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.

Different mechanisms underlie implicit visual statistical learning in honey bees and humans.

The ability of developing complex internal representations of the environment is considered a crucial antecedent to the emergence of humans' higher cognitive functions. Yet it is an open question whether there is any fundamental difference in how humans and other good visual learner species naturally encode aspects of novel visual scenes. Using the same modified visual statistical learning paradigm and multielement stimuli, we investigated how human adults and honey bees (Apis mellifera) encode spontaneously, without dedicated training, various statistical properties of novel visual scenes. We found that, similarly to humans, honey bees automatically develop a complex internal representation of their visual environment that evolves with accumulation of new evidence even without a targeted reinforcement. In particular, with more experience, they shift from being sensitive to statistics of only elemental features of the scenes to relying on co-occurrence frequencies of elements while losing their sensitivity to elemental frequencies, but they never encode automatically the predictivity of elements. In contrast, humans involuntarily develop an internal representation that includes single-element and co-occurrence statistics, as well as information about the predictivity between elements. Importantly, capturing human visual learning results requires a probabilistic chunk-learning model, whereas a simple fragment-based memory-trace model that counts occurrence summary statistics is sufficient to replicate honey bees' learning behavior. Thus, humans' sophisticated encoding of sensory stimuli that provides intrinsic sensitivity to predictive information might be one of the fundamental prerequisites of developing higher cognitive abilities.

Individual recognition is associated with holistic face processing in Polistes paper wasps in a species-specific way.

Most recognition is based on identifying features, but specialization for face recognition in primates relies on a different mechanism, termed 'holistic processing' where facial features are bound together into a gestalt which is more than the sum of its parts. Here, we test whether individual face recognition in paper wasps also involved holistic processing using a modification of the classic part-whole test in two related paper wasp species: Polistes fuscatus, which use facial patterns to individually identify conspecifics, and Polistes dominula, which lacks individual recognition. We show that P. fuscatus use holistic processing to discriminate between P. fuscatus face images but not P. dominula face images. By contrast, P. dominula do not rely on holistic processing to discriminate between conspecific or heterospecific face images. Therefore, P. fuscatus wasps have evolved holistic face processing, but this ability is highly specific and shaped by species-specific and stimulus-specific selective pressures. Convergence towards holistic face processing in distant taxa (primates, wasps) as well as divergence among closely related taxa with different recognition behaviour (P. dominula, P. fuscatus) suggests that holistic processing may be a universal adaptive strategy to facilitate expertise in face recognition.

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 them to respond 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 whether learning ability correlates between tasks of different complexity or between sensory modalities is of high interest for research on brain modularity and task-dependent specialization of neural circuits. The honeybee Apis mellifera constitutes an attractive model to address this question because of 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 relationships 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 specialization within the hive, which may contribute to ecological social success.

Higher-order discrimination learning by honeybees in a virtual environment.

Non-elemental learning constitutes a cognitive challenge because events to be learned are usually ambiguous in terms of reinforcement outcome, contrary to elemental learning, which relies on unambiguous associations. Negative patterning (NP) constitutes a paradigmatic case of non-elemental learning, as subjects have to learn that single elements are reinforced while their simultaneous presentation is not reinforced (A+, B+ vs. AB-). Solving NP requires treating AB as being different from the linear sum of its components in order to overcome the ambiguity of stimulus reinforcement (i.e. A and B are as often reinforced as not reinforced). The honeybee is currently the only insect mastering NP as shown by studies restricted mainly to the olfactory domain. Here, we tested the bees' capacity to solve a NP discrimination in the visual domain and used to this end a virtual reality (VR) environment in which a tethered bee walking stationary on a spherical treadmill faces visual stimuli projected on a semicircular screen. We show that bees learn a composite grating made of alternated green and blue bars in an elemental way, and generalize their response to both a blue and a green grating. Yet, after NP training, one-quarter of the bees inhibited elemental processing and responded significantly more to the single-coloured gratings than to the composite grating. Alternative strategies were used by the other bees, which achieved partial NP learning. These results offer attractive perspectives to study different forms of visual learning in a controlled VR environment, and dissect their underlying mechanisms.

Spontaneous quantity discrimination of artificial flowers by foraging honeybees.

Many animals need to process numerical and quantity information in order to survive. Spontaneous quantity discrimination allows differentiation between two or more quantities without reinforcement or prior training on any numerical task. It is useful for assessing food resources, aggressive interactions, predator avoidance and prey choice. Honeybees have previously demonstrated landmark counting, quantity matching, use of numerical rules, quantity discrimination and arithmetic, but have not been tested for spontaneous quantity discrimination. In bees, spontaneous quantity discrimination could be useful when assessing the quantity of flowers available in a patch and thus maximizing foraging efficiency. In the current study, we assessed the spontaneous quantity discrimination behaviour of honeybees. Bees were trained to associate a single yellow artificial flower with sucrose. Bees were then tested for their ability to discriminate between 13 different quantity comparisons of artificial flowers (numeric ratio range: 0.08-0.8). Bees significantly preferred the higher quantity only in comparisons where '1' was the lower quantity and where there was a sufficient magnitudinal distance between quantities (e.g. 1 versus 12, 1 versus 4, and 1 versus 3 but not 1 versus 2). Our results suggest a possible evolutionary benefit to choosing a foraging patch with a higher quantity of flowers when resources are scarce.

Symbolic representation of numerosity by honeybees ( Apis mellifera): matching characters to small quantities.

The assignment of a symbolic representation to a specific numerosity is a fundamental requirement for humans solving complex mathematical calculations used in diverse applications such as algebra, accounting, physics and everyday commerce. Here we show that honeybees are able to learn to match a sign to a numerosity, or a numerosity to a sign, and subsequently transfer this knowledge to novel numerosity stimuli changed in colour properties, shape and configuration. While honeybees learned the associations between two quantities (two; three) and two signs (N-shape; inverted T-shape), they failed at reversing their specific task of sign-to-numerosity matching to numerosity-to-sign matching and vice versa (i.e. a honeybee that learned to match a sign to a number of elements was not able to invert this learning to match the numerosity of elements to a sign). Thus, while bees could learn the association between a symbol and numerosity, it was linked to the specific task and bees could not spontaneously extrapolate the association to a novel, reversed task. Our study therefore reveals that the basic requirement for numerical symbolic representation can be fulfilled by an insect brain, suggesting that the absence of its spontaneous emergence in animals is not due to cognitive limitation.

Surpassing the subitizing threshold: appetitive-aversive conditioning improves discrimination of numerosities in honeybees.

Animals including humans, fish and honeybees have demonstrated a quantity discrimination threshold at four objects, often known as subitizing elements. Discrimination between numerosities at or above the subitizing range is considered a complex capacity. In the current study, we trained and tested two groups of bees on their ability to differentiate between quantities (4 versus 5 through to 4 versus 8) when trained with different conditioning procedures. Bees trained with appetitive (reward) differential conditioning demonstrated no significant learning of this task, and limited discrimination above the subitizing range. In contrast, bees trained using appetitive-aversive (reward-aversion) differential conditioning demonstrated significant learning and subsequent discrimination of all tested comparisons from 4 versus 5 to 4 versus 8. Our results show conditioning procedure is vital to performance on numerically challenging tasks, and may inform future research on numerical abilities in other animals.

Honeybees use absolute rather than relative numerosity in number discrimination.

Various vertebrate species use relative numerosity judgements in comparative assessments of quantities for which they use larger/smaller relationships rather than absolute number. The numerical ability of honeybees shares basic properties with that of vertebrates but their use of absolute or relative numerosity has not been explored. We trained free-flying bees to choose variable images containing three dots; one group ('larger') was trained to discriminate 3 from 2, while another group ('smaller') was trained to discriminate 3 from 4. In both cases, numbers were kept constant but stimulus characteristics and position were varied from trial to trial. Bees were then tested with novel stimuli displaying the previously trained numerosity (3) versus a novel numerosity (4 for 'larger' and 2 for 'smaller'). Both groups preferred the three-item stimulus, consistent with absolute numerosity. They also exhibited ratio-dependent discrimination of numbers, a property shared by vertebrates, as performance after 2 versus 3 was better than after 3 versus 4 training. Thus, bees differ from vertebrates in their use of absolute rather than of relative numerosity but they also have some numeric properties in common.

Aminergic neuromodulation of associative visual learning in harnessed honey bees.

The honey bee Apis mellifera is a major insect model for studying visual cognition. Free-flying honey bees learn to associate different visual cues with a sucrose reward and may deploy sophisticated cognitive strategies to this end. Yet, the neural bases of these capacities cannot be studied in flying insects. Conversely, immobilized bees are accessible to neurobiological investigation but training them to respond appetitively to visual stimuli paired with sucrose reward is difficult. Here we succeeded in coupling visual conditioning in harnessed bees with pharmacological analyses on the role of octopamine (OA), dopamine (DA) and serotonin (5-HT) in visual learning. We also studied if and how these biogenic amines modulate sucrose responsiveness and phototaxis behaviour as intact reward and visual perception are essential prerequisites for appetitive visual learning. Our results suggest that both octopaminergic and dopaminergic signaling mediate either the appetitive sucrose signaling or the association between color and sucrose reward in the bee brain. Enhancing and inhibiting serotonergic signaling both compromised learning performances, probably via an impairment of visual perception. We thus provide a first analysis of the role of aminergic signaling in visual learning and retention in the honey bee and discuss further research trends necessary to understand the neural bases of visual cognition in this insect.

Perception of contextual size illusions by honeybees in restricted and unrestricted viewing conditions.

How different visual systems process images and make perceptual errors can inform us about cognitive and visual processes. One of the strongest geometric errors in perception is a misperception of size depending on the size of surrounding objects, known as the Ebbinghaus or Titchener illusion. The ability to perceive the Ebbinghaus illusion appears to vary dramatically among vertebrate species, and even populations, but this may depend on whether the viewing distance is restricted. We tested whether honeybees perceive contextual size illusions, and whether errors in perception of size differed under restricted and unrestricted viewing conditions. When the viewing distance was unrestricted, there was an effect of context on size perception and thus, similar to humans, honeybees perceived contrast size illusions. However, when the viewing distance was restricted, bees were able to judge absolute size accurately and did not succumb to visual illusions, despite differing contextual information. Our results show that accurate size perception depends on viewing conditions, and thus may explain the wide variation in previously reported findings across species. These results provide insight into the evolution of visual mechanisms across vertebrate and invertebrate taxa, and suggest convergent evolution of a visual processing solution.

Free-flying honeybees extrapolate relational size rules to sort successively visited artificial flowers in a realistic foraging situation.

Learning and applying relational concepts to solve novel tasks is considered an indicator of cognitive-like ability. It requires the abstraction of relational concepts to different objects independent to the physical nature of the individual objects. Recent research has revealed the honeybee's ability to rapidly learn and manipulate relations between visual stimuli such as 'same/different', 'above/below', or 'larger/smaller' despite having a miniature-sized brain. While honeybees can solve problems using rule-based relative size comparison, it remains unresolved as to whether bees can apply size rules when stimuli are encountered successively, which requires reliance on working memory for stimuli comparison. Additionally, the potential ability of bees to extrapolate acquired information to novel sizes beyond training sets remains to be investigated. We tested whether individual free-flying honeybees could learn 'larger/smaller' size rules when visual stimuli were presented successively, and whether such rules could then be extrapolated to novel stimulus sizes. Honeybees were individually trained to a set of four sizes such that individual elements might be correct, or incorrect, depending upon the alternative stimulus. In a learning test, bees preferred the correct size relation for their respective learning group. Bees were also able to successfully extrapolate the learnt relation during transfer tests by maintaining the correct size relationships when considering either two smaller, or two larger, novel stimulus sizes. This performance demonstrates that an insect operating in a complex environment has sufficient cognitive capacity to learn rules that can be abstracted to novel problems. We discuss the possible learning mechanisms which allow their success.

The forest or the trees: preference for global over local image processing is reversed by prior experience in honeybees.

Traditional models of insect vision have assumed that insects are only capable of low-level analysis of local cues and are incapable of global, holistic perception. However, recent studies on honeybee (Apis mellifera) vision have refuted this view by showing that this insect also processes complex visual information by using spatial configurations or relational rules. In the light of these findings, we asked whether bees prioritize global configurations or local cues by setting these two levels of image analysis in competition. We trained individual free-flying honeybees to discriminate hierarchical visual stimuli within a Y-maze and tested bees with novel stimuli in which local and/or global cues were manipulated. We demonstrate that even when local information is accessible, bees prefer global information, thus relying mainly on the object's spatial configuration rather than on elemental, local information. This preference can be reversed if bees are pre-trained to discriminate isolated local cues. In this case, bees prefer the hierarchical stimuli with the local elements previously primed even if they build an incorrect global configuration. Pre-training with local cues induces a generic attentional bias towards any local elements as local information is prioritized in the test, even if the local cues used in the test are different from the pre-trained ones. Our results thus underline the plasticity of visual processing in insects and provide new insights for the comparative analysis of visual recognition in humans and animals.

Learning context modulates aversive taste strength in honey bees.

The capacity of honey bees (Apis mellifera) to detect bitter substances is controversial because they ingest without reluctance different kinds of bitter solutions in the laboratory, whereas free-flying bees avoid them in visual discrimination tasks. Here, we asked whether the gustatory perception of bees changes with the behavioral context so that tastes that are less effective as negative reinforcements in a given context become more effective in a different context. We trained bees to discriminate an odorant paired with 1 mol l(-1) sucrose solution from another odorant paired with either distilled water, 3 mol l(-1) NaCl or 60 mmol l(-1) quinine. Training was either Pavlovian [olfactory conditioning of the proboscis extension reflex (PER) in harnessed bees], or mainly operant (olfactory conditioning of free-walking bees in a Y-maze). PER-trained and maze-trained bees were subsequently tested both in their original context and in the alternative context. Whereas PER-trained bees transferred their choice to the Y-maze situation, Y-maze-trained bees did not respond with a PER to odors when subsequently harnessed. In both conditioning protocols, NaCl and distilled water were the strongest and the weakest aversive reinforcement, respectively. A significant variation was found for quinine, which had an intermediate aversive effect in PER conditioning but a more powerful effect in the Y-maze, similar to that of NaCl. These results thus show that the aversive strength of quinine varies with the learning context, and reveal the plasticity of the bee's gustatory system. We discuss the experimental constraints of both learning contexts and focus on stress as a key modulator of taste in the honey bee. Further explorations of bee taste are proposed to understand the physiology of taste modulation in bees.

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.

Cognitive components of color vision in honey bees: how conditioning variables modulate color learning and discrimination.

Since the demonstration of color vision in honey bees 100 years ago by Karl von Frisch, appetitive conditioning to color targets has been used as the principal way to access behavioral aspects of bee color vision. Yet, analyses on how conditioning parameters affect color perception remained scarce. Conclusions on bee color vision have often been made without referring them to the experimental context in which they were obtained, and thus presented as absolute facts instead of realizing that subtle variations in conditioning procedures might yield different results. Here, we review evidence showing that color learning and discrimination in bees are not governed by immutable properties of their visual system, but depend on how the insects are trained and thus learn a task. The use of absolute or differential conditioning protocols, the presence of aversive reinforcement in differential conditioning and the degrees of freedom of motor components determine dramatic variations in color discrimination. We, thus, suggest top-down attentional modulation of color vision to explain the changes in color learning and discrimination reviewed here. We discuss the possible neural mechanisms of this modulation and conclude that color vision experiments require a careful consideration of how training parameters shape behavioral responses.

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.

Efficient visual learning by bumble bees in virtual-reality conditions: Size does not matter.

Recent developments allowed establishing virtual-reality (VR) setups to study multiple aspects of visual learning in honey bees under controlled experimental conditions. Here, we adopted a VR environment to investigate the visual learning in the buff-tailed bumble bee Bombus terrestris. Based on responses to appetitive and aversive reinforcements used for conditioning, we show that bumble bees had the proper appetitive motivation to engage in the VR experiments and that they learned efficiently elemental color discriminations. In doing so, they reduced the latency to make a choice, increased the proportion of direct paths toward the virtual stimuli and walked faster toward them. Performance in a short-term retention test showed that bumble bees chose and fixated longer on the correct stimulus in the absence of reinforcement. Body size and weight, although variable across individuals, did not affect cognitive performances and had a mild impact on motor performances. Overall, we show that bumble bees are suitable experimental subjects for experiments on visual learning under VR conditions, which opens important perspectives for invasive studies on the neural and molecular bases of such learning given the robustness of these insects and the accessibility of their brain.

Visual cognition in social insects.

Visual learning admits different levels of complexity, from the formation of a simple associative link between a visual stimulus and its outcome, to more sophisticated performances, such as object categorization or rules learning, that allow flexible responses beyond simple forms of learning. Not surprisingly, higher-order forms of visual learning have been studied primarily in vertebrates with larger brains, while simple visual learning has been the focus in animals with small brains such as insects. This dichotomy has recently changed as studies on visual learning in social insects have shown that these animals can master extremely sophisticated tasks. Here we review a spectrum of visual learning forms in social insects, from color and pattern learning, visual attention, and top-down image recognition, to interindividual recognition, conditional discrimination, category learning, and rule extraction. We analyze the necessity and sufficiency of simple associations to account for complex visual learning in Hymenoptera and discuss possible neural mechanisms underlying these visual performances.