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

Visual discrimination, sequential learning and memory retrieval in the Australian desert ant Melophorus bagoti

Bees, wasps and ants--so-called central-place foragers--need potent homing strategies to return to their nest. Path integration and view-based landmark guidance are the key strategies for the ants' navigation. For instance, they memorise different views in a sequence (sequential memory) but also have a step counter that informs them about the covered distance during each foraging trip (odometer). The sequential memory and the odometer information can act as contextual cues during travel for retrieving the appropriate stored view. When and which cue is used at different stages and lengths of the foraging trips is still unknown. In this study, we examined how the Australian desert ant Melophorus bagoti uses sequential memory and odometric information to retrieve visual memories. Using a set-up made out of channels and two-choice boxes (Y-mazes), we demonstrate first that M. bagoti foragers are able to learn and discriminate a variety of visual stimuli in a sequence of views along the inbound trip back to the nest. We then forced the homing ants to encounter a fixed sequence of two visual patterns during their inbound trips. By manipulating the position and distance of the visual stimuli and decision boxes, we could set the two contextual cues (sequential memory and odometer) into conflict. After the short 4-m outbound distance, a preference for odometric information as a contextual cue was found, but after the long 8-m outbound distance, ants relied primarily on their sequential memory retrieval. Odometer precision deteriorates with increasing travel distance, and accordingly, our findings imply that desert ants may be relying on the most reliable contextual cue for retrieving visual memories.

Mind the gap: olfactory trace conditioning in honeybees

Trace conditioning is a form of classical conditioning, where a neutral stimulus (conditioned stimulus, CS) is associated with a following appetitive or aversive stimulus (unconditioned stimulus, US). Unlike classical delay conditioning, in trace conditioning there is a stimulus-free gap between CS and US, and thus a poststimulus neural representation (trace) of the CS is required to bridge the gap until its association with the US. The properties of such stimulus traces are not well understood, nor are their underlying physiological mechanisms. Using behavioral and physiological approaches, we studied appetitive olfactory trace conditioning in honeybees. We found that single-odor presentation created a trace containing information about odor identity. This trace conveyed odor information about the initial stimulus and was robust against interference by other odors. Memory acquisition decreased with increasing CS-US gap length. The maximum learnable CS-US gap length could be extended by previous trace-conditioning experience. Furthermore, acquisition improved when an additional odor was presented during the CS-US gap. Using calcium imaging, we tested whether projection neurons in the primary olfactory brain area, the antennal lobe, contain a CS trace. We found odor-specific persistent responses after stimulus offset. These post-odor responses, however, did not encode the CS trace, and perceived odor quality could be predicted by the initial but not by the post-odor response. Our data suggest that olfactory trace conditioning is a less reflexive form of learning than classical delay conditioning, indicating that odor traces might involve higher-level cognitive processes.

Specialized learning in antlions (Neuroptera: Myrmeleontidae), pit-digging predators, shortens vulnerable larval stage

Unique in the insect world for their extremely sedentary predatory behavior, pit-dwelling larval antlions dig pits, and then sit at the bottom and wait, sometimes for months, for prey to fall inside. This sedentary predation strategy, combined with their seemingly innate ability to detect approaching prey, make antlions unlikely candidates for learning. That is, although scientists have demonstrated that many species of insects possess the capacity to learn, each of these species, which together represent multiple families from every major insect order, utilizes this ability as a means of navigating the environment, using learned cues to guide an active search for food and hosts, or to avoid noxious events. Nonetheless, we demonstrate not only that sedentary antlions can learn, but also, more importantly, that learning provides an important fitness benefit, namely decreasing the time to pupate, a benefit not yet demonstrated in any other species. Compared to a control group in which an environmental cue was presented randomly vis-à-vis daily prey arrival, antlions given the opportunity to associate the cue with prey were able to make more efficient use of prey and pupate significantly sooner, thus shortening their long, highly vulnerable larval stage. Whereas "median survival time," the point at which half of the animals in each group had pupated, was 46 days for antlions receiving the Learning treatment, that point never was reached in antlions receiving the Random treatment, even by the end of the experiment on Day 70. In addition, we demonstrate a novel manifestation of antlions' learned response to cues predicting prey arrival, behavior that does not match the typical "learning curve" but which is well-adapted to their sedentary predation strategy. Finally, we suggest that what has long appeared to be instinctive predatory behavior is likely to be highly modified and shaped by learning.

Brief predator sound exposure elicits behavioral and neuronal long-term sensitization in the olfactory system of an insect

Modulation of sensitivity to sensory cues by experience is essential for animals to adapt to a changing environment. Sensitization and adaptation to signals of the same modality as a function of experience have been shown in many cases, and some of the neurobiological mechanisms underlying these processes have been described. However, the influence of sensory signals on the sensitivity of a different modality is largely unknown. In males of the noctuid moth, Spodoptera littoralis, the sensitivity to the female-produced sex pheromone increases 24 h after a brief preexposure with pheromone at the behavioral and central nervous level. Here we show that this effect is not confined to the same sensory modality: the sensitivity of olfactory neurons can also be modulated by exposure to a different sensory stimulus, i.e., a pulsed stimulus mimicking echolocating sounds from attacking insectivorous bats. We tested responses of preexposed male moths in a walking bioassay and recorded from neurons in the primary olfactory center, the antennal lobe. We show that brief exposure to a bat call, but not to a behaviorally irrelevant tone, increases the behavioral sensitivity of male moths to sex pheromone 24 h later in the same way as exposure to the sex pheromone itself. The observed behavioral modification is accompanied by an increase in the sensitivity of olfactory neurons in the antennal lobe. Our data provide thus evidence for cross-modal experience-dependent plasticity not only on the behavioral level, but also on the central nervous level, in an insect.

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.

Cognitive plasticity in foraging Vespula germanica wasps

Vespula germanica (F.) (Hymenoptera: Vespidae) is a highly invasive social wasp that exhibits a rich behavioral repertoire in which learning and memory play a fundamental role in foraging. The learning abilities of these wasps were analyzed while relocating a food source and whether V. germanica foragers are capable of discriminating between different orientation patterns and generalizing their choice to a new pattern. Foraging wasps were trained to associate two different stripe orientation patterns with their respective food locations. Their response to a novel configuration that maintained the orientation of one of the learned patterns but differed in other aspects (e.g. width of stripes) was then evaluated. The results support the hypothesis that V. germanica wasps are able to associate a particular oriented pattern with the location of a feeder and to generalize their choice to a new pattern, which differed in quality, but presented the same orientation.

Costs of memory: lessons from 'mini' brains

Variation in learning and memory abilities among closely related species, or even among populations of the same species, has opened research into the relationship between cognition, ecological context and the fitness costs, and benefits of learning and memory. Such research programmes have long been dominated by vertebrate studies and by the assumption of a relationship between cognitive abilities, brain size and metabolic costs. Research on these 'large brained' organisms has provided important insights into the understanding of cognitive functions and their adaptive value. In the present review, we discuss some aspects of the fitness costs of learning and memory by focusing on 'mini-brain' studies. Research on learning and memory in insects has challenged some traditional positions and is pushing the boundaries of our understanding of the evolution of learning and memory.

Conceptualization of above and below relationships by an insect

Relational rules such as 'same' or 'different' are mastered by humans and non-human primates and are considered as abstract conceptual thinking as they require relational learning beyond perceptual generalization. Here, we investigated whether an insect, the honeybee (Apis mellifera), can form a conceptual representation of an above/below spatial relationship. In experiment 1, bees were trained with differential conditioning to choose a variable target located above or below a black bar that acted as constant referent throughout the experiment. In experiment 2, two visual stimuli were aligned vertically, one being the referent, which was kept constant throughout the experiment, and the other the target, which was variable. In both experiments, the distance between the target and the referent, and their location within the visual field was systematically varied. In both cases, bees succeeded in transferring the learned concept to novel stimuli, preserving the trained spatial relation, thus showing an ability to manipulate this relational concept independently of the physical nature of the stimuli. Absolute location of the referent into the visual field was not a low-level cue used by the bees to solve the task. The honeybee is thus capable of conceptual learning despite having a miniature brain, showing that such elaborated learning form is not a prerogative of vertebrates.

Aversive reinforcement improves visual discrimination learning in free-flying honeybees

BACKGROUND

Learning and perception of visual stimuli by free-flying honeybees has been shown to vary dramatically depending on the way insects are trained. Fine color discrimination is achieved when both a target and a distractor are present during training (differential conditioning), whilst if the same target is learnt in isolation (absolute conditioning), discrimination is coarse and limited to perceptually dissimilar alternatives. Another way to potentially enhance discrimination is to increase the penalty associated with the distractor. Here we studied whether coupling the distractor with a highly concentrated quinine solution improves color discrimination of both similar and dissimilar colors by free-flying honeybees. As we assumed that quinine acts as an aversive stimulus, we analyzed whether aversion, if any, is based on an aversive sensory input at the gustatory level or on a post-ingestional malaise following quinine feeding.

METHODOLOGY/PRINCIPAL FINDINGS

We show that the presence of a highly concentrated quinine solution (60 mM) acts as an aversive reinforcer promoting rejection of the target associated with it, and improving discrimination of perceptually similar stimuli but not of dissimilar stimuli. Free-flying bees did not use remote cues to detect the presence of quinine solution; the aversive effect exerted by this substance was mediated via a gustatory input, i.e. via a distasteful sensory experience, rather than via a post-ingestional malaise.

CONCLUSION

The present study supports the hypothesis that aversion conditioning is important for understanding how and what animals perceive and learn. By using this form of conditioning coupled with appetitive conditioning in the framework of a differential conditioning procedure, it is possible to uncover discrimination capabilities that may remain otherwise unsuspected. We show, therefore, that visual discrimination is not an absolute phenomenon but can be modulated by experience.

Brain activity at 70-80 Hz changes during olfactory stimulation protocols in Drosophila

Oscillatory and synchronized activities in the mammalian brain have been correlated with the execution of complex cognitive tasks. Similar oscillations have been observed in local field potentials (LFPs) in flies, in this case correlated with different attentional states. To further test the significance of these oscillations we recorded LFPs from the brain of Drosophila melanogaster as it responded to the presentation of olfactory stimuli. We find that responses in the 70-80 Hz range increase during olfactory stimulation. Recurrent stimulation specifically decreased the power of LFPs in this frequency range. Delivery of electric shocks before olfactory stimulation modulated LFPs in the 70-80 Hz range by evoking a transient increase. These results suggest that these signals are a simple neuronal correlate of higher-order olfactory processing in flies.

Configural processing enables discrimination and categorization of face-like stimuli in honeybees

We studied whether honeybees can distinguish face-like configurations by using standardized stimuli commonly employed in primate and human visual research. Furthermore, we studied whether, irrespective of their capacity to distinguish between face-like stimuli, bees learn to classify visual stimuli built up of the same elements in face-like versus non-face-like categories. We showed that bees succeeded in discriminating both face-like and non-face-like stimuli and categorized appropriately novel stimuli in these two classes. To this end, they used configural information and not just isolated features or low-level cues. Bees looked for a specific configuration in which each feature had to be located in an appropriate spatial relationship with respect to the others, thus showing sensitivity for first-order relationships between features. Although faces are biologically irrelevant stimuli for bees, the fact that they were able to integrate visual features into complex representations suggests that face-like stimulus categorization can occur even in the absence of brain regions specialized in face processing.

Are bigger brains better?

Attempts to relate brain size to behaviour and cognition have rarely integrated information from insects with that from vertebrates. Many insects, however, demonstrate that highly differentiated motor repertoires, extensive social structures and cognition are possible with very small brains, emphasising that we need to understand the neural circuits, not just the size of brain regions, which underlie these feats. Neural network analyses show that cognitive features found in insects, such as numerosity, attention and categorisation-like processes, may require only very limited neuron numbers. Thus, brain size may have less of a relationship with behavioural repertoire and cognitive capacity than generally assumed, prompting the question of what large brains are for. Larger brains are, at least partly, a consequence of larger neurons that are necessary in large animals due to basic biophysical constraints. They also contain greater replication of neuronal circuits, adding precision to sensory processes, detail to perception, more parallel processing and enlarged storage capacity. Yet, these advantages are unlikely to produce the qualitative shifts in behaviour that are often assumed to accompany increased brain size. Instead, modularity and interconnectivity may be more important.

In situ hybridization analysis of the expression of futsch, tau, and MESK2 homologues in the brain of the European honeybee (Apis mellifera L.)

BACKGROUND

The importance of visual sense in Hymenopteran social behavior is suggested by the existence of a Hymenopteran insect-specific neural circuit related to visual processing and the fact that worker honeybee brain changes morphologically according to its foraging experience. To analyze molecular and neural bases that underlie the visual abilities of the honeybees, we used a cDNA microarray to search for gene(s) expressed in a neural cell-type preferential manner in a visual center of the honeybee brain, the optic lobes (OLs).

METHODOLOGY/PRINCIPAL FINDINGS

Expression analysis of candidate genes using in situ hybridization revealed two genes expressed in a neural cell-type preferential manner in the OLs. One is a homologue of Drosophila futsch, which encodes a microtubule-associated protein and is preferentially expressed in the monopolar cells in the lamina of the OLs. The gene for another microtubule-associated protein, tau, which functionally overlaps with futsch, was also preferentially expressed in the monopolar cells, strongly suggesting the functional importance of these two microtubule-associated proteins in monopolar cells. The other gene encoded a homologue of Misexpression Suppressor of Dominant-negative Kinase Suppressor of Ras 2 (MESK2), which might activate Ras/MAPK-signaling in Drosophila. MESK2 was expressed preferentially in a subclass of neurons located in the ventral region between the lamina and medulla neuropil in the OLs, suggesting that this subclass is a novel OL neuron type characterized by MESK2-expression. These three genes exhibited similar expression patterns in the worker, drone, and queen brains, suggesting that they function similarly irrespective of the honeybee sex or caste.

CONCLUSIONS

Here we identified genes that are expressed in a monopolar cell (Amfutsch and Amtau) or ventral medulla-preferential manner (AmMESK2) in insect OLs. These genes may aid in visualizing neurites of monopolar cells and ventral medulla cells, as well as in analyzing the function of these neurons.

Honey bees as a model for vision, perception, and cognition

Among the so-called simpler organisms, the honey bee is one of the few examples of an animal with a highly evolved social structure, a rich behavioral repertoire, an exquisite navigational system, an elaborate communication system, and an extraordinary ability to learn colors, shapes, fragrances, and navigational routes quickly and accurately. This review examines vision and complex visually mediated behavior in the honey bee, outlining the structure and function of the compound eyes, the perception and discrimination of colors and shapes, the learning of complex tasks, the ability to establish and exploit complex associations, and the capacity to abstract general principles from a task and apply them to tackle novel situations. All this is accomplished by a brain that weighs less than a milligram and carries fewer than a million neurons, thus making the bee a promising subject in which to study a variety of fundamental questions about behavior and brain function.

On the generality and limits of abstraction in rats and humans

In this review, we address the question, central to cognition, of whether nonhuman animals such as rats are capable of extracting and extending information from a given learning situation to a new learning situation without generalizing through a physical dimension of the stimuli.This capacity underlies abstraction, which is a hallmark of human cognition and necessary for complex information processing such as language acquisition. We selectively review recent experiments with rats in which systematic changes in information processing of new stimuli are observed after training with different stimuli. These results strongly suggest that this capacity is present in rats. We also review two articles in which clear limitations to this capacity are detected. We conclude that, within specified limits, rats are capable of using prior experience when faced with a learning situation that involves new stimuli.We interpret this ability as a rudimentary form of abstraction. In the face of these provocative results, new theories of learning should be designed to account for these findings.

Syntax-induced pattern deafness

Perceptual systems often force systematically biased interpretations upon sensory input. These interpretations are obligatory, inaccessible to conscious control, and prevent observers from perceiving alternative percepts. Here we report a similarly impenetrable phenomenon in the domain of language, where the syntactic system prevents listeners from detecting a simple perceptual pattern. Healthy human adults listened to three-word sequences conforming to patterns readily learned even by honeybees, rats, and sleeping human neonates. Specifically, sequences either started or ended with two words from the same syntactic category (e.g., noun-noun-verb or verb-verb-noun). Although participants readily processed the categories and learned repetition patterns over nonsyntactic categories (e.g., animal-animal-clothes), they failed to learn the repetition pattern over syntactic categories, even when explicitly instructed to look for it. Further experiments revealed that participants successfully learned the repetition patterns only when they were consistent with syntactically possible structures, irrespective of whether these structures were attested in English or in other languages unknown to the participants. When the repetition patterns did not match such syntactically possible structures, participants failed to learn them. Our results suggest that when human adults hear a string of nouns and verbs, their syntactic system obligatorily attempts an interpretation (e.g., in terms of subjects, objects, and predicates). As a result, subjects fail to perceive the simpler pattern of repetitions--a form of syntax-induced pattern deafness that is reminiscent of how other perceptual systems force specific interpretations upon sensory input.

On optimal decision-making in brains and social insect colonies

The problem of how to compromise between speed and accuracy in decision-making faces organisms at many levels of biological complexity. Striking parallels are evident between decision-making in primate brains and collective decision-making in social insect colonies: in both systems, separate populations accumulate evidence for alternative choices; when one population reaches a threshold, a decision is made for the corresponding alternative, and this threshold may be varied to compromise between the speed and the accuracy of decision-making. In primate decision-making, simple models of these processes have been shown, under certain parametrizations, to implement the statistically optimal procedure that minimizes decision time for any given error rate. In this paper, we adapt these same analysis techniques and apply them to new models of collective decision-making in social insect colonies. We show that social insect colonies may also be able to achieve statistically optimal collective decision-making in a very similar way to primate brains, via direct competition between evidence-accumulating populations. This optimality result makes testable predictions for how collective decision-making in social insects should be organized. Our approach also represents the first attempt to identify a common theoretical framework for the study of decision-making in diverse biological systems.

Perceptual and memory constraints on language acquisition

A wide variety of organisms employ specialized mechanisms to cope with the demands of their environment. We suggest that the same is true for humans when acquiring artificial grammars, and at least some basic properties of natural grammars. We show that two basic mechanisms can explain many results in artificial grammar learning experiments, and different linguistic regularities ranging from stress assignment to interfaces between different components of grammar. One mechanism is sensitive to identity relations, whereas the other uses sequence edges as anchor points for extracting positional regularities. This piecemeal approach to mental computations helps to explain otherwise perplexing data, and offers a working hypothesis on how statistical and symbolic accounts of cognitive processes could be bridged.

Generalization in visual recognition by the honeybee (Apis mellifera): a review and explanation

During a century of studies on honeybee vision, generalization was the word for the acceptance of an unfamiliar pattern in the place of the training pattern, or the ability to learn a common factor in a group of related patterns. The ideas that bees generalize one pattern for another, detect similarity and differences, or form categories, were derived from the use of the same terms in the human cognitive sciences. Recent work now reveals a mechanistic explanation for bees. Small groups of ommatidia converge upon feature detectors that respond selectively to certain parameters that are in the pattern: modulation in the receptors, edge orientations, or to areas of black or colour. Within each local region of the eye the responses of each type of feature detector are summed to form a cue. The cues are therefore not in the pattern, but are local totals in the bee. Each cue has a quality, a quantity and a position on the eye, like a neuron response. This summation of edge detector responses destroys the local pattern based on edge orientation but preserves a coarse, sparse and simplified version of the panorama. In order of preference, the cues are: local receptor modulation, positions of well-separated black areas, a small black spot, colour and positions of the centres of each cue, radial edges, the averaged edge orientation and tangential edges. A pattern is always accepted by a trained bee that detects the expected cues in the expected places and no unexpected cues. The actual patterns are irrelevant. Therefore we have an explanation of generalization that is based on experimental testing of trained bees, not by analogy with other animals. Historically, generalization appeared when the training patterns were regularly interchanged to make the bees examine them. This strategy forced the bees to ignore parameters outside the training pattern, so that learning was restricted to one local eye region. This in turn limited the memory to one cue of each type, so that recognition was ambiguous because the cues were insufficient to distinguish all patterns. On the other hand, bees trained on very large targets, or by landing on the pattern, learned cues in several eye regions, and were able to recognize the coarse configural layout.

Serial position learning in honeybees

Learning of stimulus sequences is considered as a characteristic feature of episodic memory since it contains not only a particular item but also the experience of preceding and following events. In sensorimotor tasks resembling navigational performance, the serial order of objects is intimately connected with spatial order. Mammals and birds develop episodic(-like) memory in serial spatio-temporal tasks, and the honeybee learns spatio-temporal order when navigating between the nest and a food source. Here I examine the structure of the bees' memory for a combined spatio-temporal task. I ask whether discrimination and generalization are based solely on simple forms of stimulus-reward learning or whether they require sequential configurations. Animals were trained to fly either left or right in a continuous T-maze. The correct choice was signaled by the sequence of colors (blue, yellow) at four positions in the access arm. If only one of the possible 4 signals is shown (either blue or yellow), the rank order of position salience is 1, 2 and 3 (numbered from T-junction). No learning is found if the signal appears at position 4. If two signals are shown, differences at positions 1 and 2 are learned best, those at position 3 at a low level, and those at position 4 not at all. If three or more signals are shown these results are corroborated. This salience rank order again appeared in transfer tests, but additional configural phenomena emerged. Most of the results can be explained with a simple model based on the assumption that the four positions are equipped with different salience scores and that these add up independently. However, deviations from the model are interpreted by assuming stimulus configuration of sequential patterns. It is concluded that, under the conditions chosen, bees rely most strongly on memories developed during simple forms of associative reward learning, but memories of configural serial patterns contribute, too.

Number-based visual generalisation in the honeybee

Although the numerical abilities of many vertebrate species have been investigated in the scientific literature, there are few convincing accounts of invertebrate numerical competence. Honeybees, Apis mellifera, by virtue of their other impressive cognitive feats, are a prime candidate for investigations of this nature. We therefore used the well-established delayed match-to-sample paradigm, to test the limits of honeybees' ability to match two visual patterns solely on the basis of the shared number of elements in the two patterns. Using a y-maze, we found that bees can not only differentiate between patterns containing two and three elements, but can also use this prior knowledge to differentiate three from four, without any additional training. However, bees trained on the two versus three task could not distinguish between higher numbers, such as four versus five, four versus six, or five versus six. Control experiments confirmed that the bees were not using cues such as the colour of the exact configuration of the visual elements, the combined area or edge length of the elements, or illusory contours formed by the elements. To our knowledge, this is the first report of number-based visual generalisation by an invertebrate.

Working memory in bees: also in flies?

Decision making requires reference to both actual and remote information in the context of the requirements of the animal. Here, I explore a cognitive approach to decision making in honeybees and ask the question whether flies may share the faculties observed in bees. Examples are drawn primarily from natural behavior in bees, particularly from navigation and communication. I conclude that studies in Drosophila learning and memory in the tradition of Martin Heisenberg may gain from cognitive concepts, meaning that the "internal doing" of the brain should be included in the search for the neural basis of decision making.

Insect brains use image interpolation mechanisms to recognise rotated objects

Recognising complex three-dimensional objects presents significant challenges to visual systems when these objects are rotated in depth. The image processing requirements for reliable individual recognition under these circumstances are computationally intensive since local features and their spatial relationships may significantly change as an object is rotated in the horizontal plane. Visual experience is known to be important in primate brains learning to recognise rotated objects, but currently it is unknown how animals with comparatively simple brains deal with the problem of reliably recognising objects when seen from different viewpoints. We show that the miniature brain of honeybees initially demonstrate a low tolerance for novel views of complex shapes (e.g. human faces), but can learn to recognise novel views of stimuli by interpolating between or 'averaging' views they have experienced. The finding that visual experience is also important for bees has important implications for understanding how three dimensional biologically relevant objects like flowers are recognised in complex environments, and for how machine vision might be taught to solve related visual problems.

Acute ethanol ingestion impairs appetitive olfactory learning and odor discrimination in the honey bee

Invertebrates are valuable models for increasing our understanding of the effects of ethanol on the nervous system, but most studies on invertebrates and ethanol have focused on the effects of ethanol on locomotor behavior. In this work we investigate the influence of an acute dose of ethanol on appetitive olfactory learning in the honey bee (Apis mellifera), a model system for learning and memory. Adult worker honey bees were fed a range of doses (2.5%, 5%, 10%, or 25%) of ethanol and then conditioned to associate an odor with a sucrose reward using either a simple or differential conditioning paradigm. Consumption of ethanol before conditioning significantly reduced both the rate of acquisition and the asymptotic strength of the association. Honey bees also exhibited a dose dependent reduction in arousal/attention during conditioning. Consumption of ethanol after conditioning did not affect recall 24h later. The observed deficits in acquisition were not due to the affect of ethanol on gustatory sensitivity or motor function. However, honey bees given higher doses of ethanol had difficulty discriminating amongst different odors suggesting that ethanol consumption influences olfactory processing. Taken together, these results demonstrate that an acute dose of ethanol affects appetitive learning and olfactory perception in the honey bee.

Olfactory interference during inhibitory backward pairing in honey bees

BACKGROUND

Restrained worker honey bees are a valuable model for studying the behavioral and neural bases of olfactory plasticity. The proboscis extension response (PER; the proboscis is the mouthpart of honey bees) is released in response to sucrose stimulation. If sucrose stimulation is preceded one or a few times by an odor (forward pairing), the bee will form a memory for this association, and subsequent presentations of the odor alone are sufficient to elicit the PER. However, backward pairing between the two stimuli (sucrose, then odor) has not been studied to any great extent in bees, although the vertebrate literature indicates that it elicits a form of inhibitory plasticity.

METHODOLOGY/PRINCIPAL FINDINGS

If hungry bees are fed with sucrose, they will release a long lasting PER; however, this PER can be interrupted if an odor is presented 15 seconds (but not 7 or 30 seconds) after the sucrose (backward pairing). We refer to this previously unreported process as olfactory interference. Bees receiving this 15 second backward pairing show reduced performance after a subsequent single forward pairing (excitatory conditioning) trial. Analysis of the results supported a relationship between olfactory interference and a form of backward pairing-induced inhibitory learning/memory. Injecting the drug cimetidine into the deutocerebrum impaired olfactory interference.

CONCLUSIONS/SIGNIFICANCE

Olfactory interference depends on the associative link between odor and PER, rather than between odor and sucrose. Furthermore, pairing an odor with sucrose can lead either to association of this odor to PER or to the inhibition of PER by this odor. Olfactory interference may provide insight into processes that gate how excitatory and inhibitory memories for odor-PER associations are formed.

Selforganizing memory: active learning of landmarks used for navigation

We propose a memory architecture that is suited to solve a specific task, namely homing, that is finding a not directly visible home place by using visually accessible landmarks. We show that an agent equipped with such a memory structure can autonomously learn the situation and can later use its memory to accomplish homing behaviour. The architecture is based on neuronal structures and grows in a self-organized way depending on experience. The basic architecture consists of three parts, (i) a pre-processor, (ii) a simple, one-layered feed-forward network, called distributor net, and (iii) a full recurrently connected net for representing the situation models to be stored. Apart from Hebbian learning and a local version of the delta-rule, explorative learning is applied that is not based on passive detection of correlations, but is actively searching for interesting hypotheses. Hypotheses are spontaneously introduced and are verified or falsified depending on how well the network representing the hypothesis approaches an internal error of zero. The stability of this approach is successfully tested by removal of one landmark or shifting the position of one or several landmarks showing results comparable to those found in biological experiments. Furthermore, we applied noise in two ways. The trained network was either due to sensory noise or to noise applied to the bias weights describing the memory content. Finally, we tested to what extent learning of the weights is affected by noisy input given to the sensor data. The architecture proposed is discussed to have some at least superficial similarity to the mushroom bodies of insects.

East learns from West: Asiatic honeybees can understand dance language of European honeybees

The honeybee waggle dance, through which foragers advertise the existence and location of a food source to their hive mates, is acknowledged as the only known form of symbolic communication in an invertebrate. However, the suggestion, that different species of honeybee might possess distinct ‘dialects’ of the waggle dance, remains controversial. Furthermore, it remains unclear whether different species of honeybee can learn from and communicate with each other. This study reports experiments using a mixed-species colony that is composed of the Asiatic bee Apis cerana cerana (Acc), and the European bee Apis mellifera ligustica (Aml). Using video recordings made at an observation hive, we first confirm that Acc and Aml have significantly different dance dialects, even when made to forage in identical environments. When reared in the same colony, these two species are able to communicate with each other: Acc foragers could decode the dances of Aml to successfully locate an indicated food source. We believe that this is the first report of successful symbolic communication between two honeybee species; our study hints at the possibility of social learning between the two honeybee species, and at the existence of a learning component in the honeybee dance language.

Languages of thought need to be distinguished from learning mechanisms, and nothing yet rules out multiple distinctively human learning systems

We distinguish the question whether only human minds are equipped with a language of thought (LoT) from the question whether human minds employ a single uniquely human learning mechanism. Thus separated, our answer to both questions is negative. Even very simple minds employ a LoT. And the comparative data reviewed by Penn et al. actually suggest that there are many distinctively human learning mechanisms.

Honeybees can recognise images of complex natural scenes for use as potential landmarks

The ability to navigate long distances to find rewarding flowers and return home is a key factor in the survival of honeybees (Apis mellifera). To reliably perform this task, bees combine both odometric and landmark cues,which potentially creates a dilemma since environments rich in odometric cues might be poor in salient landmark cues, and vice versa. In the present study, honeybees were provided with differential conditioning to images of complex natural scenes, in order to determine if they could reliably learn to discriminate between very similar scenes, and to recognise a learnt scene from a novel distractor scene. Choices made by individual bees were modelled with signal detection theory, and bees demonstrated an ability to discriminate between perceptually similar target and distractor views despite similar spatiotemporal content of the images. In a non-rewarded transfer test bees were also able to recognise target stimuli from novel distractors. These findings indicate that visual processing in bees is sufficiently accurate for recognising views of complex scenery as potential landmarks, which would enable bees flying in a forest to use trees both as landmark and/or odometric cues.

Crayfish recognize the faces of fight opponents

The capacity to associate stimuli underlies many cognitive abilities, including recognition, in humans and other animals. Vertebrates process different categories of information separately and then reassemble the distilled information for unique identification, storage and recall. Invertebrates have fewer neural networks and fewer neural processing options so study of their behavior may reveal underlying mechanisms still not fully understood for any animal. Some invertebrates form complex social colonies and are capable of visual memory–bees and wasps, for example. This ability would not be predicted in species that interact in random pairs without strong social cohesion; for example, crayfish. They have chemical memory but the extent to which they remember visual features is unknown. Here we demonstrate that the crayfish Cherax destructor is capable of visual recognition of individuals. The simplicity of their interactions allowed us to examine the behavior and some characteristics of the visual features involved. We showed that facial features are learned during face-to-face fights, that highly variable cues are used, that the type of variability is important, and that the learning is context-dependent. We also tested whether it is possible to engineer false identifications and for animals to distinguish between twin opponents.

Social learning in insects--from miniature brains to consensus building

Communication and learning from each other are part of the success of insect societies. Here, we review a spectrum of social information usage in insects--from inadvertently provided cues to signals shaped by selection specifically for information transfer. We pinpoint the sensory modalities involved and, in some cases, quantify the adaptive benefits. Well substantiated cases of social learning among the insects include learning about predation threat and floral rewards, the transfer of route information using a symbolic 'language' (the honeybee dance) and the rapid spread of chemosensory preferences through honeybee colonies via classical conditioning procedures. More controversial examples include the acquisition of motor memories by observation, teaching in ants and behavioural traditions in honeybees. In many cases, simple mechanistic explanations can de identified for such complex behaviour patterns.

A test of the effect of floral color change on pollination effectiveness using artificial inflorescences visited by bumblebees

Floral color change has been recognized as a pollination strategy, but its relative effectiveness has been evaluated insufficiently with respect to other floral traits. In this study, effects of floral color change on the visitation pattern of bumblebees were empirically assessed using artificial flowers. Four inflorescence types were postulated as strategies of flowering behavior: type 1 has no retention of old flowers, resulting in a small display size; type 2 retains old flowers without nectar production; type 3 retains old flowers with nectar; and type 4 retains color-changed old flowers without nectar. Effects of these treatments varied depending on both the total display size (single versus multiple inflorescences) and the pattern of flower-opening. In the single inflorescence experiment, a large floral display due to the retention of old flowers (types 2-4) enhanced pollinator attraction, and the number of flower visits per stay decreased with color change (type 4), suggesting a decrease in geitonogamous pollination. Type-4 plants also reduced the foraging time of bees in comparison with type-2 plants. In the multiple inflorescence experiment, the retention of old flowers did not contribute to pollinator attraction. When flowering occurred sequentially within inflorescences, type-4 plants successfully decreased the number of visits and the foraging time in comparison with type-2 plants. In contrast, floral color change did not influence the number of visits, and it extended the foraging time when flowering occurred simultaneously within inflorescences but the opening of inflorescences progressed sequentially within a plant. Therefore, the effectiveness of floral color change is highly susceptible to the display size and flowering pattern within plants, and this may limit the versatility of the color change strategy in nature.

Behavioral and neural analysis of associative learning in the honeybee: a taste from the magic well

Equipped with a mini brain smaller than one cubic millimeter and containing only 950,000 neurons, honeybees could be indeed considered as having rather limited cognitive abilities. However, bees display a rich and interesting behavioral repertoire, in which learning and memory play a fundamental role in the framework of foraging activities. We focus on the question of whether adaptive behavior in honeybees exceeds simple forms of learning and whether the neural mechanisms of complex learning can be unraveled by studying the honeybee brain. Besides elemental forms of learning, in which bees learn specific and univocal links between events in their environment, bees also master different forms of non-elemental learning, including categorization, contextual learning and rule abstraction, both in the visual and in the olfactory domain. Different protocols allow accessing the neural substrates of some of these learning forms and understanding how complex problem solving can be achieved by a relatively simple neural architecture. These results underline the enormous richness of experience-dependent behavior in honeybees, its high flexibility, and the fact that it is possible to formalize and characterize in controlled laboratory protocols basic and higher-order cognitive processing using an insect as a model.

Experience improves feature extraction in Drosophila

Previous exposure to a pattern in the visual scene can enhance subsequent recognition of that pattern in many species from honeybees to humans. However, whether previous experience with a visual feature of an object, such as color or shape, can also facilitate later recognition of that particular feature from multiple visual features is largely unknown. Visual feature extraction is the ability to select the key component from multiple visual features. Using a visual flight simulator, we designed a novel protocol for visual feature extraction to investigate the effects of previous experience on visual reinforcement learning in Drosophila. We found that, after conditioning with a visual feature of objects among combinatorial shape-color features, wild-type flies exhibited poor ability to extract the correct visual feature. However, the ability for visual feature extraction was greatly enhanced in flies trained previously with that visual feature alone. Moreover, we demonstrated that flies might possess the ability to extract the abstract category of "shape" but not a particular shape. Finally, this experience-dependent feature extraction is absent in flies with defective MBs, one of the central brain structures in Drosophila. Our results indicate that previous experience can enhance visual feature extraction in Drosophila and that MBs are required for this experience-dependent visual cognition.

Thermal radiation as a learned orientation cue in leaf-cutting ants (Atta vollenweideri)

We explored the ability of leaf-cutting ants (Atta vollenweideri) to learn the location of a food reward by using thermal information as an orientation cue. During training of single workers, the conditioned stimulus was a distant thermal source placed frontally, 15 mm away from a platform having a leaf fragment as reward. After training, single workers were confronted with the choice between two sides, one being coupled, in a pseudo-randomized design, with a thermal stimulus heated 5 degrees C above environmental temperature. After 10 learning trials, workers significantly chose the side with the thermal stimulus. This showed that workers can use thermal information for spatial orientation in the context of foraging, which may help them to locate, for instance, highly attractive sun-exposed leaves. Thermal radiation alone as orientation cue was sufficient to allow learning, since preclusion of thermal convection during training and test did not impair workers' response. Shielding of both thorax and gaster from the thermal source did not weaken learning, suggesting the sole participation of head and antennae in temperature reception. A thermal stimulus heated 1 degrees C above environmental temperature could not be used as a learned orientation cue, even when foragers were allowed to directly contact the thermal source.

Modelling memory functions with recurrent neural networks consisting of input compensation units: I. Static situations

Humans are able to form internal representations of the information they process -- a capability which enables them to perform many different memory tasks. Therefore, the neural system has to learn somehow to represent aspects of the environmental situation; this process is assumed to be based on synaptic changes. The situations to be represented are various as for example different types of static patterns but also dynamic scenes. How are neural networks consisting of mutually connected neurons capable of performing such tasks? Here we propose a new neuronal structure for artificial neurons. This structure allows one to disentangle the dynamics of the recurrent connectivity from the dynamics induced by synaptic changes due to the learning processes. The error signal is computed locally within the individual neuron. Thus, online learning is possible without any additional structures. Recurrent neural networks equipped with these computational units cope with different memory tasks. Examples illustrate how information is extracted from environmental situations comprising fixed patterns to produce sustained activity and to deal with simple algebraic relations.

Perceptual constraints and the learnability of simple grammars

Cognitive processes are often attributed to statistical or symbolic general-purpose mechanisms. Here we show that some spontaneous generalizations are driven by specialized, highly constrained symbolic operations. We explore how two types of artificial grammars are acquired, one based on repetitions and the other on characteristic relations between tones ("ordinal" grammars). Whereas participants readily acquire repetition-based grammars, displaying early electrophysiological responses to grammar violations, they perform poorly with ordinal grammars, displaying no such electrophysiological responses. This outcome is problematic for both general symbolic and statistical models, which predict that both types of grammars should be processed equally easily. This suggests that some simple grammars are acquired using perceptual primitives rather than general-purpose mechanisms; such primitives may be elements of a "toolbox" of specialized computational heuristics, which may ultimately allow constructing a psychological theory of symbol manipulation.

Insect olfactory memory in time and space

Recent studies using functional optical imaging have revealed that cellular memory traces form in different areas of the insect brain after olfactory classical conditioning. These traces are revealed as increased calcium signals or synaptic release from defined neurons, and include a short-lived trace that forms immediately after conditioning in antennal lobe projection neurons, an early trace in dopaminergic neurons, and a medium-term trace in dorsal paired medial neurons. New molecular genetic tools have revealed that for normal behavioral memory performance, synaptic transmission from the mushroom body neurons is required only during retrieval, whereas synaptic transmission from dopaminergic neurons is required at the time of acquisition and synaptic transmission from dorsal paired medial neurons is required during the consolidation period. Such experimental results are helping to identify the types of neurons that participate in olfactory learning and when their participation is required. Olfactory learning often occurs alongside crossmodal interactions of sensory information from other modalities. Recent studies have revealed complex interactions between the olfactory and the visual senses that can occur during olfactory learning, including the facilitation of learning about subthreshold olfactory stimuli due to training with concurrent visual stimuli.

Some labels that are recognized on landmarks by the honeybee (Apis mellifera)

Freely flying bees were trained in a situation that resembled the natural task of a bee arriving at a foraging site that was located by a landmark. The bees' task was to locate the reward in the arm of the Y-choice apparatus, where a black pattern on a white background was displayed in one arm versus a white target in the other arm, at a range of 27 cm. The alternative patterns for the training included previously identified cues. They were: an oblique bar, three parallel oblique bars, an oblique grating, a square cross, six spokes, a large or a small spot, a spotty modulation, or a ring. The trained bees were given a variety of interleaved tests to discover the labels they had used to identify the patterns. A label is defined as the coincidence of cues that contributed to the recognition of a single landmark. The bees learned, firstly, the black area at the expected place, secondly, modulation caused by edges at the expected place. These cues were quantified and always available. In addition, the orientation cue was learned from a grating that covered the target, but was ignored in a single bar. The bees learned the positions of the centres of black and of radial symmetry. In tests, they also recognized unfamiliar cues that were not displayed in the training. The cues and preferences were similar to those used to discriminate between two targets. The new experiments validate some old conclusions that have been controversial for 40 years.