The concepts of 'sameness' and 'difference' in an insect

A right antenna for social behaviour in honeybees

Sophisticated cognitive abilities have been documented in honeybees, possibly an aspect of their complex sociality. In vertebrates brain asymmetry enhances cognition and directional biases of brain function are a putative adaptation to social behaviour. Here we show that honeybees display a strong lateral preference to use their right antenna in social interactions. Dyads of bees tested using only their right antennae (RA) contacted after shorter latency and were significantly more likely to interact positively (proboscis extension) than were dyads of bees using only their left antennae (LA). The latter were more likely to interact negatively (C-responses) even though they were from the same hive. In dyads from different hives C-responses were higher in RA than LA dyads. Hence, RA controls social behaviour appropriate to context. Therefore, in invertebrates, as well as vertebrates, lateral biases in behaviour appear to be associated with requirements of social life.

Conceptual learning by miniature brains

Concepts act as a cornerstone of human cognition. Humans and non-human primates learn conceptual relationships such as 'same', 'different', 'larger than', 'better than', among others. In all cases, the relationships have to be encoded by the brain independently of the physical nature of objects linked by the relation. Consequently, concepts are associated with high levels of cognitive sophistication and are not expected in an insect brain. Yet, various works have shown that the miniature brain of honeybees rapidly learns conceptual relationships involving visual stimuli. Concepts such as 'same', 'different', 'above/below of' or 'left/right are well mastered by bees. We review here evidence about concept learning in honeybees and discuss both its potential adaptive advantage and its possible neural substrates. The results reviewed here challenge the traditional view attributing supremacy to larger brains when it comes to the elaboration of concepts and have wide implications for understanding how brains can form conceptual relations.

A hexapod walker using a heterarchical architecture for action selection

Moving in a cluttered environment with a six-legged walking machine that has additional body actuators, therefore controlling 22 DoFs, is not a trivial task. Already simple forward walking on a flat plane requires the system to select between different internal states. The orchestration of these states depends on walking velocity and on external disturbances. Such disturbances occur continuously, for example due to irregular up-and-down movements of the body or slipping of the legs, even on flat surfaces, in particular when negotiating tight curves. The number of possible states is further increased when the system is allowed to walk backward or when front legs are used as grippers and cannot contribute to walking. Further states are necessary for expansion that allow for navigation. Here we demonstrate a solution for the selection and sequencing of different (attractor) states required to control different behaviors as are forward walking at different speeds, backward walking, as well as negotiation of tight curves. This selection is made by a recurrent neural network (RNN) of motivation units, controlling a bank of decentralized memory elements in combination with the feedback through the environment. The underlying heterarchical architecture of the network allows to select various combinations of these elements. This modular approach representing an example of neural reuse of a limited number of procedures allows for adaptation to different internal and external conditions. A way is sketched as to how this approach may be expanded to form a cognitive system being able to plan ahead. This architecture is characterized by different types of modules being arranged in layers and columns, but the complete network can also be considered as a holistic system showing emergent properties which cannot be attributed to a specific module.

Learning non-adjacent regularities at age 0 ; 7

One important mechanism suggested to underlie the acquisition of grammar is rule learning. Indeed, infants aged 0 ; 7 are able to learn rules based on simple identity relations (adjacent repetitions, ABB: "wo fe fe" and non-adjacent repetitions, ABA: "wo fe wo", respectively; Marcus et al., 1999). One unexplored issue is whether young infants are able to process both adjacent and non-adjacent repetitions. As the previous studies always compared the two types of repetition structures directly, the ability to learn only one of them was sufficient for successful discrimination in these tasks. The present study reports two experiments, in which we test the ability of infants aged 0 ; 7 to discriminate adjacent and non-adjacent repetition structures against random controls (ABB vs. ABC and ABA vs. ABC). We show that, contrary to some previous proposals, infants aged 0 ; 7 successfully discriminate both repetition types from random controls, but show no spontaneous preference for either of them.

Specialised use of working memory by Portia africana, a spider-eating salticid

Using expectancy-violation methods, we investigated the role of working memory in the predatory strategy of Portia africana, a salticid spider from Kenya that preys by preference on other spiders. One of this predator's tactics is to launch opportunistic leaping attacks on to other spiders in their webs. Focussing on this particular tactic, our experiments began with a test spider on a ramp facing a lure (dead prey spider mounted on a cork disc) that could be reached by leaping. After the test spider faced the lure for 30 s, we blocked the test spider's view of the lure by lowering an opaque shutter before the spider leapt. When the shutter was raised 90 s later, either the same lure came into view again (control) or a different lure came into view (experimental: different prey type in same orientation or same prey type in different orientation). We recorded attack frequency (number of test spiders that leapt at the lure) and attack latency (time elapsing between shutter being raised and spiders initiating a leap). Attack latencies in control trials were not significantly different from attack latencies in experimental trials, regardless of whether it was prey type or prey orientation that changed in the experimental trials. However, compared with test spiders in the no-change control trials, significantly fewer test spiders leapt when prey type changed. There was no significant effect on attack frequency when prey orientation changed. These findings suggest that this predator represents prey type independently of prey orientation.

Invertebrate learning and cognition: relating phenomena to neural substrate

Diverse invertebrate species have been used for studies of learning and comparative cognition. Although we have gained invaluable information from this, in this study we argue that our approach to comparative learning research is rather deficient. Generally invertebrate learning research has focused mainly on arthropods, and most of that within the Hymenoptera and Diptera. Any true comparative analysis of the distribution of comparative cognitive abilities across phyla is hampered by this bias, and more fundamentally by a reporting bias toward positive results. To understand the limits of learning and cognition for a species, knowing what animals cannot do is at least as important as reporting what they can. Finally, much more effort needs to be focused on the neurobiological analysis of different types of learning to truly understand the differences and similarities of learning types. In this review, we first give a brief overview of the various forms of learning in invertebrates. We also suggest areas where further study is needed for a more comparative understanding of learning. Finally, using what is known of learning in honeybees and the well-studied honeybee brain, we present a model of how various complex forms of learning may be accounted for with the same neural circuitry required for so-called simple learning types. At the neurobiological level, different learning phenomena are unlikely to be independent, and without considering this it is very difficult to correctly interpret the phylogenetic distribution of learning and cognitive abilities. WIREs Cogn Sci 2013, 4:561-582. doi: 10.1002/wcs.1248 For further resources related to this article, please visit the WIREs website.

Honey bee promoter sequences for targeted gene expression

The honey bee, Apis mellifera, displays a rich behavioural repertoire, social organization and caste differentiation, and has an interesting mode of sex determination, but we still know little about its underlying genetic programs. We lack stable transgenic tools in honey bees that would allow genetic control of gene activity in stable transgenic lines. As an initial step towards a transgenic method, we identified promoter sequences in the honey bee that can drive constitutive, tissue-specific and cold shock-induced gene expression. We identified the promoter sequences of Am-actin5c, elp2l, Am-hsp83 and Am-hsp70 and showed that, except for the elp2l sequence, the identified sequences were able to drive reporter gene expression in Sf21 cells. We further demonstrated through electroporation experiments that the putative neuron-specific elp2l promoter sequence can direct gene expression in the honey bee brain. The identification of these promoter sequences is an important initial step in studying the function of genes with transgenic experiments in the honey bee, an organism with a rich set of interesting phenotypes.

Seeing is believing: information content and behavioural response to visual and chemical cues

Predator avoidance and foraging often pose conflicting demands. Animals can decrease mortality risk searching for predators, but searching decreases foraging time and hence intake. We used this principle to investigate how prey should use information to detect, assess and respond to predation risk from an optimal foraging perspective. A mathematical model showed that solitary bees should increase flower examination time in response to predator cues and that the rate of false alarms should be negatively correlated with the relative value of the flower explored. The predatory ant, Oecophylla smaragdina, and the harmless ant, Polyrhachis dives, differ in the profile of volatiles they emit and in their visual appearance. As predicted, the solitary bee Nomia strigata spent more time examining virgin flowers in presence of predator cues than in their absence. Furthermore, the proportion of flowers rejected decreased from morning to noon, as the relative value of virgin flowers increased. In addition, bees responded differently to visual and chemical cues. While chemical cues induced bees to search around flowers, bees detecting visual cues hovered in front of them. These strategies may allow prey to identify the nature of visual cues and to locate the source of chemical cues.

The effect of flower-like and non-flower-like visual properties on choice of unrewarding patterns by bumblebees

How do distinct visual stimuli help bumblebees discover flowers before they have experienced any reward outside of their nest? Two visual floral properties, type of a pattern (concentric vs radial) and its position on unrewarding artificial flowers (central vs peripheral on corolla), were manipulated in two experiments. Both visual properties showed significant effects on floral choice. When pitted against each other, pattern was more important than position. Experiment 1 shows a significant effect of concentric pattern position, and experiment 2 shows a significant preference towards radial patterns regardless of their position. These results show that the presence of markings at the center of a flower are not so important as the presence of markings that will direct bees there.

Numerical cognition in bees and other insects

The ability to perceive the number of objects has been known to exist in vertebrates for a few decades, but recent behavioral investigations have demonstrated that several invertebrate species can also be placed on the continuum of numerical abilities shared with birds, mammals, and reptiles. In this review article, we present the main experimental studies that have examined the ability of insects to use numerical information. These studies have made use of a wide range of methodologies, and for this reason it is striking that a common finding is the inability of the tested animals to discriminate numerical quantities greater than four. Furthermore, the finding that bees can not only transfer learnt numerical discrimination to novel objects, but also to novel numerosities, is strongly suggestive of a true, albeit limited, ability to count. Later in the review, we evaluate the available evidence to narrow down the possible mechanisms that the animals might be using to solve the number-based experimental tasks presented to them. We conclude by suggesting avenues of further research that take into account variables such as the animals' age and experience, as well as complementary cognitive systems such as attention and the time sense.

The cyanobacterial neurotoxin β-N-methylamino-l-alanine (BMAA) induces neuronal and behavioral changes in honeybees

The cyanobacterially produced neurotoxin beta-N-methylamino-l-alanine (BMAA) is thought to induce amyotrophic lateral sclerosis/Parkinsonism dementia complex (ALS/PDC)-like symptoms. However, its mechanism of action and its pathway of intoxication are yet unknown. In vivo animal models suitable for investigating the neurotoxic effect of BMAA with applicability to the human are scarce. Hence, we used the honeybee (Apis mellifera) since its nervous system is relatively simple, yet having cognitive capabilities. Bees fed with BMAA-spiked sugar water had an increased mortality rate and a reduced ability to learn odors in a classical conditioning paradigm. Using (14)C-BMAA we demonstrated that BMAA is biologically available to the bee, and is found in the head, thorax and abdomen with little to no excretion. BMAA is also transferred from one bee to the next via trophallaxis resulting in an exposure of the whole beehive. BMAA bath application directly onto the brain leads to an altered Ca(2+) homeostasis and to generation of reactive oxygen species. These behavioral and physiological observations suggest that BMAA may have effects on bee brains similar to those assumed to occur in humans. Therefore the bee could serve as a surrogate model system for investigating the neurological effects of BMAA.

Taï chimpanzees use botanical skills to discover fruit: what we can learn from their mistakes

Fruit foragers are known to use spatial memory to relocate fruit, yet it is unclear how they manage to find fruit in the first place. In this study, we investigated whether chimpanzees (Pan troglodytes verus) in the Taï National Park make use of fruiting synchrony, the simultaneous emergence of fruit in trees of the same species, which can be used together with sensory cues, such as sight and smell, to discover fruit. We conducted observations of inspections, the visual checking of fruit availability in trees, and focused our analyses on inspections of empty trees, so to say "mistakes". Learning from their "mistakes", we found that chimpanzees had expectations of finding fruit days before feeding on it and significantly increased inspection activity after tasting the first fruit. Neither the duration of feeding nor density of fruit-bearing trees in the territory could account for the variation in inspection activity, which suggests chimpanzees did not simply develop a taste for specific fruit on which they had fed frequently. Instead, inspection activity was predicted by a botanical feature-the level of synchrony in fruit production of encountered trees. We conclude that chimpanzees make use of the synchronous emergence of rainforest fruits during daily foraging and base their expectations of finding fruit on a combination of botanical knowledge founded on the success rates of fruit discovery, and a categorization of fruit species. Our results provide new insights into the variety of food-finding strategies employed by primates and the adaptive value of categorization capacities.

Bayesian learning and the psychology of rule induction

In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to spell out the underlying assumptions, and to confront them with the empirical results Frank and Tenenbaum (2011) propose to simulate, as well as with novel experiments. While rule-learning is arguably well suited to rational Bayesian approaches, I show that their models are neither psychologically plausible nor ideal observer models. Further, I show that their central assumption is unfounded: humans do not always preferentially learn more specific rules, but, at least in some situations, those rules that happen to be more salient. Even when granting the unsupported assumptions, I show that all of the experiments modeled by Frank and Tenenbaum (2011) either contradict their models, or have a large number of more plausible interpretations. I provide an alternative account of the experimental data based on simple psychological mechanisms, and show that this account both describes the data better, and is easier to falsify. I conclude that, despite the recent surge in Bayesian models of cognitive phenomena, psychological phenomena are best understood by developing and testing psychological theories rather than models that can be fit to virtually any data.

Cognitive abilities in Malawi cichlids (Pseudotropheus sp.): matching-to-sample and image/mirror-image discriminations

The ability to recognize and distinguish between visual stimuli is fundamental for everyday survival of many species. While diverse aspects of cognition, including complex visual discrimination tasks were previously successfully assessed in fish, it remains unknown if fish can learn a matching-to-sample concept using geometrical shapes and discriminate between images and their mirror-image counterparts. For this purpose a total of nine Malawi cichlids (Pseudotropheus sp.) were trained in two matching-to-sample (MTS) and three two-choice discrimination tasks using geometrical, two-dimensional visual stimuli. Two out of the three discrimination experiments focused on the ability to discriminate between images and their mirror-images, the last was a general discrimination test. All fish showed quick associative learning but were unable to perform successfully in a simultaneous MTS procedure within a period of 40 sessions. Three out of eight fish learned to distinguish between an image and its mirror-image when reflected vertically; however none of the fish mastered the task when the stimulus was reflected horizontally. These results suggest a better discrimination ability of vertical compared to horizontal mirror-images, an observation that is widespread in literature on mirror-image discrimination in animals. All fish performed well in the general visual discrimination task, thereby supporting previous results obtained for this species.

Cognition with few neurons: higher-order learning in insects

Insects possess miniature brains but exhibit a sophisticated behavioral repertoire. Recent studies have reported the existence of unsuspected cognitive capabilities in various insect species that go beyond the traditionally studied framework of simple associative learning. Here, I focus on capabilities such as attentional modulation and concept learning and discuss their mechanistic bases. I analyze whether these behaviors, which appear particularly complex, can be explained on the basis of elemental associative learning and specific neural circuitries or, by contrast, require an explanatory level that goes beyond simple associative links. In doing this, I highlight experimental challenges and suggest future directions for investigating the neurobiology of higher-order learning in insects, with the goal of uncovering the basic neural architectures underlying cognitive processing.

A comparative study of relational learning capacity in honeybees (Apis mellifera) and stingless bees (Melipona rufiventris)

BACKGROUND

Learning of arbitrary relations is the capacity to acquire knowledge about associations between events or stimuli that do not share any similarities, and use this knowledge to make behavioural choices. This capacity is well documented in humans and vertebrates, and there is some evidence it exists in the honeybee (Apis mellifera). However, little is known about whether the ability for relational learning extends to other invertebrates, although many insects have been shown to possess excellent learning capacities in spite of their small brains.

METHODOLOGY/PRINCIPAL FINDINGS

Using a symbolic matching-to-sample procedure, we show that the honeybee Apis mellifera rapidly learns arbitrary relations between colours and patterns, reaching 68.2% correct choice for pattern-colour relations and 73.3% for colour-pattern relations. However, Apis mellifera does not transfer this knowledge to the symmetrical relations when the stimulus order is reversed. A second bee species, the stingless bee Melipona rufiventris from Brazil, seems unable to learn the same arbitrary relations between colours and patterns, although it exhibits excellent discrimination learning.

CONCLUSIONS/SIGNIFICANCE

Our results confirm that the capacity for learning arbitrary relations is not limited to vertebrates, but even insects with small brains can perform this learning task. Interestingly, it seems to be a species-specific ability. The disparity in relational learning performance between the two bee species we tested may be linked to their specific foraging and recruitment strategies, which evolved in adaptation to different environments.

Modeling the insect mushroom bodies: application to a delayed match-to-sample task

Despite their small brains, insects show advanced capabilities in learning and task solving. Flies, honeybees and ants are becoming a reference point in neuroscience and a main source of inspiration for autonomous robot design issues and control algorithms. In particular, honeybees demonstrate to be able to autonomously abstract complex associations and apply them in tasks involving different sensory modalities within the insect brain. Mushroom Bodies (MBs) are worthy of primary attention for understanding memory and learning functions in insects. In fact, even if their main role regards olfactory conditioning, they are involved in many behavioral achievements and learning capabilities, as has been shown in honeybees and flies. Owing to the many neurogenetic tools, the fruit fly Drosophila became a source of information for the neuroarchitecture and biochemistry of the MBs, although the MBs of flies are by far simpler in organization than their honeybee orthologs. Electrophysiological studies, in turn, became available on the MBs of locusts and honeybees. In this paper a novel bio-inspired neural architecture is presented, which represents a generalized insect MB with the basic features taken from fruit fly neuroanatomy. By mimicking a number of different MB functions and architecture, we can replace and improve formerly used artificial neural networks. The model is a multi-layer spiking neural network where key elements of the insect brain, the antennal lobes, the lateral horn region, the MBs, and their mutual interactions are modeled. In particular, the model is based on the role of parts of the MBs named MB-lobes, where interesting processing mechanisms arise on the basis of spatio-temporal pattern formation. The introduced network is able to model learning mechanisms like olfactory conditioning seen in honeybees and flies and was found able also to perform more complex and abstract associations, like the delayed matching-to-sample tasks known only from honeybees. A biological basis of the proposed model is presented together with a detailed description of the architecture. Simulation results and remarks on the biological counterpart are also reported to demonstrate the possible applications of the designed computational model. Such neural architecture, able to autonomously learn complex associations is envisaged to be a suitable basis for an immediate implementation within an robot control architecture.

An exploration of the social brain hypothesis in insects

The "social brain hypothesis" posits that the cognitive demands of sociality have driven the evolution of substantially enlarged brains in primates and some other mammals. Whether such reasoning can apply to all social animals is an open question. Here we examine the evolutionary relationships between sociality, cognition, and brain size in insects, a taxonomic group characterized by an extreme sophistication of social behaviors and relatively simple nervous systems. We discuss the application of the social brain hypothesis in this group, based on comparative studies of brain volumes across species exhibiting various levels of social complexity. We illustrate how some of the major behavioral innovations of social insects may in fact require little information-processing and minor adjustments of neural circuitry, thus potentially selecting for more specialized rather than bigger brains. We argue that future work aiming to understand how animal behavior, cognition, and brains are shaped by the environment (including social interactions) should focus on brain functions and identify neural circuitry correlates of social tasks, not only brain sizes.

Honeybees can discriminate between Monet and Picasso paintings

Honeybees (Apis mellifera) have remarkable visual learning and discrimination abilities that extend beyond learning simple colours, shapes or patterns. They can discriminate landscape scenes, types of flowers, and even human faces. This suggests that in spite of their small brain, honeybees have a highly developed capacity for processing complex visual information, comparable in many respects to vertebrates. Here, we investigated whether this capacity extends to complex images that humans distinguish on the basis of artistic style: Impressionist paintings by Monet and Cubist paintings by Picasso. We show that honeybees learned to simultaneously discriminate between five different Monet and Picasso paintings, and that they do not rely on luminance, colour, or spatial frequency information for discrimination. When presented with novel paintings of the same style, the bees even demonstrated some ability to generalize. This suggests that honeybees are able to discriminate Monet paintings from Picasso ones by extracting and learning the characteristic visual information inherent in each painting style. Our study further suggests that discrimination of artistic styles is not a higher cognitive function that is unique to humans, but simply due to the capacity of animals-from insects to humans-to extract and categorize the visual characteristics of complex images.

Gene expression analysis following olfactory learning in Apis mellifera

The honeybee has a strong learning and memory ability, and is recognized as the best model organism for studying the neurobiological basis of learning and memory. In this study, we analyzed the gene expression difference following proboscis extension response-based olfactory learning in the A. mellifera using a tag-based digital gene expression (DGE) method. We obtained about 5.71 and 5.65 million clean tags from the trained group and untrained group, respectively. A total of 259 differentially expressed genes were detected between these two samples, with 30 genes up-regulated and 229 genes down-regulated in trained group compared to the untrained group. These results suggest that bees tend to actively suppress some genes instead of activating previously silent genes after olfactory learning. Our DGE data provide comprehensive gene expression information for olfactory learning, which will facilitate our understanding of the molecular mechanism of honey bee learning and memory.

Feature-positive and feature-negative learning in honey bees

Honey bees (Apis mellifera anatolica) were subjected to sequential trials where they were given the choice between a feature-positive and a feature-negative feeding plate. The 'feature' being manipulated is the presence of a single blue circle among three circles marking the location of a small sucrose reward. That is, a 'feature-negative' target had three white circles, while a 'feature-positive' target had two white circles and one blue one. Two experiments were performed. In both experiments, each bee was tested under two different reward scenarios (treatments). In the first experiment, during the feature-positive treatment bees received 4 μl of 2 mol l(-1) sucrose when choosing the feature-positive plate, but received 4 μl of saturated NaCl solution (saltwater) when choosing the feature-negative plate. During the feature-negative treatment, bees were rewarded when visiting the feature-negative plate, while visitation to the feature-positive plate only offered bees the saltwater. The second experiment was a repeat of the first except that pure water was offered instead of saltwater in the non-rewarding feeding plate. As an experimental control, a set of bees was offered sequential trials where both the feature-positive and feature-negative plates offered the sucrose reward. Bee feeding plate choice differed between the feature-positive and feature-negative treatments in both experiments. Bees favored the feeding plate type with the sucrose reward in each treatment, and never consumed the saltwater or pure water when encountered in either treatment. Further, behavior of bees during both the feature-positive and feature-negative treatments differed from that of control bees. However, neither feature-positive nor feature-negative learning reached high levels of success. Further, a feature-positive effect was seen when pure water was offered; bees learned to solve the feature-positive problem more rapidly. When we tested bees using simply the choice of blue versus white targets, where one color held the sucrose reward and the other the saltwater, a bee's fidelity to the color offering the sucrose reward quickly reached very high levels.

Same/different discrimination by bumblebee colonies

Bumblebees were exposed to a discrimination procedure in which reinforcement was contingent on choice of one of two spatial locations. The correct choice depended on whether a stimulus display contained two identical stimuli or two different stimuli. Some bees were trained with color stimuli and tested with line grating stimuli and others with the opposite arrangement. Four colonies of bumblebees produced more correct than incorrect choices to both identical and different stimuli during the transfer phase. This pattern of results is a signature of choices under control of an identity ("same/different") concept. The results therefore indicate the existence of an identity concept in bumblebees.

Comparison of learning and memory of Apis cerana and Apis mellifera

The honeybee is an excellent model organism for research on learning and memory among invertebrates. Learning and memory in honeybees has intrigued neuroscientists and entomologists in the last few decades, but attention has focused almost solely on the Western honeybee, Apis mellifera. In contrast, there have been few studies on learning and memory in the Eastern honeybee, Apis cerana. Here we report comparative behavioral data of color and grating learning and memory for A. cerana and A. mellifera in China, gathered using a Y-maze apparatus. We show for the first time that the learning and memory performance of A. cerana is significantly better on both color and grating patterns than that of A. mellifera. This study provides the first evidence of a learning and memory difference between A. cerana and A. mellifera under controlled conditions, and it is an important basis for the further study of the mechanism of learning and memory in honeybees.

Evaluating the evidence base for relational frame theory: a citation analysis

Relational frame theory (RFT) is a contemporary behavior-analytic account of language and cognition. Since it was first outlined in 1985, RFT has generated considerable controversy and debate, and several claims have been made concerning its evidence base. The present study sought to evaluate the evidence base for RFT by undertaking a citation analysis and by categorizing all articles that cited RFT-related search terms. A total of 174 articles were identified between 1991 and 2008, 62 (36%) of which were empirical and 112 (64%) were nonempirical articles. Further analyses revealed that 42 (68%) of the empirical articles were classified as empirical RFT and 20 (32%) as empirical other, whereas 27 (24%) of the nonempirical articles were assigned to the nonempirical reviews category and 85 (76%) to the nonempirical conceptual category. In addition, the present findings show that the majority of empirical research on RFT has been conducted with typically developing adult populations, on the relational frame of sameness, and has tended to be published in either The Psychological Record or the Journal of the Experimental Analysis of Behavior. Overall, RFT has made a substantial contribution to the literature in a relatively short period of time.

Face recognition: lessons from a wasp

The golden paper wasp is a social insect whose colony members have the remarkable ability to recognise each others' faces. New research shows that this species is singularly skilled at learning about faces, opening interesting perspectives on convergent evolution of specialist cognitive abilities in insects and vertebrates.

The proboscis extension reflex to evaluate learning and memory in honeybees (Apis mellifera): some caveats

The proboscis extension reflex (PER) is widely used in a classical conditioning (Pavlovian) context to evaluate learning and memory of a variety of insect species. The literature is particularly prodigious for honeybees (Apis mellifera) with more than a thousand publications. Imagination appears to be the only limit to the types of challenges to which researchers subject honeybees, including all the sensory modalities and a broad diversity of environmental treatments. Accordingly, some remarkable insights have been achieved using PER. However, there are several challenges to evaluating the PER literature that warrant a careful and thorough review. We assess here variation in methods that makes interpretation of studies, even those researching the same question, tenuous. We suggest that the numerous variables that might influence experimental outcomes from PER be thoroughly detailed by researchers. Moreover, the influence of individual variables on results needs to carefully evaluated, as well as among two or more variables. Our intent is to encourage investigation of the influence of numerous variables on PER results.

Visually targeted reaching in horse-head grasshoppers

Visually targeted reaching to a specific object is a demanding neuronal task requiring the translation of the location of the object from a two-dimensionsal set of retinotopic coordinates to a motor pattern that guides a limb to that point in three-dimensional space. This sensorimotor transformation has been intensively studied in mammals, but was not previously thought to occur in animals with smaller nervous systems such as insects. We studied horse-head grasshoppers (Orthoptera: Proscopididae) crossing gaps and found that visual inputs are sufficient for them to target their forelimbs to a foothold on the opposite side of the gap. High-speed video analysis showed that these reaches were targeted accurately and directly to footholds at different locations within the visual field through changes in forelimb trajectory and body position, and did not involve stereotyped searching movements. The proscopids estimated distant locations using peering to generate motion parallax, a monocular distance cue, but appeared to use binocular visual cues to estimate the distance of nearby footholds. Following occlusion of regions of binocular overlap, the proscopids resorted to peering to target reaches even to nearby locations. Monocular cues were sufficient for accurate targeting of the ipsilateral but not the contralateral forelimb. Thus, proscopids are capable not only of the sensorimotor transformations necessary for visually targeted reaching with their forelimbs but also of flexibly using different visual cues to target reaches.

The mysterious cognitive abilities of bees: why models of visual processing need to consider experience and individual differences in animal performance

Vision is one of the most important modalities for the remote perception of biologically important stimuli. Insects like honeybees and bumblebees use their colour and spatial vision to solve tasks, such as navigation, or to recognise rewarding flowers during foraging. Bee vision is one of the most intensively studied animal visual systems, and several models have been developed to describe its function. These models have largely assumed that bee vision is determined by mechanistic hard-wired circuits, with little or no consideration for behavioural plasticity or cognitive factors. However, recent work on both bee colour vision and spatial vision suggests that cognitive factors are indeed a very significant factor in determining what a bee sees. Individual bumblebees trade-off speed for accuracy, and will decide on which criteria to prioritise depending upon contextual information. With continued visual experience, honeybees can learn to use non-elemental processing, including configural mechanisms and rule learning, and can access top-down information to enhance learning of sophisticated, novel visual tasks. Honeybees can learn delayed-matching-to-sample tasks and the rules governing this decision making, and even transfer learned rules between different sensory modalities. Finally, bees can learn complex categorisation tasks and display numerical processing abilities for numbers up to and including four. Taken together, this evidence suggests that bees do have a capacity for sophisticated visual behaviours that fit a definition for cognition, and thus simple elemental models of bee vision need to take account of how a variety of factors may influence the type of results one may gain from animal behaviour experiments.

Visually guided decision making in foraging honeybees

Honeybees can easily be trained to perform different types of discrimination tasks under controlled laboratory conditions. This review describes a range of experiments carried out with free-flying forager honeybees under such conditions. The research done over the past 30 or so years suggests that cognitive abilities (learning and perception) in insects are more intricate and flexible than was originally imagined. It has become apparent that honeybees are capable of a variety of visually guided tasks, involving decision making under challenging situations: this includes simultaneously making use of different sensory modalities, such as vision and olfaction, and learning to use abstract concepts such as "sameness" and "difference." Many studies have shown that decision making in foraging honeybees is highly flexible. The trained animals learn how to solve a task, and do so with a high accuracy, but when they are presented with a new variation of the task, they apply the learnt rules from the earlier setup to the new situation, and solve the new task as well. Honeybees therefore not only feature a rich behavioral repertoire to choose from, but also make decisions most apt to the current situation. The experiments in this review give an insight into the environmental cues and cognitive resources that are probably highly significant for a forager bee that must continually make decisions regarding patches of resources to be exploited.

Spatial reorientation by geometry in bumblebees

Human and non-human animals are capable of using basic geometric information to reorient in an environment. Geometric information includes metric properties associated with spatial surfaces (e.g., short vs. long wall) and left-right directionality or 'sense' (e.g. a long wall to the left of a short wall). However, it remains unclear whether geometric information is encoded by explicitly computing the layout of surface geometry or by matching images of the environment. View-based spatial encoding is generally thought to hold for insect navigation and, very recently, evidence for navigation by geometry has been reported in ants but only in a condition which does not allow the animals to use features located far from the goal. In this study we tested the spatial reorientation abilities of bumblebees (Bombus terrestris). After spatial disorientation, by passive rotation both clockwise and anticlockwise, bumblebees had to find one of the four exit holes located in the corners of a rectangular enclosure. Bumblebees systematically confused geometrically equivalent exit corners (i.e. corners with the same geometric arrangement of metric properties and sense, for example a short wall to the left of a long wall). However, when one wall of the enclosure was a different colour, bumblebees appeared to combine this featural information (either near or far from the goal) with geometric information to find the correct exit corner. Our results show that bumblebees are able to use both geometric and featural information to reorient themselves, even when features are located far from the goal.

Simultaneous mastering of two abstract concepts by the miniature brain of bees

Sorting objects and events into categories and concepts is a fundamental cognitive capacity that reduces the cost of learning every particular situation encountered in our daily lives. Relational concepts such as "same," "different," "better than," or "larger than"--among others--are essential in human cognition because they allow highly efficient classifying of events irrespective of physical similarity. Mastering a relational concept involves encoding a relationship by the brain independently of the physical objects linked by the relation and is, therefore, consistent with abstraction capacities. Processing several concepts at a time presupposes an even higher level of cognitive sophistication that is not expected in an invertebrate. We found that the miniature brains of honey bees rapidly learn to master two abstract concepts simultaneously, one based on spatial relationships (above/below and right/left) and another based on the perception of difference. Bees that learned to classify visual targets by using this dual concept transferred their choices to unknown stimuli that offered a best match in terms of dual-concept availability: their components presented the appropriate spatial relationship and differed from one another. This study reveals a surprising facility of brains to extract abstract concepts from a set of complex pictures and to combine them in a rule for subsequent choices. This finding thus provides excellent opportunities for understanding how cognitive processing is achieved by relatively simple neural architectures.

Rats can make relative perceptual judgments about sequential stimuli

In their natural environment, animals often make decisions based on abstract relationships among multiple stimulus representations. Humans and other primates can determine not only whether a sensory stimulus differs from a remembered sensory representation, but also how they differ along a particular dimension. However, much remains unknown about how such relative comparisons are made, and which species share this capacity, in part because most studies of sensory-guided decision making have utilized instrumental tasks in which choices are based on very simple stimulus-response associations. Here, we used a two-stimulus-interval discrimination task to test whether rats could determine how two sequentially presented stimuli were related along the dimension of odor quality (i.e., what the stimulus smells like). At a central port, rats sampled and compared two odor mixtures that consisted of spearmint and caraway in different ratios, separated by a 2-4-s interval, and then entered the left or right reward port. Water was delivered at the left if the first mixture consisted of more spearmint than the second did, and at the right otherwise. We found that the difference in mixture ratio predicted choice accuracy. Control experiments suggest that rats were indeed basing their choices on a comparison of odor quality across mixtures and were not using associative strategies. This study is the first demonstration of the use of a sequential "more than versus less than" rule in rats and provides a well-controlled paradigm for studying abstract comparisons in a rodent model system.

Optimal inference of sameness

Deciding whether a set of objects are the same or different is a cornerstone of perception and cognition. Surprisingly, no principled quantitative model of sameness judgment exists. We tested whether human sameness judgment under sensory noise can be modeled as a form of probabilistically optimal inference. An optimal observer would compare the reliability-weighted variance of the sensory measurements with a set size-dependent criterion. We conducted two experiments, in which we varied set size and individual stimulus reliabilities. We found that the optimal-observer model accurately describes human behavior, outperforms plausible alternatives in a rigorous model comparison, and accounts for three key findings in the animal cognition literature. Our results provide a normative footing for the study of sameness judgment and indicate that the notion of perception as near-optimal inference extends to abstract relations.

Seeing near and seeing far; behavioural evidence for dual mechanisms of pattern vision in the honeybee (Apis mellifera)

Visual perception is a primary modality for interacting with complex environments. Recent work has shown that the brain and visual system of the honeybee is able, in some cases, to learn complex spatial relationships, while in other cases, bee vision is relatively rudimentary and based upon simple elemental-type visual processing. In the present study, we test the ability of honeybees to learn 4-bar asymmetric patterns in a Y-maze with aversive–appetitive differential conditioning. In Experiment 1, a group of bees were trained at a small visual angle of 50 deg by constraining individuals to the decision chamber within the Y-maze. Bees learned this task, and were able to solve the task even in the presence of background noise. However, these bees failed to solve the task when the stimuli were presented at a novel visual angle of 100 deg. In Experiment 2, a separate group of bees were trained to sets of 4-bar asymmetric patterns that excluded retinotopic matching and, in this case, bees learned the configural rule describing stimuli at a visual angle of approximately 50 deg, and this allowed the bees to solve the task when the stimuli were presented at a novel vision angle of 100 deg. This shows that the bee brain contains multiple mechanisms for pattern recognition, and what a bee sees is very dependent upon the specific experience that it receives. These multiple mechanisms would allow bees to interact with complex environments to solve tasks like recognising landmarks at variable distances or quickly discriminating between rewarding/non-rewarding flowers at reasonable constant visual angles.

Associative olfactory learning in the desert locust, Schistocerca gregaria

Locusts can learn associations between olfactory stimuli and food rewards, and use the acquired memories to choose between foods according to their nutrient requirements. They are a model system for both the study of olfactory coding and insect nutritional regulation. Previous studies have used operant paradigms for conditioning freely moving locusts, restricting the study of the neural mechanisms underlying the acquisition of olfactory memories, which requires restrained preparations for electrophysiological recordings. Here we present two complementary paradigms for the classical conditioning of olfactory memories in restrained desert locusts (Schistocerca gregaria). These paradigms allow precise experimental control over the parameters influencing learning. The first paradigm is based on classical (Pavlovian) appetitive conditioning. We show that opening of the maxillary palps can be used as a measure of memory acquisition. Maxillary palp opening in response to odour presentation is significantly higher in locusts trained with paired presentation of an odour and a food reward than in locusts trained either with unpaired presentation of food and odour or the odour alone. The memory formed by this conditioning paradigm lasts for at least 24 h. In the second paradigm, we show that classical conditioning of an odour memory in restrained locusts influences their decisions in a subsequent operant task. When locusts that have been trained to associate an odour with a food reward are placed in a Y-maze, they choose the arm containing that odour significantly more often than naïve locusts. A single conditioning trial is sufficient to induce a significant bias for that odour for up to 4 h. Multiple- and block-trial training induce a significant bias that lasts at least 24 h. Thus, locusts are capable of forming appetitive olfactory memories in classical conditioning paradigms and can use these memories to modify their decisions.

Agitated honeybees exhibit pessimistic cognitive biases

Whether animals experience human-like emotions is controversial and of immense societal concern [1–3]. Because animals cannot provide subjective reports of how they feel, emotional state can only be inferred using physiological, cognitive, and behavioral measures [4–8]. In humans, negative feelings are reliably correlated with pessimistic cognitive biases, defined as the increased expectation of bad outcomes [9–11]. Recently, mammals [12–16] and birds [17–20] with poor welfare have also been found to display pessimistic-like decision making, but cognitive biases have not thus far been explored in invertebrates. Here, we ask whether honeybees display a pessimistic cognitive bias when they are subjected to an anxiety-like state induced by vigorous shaking designed to simulate a predatory attack. We show for the first time that agitated bees are more likely to classify ambiguous stimuli as predicting punishment. Shaken bees also have lower levels of hemolymph dopamine, octopamine, and serotonin. In demonstrating state-dependent modulation of categorization in bees, and thereby a cognitive component of emotion, we show that the bees' response to a negatively valenced event has more in common with that of vertebrates than previously thought. This finding reinforces the use of cognitive bias as a measure of negative emotional states across species and suggests that honeybees could be regarded as exhibiting emotions.

Video Abstract

Brain modularity in arthropods: individual neurons that support "what" but not "where" memories

Experiments with insects and crabs have demonstrated their remarkable capacity to learn and memorize complex visual features (Giurfa et al., 2001; Pedreira and Maldonado, 2003; Chittka and Niven, 2009). Such abilities are thought to require modular brain processing similar to that occurring in vertebrates (Menzel and Giurfa, 2001). Yet, physiological evidence for this type of functioning in the small brains of arthropods is still scarce (Liu et al., 1999, 2006; Menzel and Giurfa, 2001). In the crab Chasmagnathus granulatus, the learning rate as well as the long-term memory of a visual stimulus has been found to be reflected in the performance of identified lobula giant neurons (LGs) (Tomsic et al., 2003). The memory can only be evoked in the training context, indicating that animals store two components of the learned experience, one related to the visual stimulus and one related to the visual context (Tomsic et al., 1998; Hermitte et al., 1999). By performing intracellular recordings in the intact animal, we show that the ability of crabs to generalize the learned stimulus into new space positions and to distinguish it from a similar but unlearned stimulus, two of the main attributes of stimulus memory, is reflected by the performance of the LGs. Conversely, we found that LGs do not support the visual context memory component. Our results provide physiological evidence that the memory traces regarding "what" and "where" are stored separately in the arthropod brain.