of l-Arginine through the Polyamine Pathway in the Proboscis Extension Response (PER)

The proboscis extension response (PER) reflex may be used to condition the pairing of an odor with sucrose, which is applied to the antennae, in experiments to induce learning, where the odor represents a conditioned stimulus, while sucrose represents an unconditioned stimulus. A series of studies have been conducted on honeybees, relating learning and memory acquisition/retrieval using the PER as a strategy for accessing their ability to exhibit an unconditioned stimulus; however, the major metabolic processes involved in the PER are not well known. Thus, the aim of this investigation is profiling the metabolome of the honeybee brain involved in the PER. In this study, a semiquantitative approach of matrix-assisted laser desorption ionization (MALDI) mass spectral imaging (MSI) was used to profile the most abundant metabolites of the honeybee brain that support the PER. It was reported that execution of the PER requires the metabolic transformations of arginine, ornithine, and lysine as substrates for the production of putrescine, cadaverine, spermine, spermidine, 1,3-diaminopropane, and γ-aminobutyric acid (GABA). Considering the global metabolome of the brain of honeybee workers, the PER requires the consumption of large amounts of cadaverine and 1,3-diaminopropane, in parallel with the biosynthesis of high amounts of spermine, spermidine, and ornithine. To exhibit the PER, the brain of honeybee workers processes the conversion of l-arginine and l-lysine through the polyamine pathway, with different regional metabolomic profiles at the individual neuropil level. The outcomes of this study using this metabolic route as a reference are indicating that the antennal lobes and the calices (medial and lateral) were the most active brain regions for supporting the PER.

Reversal learning in Drosophila larvae

Adjusting behavior to changed environmental contingencies is critical for survival, and reversal learning provides an experimental handle on such cognitive flexibility. Here, we investigate reversal learning in larval Drosophila Using odor-taste associations, we establish olfactory reversal learning in the appetitive and the aversive domain, using either fructose as a reward or high-concentration sodium chloride as a punishment, respectively. Reversal learning is demonstrated both in differential and in absolute conditioning, in either valence domain. In differential conditioning, the animals are first trained such that an odor A is paired, for example, with the reward whereas odor B is not (A+/B); this is followed by a second training phase with reversed contingencies (A/B+). In absolute conditioning, odor B is omitted, such that the animals are first trained with paired presentations of A and reward, followed by unpaired training in the second training phase. Our results reveal "true" reversal learning in that the opposite associative effects of both the first and the second training phase are detectable after reversed-contingency training. In what is a surprisingly quick, one-trial contingency adjustment in the Drosophila larva, the present study establishes a simple and genetically easy accessible study case of cognitive flexibility.

Abstract concept learning in a simple neural network inspired by the insect brain

The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly have this capacity. Here we report a model of the structures of the honey bee brain that can learn sameness and difference, as well as a range of complex and simple associative learning tasks. Our model is constrained by the known connections and properties of the mushroom body, including the protocerebral tract, and provides a good fit to the learning rates and performances of real bees in all tasks, including learning sameness and difference. The model proposes a novel mechanism for learning the abstract concepts of 'sameness' and 'difference' that is compatible with the insect brain, and is not dependent on top-down or executive control processing.

Associative Learning of Stimuli Paired and Unpaired With Reinforcement: Evaluating Evidence From Maggots, Flies, Bees, and Rats

Finding rewards and avoiding punishments are powerful goals of behavior. To maximize reward and minimize punishment, it is beneficial to learn about the stimuli that predict their occurrence, and decades of research have provided insight into the brain processes underlying such associative reinforcement learning. In addition, it is well known in experimental psychology, yet often unacknowledged in neighboring scientific disciplines, that subjects also learn about the stimuli that predict the absence of reinforcement. Here we evaluate evidence for both these learning processes. We focus on two study cases that both provide a baseline level of behavior against which the effects of associative learning can be assessed. Firstly, we report pertinent evidence from Drosophila larvae. A re-analysis of the literature reveals that through paired presentations of an odor A and a sugar reward (A+) the animals learn that the reward can be found where the odor is, and therefore show an above-baseline preference for the odor. In contrast, through unpaired training (A/+) the animals learn that the reward can be found precisely where the odor is not, and accordingly these larvae show a below-baseline preference for it (the same is the case, with inverted signs, for learning through taste punishment). In addition, we present previously unpublished data demonstrating that also during a two-odor, differential conditioning protocol (A+/B) both these learning processes take place in larvae, i.e., learning about both the rewarded stimulus A and the non-rewarded stimulus B (again, this is likewise the case for differential conditioning with taste punishment). Secondly, after briefly discussing published evidence from adult Drosophila, honeybees, and rats, we report an unpublished data set showing that relative to baseline behavior after truly random presentations of a visual stimulus A and punishment, rats exhibit memories of opposite valence upon paired and unpaired training. Collectively, the evidence conforms to classical findings in experimental psychology and suggests that across species animals associatively learn both through paired and through unpaired presentations of stimuli with reinforcement – with opposite valence. While the brain mechanisms of unpaired learning for the most part still need to be uncovered, the immediate implication is that using unpaired procedures as a mnemonically neutral control for associative reinforcement learning may be leading analyses astray.

Neural Organization of A3 Mushroom Body Extrinsic Neurons in the Honeybee Brain

In the insect brain, the mushroom body is a higher order brain area that is key to memory formation and sensory processing. Mushroom body (MB) extrinsic neurons leaving the output region of the MB, the lobes and the peduncle, are thought to be especially important in these processes. In the honeybee brain, a distinct class of MB extrinsic neurons, A3 neurons, are implicated in playing a role in learning. Their MB arborisations are either restricted to the lobes and the peduncle, here called A3 lobe connecting neurons, or they provide feedback information from the lobes to the input region of the MB, the calyces, here called A3 feedback neurons. In this study, we analyzed the morphology of individual A3 lobe connecting and feedback neurons using confocal imaging. A3 feedback neurons were previously assumed to innervate each lip compartment homogenously. We demonstrate here that A3 feedback neurons do not innervate whole subcompartments, but rather innervate zones of varying sizes in the MB lip, collar, and basal ring. We describe for the first time the anatomical details of A3 lobe connecting neurons and show that their connection pattern in the lobes resemble those of A3 feedback cells. Previous studies showed that A3 feedback neurons mostly connect zones of the vertical lobe that receive input from Kenyon cells of distinct calycal subcompartments with the corresponding subcompartments of the calyces. We can show that this also applies to the neck of the peduncle and the medial lobe, where both types of A3 neurons arborize only in corresponding zones in the calycal subcompartments. Some A3 lobe connecting neurons however connect multiple vertical lobe areas. Contrarily, in the medial lobe, the A3 neurons only innervate one division. We found evidence for both input and output areas in the vertical lobe. Thus, A3 neurons are more diverse than previously thought. The understanding of their detailed anatomy might enable us to derive circuit models for learning and memory and test physiological data.

Quantifying the impact of pesticides on learning and memory in bees

Most insecticides are insect neurotoxins. Evidence is emerging that sublethal doses of these neurotoxins are affecting the learning and memory of both wild and managed bee colonies, exacerbating the negative effects of pesticide exposure and reducing individual foraging efficiency.

Variation in methodologies and interpretation of results across studies has precluded the quantitative evaluation of these impacts that is needed to make recommendations for policy change. It is not clear whether robust effects occur under acute exposure regimes (often argued to be more field‐realistic than the chronic regimes upon which many studies are based), for field‐realistic dosages, and for pesticides other than neonicotinoids.

Here we use meta‐analysis to examine the impact of pesticides on bee performance in proboscis extension‐based learning assays, the paradigm most commonly used to assess learning and memory in bees. We draw together 104 (learning) and 167 (memory) estimated effect sizes across a diverse range of studies.

We detected significant negative effects of pesticides on learning and memory (i) at field realistic dosages, (ii) under both chronic and acute application, and (iii) for both neonicotinoid and non‐neonicotinoid pesticides groups.

We also expose key gaps in the literature that include a critical lack of studies on non‐Apis bees, on larval exposure (potentially one of the major exposure routes), and on performance in alternative learning paradigms.

Policy implications. Procedures for the registration of new pesticides within EU member states now typically require assessment of risks to pollinators if potential target crops are attractive to bees. However, our results provide robust quantitative evidence for subtle, sublethal effects, the consequences of which are unlikely to be detected within small‐scale prelicensing laboratory or field trials, but can be critical when pesticides are used at a landscape scale. Our findings highlight the need for long‐term postlicensing environmental safety monitoring as a requirement within licensing policy for plant protection products.

Relationship between brain plasticity, learning and foraging performance in honey bees

Brain structure and learning capacities both vary with experience, but the mechanistic link between them is unclear. Here, we investigated whether experience-dependent variability in learning performance can be explained by neuroplasticity in foraging honey bees. The mushroom bodies (MBs) are a brain center necessary for ambiguous olfactory learning tasks such as reversal learning. Using radio frequency identification technology, we assessed the effects of natural variation in foraging activity, and the age when first foraging, on both performance in reversal learning and on synaptic connectivity in the MBs. We found that reversal learning performance improved at foraging onset and could decline with greater foraging experience. If bees started foraging before the normal age, as a result of a stress applied to the colony, the decline in learning performance with foraging experience was more severe. Analyses of brain structure in the same bees showed that the total number of synaptic boutons at the MB input decreased when bees started foraging, and then increased with greater foraging intensity. At foraging onset MB structure is therefore optimized for bees to update learned information, but optimization of MB connectivity deteriorates with foraging effort. In a computational model of the MBs sparser coding of information at the MB input improved reversal learning performance. We propose, therefore, a plausible mechanistic relationship between experience, neuroplasticity, and cognitive performance in a natural and ecological context.

Experience during early adulthood shapes the learning capacities and the number of synaptic boutons in the mushroom bodies of honey bees (Apis mellifera)

The honey bee mushroom bodies (MBs) are brain centers required for specific learning tasks. Here, we show that environmental conditions experienced as young adults affect the maturation of MB neuropil and performance in a MB-dependent learning task. Specifically, olfactory reversal learning was selectively impaired following early exposure to an impoverished environment lacking some of the sensory and social interactions present in the hive. In parallel, the overall number of synaptic boutons increased within the MB olfactory neuropil, whose volume remained unaffected. This suggests that experience of the rich in-hive environment promotes MB maturation and the development of MB-dependent learning capacities.

Different Roles for Honey Bee Mushroom Bodies and Central Complex in Visual Learning of Colored Lights in an Aversive Conditioning Assay

The honey bee is an excellent visual learner, but we know little about how and why it performs so well, or how visual information is learned by the bee brain. Here we examined the different roles of two key integrative regions of the brain in visual learning: the mushroom bodies and the central complex. We tested bees' learning performance in a new assay of color learning that used electric shock as punishment. In this assay a light field was paired with electric shock. The other half of the conditioning chamber was illuminated with light of a different wavelength and not paired with shocks. The unrestrained bee could run away from the light stimulus and thereby associate one wavelength with punishment, and the other with safety. We compared learning performance of bees in which either the central complex or mushroom bodies had been transiently inactivated by microinjection of the reversible anesthetic procaine. Control bees learned to escape the shock-paired light field and to spend more time in the safe light field after a few trials. When ventral lobe neurons of the mushroom bodies were silenced, bees were no longer able to associate one light field with shock. By contrast, silencing of one collar region of the mushroom body calyx did not alter behavior in the learning assay in comparison to control treatment. Bees with silenced central complex neurons did not leave the shock-paired light field in the middle trials of training, even after a few seconds of being shocked. We discussed how mushroom bodies and the central complex both contribute to aversive visual learning with an operant component.

Why Bees Are So Vulnerable to Environmental Stressors

Bee populations are declining in the industrialized world, raising concerns for the sustainable pollination of crops. Pesticides, pollutants, parasites, diseases, and malnutrition have all been linked to this problem. We consider here neurobiological, ecological, and evolutionary reasons why bees are particularly vulnerable to these environmental stressors. Central-place foraging on flowers demands advanced capacities of learning, memory, and navigation. However, even at low intensity levels, many stressors damage the bee brain, disrupting key cognitive functions needed for effective foraging, with dramatic consequences for brood development and colony survival. We discuss how understanding the relationships between the actions of stressors on the nervous system, individual cognitive impairments, and colony decline can inform constructive interventions to sustain bee populations.

Advances and limitations of visual conditioning protocols in harnessed bees

Bees are excellent invertebrate models for studying visual learning and memory mechanisms, because of their sophisticated visual system and impressive cognitive capacities associated with a relatively simple brain. Visual learning in free-flying bees has been traditionally studied using an operant conditioning paradigm. This well-established protocol, however, can hardly be combined with invasive procedures for studying the neurobiological basis of visual learning. Different efforts have been made to develop protocols in which harnessed honey bees could associate visual cues with reinforcement, though learning performances remain poorer than those obtained with free-flying animals. Especially in the last decade, the intention of improving visual learning performances of harnessed bees led many authors to adopt distinct visual conditioning protocols, altering parameters like harnessing method, nature and duration of visual stimulation, number of trials, inter-trial intervals, among others. As a result, the literature provides data hardly comparable and sometimes contradictory. In the present review, we provide an extensive analysis of the literature available on visual conditioning of harnessed bees, with special emphasis on the comparison of diverse conditioning parameters adopted by different authors. Together with this comparative overview, we discuss how these diverse conditioning parameters could modulate visual learning performances of harnessed bees.

Complete identification of four giant interneurons supplying mushroom body calyces in the cockroach Periplaneta americana

Global inhibition is a fundamental physiological mechanism that has been proposed to shape odor representation in higher-order olfactory centers. A pair of mushroom bodies (MBs) in insect brains, an analog of the mammalian olfactory cortex, are implicated in multisensory integration and associative memory formation. With the use of single/multiple intracellular recording and staining in the cockroach Periplaneta americana, we succeeded in unambiguous identification of four tightly bundled GABA-immunoreactive giant interneurons that are presumably involved in global inhibitory control of the MB. These neurons, including three spiking neurons and one nonspiking neuron, possess dendrites in termination fields of MB output neurons and send axon terminals back to MB input sites, calyces, suggesting feedback roles onto the MB. The largest spiking neuron innervates almost exclusively the basal region of calyces, while the two smaller spiking neurons and the second-largest nonspiking neuron innervate more profusely the peripheral (lip) region of the calyces than the basal region. This subdivision corresponds well to the calycal zonation made by axon terminals of two populations of uniglomerular projection neurons with dendrites in distinct glomerular groups in the antennal lobe. The four giant neurons exhibited excitatory responses to every odor tested in a neuron-specific fashion, and two of the neurons also exhibited inhibitory responses in some recording sessions. Our results suggest that two parallel olfactory inputs to the MB undergo different forms of inhibitory control by the giant neurons, which may, in turn, be involved in different aspects of odor discrimination, plasticity, and state-dependent gain control. J. Comp. Neurol. 525:204-230, 2017. © 2016 Wiley Periodicals, Inc.

Neural substrate for higher-order learning in an insect: Mushroom bodies are necessary for configural discriminations

Learning theories distinguish elemental from configural learning based on their different complexity. Although the former relies on simple and unambiguous links between the learned events, the latter deals with ambiguous discriminations in which conjunctive representations of events are learned as being different from their elements. In mammals, configural learning is mediated by brain areas that are either dispensable or partially involved in elemental learning. We studied whether the insect brain follows the same principles and addressed this question in the honey bee, the only insect in which configural learning has been demonstrated. We used a combination of conditioning protocols, disruption of neural activity, and optophysiological recording of olfactory circuits in the bee brain to determine whether mushroom bodies (MBs), brain structures that are essential for memory storage and retrieval, are equally necessary for configural and elemental olfactory learning. We show that bees with anesthetized MBs distinguish odors and learn elemental olfactory discriminations but not configural ones, such as positive and negative patterning. Inhibition of GABAergic signaling in the MB calyces, but not in the lobes, impairs patterning discrimination, thus suggesting a requirement of GABAergic feedback neurons from the lobes to the calyces for nonelemental learning. These results uncover a previously unidentified role for MBs besides memory storage and retrieval: namely, their implication in the acquisition of ambiguous discrimination problems. Thus, in insects as in mammals, specific brain regions are recruited when the ambiguity of learning tasks increases, a fact that reveals similarities in the neural processes underlying the elucidation of ambiguous tasks across species.