What is comparable in comparative cognition?

Judgement bias may be explained by shifts in stimulus response curves

Judgement bias, or 'optimism' and 'pessimism', has been demonstrated across many taxa, yet the cognitive mechanisms underlying this behaviour remain unclear. In an optimism paradigm, animals are trained to an association, and, if given a positive experience, behave more favourably towards 'ambiguous' stimuli. We tested whether this effect could be explained by changes to stimulus response gradients by giving bees a task where their response was tested across a wider gradient of stimuli than typically tested. In line with previous work, we found that bees given a positive experience demonstrated judgement bias, being more likely to visit ambiguous stimuli. However, bees were also less likely to visit a stimulus on the other side of the rewarded stimulus (S+), and as such had a shifted stimulus response curve, showing a diminished peak shift response. In two follow-up experiments we tested the hypothesis that our manipulation altered bees' stimulus response curves via changes to the peak shift response by reducing peak shift in controls. We found that, in support of our hypothesis, elimination of peak shift also eliminated differences between treatments. Our results point towards a cognitive explanation of 'optimistic' behaviour in non-human animals and offer a new paradigm for considering emotion-like states.

Learning with lacertids: Studying the link between ecology and cognition within a comparative framework

Cognition is an essential tool for animals to deal with environmental challenges. Nonetheless, the ecological forces driving the evolution of cognition throughout the animal kingdom remain enigmatic. Large-scale comparative studies on multiple species and cognitive traits have been advanced as the best way to facilitate our understanding of cognitive evolution, but such studies are rare. Here, we tested 13 species of lacertid lizards (Reptilia: Lacertidae) using a battery of cognitive tests measuring inhibitory control, problem-solving, and spatial and reversal learning. Next, we tested the relationship between species' performance and (a) resource availability (temperature and precipitation), habitat complexity (Normalized Difference Vegetation Index), and habitat variability (seasonality) in their natural habitat and (b) their life history (size at hatching and maturity, clutch size, and frequency). Although species differed markedly in their cognitive abilities, such variation was mostly unrelated to their ecology and life history. Yet, species living in more variable environments exhibited lower behavioral flexibility, likely due to energetic constrains in such habitats. Our standardized protocols provide opportunities for collaborative research, allowing increased sample sizes and replication, essential for moving forward in the field of comparative cognition. Follow-up studies could include more detailed measures of habitat structure and look at other potential selective drivers such as predation.

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.

Current Understanding of the "Insight" Phenomenon Across Disciplines

Despite countless anecdotes and the historical significance of insight as a problem solving mechanism, its nature has long remained elusive. The conscious experience of insight is notoriously difficult to trace in non-verbal animals. Although studying insight has presented a significant challenge even to neurobiology and psychology, human neuroimaging studies have cleared the theoretical landscape, as they have begun to reveal the underlying mechanisms. The study of insight in non-human animals has, in contrast, remained limited to innovative adjustments to experimental designs within the classical approach of judging cognitive processes in animals, based on task performance. This leaves no apparent possibility of ending debates from different interpretations emerging from conflicting schools of thought. We believe that comparative cognition has thus much to gain by embracing advances from neuroscience and human cognitive psychology. We will review literature on insight (mainly human) and discuss the consequences of these findings to comparative cognition.

Genome-Wide Association Studies Reveal Neurological Genes for Dog Herding, Predation, Temperament, and Trainability Traits

Genome-wide association study (GWAS) using dog breed standard values as phenotypic measurements is an efficient way to identify genes associated with morphological and behavioral traits. As a result of strong human purposeful selections, several specialized behavioral traits such as herding and hunting have been formed in different modern dog breeds. However, genetic analyses on this topic are rather limited due to the accurate phenotyping difficulty for these complex behavioral traits. Here, 268 dog whole-genome sequences from 130 modern breeds were used to investigate candidate genes underlying dog herding, predation, temperament, and trainability by GWAS. Behavioral phenotypes were obtained from the American Kennel Club based on dog breed standard descriptions or groups (conventional categorization of dog historical roles). The GWAS results of herding behavior (without body size as a covariate) revealed 44 significantly associated sites within five chromosomes. Significantly associated sites on CFA7, 9, 10, and 20 were located either in or near neuropathological or neuronal genes including THOC1, ASIC2, MSRB3, LLPH, RFX8, and CHL1. MSRB3 and CHL1 genes were reported to be associated with dog fear. Since herding is a restricted hunting behavior by removing killing instinct, 36 hounds and 55 herding dogs were used to analyze predation behavior. Three neuronal-related genes (JAK2, MEIS1, and LRRTM4) were revealed as candidates for predation behavior. The significantly associated variant of temperament GWAS was located within ACSS3 gene. The highest associated variant in trainability GWAS is located on CFA22, with no variants detected above the Bonferroni threshold. Since dog behaviors are correlated with body size, we next incorporate body mass as covariates into GWAS; and significant signals around THOC1, MSRB3, LLPH, RFX8, CHL1, LRRTM4, and ACSS3 genes were still detected for dog herding, predation, and temperament behaviors. In humans, these candidate genes are either involved in nervous system development or associated with mental disorders. In conclusion, our results imply that these neuronal or psychiatric genes might be involved in biological processes underlying dog herding, predation, and temperament behavioral traits.

Quantitative abilities of invertebrates: a methodological review

Quantitative abilities are widely recognized to play important roles in several ecological contexts, such as foraging, mate choice, and social interaction. Indeed, such abilities are widespread among vertebrates, in particular mammals, birds, and fish. Recently, there has been an increasing number of studies on the quantitative abilities of invertebrates. In this review, we present the current knowledge in this field, especially focusing on the ecological relevance of the capacity to process quantitative information, the similarities with vertebrates, and the different methods adopted to investigate this cognitive skill. The literature argues, beyond methodological differences, a substantial similarity between the quantitative abilities of invertebrates and those of vertebrates, supporting the idea that similar ecological pressures may determine the emergence of similar cognitive systems even in distantly related species.

Nesting ecology does not explain slow-fast cognitive differences among honeybee species

Slow-fast behavioral and life history differences have been tied to slow-fast variation in cognition that is part of the general speed-accuracy tradeoff. While there is growing evidence for such cognitive variation and its association with behavior and life history at the intraspecific level, it is unknown if a similar relationship extends to the interspecific level. Since interspecific differences in cognition have been shown to be a function of ecology and life history, such differences should be reflected in multiple traits that comprise the slow-fast cognitive axis. In this study, by measuring multiple cognitive traits in individuals, we tested for differences in the cognitive phenotype among four honeybee species, which differ in their behavior and life history in a manner that is associated with differences in their nesting ecology. Our results indicate that a set of cognitive traits consistently covary within each species, resulting in slow and fast cognitive phenotypes that largely meet the predictions of the speed-accuracy tradeoff. We also find that the four species group into two distinct clusters on a slow-fast cognitive axis, although their positions do not align with the known differences in their life history and nesting ecology. We instead find that cognitive differences among the four species are correlated with their brain size. We discuss the possible implications of these results for the role of ecology on slow-fast cognitive differences and the evolution of cognition.

Non-numerical strategies used by bees to solve numerical cognition tasks

We examined how bees solve a visual discrimination task with stimuli commonly used in numerical cognition studies. Bees performed well on the task, but additional tests showed that they had learned continuous (non-numerical) cues. A network model using biologically plausible visual feature filtering and a simple associative rule was capable of learning the task using only continuous cues inherent in the training stimuli, with no numerical processing. This model was also able to reproduce behaviours that have been considered in other studies indicative of numerical cognition. Our results support the idea that a sense of magnitude may be more primitive and basic than a sense of number. Our findings highlight how problematic inadvertent continuous cues can be for studies of numerical cognition. This remains a deep issue within the field that requires increased vigilance and cleverness from the experimenter. We suggest ways of better assessing numerical cognition in non-speaking animals, including assessing the use of all alternative cues in one test, using cross-modal cues, analysing behavioural responses to detect underlying strategies, and finding the neural substrate.

Jumping spiders: An exceptional group for comparative cognition studies

Several non-mutually exclusive hypotheses have been proposed to explain the evolution of cognition in animals. Broadly, these hypotheses fall under two categories: those that pertain to the selective pressures exerted either by sociality or by the ecological niche in which animals live. We review these ideas and then discuss why the highly visual jumping spiders (Salticidae) are excellent models for investigating how cognitive ability evolves. With few exceptions, these behaviorally complex spiders are non-social, making them ideal candidates to explore ideas pertaining to selection based on habitat complexity and selection based on predatory behavior (foraging niche hypotheses). With the exception of Antarctica, salticids are found in all habitats on Earth, ranging from very complex to barren and simple. While many species are generalist predators, a minority also have specialized predatory behavior and prey specialization on dangerous prey, which has been proposed as an explanation for advanced cognitive ability. As this large group has a diversity of habitats in which it lives, diverse predatory behavior, as well as some "social" species, we argue that salticids are ideal candidates for comparative studies to explore the myriad selection factors acting upon a group well known for their cognitive prowess, despite having miniature brains.

The Rules of Attraction: The Necessary Role of Animal Cognition in Explaining Conservation Failures and Successes

Integrating knowledge and principles of animal behavior into wildlife conservation and management has led to some concrete successes but has failed to improve conservation outcomes in other cases. Many conservation interventions involve attempts to either attract or repel animals, which we refer to as approach/avoidance issues. These attempts can be reframed as issues of manipulating the decisions animals make, which are driven by their perceptual abilities and attentional biases, as well as the value animals attribute to current stimuli and past learned experiences. These processes all fall under the umbrella of animal cognition. Here, we highlight rules that emerge when considering approach/avoidance conservation issues through the lens of cognitive-based management. For each rule, we review relevant conservation successes and failures to better predict the conditions in which behavior can be manipulated, and we suggest how to avoid future failures.

Integrative Comparative Cognition: Can Neurobiology and Neurogenomics Inform Comparative Analyses of Cognitive Phenotype?

A long-standing question in animal behavior is what are the patterns and processes that shape the evolution of cognition? One effective way to address this question is to study cognitive abilities in a broad spectrum of animals. While comparative psychologists have traditionally focused on a narrow range of organisms, today they may work with any number of species, from frogs to birds or bees. This broader range of study species has greatly enriched our understanding of the diversity of cognitive processes among animals. Yet, this diversity has highlighted the fundamental challenge of comparing cognitive processes across animals. An analysis of the neural and molecular mechanisms of cognition may be necessary to solve this problem. The goal of our symposium was to bring together speakers studying a range of species to gain a broadly integrative perspective on cognition while at the same time considering the potentially important role of neurobiology and genomics in addressing the difficult problem of comparing cognition across species. For example, work by MaBouDi et al. indicates that neural constraints on computing power may impact the cognitive processes underlying numerical discrimination in bees. A presentation by Lara LaDage demonstrated how neurobiology can be used to better understand cognition and its evolution in reptiles while Edwards et al. identify the cerebellum as potentially important in the performance of the complex process of nest building. We see that molecular approaches highlight the contributions of the prefrontal cortex and hippocampus to cognitive phenotype across vertebrates while, at the same time, identifying the genes and cellular processes that may contribute to evolution of cognition. The potentially important role of neurogenesis and synaptic plasticity emerge clearly from such studies. Still unanswered is the question of whether molecular tools will contribute to our ability to discriminate convergent/parallel evolution from homology in the evolution of cognitive phenotype.

Ants resort to heuristics when facing relational-learning tasks they cannot solve

We humans sort the world around us into conceptual groups, such as 'the same' or 'different', which facilitates many cognitive tasks. Applying such abstract concepts can improve problem-solving success and is therefore worth the cognitive investment. In this study, we investigated whether ants (Lasius niger) can learn the relational rule of 'the same' or 'different' by training them in an odour match-to-sample test over 48 visits. While ants in the 'different' treatment improved significantly over time, reaching around 65% correct decisions, ants in the 'same' treatment did not. Ants did not seem able to learn such abstract relational concepts, but instead created their own individual strategy to try to solve the problem: some ants decided to 'always go left', others preferred a 'go to the more salient cue' heuristic which systematically biased their decisions. These heuristics even occasionally lowered the success rate in the experiment below chance, indicating that following any rule may be more desirable then making truly random decisions. As the finding that ants resort to heuristics when facing hard-to-solve decisions was discovered post-hoc, we strongly encourage other researchers to ask whether employing heuristics in the face of challenging tasks is a widespread phenomenon in insects.

Bumblebees Learn a Relational Rule but Switch to a Win-Stay/Lose-Switch Heuristic After Extensive Training

Mapping animal performance in a behavioral task to underlying cognitive mechanisms and strategies is rarely straightforward, since a task may be solvable in more than one manner. Here, we show that bumblebees perform well on a concept-based visual discrimination task but spontaneously switch from a concept-based solution to a simpler heuristic with extended training, all while continually increasing performance. Bumblebees were trained in an arena to find rewards on displays with shapes of different sizes where they could not use low-level visual cues. One group of bees was rewarded at displays with larger shapes and another group at displays with smaller shapes. Analysis of total choices shows bees increased their performance over 30 bouts to above chance. However, analyses of first and sequential choices suggest that after approximately 20 bouts, bumblebees changed to a win-stay/lose-switch strategy. Comparing bees' behavior to a probabilistic model based on a win-stay/lose-switch strategy further supports the idea that bees changed strategies with extensive training. Analyses of unrewarded tests indicate that bumblebees learned and retained the concept of relative size even after they had already switched to a win-stay, lost-shift strategy. We propose that the reason for this strategy switching may be due to cognitive flexibility and efficiency.

Breed Differences in Dog Cognition Associated with Brain-Expressed Genes and Neurological Functions

Given their remarkable phenotypic diversity, dogs present a unique opportunity for investigating the genetic bases of cognitive and behavioral traits. Our previous work demonstrated that genetic relatedness among breeds accounts for a substantial portion of variation in dog cognition. Here, we investigated the genetic architecture of breed differences in cognition, seeking to identify genes that contribute to variation in cognitive phenotypes. To do so, we combined cognitive data from the citizen science project Dognition.com with published breed-average genetic polymorphism data, resulting in a dataset of 1654 individuals with cognitive phenotypes representing 49 breeds. We conducted a breed-average genome-wide association study to identify specific polymorphisms associated with breed differences in inhibitory control, communication, memory, and physical reasoning. We found five single nucleotide polymorphisms (SNPs) that reached genome-wide significance after Bonferroni correction, located in EML1, OR52E2, HS3ST5, a U6 spliceosomal RNA, and a long noncoding RNA. When we combined results across multiple SNPs within the same gene, we identified 188 genes implicated in breed differences in cognition. This gene set included more genes than expected by chance that were (1) differentially expressed in brain tissue and (2) involved in nervous system functions including peripheral nervous system development, Wnt signaling, presynapse assembly, and synaptic vesicle exocytosis. These results advance our understanding of the genetic underpinnings of complex cognitive phenotypes and identify specific genetic variants for further research.

Insect Neurobiology: Divergent Neural Computations in Predatory Insects

A comparative approach to neuroscience can greatly increase our understanding of how mechanisms map onto behaviour. A new study comparing two predatory insects demonstrates how neurons that are homologous can nonetheless mediate different computations and behaviour.

Replications in Comparative Cognition: What Should We Expect and How Can We Improve?

Direct replication studies follow an original experiment's methods as closely as possible. They provide information about the reliability and validity of an original study's findings. The present paper asks what comparative cognition should expect if its studies were directly replicated, and how researchers can use this information to improve the reliability of future research. Because published effect sizes are likely overestimated, comparative cognition researchers should not expect findings with p-values just below the significance level to replicate consistently. Nevertheless, there are several statistical and design features that can help researchers identify reliable research. However, researchers should not simply aim for maximum replicability when planning studies; comparative cognition faces strong replicability-validity and replicability-resource trade-offs. Next, the paper argues that it may not even be possible to perform truly direct replication studies in comparative cognition because of: 1) a lack of access to the species of interest; 2) real differences in animal behavior across sites; and 3) sample size constraints producing very uncertain statistical estimates, meaning that it will often not be possible to detect statistical differences between original and replication studies. These three reasons suggest that many claims in the comparative cognition literature are practically unfalsifiable, and this presents a challenge for cumulative science in comparative cognition. To address this challenge, comparative cognition can begin to formally assess the replicability of its findings, improve its statistical thinking and explore new infrastructures that can help to form a field that can create and combine the data necessary to understand how cognition evolves.

Interactive rhythms across species: the evolutionary biology of animal chorusing and turn-taking

The study of human language is progressively moving toward comparative and interactive frameworks, extending the concept of turn-taking to animal communication. While such an endeavor will help us understand the interactive origins of language, any theoretical account for cross-species turn-taking should consider three key points. First, animal turn-taking must incorporate biological studies on animal chorusing, namely how different species coordinate their signals over time. Second, while concepts employed in human communication and turn-taking, such as intentionality, are still debated in animal behavior, lower level mechanisms with clear neurobiological bases can explain much of animal interactive behavior. Third, social behavior, interactivity, and cooperation can be orthogonal, and the alternation of animal signals need not be cooperative. Considering turn-taking a subset of chorusing in the rhythmic dimension may avoid overinterpretation and enhance the comparability of future empirical work.

Variation in sexual brain size dimorphism over the breeding cycle in the three-spined stickleback

Snapshot analyses have demonstrated dramatic intraspecific variation in the degree of brain sexual size dimorphism (SSD). Although brain SSD is believed to be generated by the sex-specific cognitive demands of reproduction, the relative roles of developmental and population-specific contributions to variation in brain SSD remain little studied. Using a common garden experiment, we tested for sex-specific changes in brain anatomy over the breeding cycle in three-spined stickleback (Gasterosteus aculeatus) sampled from four locations in northern Europe. We found that the male brain increased in size (ca. 24%) significantly more than the female brain towards breeding, and that the resulting brain SSD was similar (ca. 20%) for all populations over the breeding cycle. Our findings support the notion that the stickleback brain is highly plastic and changes over the breeding cycle, especially in males, likely as an adaptive response to the cognitive demands of reproduction (e.g. nest construction and parental care). The results also provide evidence to suggest that breeding-related changes in brain size may be the reason for the widely varying estimates of brain SSD across studies of this species, cautioning against interpreting brain size measurements from a single time point as fixed/static.

Insect-Inspired Sequential Inspection Strategy Enables an Artificial Network of Four Neurons to Estimate Numerosity

Varying levels of numerical cognition have been found in several animal species. Bees, in particular, have been argued to be able to count up to four items and solve complex numerical tasks. Here we present an exceedingly simple neural circuit that, when provided with the actual visual input that the bee is receiving while carrying out the task, can make reliable estimates on the number of items in the display. Thus we suggest that the elegance of numerical problem solving in bees might not lie in the formation of numerical concepts (such as “more,” “less,” or “zero”), but in the use of specific flight movements to scan targets, which streamlines the visual input and so renders the task of counting computationally inexpensive. Careful examination of the actual inspection strategies used by animals might reveal that animals often employ active scanning behaviors as shortcuts to simplify complex visual pattern discrimination tasks.

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Small-brained animals such as bees can solve counting tasks

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Exceedingly small neural circuits can mediate numerosity estimations

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The method requires a sequential inspection strategy to generate the visual input

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Active scanning behavior is suggested to play a role in complex cognitive tasks

High-Speed Videography Reveals How Honeybees Can Turn a Spatial Concept Learning Task Into a Simple Discrimination Task by Stereotyped Flight Movements and Sequential Inspection of Pattern Elements

Honey bees display remarkable visual learning abilities, providing insights regarding visual information processing in a miniature brain. It was discovered that bees can solve a task that is generally viewed as spatial concept learning in primates, specifically the concept of “above” and “below.” In these works, two pairs of visual stimuli were shown in the two arms of a Y-maze. Each arm displayed a “referent” shape (e.g., a cross, or a horizontal line) and a second geometric shape that appeared either above or below the referent. Bees learning the “concept of aboveness” had to choose the arm of the Y-maze in which a shape–any shape–occurred above the referent, while those learning the “concept of belowness” had to pick the arm in which there was an arbitrary item beneath the referent. Here, we explore the sequential decision-making process that allows bees to solve this task by analyzing their flight trajectories inside the Y-maze. Over 368 h of high-speed video footage of the bees' choice strategies were analyzed in detail. In our experiments, many bees failed the task, and, with the possible exception of a single forager, bees as a group failed to reach significance in picking the correct arm from the decision chamber of the maze. Of those bees that succeeded in choosing correctly, most required a close-up inspection of the targets. These bees typically employed a close-up scan of only the bottom part of the pattern before taking the decision of landing on a feeder. When rejecting incorrect feeders, they repeatedly scanned the pattern features, but were still, on average, faster at completing the task than the non-leaners. This shows that solving a concept learning task could actually be mediated by turning it into a more manageable discrimination task by some animals, although one individual in this study appeared to have gained the ability (by the end of the training) to solve the task in a manner predicted by concept learning.

Cognitive Aspects of Comb-Building in the Honeybee?

The wax-made comb of the honeybee is a masterpiece of animal architecture. The highly regular, double-sided hexagonal structure is a near-optimal solution to storing food and housing larvae, economizing on building materials and space. Elaborate though they may seem, such animal constructions are often viewed as the result of 'just instinct,' governed by inflexible, pre-programmed, innate behavior routines. An inspection of the literature on honeybee comb construction, however, reveals a different picture. Workers have to learn, at least in part, certain elements of the technique, and there is considerable flexibility in terms of how the shape of the comb and its gradual manufacture is tailored to the circumstances, especially the available space. Moreover, we explore the 2-century old and now largely forgotten work by François Huber, where glass screens were placed between an expanding comb construction and the intended target wall. Bees took corrective action before reaching the glass obstacle, and altered the ongoing construction so as to reach the nearest wooden wall. Though further experiments will be necessary, these results suggest a form of spatial planning skills. We discuss these findings in the context of what is now known about insect cognition, and ask if it is possible that the production of hexagonal wax combs is the result of behavioral heuristics where a complex structure emerges as the result of simple behavioral rules applied by each individual, or whether prospective cognition might be involved.

Evolving understanding of nervous system evolution

In this Guest Editorial, Jeremy Niven and Lars Chittka introduce our special issue on the evolution of nervous systems.

Is behavioural flexibility evidence of cognitive complexity? How evolution can inform comparative cognition

Behavioural flexibility is often treated as the gold standard of evidence for more sophisticated or complex forms of animal cognition, such as planning, metacognition and mindreading. However, the evidential link between behavioural flexibility and complex cognition has not been explicitly or systematically defended. Such a defence is particularly pressing because observed flexible behaviours can frequently be explained by putatively simpler cognitive mechanisms. This leaves complex cognition hypotheses open to 'deflationary' challenges that are accorded greater evidential weight precisely because they offer putatively simpler explanations of equal explanatory power. This paper challenges the blanket preference for simpler explanations, and shows that once this preference is dispensed with, and the full spectrum of evidence-including evolutionary, ecological and phylogenetic data-is accorded its proper weight, an argument in support of the prevailing assumption that behavioural flexibility can serve as evidence for complex cognitive mechanisms may begin to take shape. An adaptive model of cognitive-behavioural evolution is proposed, according to which the existence of convergent trait-environment clusters in phylogenetically disparate lineages may serve as evidence for the same trait-environment clusters in other lineages. This, in turn, could permit inferences of cognitive complexity in cases of experimental underdetermination, thereby placing the common view that behavioural flexibility can serve as evidence for complex cognition on firmer grounds.

Studying small brains to understand the building blocks of cognition

Cognition encompasses a range of higher-order mental processes, such as attention, working memory, and model-based decision-making. These processes are thought to involve the dynamic interaction of multiple central brain regions. A mechanistic understanding of such computations requires not only monitoring and manipulating specific neural populations during behavior, but also knowing the connectivity of the underlying circuitry. These goals are experimentally challenging in mammals, but are feasible in numerically simpler insect brains. In Drosophila melanogaster in particular, genetic tools enable precisely targeted physiology and optogenetics in actively behaving animals. In this article we discuss how these advantages are increasingly being leveraged to study abstract neural representations and sensorimotor computations that may be relevant for cognition in both insects and mammals.

More than one way to see it: Individual heuristics in avian visual computation

Comparative pattern learning experiments investigate how different species find regularities in sensory input, providing insights into cognitive processing in humans and other animals. Past research has focused either on one species' ability to process pattern classes or different species' performance in recognizing the same pattern, with little attention to individual and species-specific heuristics and decision strategies. We trained and tested two bird species, pigeons (Columba livia) and kea (Nestor notabilis, a parrot species), on visual patterns using touch-screen technology. Patterns were composed of several abstract elements and had varying degrees of structural complexity. We developed a model selection paradigm, based on regular expressions, that allowed us to reconstruct the specific decision strategies and cognitive heuristics adopted by a given individual in our task. Individual birds showed considerable differences in the number, type and heterogeneity of heuristic strategies adopted. Birds' choices also exhibited consistent species-level differences. Kea adopted effective heuristic strategies, based on matching learned bigrams to stimulus edges. Individual pigeons, in contrast, adopted an idiosyncratic mix of strategies that included local transition probabilities and global string similarity. Although performance was above chance and quite high for kea, no individual of either species provided clear evidence of learning exactly the rule used to generate the training stimuli. Our results show that similar behavioral outcomes can be achieved using dramatically different strategies and highlight the dangers of combining multiple individuals in a group analysis. These findings, and our general approach, have implications for the design of future pattern learning experiments, and the interpretation of comparative cognition research more generally.

How do infants recognize joint attention?

The emergence of joint attention is still a matter of vigorous debate. It involves diverse hypotheses ranging from innate modules dedicated to intention reading to more neuro-constructivist approaches. The aim of this study was to assess whether 12-month-old infants are able to recognize a "joint attention" situation when observing such a social interaction. Using a violation-of-expectation paradigm, we habituated infants to a "joint attention" video and then compared their looking time durations between "divergent attention" videos and "joint attention" ones using a 2 (familiar or novel perceptual component)×2 (familiar or novel conceptual component) factorial design. These results were enriched with measures of pupil dilation, which are considered to be reliable measures of cognitive load. Infants looked longer at test events that involved novel speaker and divergent attention but no changes in infants' pupil dilation were observed in any conditions. Although looking time data suggest that infants may appreciate discrepancies from expectations related to joint attention behavior, in the absence of clear evidence from pupillometry, the results show no demonstration of understanding of joint attention, even at a tacit level. Our results suggest that infants may be sensitive to relevant perceptual variables in joint attention situations, which would help scaffold social cognitive development. This study supports a gradual, learning interpretation of how infants come to recognize, understand, and participate in joint attention.

Insect-inspired navigation algorithm for an aerial agent using satellite imagery

Humans have long marveled at the ability of animals to navigate swiftly, accurately, and across long distances. Many mechanisms have been proposed for how animals acquire, store, and retrace learned routes, yet many of these hypotheses appear incongruent with behavioral observations and the animals' neural constraints. The "Navigation by Scene Familiarity Hypothesis" proposed originally for insect navigation offers an elegantly simple solution for retracing previously experienced routes without the need for complex neural architectures and memory retrieval mechanisms. This hypothesis proposes that an animal can return to a target location by simply moving toward the most familiar scene at any given point. Proof of concept simulations have used computer-generated ant's-eye views of the world, but here we test the ability of scene familiarity algorithms to navigate training routes across satellite images extracted from Google Maps. We find that Google satellite images are so rich in visual information that familiarity algorithms can be used to retrace even tortuous routes with low-resolution sensors. We discuss the implications of these findings not only for animal navigation but also for the potential development of visual augmentation systems and robot guidance algorithms.

Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees

Network-based diffusion analysis demonstrates that a novel tool-use behavior, “moss-sponging”, spread via social learning in a wild East-African chimpanzee community.

Social network analysis methods have made it possible to test whether novel behaviors in animals spread through individual or social learning. To date, however, social network analysis of wild populations has been limited to static models that cannot precisely reflect the dynamics of learning, for instance, the impact of multiple observations across time. Here, we present a novel dynamic version of network analysis that is capable of capturing temporal aspects of acquisition—that is, how successive observations by an individual influence its acquisition of the novel behavior. We apply this model to studying the spread of two novel tool-use variants, “moss-sponging” and “leaf-sponge re-use,” in the Sonso chimpanzee community of Budongo Forest, Uganda. Chimpanzees are widely considered the most “cultural” of all animal species, with 39 behaviors suspected as socially acquired, most of them in the domain of tool-use. The cultural hypothesis is supported by experimental data from captive chimpanzees and a range of observational data. However, for wild groups, there is still no direct experimental evidence for social learning, nor has there been any direct observation of social diffusion of behavioral innovations. Here, we tested both a static and a dynamic network model and found strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, were significantly better explained by social than individual learning. The most conservative estimate of social transmission accounted for 85% of observed events, with an estimated 15-fold increase in learning rate for each time a novice observed an informed individual moss-sponging. We conclude that group-specific behavioral variants in wild chimpanzees can be socially learned, adding to the evidence that this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans.

Chimpanzees are widely considered as the most “cultural” of all animals, despite the lack of direct evidence for the spread of novel behaviors through social learning in the wild. Here, we present a novel, dynamic network-based diffusion analysis to describe the acquisition patterns of novel tool-use behavior in the Sonso chimpanzee community of Budongo Forest, Uganda. We find strong evidence for social transmission of “moss-sponging” (the production of a sponge consisting of moss) along the innovators' social network, demonstrating that wild chimpanzees learn novel tool-use behaviors from each other and supporting the more general claim that some of the observed behavioral diversity in wild chimpanzees should be interpreted as “cultural.” Our model also estimated that, for each new observation, naïve individuals enhanced their chances of developing moss-sponging by a factor of 15. We conclude that group-specific behavioral variants can be socially learned in wild chimpanzees, addressing an important critique of the claim of culture in our closest relatives.

Contrasting styles in cognition and behaviour in bumblebees and honeybees

Bumblebees and honeybees have been the subjects of a great deal of recent research in animal cognition. Many of the major topics in cognition, including memory, attention, concept learning, numerosity, spatial cognition, timing, social learning, and metacognition have been examined in bumblebees, honeybees, or both. Although bumblebees and honeybees are very closely related, they also differ in important ways, including social organization, development, and foraging behaviour. We examine whether differences between bumblebees and honeybees in cognitive processes are related to differences in their natural history and behaviour. There are differences in some cognitive traits, such as serial reversal learning and matching-to-sample, that appear related to differences between bumblebees and honeybees in foraging and social behaviour. Other cognitive processes, such as numerosity, appear to be very similar. Despite the wealth of information that is available on some aspects of bumblebee and honeybee cognition and behaviour, there are relatively few instances, however, in which adequate data exist to make direct comparisons. We highlight a number of phenomena, including concept learning, spatial cognition, timing, and metacognition, for which targeted comparative research may reveal unexpected adaptive variation in cognitive processes in these complex animals. This article is part of a Special Issue entitled: In Honor of Jerry Hogan.

An arms race between producers and scroungers can drive the evolution of social cognition

The "social intelligence hypothesis" states that the need to cope with complexities of social life has driven the evolution of advanced cognitive abilities. It is usually invoked in the context of challenges arising from complex intragroup structures, hierarchies, and alliances. However, a fundamental aspect of group living remains largely unexplored as a driving force in cognitive evolution: the competition between individuals searching for resources (producers) and conspecifics that parasitize their findings (scroungers). In populations of social foragers, abilities that enable scroungers to steal by outsmarting producers, and those allowing producers to prevent theft by outsmarting scroungers, are likely to be beneficial and may fuel a cognitive arms race. Using analytical theory and agent-based simulations, we present a general model for such a race that is driven by the producer-scrounger game and show that the race's plausibility is dramatically affected by the nature of the evolving abilities. If scrounging and scrounging avoidance rely on separate, strategy-specific cognitive abilities, arms races are short-lived and have a limited effect on cognition. However, general cognitive abilities that facilitate both scrounging and scrounging avoidance undergo stable, long-lasting arms races. Thus, ubiquitous foraging interactions may lead to the evolution of general cognitive abilities in social animals, without the requirement of complex intragroup structures.

Can Bees See at a Glance?

Primates can analyse visual scenes extremely rapidly, making accurate decisions for presentation times of only 20ms. We asked if bumblebees, despite having potentially more limited processing power, could similarly detect and discriminate visual patterns presented for durations of 100ms or less. Bumblebees detected stimuli and discriminated between differently oriented and coloured stimuli even when presented as briefly as 20ms but failed to identify ecologically relevant shapes (predatory spiders on flowers) even when presented for 100ms. This suggests a profound difference between primate and insect visual processing, so that while primates can capture entire visual scenes 'at a glance', insects might have to rely on continuous online sampling of the world around them, using a process of active vision which requires longer integration times.

The origins of pedagogy: developmental and evolutionary perspectives

The question of whether and how information is actively transferred from knowledgeable to ignorant individuals has received much attention in psychology and evolutionary biology. Research in these fields has proceeded largely independently, with studies of nonhuman animals focusing on knowledgeable individuals and whether or not they meet a functional definition of teaching, while studies of children focus on the learner's assumptions and inferences. We argue that a comprehensive theory of teaching will benefit from integrating perspectives and empirical phenomena from evolutionary and developmental disciplines. In this review, we identify cases of seemingly purposeful information transfer (i.e. teaching) in human and nonhuman animals, discuss what is known about the cognitive processes that support teaching in different species, and highlight ways in which each discipline might be informed by extant theories and empirical tools from the other.

An introduction to comparative evolutionary psychology

Previously we (Vonk and Shackelford, 2012, in press) proposed an integration of comparative psychology and evolutionary psychology into a new field of "comparative evolutionary psychology." This integrative discipline incorporates principles from ethology, ecology, biology, anthropology, and psychology, broadly defined. We present in this special issue a collection of original empirical and theoretical review articles in which leading researchers propose ways to successfully integrate comparative and evolutionary approaches within their particular areas of study. We showcase the key contributions of these articles and highlight several empirical and theoretical challenges, as well as key future directions, for comparative evolutionary psychology.

The Origins of Pedagogy: Developmental and Evolutionary Perspectives

The question of whether and how information is actively transferred from knowledgeable to ignorant individuals has received much attention in psychology and evolutionary biology. Research in these fields has proceeded largely independently, with studies of nonhuman animals focusing on knowledgeable individuals and whether or not they meet a functional definition of teaching, while studies of children focus on the learner's assumptions and inferences. We argue that a comprehensive theory of teaching will benefit from integrating perspectives and empirical phenomena from evolutionary and developmental disciplines. In this review, we identify cases of seemingly purposeful information transfer (i. e. teaching) in human and nonhuman animals, discuss what is known about the cognitive processes that support teaching in different species, and highlight ways in which each discipline might be informed by extant theories and empirical tools from the other.

Reconsidering the evolution of brain, cognition, and behavior in birds and mammals

Despite decades of research, some of the most basic issues concerning the extraordinarily complex brains and behavior of birds and mammals, such as the factors responsible for the diversity of brain size and composition, are still unclear. This is partly due to a number of conceptual and methodological issues. Determining species and group differences in brain composition requires accounting for the presence of taxon-cerebrotypes and the use of precise statistical methods. The role of allometry in determining brain variables should be revised. In particular, bird and mammalian brains appear to have evolved in response to a variety of selective pressures influencing both brain size and composition. “Brain” and “cognition” are indeed meta-variables, made up of the variables that are ecologically relevant and evolutionarily selected. External indicators of species differences in cognition and behavior are limited by the complexity of these differences. Indeed, behavioral differences between species and individuals are caused by cognitive and affective components. Although intra-species variability forms the basis of species evolution, some of the mechanisms underlying individual differences in brain and behavior appear to differ from those between species. While many issues have persisted over the years because of a lack of appropriate data or methods to test them; several fallacies, particularly those related to the human brain, reflect scientists' preconceptions. The theoretical framework on the evolution of brain, cognition, and behavior in birds and mammals should be reconsidered with these biases in mind.

An Introduction to Comparative Evolutionary Psychology

Previously we ( Vonk and Shackelford, 2012 , in press) proposed an integration of comparative psychology and evolutionary psychology into a new field of “comparative evolutionary psychology.” This integrative discipline incorporates principles from ethology, ecology, biology, anthropology, and psychology, broadly defined. We present in this special issue a collection of original empirical and theoretical review articles in which leading researchers propose ways to successfully integrate comparative and evolutionary approaches within their particular areas of study. We showcase the key contributions of these articles and highlight several empirical and theoretical challenges, as well as key future directions, for comparative evolutionary psychology.

Numerical cognition in bees and other insects

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

Cognition in insects

A traditional view of cognition is that it involves an internal process that represents, tracks or predicts an external process. This is not a general characteristic of all complex neural processing or feedback control, but rather implies specific forms of processing giving rise to specific behavioural capabilities. In this paper, I will review the evidence for such capabilities in insect navigation and learning. Do insects know where they are, or do they only know what to do? Do they learn what stimuli mean, or do they only learn how to behave?

Biological and artificial cognition: what can we learn about mechanisms by modelling physical cognition problems using artificial intelligence planning techniques?

Do we fully understand the structure of the problems we present to our subjects in experiments on animal cognition, and the information required to solve them? While we currently have a good understanding of the behavioural and neurobiological mechanisms underlying associative learning processes, we understand much less about the mechanisms underlying more complex forms of cognition in animals. In this study, we present a proposal for a new way of thinking about animal cognition experiments. We describe a process in which a physical cognition task domain can be decomposed into its component parts, and models constructed to represent both the causal events of the domain and the information available to the agent. We then implement a simple set of models, using the planning language MAPL within the MAPSIM simulation environment, and applying it to a puzzle tube task previously presented to orangutans. We discuss the results of the models and compare them with the results from the experiments with orangutans, describing the advantages of this approach, and the ways in which it could be extended.

An exploration of the social brain hypothesis in insects

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

Individual variation in cognitive performance: developmental and evolutionary perspectives

Animal cognition experiments frequently reveal striking individual variation but rarely consider its causes and largely ignore its potential consequences. Studies often focus on a subset of high-performing subjects, sometimes viewing evidence from a single individual as sufficient to demonstrate the cognitive capacity of a species. We argue that the emphasis on demonstrating species-level cognitive capacities detracts from the value of individual variation in understanding cognitive development and evolution. We consider developmental and evolutionary interpretations of individual variation and use meta-analyses of data from published studies to examine predictors of individual performance. We show that reliance on small sample sizes precludes robust conclusions about individual abilities as well as inter- and intraspecific differences. We advocate standardization of experimental protocols and pooling of data between laboratories to improve statistical rigour. Our analyses show that cognitive performance is influenced by age, sex, rearing conditions and previous experience. These effects limit the validity of comparative analyses unless developmental histories are taken into account, and complicate attempts to understand how cognitive traits are expressed and selected under natural conditions. Further understanding of cognitive evolution requires efforts to elucidate the heritability of cognitive traits and establish whether elevated cognitive performance confers fitness advantages in nature.