Psychophysics: bees trade off foraging speed for accuracy

A reinvestigation of cognitive styles in sticklebacks: decision success varies with behavioral type

The "cognitive styles" hypothesis suggests that individual differences in behavior are associated with variation in cognitive performance via underlying speed-accuracy trade-offs. While this is supported, in part, by a growing body of evidence, some studies did not find the expected relationships between behavioral type and cognitive performance. In some cases, this may reflect methodological limitations rather than the absence of a true relationship. The physical design of the testing arena and the number of choices offered in an assay can hinder our ability to detect inter-individual differences in cognitive performance. Here, we re-investigated the cognitive styles hypothesis in threespine stickleback (Gasterosteus aculeatus), adapting the maze design of a previous study which found no cost to decision success by faster (bolder) individuals. We used a similar design but increased the size of the maze and incorporated an additional choice in the form of a third maze arm. We found, in accordance with cognitive style expectations, that individuals who were consistently slower to emerge from the start chamber made fewer errors than fish that emerged faster. Activity in an open field test, however, did not show evidence of a relationship with decision success, possibly due to the low number of repeated observations per fish in this separate assay. Our results provide further empirical support for the cognitive styles hypothesis and highlight important methodological aspects to consider in studies of inter-individual differences in cognition.

Speed is associated with polarization during subjective evaluation: no tradeoff, but an effect of the ease of processing

In human perceptual decision-making, the speed-accuracy tradeoff establishes a causal link between urgency and reduced accuracy. Less is known about how speed relates to the subjective evaluation of visual images. Here, we conducted a set of four experiments to tease apart two alternative hypotheses for the relation between speed and subjective evaluation. The hypothesis of "Speed-Polarization Tradeoff" implies that urgency causes more polarized evaluations. In contrast, the "Ease-of-Processing" hypothesis suggests that any association between speed and polarization is due to the salience of evaluation-relevant image content. The more salient the content, the easier to process, and therefore the faster and more extreme the evaluation. In each experiment, we asked participants to evaluate images on a continuous scale from - 10 to + 10 and measured their response times; in Experiments 1-3, the participants rated real-world images in terms of morality (from "very immoral," -10, to "very moral," +10); in Experiment 4, the participants rated food images in terms of appetitiveness (from "very disgusting," -10, to "very attractive," +10). In Experiments 1, 3, and 4, we used a cueing procedure to inform the participants on a trial-by-trial basis whether they could make a self-paced (SP) evaluation or whether they had to perform a time-limited (TL) evaluation within 2 s. In Experiment 2, we asked participants to rate the easiness of their SP moral evaluations. Compared to the SP conditions, the responses in the TL condition were consistently much faster, indicating that our urgency manipulation was successful. However, comparing the SP versus TL conditions, we found no significant differences in any of the evaluations. Yet, the reported ease of processing of moral evaluation covaried strongly with both the response speed and the polarization of evaluation. The overall pattern of data indicated that, while speed is associated with polarization, urgency does not cause participants to make more extreme evaluations. Instead, the association between speed and polarization reflects the ease of processing. Images that are easy to evaluate evoke faster and more extreme scores than images for which the interpretation is uncertain.

Brain energy metabolism as an underlying basis of slow and fast cognitive phenotypes in honeybees

In the context of slow-fast behavioral variation, fast individuals are hypothesized to be those who prioritize speed over accuracy while slow individuals are those which do the opposite. Since energy metabolism is a critical component of neural and cognitive functioning, this predicts such differences in cognitive style to be reflected at the level of the brain. We tested this idea in honeybees by first classifying individuals into slow and fast cognitive phenotypes based on a learning assay and then measuring their brain respiration with high-resolution respirometry. Our results broadly show that inter-individual differences in cognition are reflected in differences in brain mass and accompanying energy use at the level of the brain and the whole animal. Larger brains had lower mass-specific energy usage and bees with larger brains had a higher metabolic rate. These differences in brain respiration and brain mass were, in turn, associated with cognitive differences, such that bees with larger brains were fast cognitive phenotypes whereas those with smaller brains were slow cognitive phenotypes. We discuss these results in the context of the role of energy in brain functioning and slow-fast decision making and speed accuracy trade-off.

Fast decisions reflect biases; slow decisions do not

Decisions are often made by heterogeneous groups of individuals, each with distinct initial biases and access to information of different quality. We show that in groups of independent agents who accumulate evidence the first to decide are those with the strongest initial biases. Their decisions align with their initial bias, regardless of the underlying truth. In contrast, agents who decide last make decisions as if they were initially unbiased and hence make better choices. We obtain asymptotic expressions in the large population limit quantifying how agents' initial inclinations shape early decisions. Our analysis shows how bias, information quality, and decision order interact in nontrivial ways to determine the reliability of decisions in a group.

Quantity misperception by hymenopteran insects observing the solitaire illusion

Visual illusions are errors in signal perception and inform us about the visual and cognitive processes of different animals. Invertebrates are relatively less studied for their illusionary perception, despite the insight that comparative data provides on the evolution of common perceptual mechanisms. The Solitaire Illusion is a numerosity illusion where a viewer typically misperceives the relative quantities of two items of different colors consisting of identical quantity, with more centrally clustered items appearing more numerous. We trained European honeybees (Apis mellifera) and European wasps (Vespula vulgaris) to select stimuli containing a higher quantity of yellow dots in arrays of blue and yellow dots and then presented them with the Solitaire Illusion. Insects learnt to discriminate between dot quantities and showed evidence of perceiving the Solitaire Illusion. Further work should determine whether the illusion is caused by numerical cues only or by both quantity and non-numerical spatial cues.

Uncertainty about predation risk: a conceptual review

Uncertainty has long been of interest to economists and psychologists and has more recently gained attention among ecologists. In the ecological world, animals must regularly make decisions related to finding resources and avoiding threats. Here, we describe uncertainty as a perceptual phenomenon of decision-makers, and we focus specifically on the functional ecology of such uncertainty regarding predation risk. Like all uncertainty, uncertainty about predation risk reflects informational limitations. When cues are available, they may be novel (i.e. unknown information), incomplete, unreliable, overly abundant and complex, or conflicting. We review recent studies that have used these informational limitations to induce uncertainty of predation risk. These studies have typically used either over-responses to novelty (i.e. neophobia) or memory attenuation as proxies for measuring uncertainty. Because changes in the environment, particularly unpredictable changes, drive informational limitations, we describe studies assessing unpredictable variance in spatio-temporal predation risk, intensity of predation risk, predator encounter rate, and predator diversity. We also highlight anthropogenic changes within habitats that are likely to have dramatic impacts on information availability and thus uncertainty in antipredator decisions in the modern world.

Prediction error drives associative learning and conditioned behavior in a spiking model of Drosophila larva

Predicting reinforcement from sensory cues is beneficial for goal-directed behavior. In insect brains, underlying associations between cues and reinforcement, encoded by dopaminergic neurons, are formed in the mushroom body. We propose a spiking model of the Drosophila larva mushroom body. It includes a feedback motif conveying learned reinforcement expectation to dopaminergic neurons, which can compute prediction error as the difference between expected and present reinforcement. We demonstrate that this can serve as a driving force in learning. When combined with synaptic homeostasis, our model accounts for theoretically derived features of acquisition and loss of associations that depend on the intensity of the reinforcement and its temporal proximity to the cue. From modeling olfactory learning over the time course of behavioral experiments and simulating the locomotion of individual larvae toward or away from odor sources in a virtual environment, we conclude that learning driven by prediction errors can explain larval behavior.

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.

Maze design: size and number of choices impact fish performance in cognitive assays

Although studies on fish cognition are increasing, consideration of how methodological details influence the ability to detect and measure performance is lagging. Here, in two separate experiments the authors compared latency to leave the start position, latency to make a decision, levels of participation and success rates (whether fish entered the rewarded chamber as first choice) across different physical designs. Experiments compared fish performance across (a) two sizes of T-mazes, large and standard, and a plus-maze, and (b) open choice arenas with either two or four doors. Fish in T-mazes with longer arms took longer to leave the start chamber and were less likely to participate in a trial than fish in T-mazes with shorter arms. The number of options, or complexity, in a maze significantly impacted success but did not necessarily impact behavioural measures, and did not impact the number of fish that reached a chamber. Fish in the plus-maze had similar latencies to leave the start box and time to reach any chamber as fish in the same-sized T-maze but exhibited lower overall success. Similarly, in an open choice arena, increasing the number of options - doors to potential reward chambers - resulted in lower probability of success. There was an influence of reward position in the choice arena, with rewarded chambers closest to the sides of the arena resulting in lower latencies to enter and higher probability of decision success. Together the results allow the authors to offer practical suggestions towards optimal maze design for studies of fish cognition.

Natural variability in bee brain size and symmetry revealed by micro-CT imaging and deep learning

Analysing large numbers of brain samples can reveal minor, but statistically and biologically relevant variations in brain morphology that provide critical insights into animal behaviour, ecology and evolution. So far, however, such analyses have required extensive manual effort, which considerably limits the scope for comparative research. Here we used micro-CT imaging and deep learning to perform automated analyses of 3D image data from 187 honey bee and bumblebee brains. We revealed strong inter-individual variations in total brain size that are consistent across colonies and species, and may underpin behavioural variability central to complex social organisations. In addition, the bumblebee dataset showed a significant level of lateralization in optic and antennal lobes, providing a potential explanation for reported variations in visual and olfactory learning. Our fast, robust and user-friendly approach holds considerable promises for carrying out large-scale quantitative neuroanatomical comparisons across a wider range of animals. Ultimately, this will help address fundamental unresolved questions related to the evolution of animal brains and cognition.

Impact of correlated information on pioneering decisions

Normative models are often used to describe how humans and animals make decisions. These models treat deliberation as the accumulation of uncertain evidence that terminates with a commitment to a choice. When extended to social groups, such models often assume that individuals make independent observations. However, individuals typically gather evidence from common sources, and their observations are rarely independent. Here we ask: For a group of ideal observers who do not exchange information, what is the impact of correlated evidence on decision accuracy? We show that even when agents are identical, correlated evidence causes decision accuracy to depend on temporal decision order. The first decider is less accurate than a lone observer, and early deciders are less accurate than late deciders. These phenomena occur despite the fact that the rational observers use the same decision criterion, so they are equally confident in their decisions. We analyze discrete and macroscopic evidence-gathering models to explain why the first decider is less accurate than a lone observer when evidence is correlated. Pooling the decisions of early deciders using a majority rule does not rescue accuracy results in only a modest accuracy gain. Although we analyze an idealized model, we believe that our analysis offers insights that do not depend on exactly how groups integrate evidence and form decisions.

How honey bees make fast and accurate decisions

Honey bee ecology demands they make both rapid and accurate assessments of which flowers are most likely to offer them nectar or pollen. To understand the mechanisms of honey bee decision-making, we examined their speed and accuracy of both flower acceptance and rejection decisions. We used a controlled flight arena that varied both the likelihood of a stimulus offering reward and punishment and the quality of evidence for stimuli. We found that the sophistication of honey bee decision-making rivalled that reported for primates. Their decisions were sensitive to both the quality and reliability of evidence. Acceptance responses had higher accuracy than rejection responses and were more sensitive to changes in available evidence and reward likelihood. Fast acceptances were more likely to be correct than slower acceptances; a phenomenon also seen in primates and indicative that the evidence threshold for a decision changes dynamically with sampling time. To investigate the minimally sufficient circuitry required for these decision-making capacities, we developed a novel model of decision-making. Our model can be mapped to known pathways in the insect brain and is neurobiologically plausible. Our model proposes a system for robust autonomous decision-making with potential application in robotics.

Dynamic pathogen detection and social feedback shape collective hygiene in ants

Cooperative disease defense emerges as group-level collective behavior, yet how group members make the underlying individual decisions is poorly understood. Using garden ants and fungal pathogens as an experimental model, we derive the rules governing individual ant grooming choices and show how they produce colony-level hygiene. Time-resolved behavioral analysis, pathogen quantification, and probabilistic modeling reveal that ants increase grooming and preferentially target highly-infectious individuals when perceiving high pathogen load, but transiently suppress grooming after having been groomed by nestmates. Ants thus react to both, the infectivity of others and the social feedback they receive on their own contagiousness. While inferred solely from momentary ant decisions, these behavioral rules quantitatively predict hour-long experimental dynamics, and synergistically combine into efficient colony-wide pathogen removal. Our analyses show that noisy individual decisions based on only local, incomplete, yet dynamically-updated information on pathogen threat and social feedback can lead to potent collective disease defense.

The potential underlying mechanisms during learning flights

Hymenopterans, such as bees and wasps, have long fascinated researchers with their sinuous movements at novel locations. These movements, such as loops, arcs, or zigzags, serve to help insects learn their surroundings at important locations. They also allow the insects to explore and orient themselves in their environment. After they gained experience with their environment, the insects fly along optimized paths guided by several guidance strategies, such as path integration, local homing, and route-following, forming a navigational toolkit. Whereas the experienced insects combine these strategies efficiently, the naive insects need to learn about their surroundings and tune the navigational toolkit. We will see that the structure of the movements performed during the learning flights leverages the robustness of certain strategies within a given scale to tune other strategies which are more efficient at a larger scale. Thus, an insect can explore its environment incrementally without risking not finding back essential locations.

Complex preference relationships between native and non-native angiosperms and foraging insect visitors in a suburban greenspace under field and laboratory conditions

The introduction and spread of non-native flora threatens native pollinators and plants. Non-native angiosperms can compete with native plants for pollinators, space, and other resources which can leave native bees without adequate nutritional or nesting resources, particularly specialist species. In the current study, we conducted flower preference experiments through field observations and controlled binary choice tests in an artificial arena to determine the impact of field vs. laboratory methods on flower preferences of native bees for native or non-native flowers within their foraging range. We conducted counts of insect pollinators foraging on the flowers of three plant species in a suburban green belt including one native (Arthropodium strictum) and two non-native (Arctotheca calendula and Taraxacum officinale) plant species. We then collected native halictid bees foraging on each of the three plant species and conducted controlled binary tests to determine their preferences for the flowers of native or non-native plant species. In the field counts, halictid bees visited the native plant significantly more than the non-native species. However, in the behavioural assays when comparing A. strictum vs. A. calendula, Lasioglossum (Chilalictus) lanarium (Family: Halictidae), bees significantly preferred the non-native species, regardless of their foraging history. When comparing A. strictum vs. T. officinale, bees only showed a preference for the non-native flower when it had been collected foraging on the flowers of that plant species immediately prior to the experiment; otherwise, they showed no flower preference. Our results highlight the influence that non-native angiosperms have on native pollinators and we discuss the complexities of the results and the possible reasons for different flower preferences under laboratory and field conditions.

Temporal order judgment of multisensory stimuli in rat and human

We do not fully understand the resolution at which temporal information is processed by different species. Here we employed a temporal order judgment (TOJ) task in rats and humans to test the temporal precision with which these species can detect the order of presentation of simple stimuli across two modalities of vision and audition. Both species reported the order of audiovisual stimuli when they were presented from a central location at a range of stimulus onset asynchronies (SOA)s. While both species could reliably distinguish the temporal order of stimuli based on their sensory content (i.e., the modality label), rats outperformed humans at short SOAs (less than 100 ms) whereas humans outperformed rats at long SOAs (greater than 100 ms). Moreover, rats produced faster responses compared to humans. The reaction time data further revealed key differences in decision process across the two species: at longer SOAs, reaction times increased in rats but decreased in humans. Finally, drift-diffusion modeling allowed us to isolate the contribution of various parameters including evidence accumulation rates, lapse and bias to the sensory decision. Consistent with the psychophysical findings, the model revealed higher temporal sensitivity and a higher lapse rate in rats compared to humans. These findings suggest that these species applied different strategies for making perceptual decisions in the context of a multimodal TOJ task.

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.

Mimicking orchids lure bees from afar with exaggerated ultraviolet signals

Flowers have many traits to appeal to pollinators, including ultraviolet (UV) absorbing markings, which are well-known for attracting bees at close proximity (e.g., <1 m). While striking UV signals have been thought to attract pollinators also from far away, if these signals impact the plant pollinia removal over distance remains unknown. Here, we report the case of the Australian orchid Diuris brumalis, a nonrewarding species, pollinated by bees via mimicry of the rewarding pea plant Daviesia decurrens. When distant from the pea plant, Diuris was hypothesized to enhance pollinator attraction by exaggeratedly mimicking the floral ultraviolet (UV) reflecting patterns of its model. By experimentally modulating floral UV reflectance with a UV screening solution, we quantified the orchid pollinia removal at a variable distance from the model pea plants. We demonstrate that the deceptive orchid Diuris attracts bee pollinators by emphasizing the visual stimuli, which mimic the floral UV signaling of the rewarding model Daviesia. Moreover, the exaggerated UV reflectance of Diuris flowers impacted pollinators' visitation at an optimal distance from Da. decurrens, and the effect decreased when orchids were too close or too far away from the model. Our findings support the hypothesis that salient UV flower signaling plays a functional role in visual floral mimicry, likely exploiting perceptual gaps in bee neural coding, and mediates the plant pollinia removal at much greater spatial scales than previously expected. The ruse works most effectively at an optimal distance of several meters revealing the importance of salient visual stimuli when mimicry is imperfect.

Motivation by reward jointly improves speed and accuracy, whereas task-relevance and meaningful images do not

Visual selection is characterized by a trade-off between speed and accuracy. Speed or accuracy of the selection process can be affected by higher level factors—for example, expecting a reward, obtaining task-relevant information, or seeing an intrinsically relevant target. Recently, motivation by reward has been shown to simultaneously increase speed and accuracy, thus going beyond the speed–accuracy-trade-off. Here, we compared the motivating abilities of monetary reward, task-relevance, and image content to simultaneously increase speed and accuracy. We used a saccadic distraction task that required suppressing a distractor and selecting a target. Across different blocks successful target selection was followed either by (i) a monetary reward, (ii) obtaining task-relevant information, or (iii) seeing the face of a famous person. Each block additionally contained the same number of irrelevant trials lacking these consequences, and participants were informed about the upcoming trial type. We found that postsaccadic vision of a face affected neither speed nor accuracy, suggesting that image content does not affect visual selection via motivational mechanisms. Task relevance increased speed but decreased selection accuracy, an observation compatible with a classical speed–accuracy trade-off. Motivation by reward, however, simultaneously increased response speed and accuracy. Saccades in all conditions deviated away from the distractor, suggesting that the distractor was suppressed, and this deviation was strongest in the reward block. Drift-diffusion modelling revealed that task-relevance affected behavior by affecting decision thresholds, whereas motivation by reward additionally increased the rate of information uptake. The present findings thus show that the three consequences differ in their motivational abilities.

Emphasizing speed or accuracy in an eye-tracking version of the Trail-Making-Test: Towards experimental diagnostics for decomposing executive functions

The Trail-Making-Test (TMT) is one of the most widely used neuropsychological tests for assessing executive functions, the brain functions underlying cognitively controlled thought and action. Obtaining a number of test scores at once, the TMT allows to characterize an assortment of executive functions efficiently. Critically, however, as most test scores are derived from test completion times, the scores only provide a summary measure of various cognitive control processes. To address this problem, we extended the TMT in two ways. First, using a computerized eye-tracking version of the TMT, we added specific eye movement measures that deliver a richer set of data with a higher degree of cognitive process specificity. Second, we included an experimental manipulation of a fundamental executive function, namely participants' ability to emphasize speed or accuracy in task performance. Our study of healthy participants showed that eye movement measures differed between TMT conditions that are usually compared to assess the cognitive control process of alternating between task sets for action control. This demonstrates that eye movement measures are indeed sensitive to executive functions implicated in the TMT. Crucially, comparing performance under cognitive control sets of speed vs. accuracy emphasis revealed which test scores primarily varied due to this manipulation (e.g., trial duration, number of fixations), and which were still more sensitive to other differences between individuals (e.g., fixation duration, saccade amplitude). This provided an experimental construct validation of the test scores by distinguishing scores primarily reflecting the executive function of emphasizing speed vs. accuracy and those independent from it. In sum, both the inclusion of eye movement measures and of the experimental manipulation of executive functions in the TMT enabled a more specific interpretation of the TMT in terms of cognitive functions and mechanisms, which offers more precise diagnoses in clinical applications and basic research.

Lizards lack speed-accuracy trade-offs in a quantitative foraging task when unable to sample the reward

To make decisions, animals gather information from the environment in order to avoid costs (e.g., reduced survival) and increase benefits (e.g., foraging success). When time is limited or information is insufficient, most animals face a speed-accuracy trade-off (SAT) - they have to balance the benefits of making quick decisions against the costs of inaccurate decisions. Here, we investigated the relationship between decision accuracy and decision speed in gidgee skinks (Egernia stokesii) performing a food-based spontaneous quantity discrimination task. Rather than a SAT we found a speed-accuracy alignment; lizards made decisions that were fast and accurate, rather than inaccurate. Furthermore, we found only within-, but no between-individual differences in decision making indicating behavioural plasticity in the absence of individual decision styles. Finally, latency to choice was highly repeatable, more so than choice accuracy. Previous work has shown that learning, the costs of a bad decision and task difficulty frequently result in SATs. The lack of a SAT in our lizards might be a direct consequence of our simple testing methodology which prevented learning by not allowing lizards to consume the chosen quantity. To fully understand how SATs develop, different methodologies that control the costs and benefits of decisions should be compared.

Haste makes waste: shorter time for nest-site assessment leads to higher nest predation in a cavity nester

A fundamental problem for any animal is how to weigh the benefits of making a rapid decision against the costs of making a poor decision, because time for detecting and evaluating all options is often restricted. For nest-site selection in birds, an important cost of a speedy decision would be nest predation, which is a major factor lowering reproductive success. I tested whether shorter time available for assessment of nest sites would lead to a decision with higher probability of nest predation. Where boreal owls (Aegolius funereus) had nested successfully in a box in the previous season, I manipulated nest box availability by offering a dyad of nest boxes. One box (kept or exchanged) was in the original nest tree and one box (new or taken from the original tree) was in a new tree for the season, each box containing either “post-nesting residue” from the successful nesting or new wood shavings. Hence, the owls could assess the risk of nest predation at a familiar site relative to that at a new site. The timing of nest box installation and relocation was such that time for assessment varied among localities, from the whole non-breeding season to just a few days prior to laying in spring. Owls that had had longer time in which to make their assessment and selection were less likely to have their nest predated by pine martens (Martes martes). Boreal owls are non-migratory and probably gained information on the relative safety of the two options by a Bayesian-like updating process in the days, weeks or months before the decision had to be made. A migratory cavity-nester exposed to the same landscape of nest predation would be more time-constrained and forced to rely on the win-stay loose-shift tactic, which underperforms relative to Bayesian-like updating.

Discrimination of edge orientation by bumblebees

Simple feature detectors in the visual system, such as edge-detectors, are likely to underlie even the most complex visual processing, so understanding the limits of these systems is crucial for a fuller understanding of visual processing. We investigated the ability of bumblebees (Bombus terrestris) to discriminate between differently angled edges. In a multiple-choice, “meadow-like” scenario, bumblebees successfully discriminated between angled bars with 7° differences, significantly exceeding the previously reported performance of eastern honeybees (Apis cerana, limit: 15°). Neither the rate at which bees learned, nor their final discrimination performance were affected by the angular orientation of the training bars, indicating a uniform performance across the visual field. Previous work has found that, in dual-choice tests, eastern honeybees cannot reliably discriminate between angles with less than 25° difference, suggesting that performance in discrimination tasks is affected by the training regime, and doesn’t simply reflect the perceptual limitations of the visual system. We used high resolution LCD monitors to investigate bumblebees’ angular resolution in a dual-choice experiment. Bumblebees could still discriminate 7° angle differences under such conditions (exceeding the previously reported limit for Apis mellifera, of 10°, as well as that of A. cerana). Bees eventually reached similar levels of accuracy in the dual-choice experiment as they did under multiple-choice conditions but required longer learning periods. Bumblebees show impressive abilities to discriminate between angled edges, performing better than two previously tested species of honeybee. This high performance may, in turn, support complex visual processing in the bumblebee brain.

Numerosity Categorization by Parity in an Insect and Simple Neural Network

A frequent question as technology improves and becomes increasingly complex, is how we enable technological solutions and models inspired by biological systems. Creating technology based on humans is challenging and costly as human brains and cognition are complex. The honeybee has emerged as a valuable comparative model which exhibits some cognitive-like behaviors. The relative simplicity of the bee brain compared to large mammalian brains enables learning tasks, such as categorization, that can be mimicked by simple neural networks. Categorization of abstract concepts can be essential to how we understand complex information. Odd and even numerical processing is known as a parity task in human mathematical representations, but there appears to be a complete absence of research exploring parity processing in non-human animals. We show that free-flying honeybees can visually acquire the capacity to differentiate between odd and even quantities of 1–10 geometric elements and extrapolate this categorization to the novel numerosities of 11 and 12, revealing that such categorization is accessible to a comparatively simple system. We use this information to construct a neural network consisting of five neurons that can reliably categorize odd and even numerosities up to 40 elements. While the simple neural network is not directly based on the biology of the honeybee brain, it was created to determine if simple systems can replicate the parity categorization results we observed in honeybees. This study thus demonstrates that a task, previously only shown in humans, is accessible to a brain with a comparatively small numbers of neurons. We discuss the possible mechanisms or learning processes allowing bees to perform this categorization task, which range from numeric explanations, such as counting, to pairing elements and memorization of stimuli or patterns. The findings should encourage further testing of parity processing in a wider variety of animals to inform on its potential biological roots, evolutionary drivers, and potential technology innovations for concept processing.

Research Trends in Collaborative Drones

The last decade has seen an explosion of interest in drones-introducing new networking technologies, such as 5G wireless connectivity and cloud computing. The resulting advancements in communication capabilities are already expanding the ubiquitous role of drones as primary solution enablers, from search and rescue missions to information gathering and parcel delivery. Their numerous applications encompass all aspects of everyday life. Our focus is on networked and collaborative drones. The available research literature on this topic is vast. No single survey article could do justice to all critical issues. Our goal in this article is not to cover everything and include everybody but rather to offer a personal perspective on a few selected research topics that might lead to fruitful future investigations that could play an essential role in developing drone technologies. The topics we address include distributed computing with drones for the management of anonymity, countering threats posed by drones, target recognition, navigation under uncertainty, risk avoidance, and cellular technologies. Our approach is selective. Every topic includes an explanation of the problem, a discussion of a potential research methodology, and ideas for future research.

Bees can be trained to identify SARS-CoV-2 infected samples

The COVID-19 pandemic has illustrated the need for the development of fast and reliable testing methods for novel, zoonotic, viral diseases in both humans and animals. Pathologies lead to detectable changes in the volatile organic compound (VOC) profile of animals, which can be monitored, thus allowing the development of a rapid VOC-based test. In the current study, we successfully trained honeybees (Apis mellifera) to identify SARS-CoV-2 infected minks (Neovison vison) thanks to Pavlovian conditioning protocols. The bees can be quickly conditioned to respond specifically to infected mink's odours and could therefore be part of a wider SARS-CoV-2 diagnostic system. We tested two different training protocols to evaluate their performance in terms of learning rate, accuracy and memory retention. We designed a non-invasive rapid test in which multiple bees are tested in parallel on the same samples. This provided reliable results regarding a subject's health status. Using the data from the training experiments, we simulated a diagnostic evaluation trial to predict the potential efficacy of our diagnostic test, which yielded a diagnostic sensitivity of 92% and specificity of 86%. We suggest that a honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods. A honeybee-based diagnostic test might be particularly relevant for remote and developing communities that lack the resources and infrastructure required for mainstream testing methods.

Summary: Honeybees can be quickly trained to identify SARS-CoV2 infected samples. SARS-CoV2 positive sample detection by bees reached a diagnostic sensitivity of 92% and a specificity of 86%. Honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods.

Reconstructing an historical pollination syndrome: keel flowers

Background

Keel flowers are bilaterally symmetrical, pentamerous flowers with three different petal types and reproductive organs enclosed by keel petals; generally there is also connation of floral parts such as stamens and keel petals. In this study, the evolution of keel flowers within the order Fabales is explored to investigate whether the establishment of this flower type within one of the species-rich families, the Fabaceae (Leguminosae), preceded and could have influenced the evolution of keel flowers in the Polygalaceae. We conducted molecular dating, and ancestral area and ancestral state analyses for a phylogeny constructed for 678 taxa using published matK, rbcL and trnL plastid gene regions.

Results

We reveal the temporal and spatial origins of keel flowers and traits associated with pollinators, specifically floral symmetry, the presence or absence of a pentamerous corolla and three distinct petal types, the presence or absence of enclosed reproductive organs, androecium types, inflorescence types, inflorescence size, flower size, plant height and habit. Ancestral area reconstructions show that at the time keel flowers appeared in the Polygaleae, subfamily Papilionoideae of the Fabaceae was already distributed almost globally; at least eight clades of the Papilionoideae had keel flowers with a functional morphology broadly similar to the morphology of the first evolving Polygaleae flowers.

Conclusions

The multiple origins of keel flowers within angiosperms likely represent convergence due to bee specialization, and therefore pollinator pressure. In the case of the Fabales, the first evolving keel flowers of Polygaleae have a functional morphology that corresponds with keel flowers of species of the Papilionoideae already present in the environment. These findings are consistent with the keel-flowered Polygaleae exploiting pollinators of keel-flowered Papilionoideae. The current study is the first to use ancestral reconstructions of traits associated with pollination to demonstrate that the multiple evolutionary origins of the keel flower pollinator syndrome in Fabales are consistent with, though do not prove, mimicry.

Heatwave-Like Events During Development Are Sufficient to Impair Bumblebee Worker Responses to Sensory Stimuli

Heatwaves are increasingly common globally and are known to have detrimental impacts on animal morphology and behaviour. These impacts can be severe, especially if heatwaves occur during development, even on animals that can regulate the temperature of their developing young. The onset and duration of heatwaves are stochastic and therefore may affect all or only part of development. In the heterothermic bumblebee Bombus terrestris, elevated temperatures over the entirety of development cause morphological changes in adults, despite their capability to regulate brood temperature. However, the effects of heatwaves that occur during a short period of development are unclear. We test the impact of elevated developmental temperature during the latter fraction of development on the behaviour and morphology of adult worker B. terrestris. We show that exposure to elevated temperature over a portion of late development is sufficient to impair the initial behavioural responses of workers to various sensory stimuli. Despite this, exposure to elevated temperatures during a period of development did not have any significant impact on body or organ size. The negative effect of elevated developmental temperatures was independent of the exposure time, which lasted from 11–20 days at the end of the workers’ developmental period. Thus, heat stress in bumblebees can manifest without morphological indicators and impair critical behavioural responses to relevant sensory stimuli, even if only present for a short period of time at the end of development. This has important implications for our understanding of deleterious climactic events and how we measure indicators of stress in pollinators.

Interindividual variation in the use of social information during learning in honeybees

Slow-fast differences in cognition among individuals have been proposed to be an outcome of the speed-accuracy trade-off in decision-making. Based on the different costs associated with acquiring information via individual and social learning, we hypothesized that slow-fast cognitive differences would also be tied to the adoption of these different learning modes. Since foragers in honeybee colonies likely have both these information acquisition modes available to them, we chose to test them for interindividual differences in individual and social learning. By measuring performance on a learning task with and without a social cue and quantifying learning rate and maximum accuracy in these two tasks, our results show the existence of a speed-accuracy trade-off in both the individual and the social learning contexts. However, the trade-off is steeper during individual learning, which was slower than social learning but led to higher accuracy. Most importantly, our results also show that bees that attained high accuracy on the individual learning task had low accuracy on the social learning task and vice versa. We discuss how these two information acquisition strategies tie to slow-fast differences in cognitive phenotypes and how they might contribute to division of labour and social behaviour.

Slow-Fast Cognitive Phenotypes and Their Significance for Social Behavior: What Can We Learn From Honeybees?

Cognitive variation is proposed to be the fundamental underlying factor that drives behavioral variation, yet it is still to be fully integrated with the observed variation at other phenotypic levels that has recently been unified under the common pace-of-life framework. This cognitive and the resulting behavioral diversity is especially significant in the context of a social group, the performance of which is a collective outcome of this diversity. In this review, we argue about the utility of classifying cognitive traits along a slow-fast continuum in the larger context of the pace-of-life framework. Using Tinbergen’s explanatory framework for different levels of analyses and drawing from the large body of knowledge about honeybee behavior, we discuss the observed interindividual variation in cognitive traits and slow-fast cognitive phenotypes from an adaptive, evolutionary, mechanistic and developmental perspective. We discuss the challenges in this endeavor and suggest possible next steps in terms of methodological, statistical and theoretical approaches to move the field forward for an integrative understanding of how slow-fast cognitive differences, by influencing collective behavior, impact social evolution.

Innate and learnt color preferences in the common green-eyed white butterfly (Leptophobia aripa): experimental evidence

Background

Learning abilities help animals modify their behaviors based on experience and innate sensory biases to confront environmental unpredictability. In a food acquisition context, the ability to detect, learn, and switch is fundamental in a wide range of insect species facing the ever-changing availability of their floral rewards. Here, we used an experimental approach to address the innate color preferences and learning abilities of the common green-eyed white butterfly (Leptophobia aripa).

Methods

In Experiment 1, we conducted innate preference choice-tests to determine whether butterflies had a strong innate color preference and to evaluate whether color preferences differed depending on the array of colors offered. We faced naïve butterflies to artificial flowers of four colors (quadruple choice-test): yellow, pink, white, and red; their choices were assessed. In Experiment 2, we examined the ability of this butterfly species to associate colors with rewards while exploring if the spectral reflectance value of a flower color can slow or accelerate this behavioral response. Butterflies were first trained to be fed from artificial yellow flowers inserted in a feeder. These were later replaced by artificial flowers with a similar (blue) or very different (white) spectral reflectance range. Each preference test comprised a dual-choice test (yellow vs blue, yellow vs white).

Results

Butterflies showed an innate strong preference for red flowers. Both the number of visits and the time spent probing these flowers were much greater than the pink, white, and yellow color flowers. Butterflies learn to associate colors with sugar rewards. They then learned the newly rewarded colors as quickly and proficiently as if the previously rewarded color was similar in spectral reflectance value; the opposite occurs if the newly rewarded color is very different than the previously rewarded color.

Conclusions

Our findings suggest that common green-eyed white butterflies have good learning abilities. These capabilities may allow them to respond rapidly to different color stimulus.

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

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

Formic acid modulates latency and accuracy of nestmate recognition in carpenter ants

Decision-making processes face the dilemma of being accurate or faster, a phenomenon that has been described as speed-accuracy trade-off in numerous studies on animal behaviour. In social insects, discriminating between colony members and aliens is subject to this trade-off as rapid and accurate rejection of enemies is of primary importance for the maintenance and ecological success of insect societies. Recognition cues distinguishing aliens from nestmates are embedded in the cuticular hydrocarbon (CHC) layer and vary among colonies. In walking carpenter ants, exposure to formic acid (FA), an alarm pheromone, improves the accuracy of nestmate recognition by decreasing both alien acceptance and nestmate rejection. Here, we studied the effect of FA exposure on the spontaneous aggressive mandible opening response (MOR) of harnessed Camponotus aethiops ants presented with either nestmate or alien CHCs. FA modulated both MOR accuracy and the latency to respond to odours of conspecifics. In particular, FA decreased the MOR towards nestmates but increased it towards aliens. Furthermore, FA decreased MOR latency towards aliens but not towards nestmates. As response latency can be used as a proxy of response speed, we conclude that contrary to the prediction of the speed-accuracy trade-off theory, ants did not trade off speed against accuracy in the process of nestmate recognition.

The Sensory and Cognitive Ecology of Nectar Robbing

Animals foraging from flowers must assess their environment and make critical decisions about which patches, plants, and flowers to exploit to obtain limiting resources. The cognitive ecology of plant-pollinator interactions explores not only the complex nature of pollinator foraging behavior and decision making, but also how cognition shapes pollination and plant fitness. Floral visitors sometimes depart from what we think of as typical pollinator behavior and instead exploit floral resources by robbing nectar (bypassing the floral opening and instead consuming nectar through holes or perforations made in floral tissue). The impacts of nectar robbing on plant fitness are well-studied; however, there is considerably less understanding, from the animal’s perspective, about the cognitive processes underlying nectar robbing. Examining nectar robbing from the standpoint of animal cognition is important for understanding the evolution of this behavior and its ecological and evolutionary consequences. In this review, we draw on central concepts of foraging ecology and animal cognition to consider nectar robbing behavior either when individuals use robbing as their only foraging strategy or when they switch between robbing and legitimate foraging. We discuss sensory and cognitive biases, learning, and the role of a variable environment in making decisions about robbing vs. foraging legitimately. We also discuss ways in which an understanding of the cognitive processes involved in nectar robbing can address questions about how plant-robber interactions affect patterns of natural selection and floral evolution. We conclude by highlighting future research directions on the sensory and cognitive ecology of nectar robbing.

The Size of it: Scant Evidence That Flower Size Variation Affects Deception in Intersexual Floral Mimicry

Mutualisms involve cooperation, but also frequently involve conflict. Plant-pollinator mutualisms are no exception. To facilitate animal pollination, flowering plants often offer pollen (their male gametes) as a food reward. Since plants benefit by maximizing pollen export to conspecific flowers, we might expect plants to cheat on pollen rewards. In intersexual floral mimicry, rewarding pollen-bearing male flowers (models) are mimicked by rewardless female flowers (mimics) on the same plant. Pollinators should therefore learn to avoid the unrewarding mimics. Plants might impede such learning by producing phenotypically variable flowers that cause bees to generalize among models and mimics during learning. In this laboratory study, we used partially artificial flowers (artificial petals, live reproductive parts) modeled after Begonia odorata to test whether variation in the size of rewarding male flowers (models) and unrewarding female flowers (mimics) affected how quickly bees learned both to recognize models and to reject mimics. Live unrewarding female flowers have 33% longer petals and have 31% greater surface area than live rewarding male flowers, which bees should easily discriminate. Yet while bees rapidly learned to reduce foraging effort on mimics, learning was not significantly affected by the degree to which flower size varied. Additionally, we found scant evidence that this was a result of bees altering response speed to maintain decision accuracy. Our study failed to provide evidence that flower size variation in intersexual floral mimicry systems exploits pollinator cognition, though we cannot rule out that other floral traits that are variable may be important. Furthermore, we propose that contrary to expectation, phenotypic variability in a Batesian mimicry system may not necessarily have significant effects on whether receivers effectively learn to discriminate models and mimics.

Spontaneous choices for insect-pollinated flower shapes by wild non-eusocial halictid bees

The majority of angiosperms require animal pollination for reproduction, and insects are the dominant group of animal pollinators. Bees are considered one of the most important and abundant insect pollinators. Research into bee behaviour and foraging decisions has typically centred on managed eusocial bee species, including Apis mellifera and Bombus terrestris. Non-eusocial bees are understudied with respect to foraging strategies and decision making, such as flower preferences. Understanding whether there are fundamental foraging strategies and preferences that are features of insect groups can provide key insights into the evolution of flower-pollinator co-evolution. In the current study, Lasioglossum (Chilalictus) lanarium and Lasioglossum (Parasphecodes) sp., two native Australian generalist halictid bees, were tested for flower shape preferences between native insect-pollinated and bird-pollinated flowers. Each bee was presented with achromatic images of either insect-pollinated or bird-pollinated flowers in a circular arena. Both native bee species demonstrated a significant preference for images of insect-pollinated flowers. These preferences are similar to those found in A. mellifera, suggesting that flower shape preference may be a deep-rooted evolutionary occurrence within bees. With growing interest in the sensory capabilities of non-eusocial bees as alternative pollinators, the current study also provides a valuable framework for further behavioural testing of such species.

The Hare and the Hedgehog: Empirical evidence on the relationship between the individual Pace of Life and the speed-accuracy continuum

Against the background of the speed-accuracy trade-off, we explored whether the Pace of Life can be used to identify heterogeneity in the strategy to place more weight on either fast or accurate accomplishments. The Pace of Life approaches an individual's exposure to time and is an intensively studied concept in the evolutionary biology research. Albeit overall rarely, it is increasingly used to understand human behavior and may fulfill many criteria of a personal trait. In a controlled laboratory environment, we measured the participants' Pace of Life, as well as their performance on a real-effort task. In the real-effort task, the participants had to encode words, whereby each word encoded correctly was associated with a monetary reward. We found that individuals with a faster Pace of Life accomplished more tasks in total. At the same time, they were less accurate and made more mistakes (in absolute terms) than those with a slower Pace of Life. Thus, the Pace of Life seems to be useful to identify an individual's stance on the speed-accuracy continuum. In our specific task, placing more weight on speed instead of accuracy paid off: Individuals with a faster Pace of Life were ultimately more successful (with regard to their monetary revenue).

Tracking Changes of Hidden Food: Spatial Pattern Learning in Two Macaw Species

Food availability may vary spatially and temporally within an environment. Efficiency in locating alternative food sources using spatial information (e.g., distribution patterns) may vary according to a species’ diet and habitat specialisation. Hypothetically, more generalist species would learn faster than more specialist species due to being more explorative when changes occur. We tested this hypothesis in two closely related macaw species, differing in their degree of diet and habitat specialisation; the more generalist Great Green Macaw and the more specialist Blue-throated Macaw. We examined their spatial pattern learning performance under predictable temporal and spatial change, using a ‘poke box’ that contained hidden food placed within wells. Each week, the rewarded wells formed two patterns (A and B), which were changed on a mid-week schedule. We found that the two patterns varied in their difficulty. We also found that the more generalist Great Green Macaws took fewer trials to learn the easier pattern and made more mean correct responses in the difficult pattern than the more specialist Blue-throated Macaws, thus supporting our hypothesis. The better learning performance of the Great Green Macaws may be explained by more exploration and trading-off accuracy for speed. These results suggest how variation in diet and habitat specialisation may relate to a species’ ability to adapt to spatial variation in food availability.

Odour Learning Bees Have Longer Foraging Careers Than Non-learners in a Natural Environment

Individual animals allowed the opportunity to learn generally outperform those prevented from learning, yet, within a species the capacity for learning varies markedly. The evolutionary processes that maintain this variation in learning ability are not yet well understood. Several studies demonstrate links between fitness traits and visual learning, but the selection pressures operating on cognitive traits are likely influenced by multiple sensory modalities. In addition to vision, most animals will use a combination of hearing, olfaction (smell), gustation (taste), and touch to gain information about their environment. Some animals demonstrate individual preference for, or enhanced learning performance using certain senses in relation to particular aspects of their behaviour (e.g., foraging), whereas conspecific individuals may show different preferences. By assessing fitness traits in relation to different sensory modalities we will strengthen our understanding of factors driving observed variation in learning ability. We assessed the relationship between the olfactory learning ability of bumble bees (Bombus terrestris) and their foraging performance in their natural environment. We found that bees which failed to learn this odour-reward association had shorter foraging careers; foraging for fewer days and thus provisioning their colonies with fewer resources. This was not due to a reduced propensity to forage, but may have been due to a reduced ability to return to their colony. When comparing among only individuals that did learn, we found that the rate at which floral resources were collected was similar, regardless of how they performed in the olfactory learning task. Our results demonstrate that an ability to learn olfactory cues can have a positive impact of the foraging performance of B. terrestris in a natural environment, but echo findings of earlier studies on visual learning, which suggest that enhanced learning is not necessarily beneficial for bee foragers provisioning their colony.

Flower Color Evolution and the Evidence of Pollinator-Mediated Selection

The evolution of floral traits in animal-pollinated plants involves the interaction between flowers as signal senders and pollinators as signal receivers. Flower colors are very diverse, effect pollinator attraction and flower foraging behavior, and are hypothesized to be shaped through pollinator-mediated selection. However, most of our current understanding of flower color evolution arises from variation between discrete color morphs and completed color shifts accompanying pollinator shifts, while evidence for pollinator-mediated selection on continuous variation in flower colors within populations is still scarce. In this review, we summarize experiments quantifying selection on continuous flower color variation in natural plant populations in the context of pollinator interactions. We found that evidence for significant pollinator-mediated selection is surprisingly limited among existing studies. We propose several possible explanations related to the complexity in the interaction between the colors of flowers and the sensory and cognitive abilities of pollinators as well as pollinator behavioral responses, on the one hand, and the distribution of variation in color phenotypes and fitness, on the other hand. We emphasize currently persisting weaknesses in experimental procedures, and provide some suggestions for how to improve methodology. In conclusion, we encourage future research to bring together plant and animal scientists to jointly forward our understanding of the mechanisms and circumstances of pollinator-mediated selection on flower color.

A model of resource partitioning between foraging bees based on learning

Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in detail, how populations of foragers use resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, the addition of a negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structures, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging. Our study fills a major gap in modelling pollinator behaviour and constitutes a unique tool to guide future experimental programs.

Wild non-eusocial bees learn a colour discrimination task in response to simulated predation events

Despite representing the majority of bee species, non-eusocial bees (e.g. solitary, subsocial, semisocial, and quasisocial species) are comparatively understudied in learning, memory, and cognitive-like behaviour compared to eusocial bees, such as honeybees and bumblebees. Ecologically relevant colour discrimination tasks are well-studied in eusocial bees, and research has shown that a few non-eusocial bee species are also capable of colour learning and long-term memory retention. Australia hosts over 2000 native bee species, most of which are non-eusocial, yet evidence of cognitive-like behaviour and learning abilities under controlled testing conditions is lacking. In the current study, I examine the learning ability of a non-eusocial Australian bee, Lasioglossum (Chilalictus) lanarium, using aversive differential conditioning during a colour discrimination task. L. lanarium learnt to discriminate between salient blue- and yellow-coloured stimuli following training with simulated predation events. This study acts as a bridge between cognitive studies on eusocial and non-social bees and introduces a framework for testing non-eusocial wild bees on elemental visual learning tasks using aversive conditioning. Non-eusocial bee species are far more numerous than eusocial species and contribute to agriculture, economics, and ecosystem services in Australia and across the globe. Thus, it is important to study their capacity to learn flower traits allowing for successful foraging and pollination events, thereby permitting us a better understanding of their role in plant-pollinator interactions.

Automated Operant Conditioning Devices for Fish. Do They Work?

Simple Summary

Automated training devices are commonly used for investigating learning, memory, and other cognitive functions in warm-blood vertebrates, whereas manual training procedures are the standard in fish and other lower vertebrates, thus limiting comparison among species. Here, we directly compared the two different approaches to training in guppies (Poecilia reticulata) by administering numerical discrimination tasks of increasing difficulty. The automated device group showed a much lower performance compared to the traditionally-trained group. We modified some features of the automated device in order to improve its efficiency. Increasing the decision time or inter-trial interval was ineffective, while reducing the cognitive load and allowing subjects to reside in the test tank improved numerical performance. Yet, in no case did subjects match the performance of traditionally-trained subjects, suggesting that small teleosts may be limited in their capacity to cope with operant conditioning devices.

Abstract

The growing use of teleosts in comparative cognition and in neurobiological research has prompted many researchers to develop automated conditioning devices for fish. These techniques can make research less expensive and fully comparable with research on warm-blooded species, in which automated devices have been used for more than a century. Tested with a recently developed automated device, guppies (Poecilia reticulata) easily performed 80 reinforced trials per session, exceeding 80% accuracy in color or shape discrimination tasks after only 3–4 training session, though they exhibit unexpectedly poor performance in numerical discrimination tasks. As several pieces of evidence indicate, guppies possess excellent numerical abilities. In the first part of this study, we benchmarked the automated training device with a standard manual training procedure by administering the same set of tasks, which consisted of numerical discriminations of increasing difficulty. All manually-trained guppies quickly learned the easiest discriminations and a substantial percentage learned the more difficult ones, such as 4 vs. 5 items. No fish trained with the automated conditioning device reached the learning criterion for even the easiest discriminations. In the second part of the study, we introduced a series of modifications to the conditioning chamber and to the procedure in an attempt to improve its efficiency. Increasing the decision time, inter-trial interval, or visibility of the stimuli did not produce an appreciable improvement. Reducing the cognitive load of the task by training subjects first to use the device with shape and color discriminations, significantly improved their numerical performance. Allowing the subjects to reside in the test chamber, which likely reduced the amount of attentional resources subtracted to task execution, also led to an improvement, although in no case did subjects match the performance of fish trained with the standard procedure. Our results highlight limitations in the capacity of small laboratory teleosts to cope with operant conditioning automation that was not observed in laboratory mammals and birds and that currently prevent an easy and straightforward comparison with other vertebrates.

Intraspecific relationships between floral signals and rewards with implications for plant fitness

Within-species variation in traits such as petal size or colour often provides reliable information to pollinators about the rewards offered to them by flowers. In spite of potential disadvantages of allowing pollinators to discriminate against less-rewarding flowers, examples of informative floral signals are diverse in form and widely distributed across plant taxa, apparently having evolved repeatedly in different lineages. Although hypotheses about the adaptive value of providing reward information have been proposed and tested in a few cases, a unified effort to understand the evolutionary mechanisms favouring informative floral signals has yet to emerge. This review describes the diversity of ways in which floral signals can be linked with floral rewards within plant species and discusses the constraints and selective pressures on floral signal-reward relationships. It focuses particularly on how information about floral rewards can influence pollinator behaviour and how those behavioural changes may, in turn, affect plant fitness, selecting either for providing or withholding reward information. Most of the hypotheses about the evolution of floral signal-reward relationships are, as yet, untested, and the review identifies promising research directions for addressing these considerable gaps in knowledge. The advantages and disadvantages of sharing floral reward information with pollinators likely play an important role in floral trait evolution, and opportunities abound to further our understanding of this neglected aspect of floral signalling.

Sex-specific speed-accuracy trade-offs shape neural processing of acoustic signals in a grasshopper

Speed-accuracy trade-offs-being fast at the risk of being wrong-are fundamental to many decisions and natural selection is expected to resolve these trade-offs according to the costs and benefits of behaviour. We here test the prediction that females and males should integrate information from courtship signals differently because they experience different pay-offs along the speed-accuracy continuum. We fitted a neural model of decision making (a drift-diffusion model of integration to threshold) to behavioural data from the grasshopper Chorthippus biguttulus to determine the parameters of temporal integration of acoustic directional information used by male grasshoppers to locate receptive females. The model revealed that males had a low threshold for initiating a turning response, yet a large integration time constant enabled them to continue to gather information when cues were weak. This contrasts with parameters estimated for females of the same species when evaluating potential mates, in which response thresholds were much higher and behaviour was strongly influenced by unattractive stimuli. Our results reveal differences in neural integration consistent with the sex-specific costs of mate search: males often face competition and need to be fast, while females often pay high error costs and need to be deliberate.