Simple minds: a qualified defence of associative learning

A sequence bottleneck for animal intelligence and language?

We discuss recent findings suggesting that non-human animals lack memory for stimulus sequences, and therefore do not represent the order of stimuli faithfully. These observations have far-reaching consequences for animal cognition, neuroscience, and studies of the evolution of language and culture. This is because, if non-human animals do not remember or process information about order faithfully, then it is unlikely that non-human animals perform mental simulations, construct mental world models, have episodic memory, or transmit culture faithfully. If this suggested sequence bottleneck proves to be a prevalent characteristic of animal memory systems, as suggested by recent work, it would require a re-examination of some influential concepts and ideas.

Associative learning, priming, and the fostering of adaptive flexibility

Therapies, including those incorporating clinical hypnosis, occur in the context of consciously mediated interpersonal interactions. While the presence of the non-conscious and its content is often acknowledged, how non-conscious content is accessed and utilized in the training curricula to which clinical hypnosis students are exposed is under-emphasized. This article explores two phenomena - priming and the innate tendency of the human brain to engage in associative learning - that, when incorporated into the interpersonal process that constitutes clinical hypnosis, could expand and enrich outcomes for clients. The processes by which non-conscious processing shapes conscious experience, the role of the social environment in prioritizing and predisposing certain content that later makes its way into consciousness, and examples of how that content can be used to enhance clients' adaptive flexibility are discussed.

Palaeognath birds innovate to solve a novel foraging problem

The ability to innovate implies flexible cognition, and is used as a broad metric of intelligence. Innovation in birds has been intensively studied in the larger and more taxonomically diverse Neognathae clade (particularly crows and parrots) and overlooked in the smaller and more ancestral Palaeognathae clade. The current study provides the first known evidence of technical innovation in palaeognath birds. We tested the ability of nine individuals of three species to move a hole towards a chamber to access a food reward. This problem was different to traditional innovation puzzle-boxes where an obstacle is moved away from a food chamber. Three emus and one rhea produced a wheel-turning innovation, moving the hole in the most efficient direction (closer to the nearest food item) in 90% of cases. One rhea dismantled the task twice by removing the central bolt, which we suggest is a second type of innovation, and it did not persist once they innovated the wheel turning solution. Ostriches did not innovate. We classify innovation in palaeognaths as low level/simplistic, relying on general exploration and asocial trial and error learning. Our research suggests that technical innovation may have evolved far earlier in birds than previously thought, and palaeognath birds are a compelling taxonomic group for further cognitive research.

Disentangled representations for causal cognition

Complex adaptive agents consistently achieve their goals by solving problems that seem to require an understanding of causal information, information pertaining to the causal relationships that exist among elements of combined agent-environment systems. Causal cognition studies and describes the main characteristics of causal learning and reasoning in human and non-human animals, offering a conceptual framework to discuss cognitive performances based on the level of apparent causal understanding of a task. Despite the use of formal intervention-based models of causality, including causal Bayesian networks, psychological and behavioural research on causal cognition does not yet offer a computational account that operationalises how agents acquire a causal understanding of the world seemingly from scratch, i.e. without a-priori knowledge of relevant features of the environment. Research on causality in machine and reinforcement learning, especially involving disentanglement as a candidate process to build causal representations, represents on the other hand a concrete attempt at designing artificial agents that can learn about causality, shedding light on the inner workings of natural causal cognition. In this work, we connect these two areas of research to build a unifying framework for causal cognition that will offer a computational perspective on studies of animal cognition, and provide insights in the development of new algorithms for causal reinforcement learning in AI.

Don't throw the associative baby out with the Bayesian bathwater: Children are more associative when reasoning retrospectively under information processing demands

Causal reasoning is a fundamental cognitive ability that enables individuals to learn about the complex interactions in the world around them. However, the mechanisms that underpin causal reasoning are not well understood. For example, it remains unresolved whether children's causal inferences are best explained by Bayesian inference or associative learning. The two experiments and computational models reported here were designed to examine whether 5- and 6-year-olds will retrospectively reevaluate objects-that is, adjust their beliefs about the causal status of some objects presented at an earlier point in time based on the observed causal status of other objects presented at a later point in time-when asked to reason about 3 and 4 objects and under varying degrees of information processing demands. Additionally, the experiments and models were designed to determine whether children's retrospective reevaluations were best explained by associative learning, Bayesian inference, or some combination of both. The results indicated that participants retrospectively reevaluated causal inferences under minimal information-processing demands (Experiment 1) but failed to do so under greater information processing demands (Experiment 2) and that their performance was better captured by an associative learning mechanism, with less support for descriptions that rely on Bayesian inference. RESEARCH HIGHLIGHTS: Five- and 6-year-old children engage in retrospective reevaluation under minimal information-processing demands (Experiment 1). Five- and 6-year-old children do not engage in retrospective reevaluation under more extensive information-processing demands (Experiment 2). Across both experiments, children's retrospective reevaluations were better explained by a simple associative learning model, with only minimal support for a simple Bayesian model. These data contribute to our understanding of the cognitive mechanisms by which children make causal judgements.

Chimpanzees demonstrate a behavioural signature of human joint action

The strength of human society can largely be attributed to the tendency to work together to achieve outcomes that are not possible alone. Effective social coordination benefits from mentally representing a partner's actions. Specifically, humans optimize social coordination by forming internal action models adapted to joint rather than individual task demands. To what extent do humans share the cognitive mechanisms that support optimal human coordination and collaboration with other species? An ecologically inspired joint handover-to-retrieve task was systematically manipulated across several experiments to assess whether joint action planning in chimpanzees reflects similar patterns to humans. Chimpanzees' chosen handover locations shifted towards the location of the experimenter's free or unobstructed hand, suggesting they represent the constraints of the joint task even though their individual half of the task was unobstructed. These findings indicate that chimpanzees and humans may share common cognitive mechanisms or predispositions that support joint action.

The irreconcilability of insight

We are said to experience insight when we suddenly and unexpectedly become aware of the solution to a problem that we previously took ourselves to be unable to solve. In the field of comparative cognition, there is rising interest in the question of whether non-human animals are capable of insightful problem-solving. Putative cases of animals demonstrating insight have generally attracted two types of criticism: first, that insight is being conflated with other cognitive capacities (e.g., causal cognition, or mental trial and error); and, second, that the relevant performances merely reflect associative learning-and on the received understanding of insight within comparative cognition, insight necessarily involves non-associative processes. I argue that even if we grant that some cases of animal insight do withstand these two criticisms, these cases of purported animal insight cannot shed light on the nature of insightful problem-solving in humans. For the phenomenon studied by cognitive psychologists under the heading of insight is fundamentally different from that studied in comparative cognition. In light of this impasse, I argue that the reinterpretation of the extant research on animal insight in terms of other high-level cognitive capacities (means-end reasoning in particular) can improve the prospect of a successful comparative research program.

Inducing Novel Sound-Taste Correspondences via an Associative Learning Task

The interest in crossmodal correspondences, including those involving sounds and involving tastes, has experienced rapid growth in recent years. However, the mechanisms underlying these correspondences are not well understood. In the present study (N = 302), we used an associative learning paradigm, based on previous literature using simple sounds with no consensual taste associations (i.e., square and triangle wave sounds at 200 Hz) and taste words (i.e., sweet and bitter), to test the influence of two potential mechanisms in establishing sound-taste correspondences and investigate whether either learning mechanism could give rise to new and long-lasting associations. Specifically, we examined an emotional mediation account (i.e., using sad and happy emoji facial expressions) and a transitive path (i.e., sound-taste correspondence being mediated by color, using red and black colored squares). The results revealed that the associative learning paradigm mapping the triangle wave tone with a happy emoji facial expression induced a novel crossmodal correspondence between this sound and the word sweet. Importantly, we found that this novel association was still present two months after the experimental learning paradigm. None of the other mappings, emotional or transitive, gave rise to any significant associations between sound and taste. These findings provide evidence that new crossmodal correspondences between sounds and tastes can be created by leveraging the affective connection between both dimensions, helping elucidate the mechanisms underlying these associations. Moreover, these findings reveal that these associations can last for several weeks after the experimental session through which they were induced.

Tyramine and its Amtyr1 receptor modulate attention in honey bees (Apis mellifera)

Animals must learn to ignore stimuli that are irrelevant to survival and attend to ones that enhance survival. When a stimulus regularly fails to be associated with an important consequence, subsequent excitatory learning about that stimulus can be delayed, which is a form of nonassociative conditioning called 'latent inhibition'. Honey bees show latent inhibition toward an odor they have experienced without association with food reinforcement. Moreover, individual honey bees from the same colony differ in the degree to which they show latent inhibition, and these individual differences have a genetic basis. To investigate the mechanisms that underly individual differences in latent inhibition, we selected two honey bee lines for high and low latent inhibition, respectively. We crossed those lines and mapped a Quantitative Trait Locus for latent inhibition to a region of the genome that contains the tyramine receptor gene Amtyr1 [We use Amtyr1 to denote the gene and AmTYR1 the receptor throughout the text.]. We then show that disruption of Amtyr1 signaling either pharmacologically or through RNAi qualitatively changes the expression of latent inhibition but has little or slight effects on appetitive conditioning, and these results suggest that AmTYR1 modulates inhibitory processing in the CNS. Electrophysiological recordings from the brain during pharmacological blockade are consistent with a model that AmTYR1 indirectly regulates at inhibitory synapses in the CNS. Our results therefore identify a distinct Amtyr1-based modulatory pathway for this type of nonassociative learning, and we propose a model for how Amtyr1 acts as a gain control to modulate hebbian plasticity at defined synapses in the CNS. We have shown elsewhere how this modulation also underlies potentially adaptive intracolonial learning differences among individuals that benefit colony survival. Finally, our neural model suggests a mechanism for the broad pleiotropy this gene has on several different behaviors.

Why is the Rescorla-Wagner model so influential?

The influence of the Rescorla-Wagner model cannot be overestimated, despite that (1) the model does not differ much computationally from its predecessors and competitors, and (2) its shortcomings are well-known in the learning community. Here we discuss the reasons behind its widespread influence in the cognitive and neural sciences, and argue that it is the constant search for general-process theories by learning scholars which eventually produced a model whose application spans many different areas of research to this day. We focus on the theoretical and empirical background of the model, the theoretical connections that it has with later developments across Marr's levels of analysis, as well as the broad variety of research that it has guided and inspired.

Flexible social inference facilitates targeted social learning when rewards are not observable

Groups coordinate more effectively when individuals are able to learn from others' successes. But acquiring such knowledge is not always easy, especially in real-world environments where success is hidden from public view. We suggest that social inference capacities may help bridge this gap, allowing individuals to update their beliefs about others' underlying knowledge and success from observable trajectories of behaviour. We compared our social inference model against simpler heuristics in three studies of human behaviour in a collective-sensing task. Experiment 1 demonstrated that average performance improved as a function of group size at a rate greater than predicted by heuristic models. Experiment 2 introduced artificial agents to evaluate how individuals selectively rely on social information. Experiment 3 generalized these findings to a more complex reward landscape. Taken together, our findings provide insight into the relationship between individual social cognition and the flexibility of collective behaviour.

Wild jackdaws can selectively adjust their social associations while preserving valuable long-term relationships

Influential theories of the evolution of cognition and cooperation posit that tracking information about others allows individuals to adjust their social associations strategically, re-shaping social networks to favour connections between compatible partners. Crucially, to our knowledge, this has yet to be tested experimentally in natural populations, where the need to maintain long-term, fitness-enhancing relationships may limit social plasticity. Using a social-network-manipulation experiment, we show that wild jackdaws (Corvus monedula) learned to favour social associations with compatible group members (individuals that provided greater returns from social foraging interactions), but resultant change in network structure was constrained by the preservation of valuable pre-existing relationships. Our findings provide insights into the cognitive basis of social plasticity and the interplay between individual decision-making and social-network structure.

Great ape cognition is structured by stable cognitive abilities and predicted by developmental conditions

Great ape cognition is used as a reference point to specify the evolutionary origins of complex cognitive abilities, including in humans. This research often assumes that great ape cognition consists of cognitive abilities (traits) that account for stable differences between individuals, which change and develop in response to experience. Here, we test the validity of these assumptions by assessing repeatability of cognitive performance among captive great apes (Gorilla gorilla, Pongo abelii, Pan paniscus, Pan troglodytes) in five tasks covering a range of cognitive domains. We examine whether individual characteristics (age, group, test experience) or transient situational factors (life events, testing arrangements or sociality) influence cognitive performance. Our results show that task-level performance is generally stable over time; four of the five tasks were reliable measurement tools. Performance in the tasks was best explained by stable differences in cognitive abilities (traits) between individuals. Cognitive abilities were further correlated, suggesting shared cognitive processes. Finally, when predicting cognitive performance, we found stable individual characteristics to be more important than variables capturing transient experience. Taken together, this study shows that great ape cognition is structured by stable cognitive abilities that respond to different developmental conditions.

Ensembles code for associative learning in the primate lateral prefrontal cortex

The lateral prefrontal cortex (LPFC) of primates is thought to play a role in associative learning. However, it remains unclear how LPFC neuronal ensembles dynamically encode and store memories for arbitrary stimulus-response associations. We recorded the activity of neurons in LPFC of two macaques during an associative learning task using multielectrode arrays. During task trials, the color of a symbolic cue indicated the location of one of two possible targets for a saccade. During a trial block, multiple randomly chosen associations were learned by the subjects. A state-space analysis indicated that LPFC neuronal ensembles rapidly learn new stimulus-response associations mirroring the animals' learning. Multiple associations acquired during training are stored in a neuronal subspace and can be retrieved hours after learning. Finally, knowledge of old associations facilitates learning new, similar associations. These results indicate that neuronal ensembles in the primate LPFC provide a flexible and dynamic substrate for associative learning.

Influence of reward and location on dogs' behaviour toward an interactive artificial agent

Animal-robot interaction studies provide outstanding opportunities to understand the principles of social interactions. Here we investigated whether dogs' behaviour toward a cooperative artificial agent (Unidentified Moving Object (UMO)) is influenced by receiving a reward directly from the agent, and by variability in the UMO's location. In a problem-solving task, the UMO either helped dogs to obtain food (Direct Reward Group, DRG) or to fetch an object followed by an indirect reward from the owner/experimenter (Indirect Reward Group, IRG). During the Familiarization, the UMO either started from the same location or changed its starting location in all trials. In the Test phase, dogs faced the same task, but additionally a second, unfamiliar UMO was present. We found that both reward groups gazed at the UMO with decreasing latency during the Familiarization, with the IRG showing more gaze alternations between UMO and hiding location. Dogs showed no preference for either UMO in the Test phase but looked at the familiar UMO sooner if it had changed its location during the Familiarization. Thus, direct reward is not necessary to elicit elements of socially competent behavior in dogs, but variability in its motion may be important to improve the UMO's animacy and promote flexible learning.

Grounding Mental Representations in a Virtual Multi-Level Functional Framework

According to the associative theory of learning, reactive behaviors described by stimulus-response pairs result in the progressive wiring of a plastic brain. In contrast, flexible behaviors are supposedly driven by neurologically grounded mental states that involve computations on informational contents. These theories appear complementary, but are generally opposed to each other. The former is favored by neuro-scientists who explore the low-level biological processes supporting cognition, and the later by cognitive psychologists who look for higher-level structures. This situation can be clarified through an analysis that independently defines abstract neurological and informational functionalities, and then relate them through a virtual interface. This framework is validated through a modeling of the first stage of Piaget's cognitive development theory, whose reported end experiments demonstrate the emergence of mental representations of object displacements. The neural correlates grounding this emergence are given in the isomorphic format of an associative memory. As a child's exploration of the world progresses, his mental models will eventually include representations of space, time and causality. Only then epistemological concepts, such as beliefs, will give rise to higher level mental representations in a possibly richer propositional format. This raises the question of which additional neurological functionalities, if any, would be required in order to include these extensions into a comprehensive grounded model. We relay previously expressed views, which in summary hypothesize that the ability to learn has evolved from associative reflexes and memories, to suggest that the functionality of associative memories could well provide the sufficient means for grounding cognitive capacities.

After 150 years of watching: is there a need for synthetic ethology?

The Darwinian idea of mental continuity is about 150 years old. Although nobody has strongly denied this evolutionary link, both conceptually and practically, relative slow advance has been made by ethology and comparative psychology to quantify mental evolution. Debates on the mechanistic interpretation of cognition often struggle with the same old issues (e.g., associationism vs cognitivism), and in general, experimental methods have made also relative slow progress since the introduction of the puzzle box. In this paper, we illustrate the prevailing issues using examples on 'mental state attribution' and 'perspective taking" and argue that the situation could be improved by the introduction of novel methodological inventions and insights. We suggest that focusing on problem-solving skills and constructing artificial agents that aim to correspond and interact with biological ones, may help to understand the functioning of the mind. We urge the establishment of a novel approach, synthetic ethology, in which researchers take on a practical stance and construct artificial embodied minds relying of specific computational architectures the performance of which can be compared directly to biological agents.

Ideomotor learning: Time to generalize a longstanding principle

The ideomotor principle holds that anticipating the sensory consequences of a movement triggers an associated motor response. Even though this framework dates back to the 19th century, it continues to lie at the heart of many contemporary approaches to human action control. Here we specifically focus on the ideomotor learning mechanism that has to precede action initiation via effect anticipation. Traditional approaches to this learning mechanism focused on establishing novel action-effect (or response-effect) associations. Here we apply the theoretical concept of common coding for action and perception to argue that the same learning principle should result in response-response and stimulus-stimulus associations just as well. Generalizing ideomotor learning in such a way results in a powerful and general framework of ideomotor action control, and it allows for integrating the two seemingly separate fields of ideomotor approaches and hierarchical learning.

Captive Asian short-clawed otters (Aonyx cinereus) learn to exploit unfamiliar natural prey

Foraging plays a vital role in animal life histories, and learning whether unfamiliar food items are palatable is a key part of this process. Animals that engage in extractive foraging must also learn how to overcome the protective measures of their prey. While otters (subfamily Lutrinae) are a taxon known for their extractive foraging behaviour, how they learn about prey palatability and acquire extractive foraging techniques remains poorly understood. Here we investigated (i) how captive Asian short-clawed otters (Aonyx cinereus) learned to interact with, and extract meat from, unfamiliar natural prey and (ii) how their exploitation of such prey compared to their ability to overcome artificial foraging tasks containing familiar food rewards. Network-based diffusion analysis showed that otters learned to interact with unfamiliar natural prey by observing their group mates. However, once interacting with the prey, they learned to extract the meat mainly asocially. In addition, otters took longer to overcome the protective measures of unfamiliar natural prey than those of extractive food puzzles. Asian short-clawed otter populations are declining in the wild. Increasing our understanding of how they learn to overcome novel foraging challenges could help develop pre-release training procedures as part of reintroduction programmes for otter conservation.

Can female guppies learn to like male colours? A test of the role of associative learning in originating sexual preferences

How do female sexual preferences for male ornamental traits arise? The developmental origins of female preferences are still an understudied area, with most explanations pointing to genetic mechanisms. One intriguing, little-explored, alternative focuses on the role of associative learning in driving this process. According to this hypothesis, a preference learned in an ecological context can be transferred into a sexual context, resulting in changes in mating preferences as a by-product. I tested this hypothesis by first training female guppies to associate either orange or black colour with food delivery; I then presented videos of males with computer-manipulated coloured spots and measured female preference towards them. I also allowed females from both treatments to mate with males differing in their ratio of orange-to-black spots and measured the males' reproductive success. After training, female sexual preferences significantly diverged among treatments in the expected direction. In addition, orange males sired a greater proportion of offspring with females food-conditioned on orange compared to those conditioned on black. These results show that mating preferences can arise as a by-product of associative learning, which, via translation into variation in male fitness, can become associated with indirect genetic benefits, potentially leading to further evolution.

Fishnition: Developing Models From Cognition Toward Consciousness

A challenge to developing a model for testing animal consciousness is the pull of opposite intuitions. On one extreme, the anthropocentric view holds that consciousness is a highly sophisticated capacity involving self-reflection and conceptual categorization that is almost certainly exclusive to humans. At the opposite extreme, an anthropomorphic view attributes consciousness broadly to any behavior that involves sensory responsiveness. Yet human experience and observation of diverse species suggest that the most plausible case is that consciousness functions between these poles. In exploring the middle ground, we discuss the pros and cons of "high level" approaches such as the dual systems approach. According to this model, System 1 can be thought of as unconscious; processing is fast, automatic, associative, heuristic, parallel, contextual, and likely to be conserved across species. Consciousness is associated with System 2 processing that is slow, effortful, rule-based, serial, abstract, and exclusively human. An advantage of this model is the clear contrast between heuristic and decision-based responses, but it fails to include contextual decision-making in novel conditions which falls in between these two categories. We also review a "low level" model involving trace conditioning, which is a trained response to the first of two paired stimuli separated by an interval. This model highlights the role of consciousness in maintaining a stimulus representation over a temporal span, though it overlooks the importance of attention in subserving and also disrupting trace conditioning in humans. Through a critical analysis of these two extremes, we will develop the case for flexible behavioral response to the stimulus environment as the best model for demonstrating animal consciousness. We discuss a methodology for gauging flexibility across a wide variety of species and offer a case study in spatial navigation to illustrate our proposal. Flexibility serves the evolutionary function of enabling the complex evaluation of changing conditions, where motivation is the basis for goal valuation, and attention selects task-relevant stimuli to aid decision-making processes. We situate this evolutionary function within the Temporal Representation Theory of consciousness, which proposes that consciousness represents the present moment in order to facilitate flexible action.

The hidden side of animal cognition research: Scientists' attitudes toward bias, replicability and scientific practice

Animal cognition research aims to understand animal minds by using a diverse range of methods across an equally diverse range of species. Throughout its history, the field has sought to mitigate various biases that occur when studying animal minds, from experimenter effects to anthropomorphism. Recently, there has also been a focus on how common scientific practices might affect the reliability and validity of published research. Usually, these issues are discussed in the literature by a small group of scholars with a specific interest in the topics. This study aimed to survey a wider range of animal cognition researchers to ask about their attitudes towards classic and contemporary issues facing the field. Two-hundred and ten active animal cognition researchers completed our survey, and provided answers on questions relating to bias, replicability, statistics, publication, and belief in animal cognition. Collectively, researchers were wary of bias in the research field, but less so in their own work. Over 70% of researchers endorsed Morgan’s canon as a useful principle but many caveated this in their free-text responses. Researchers self-reported that most of their studies had been published, however they often reported that studies went unpublished because they had negative or inconclusive results, or results that questioned “preferred” theories. Researchers rarely reported having performed questionable research practices themselves—however they thought that other researchers sometimes (52.7% of responses) or often (27.9% of responses) perform them. Researchers near unanimously agreed that replication studies are important but too infrequently performed in animal cognition research, 73.0% of respondents suggested areas of animal cognition research could experience a ‘replication crisis’ if replication studies were performed. Consistently, participants’ free-text responses provided a nuanced picture of the challenges animal cognition research faces, which are available as part of an open dataset. However, many researchers appeared concerned with how to interpret negative results, publication bias, theoretical bias and reliability in areas of animal cognition research. Collectively, these data provide a candid overview of barriers to progress in animal cognition and can inform debates on how individual researchers, as well as organizations and journals, can facilitate robust scientific research in animal cognition.

Wild jackdaws respond to their partner's distress, but not with consolation

Individuals are expected to manage their social relationships to maximize fitness returns. For example, reports of some mammals and birds offering unsolicited affiliation to distressed social partners (commonly termed 'consolation') are argued to illustrate convergent evolution of prosocial traits across divergent taxa. However, most studies cannot discriminate between consolation and alternative explanations such as self-soothing. Crucially, no study that controls for key confounds has examined consolation in the wild, where individuals face more complex and dangerous environments than in captivity. Controlling for common confounds, we find that male jackdaws (Corvus monedula) respond to their mate's stress-states, but not with consolation. Instead, they tended to decrease affiliation and partner visit rate in both experimental and natural contexts. This is striking because jackdaws have long-term monogamous relationships with highly interdependent fitness outcomes, which is precisely where theory predicts consolation should occur. Our findings challenge common conceptions about where consolation should evolve, and chime with concerns that current theory may be influenced by anthropomorphic expectations of how social relationships should be managed. To further our understanding of the evolution of such traits, we highlight the need for our current predictive frameworks to incorporate the behavioural trade-offs inherent to life in the wild.

Deductive-reasoning brain networks: A coordinate-based meta-analysis of the neural signatures in deductive reasoning

OBJECTIVE

Deductive reasoning is a complex and poorly understood concept in the field of psychology. Many cognitive neuroscience studies have been published on deductive reasoning but have yielded inconsistent findings.

METHODS

In this study, we analyzed collected data from 38 articles using a recently proposed activation likelihood estimation (ALE) approach and used conjunction analysis to better determine the intersection of the results of meta-analyses.

RESULTS

First, the left hemispheres in the inferior parietal lobule (Brodmann area 40 [BA40]), middle frontal gyrus (BA6), medial frontal gyrus (BA8), inferior frontal gyrus (BA45/46), caudate, and insula (BA47) were revealed to be significant brain regions via simple-effect analysis (deductive reasoning versus baseline). Furthermore, IFG, insula, and cingulate (the key neural hubs of the cingulo-opercular network) were highlighted in overlapped functional connectivity maps.

CONCLUSION

The findings of the current study are consistent with the view that deductive reasoning requires a succession of stages, which included decoding of linguistic information, conversion and correction of rules, and transformation of inferential results into conclusive outputs, all of which are putatively processed via a distributed network of brain regions encompassing frontal/parietal cortices, as well as the caudate and other subcortical structures, which suggested that in the process of deductive reasoning, the coding and integration of premise information is indispensable, and it is also crucial to the execution and monitoring of the cognitive processing of reasoning.

Learning strategies and long-term memory in Asian short-clawed otters (Aonyx cinereus)

Social learning, where information is acquired from others, is taxonomically widespread. There is growing evidence that animals selectively employ 'social learning strategies', which determine e.g. when to copy others instead of learning asocially and whom to copy. Furthermore, once animals have acquired new information, e.g. regarding profitable resources, it is beneficial for them to commit it to long-term memory (LTM), especially if it allows access to profitable resources in the future. Research into social learning strategies and LTM has covered a wide range of taxa. However, otters (subfamily Lutrinae), popular in zoos due to their social nature and playfulness, remained neglected until a recent study provided evidence of social learning in captive smooth-coated otters (Lutrogale perspicillata), but not in Asian short-clawed otters (Aonyx cinereus). We investigated Asian short-clawed otters' learning strategies and LTM performance in a foraging context. We presented novel extractive foraging tasks twice to captive family groups and used network-based diffusion analysis to provide evidence of a capacity for social learning and LTM in this species. A major cause of wild Asian short-clawed otter declines is prey scarcity. Furthering our understanding of how they learn about and remember novel food sources could inform key conservation strategies.

Delineating implicit and explicit processes in neurofeedback learning

Neurofeedback allows humans to self-regulate neural activity in specific brain regions and is considered a promising tool for psychiatric interventions. Recently, methods have been developed to use neurofeedback implicitly, prompting a theoretical debate on the role of awareness in neurofeedback learning. We offer a critical review of the role of awareness in neurofeedback learning, with a special focus on recently developed neurofeedback paradigms. We detail differences in instructions and propose a fine-grained categorization of tasks based on the degree of involvement of explicit and implicit processes. Finally, we review the methods used to measure awareness in neurofeedback and propose new candidate measures. We conclude that explicit processes cannot be eschewed in most current implicit tasks that have explicit goals, and suggest ways in which awareness could be better measured in the future. Investigating awareness during learning will help understand the learning mechanisms underlying neurofeedback learning and will help shape future tasks.

A Comparison of Individual Learning and Social Learning in Zebrafish Through an Ethorobotics Approach

Social learning is ubiquitous across the animal kingdom, where animals learn from group members about predators, foraging strategies, and so on. Despite its prevalence and adaptive benefits, our understanding of social learning is far from complete. Here, we study observational learning in zebrafish, a popular animal model in neuroscience. Toward fine control of experimental variables and high consistency across trials, we developed a novel robotics-based experimental test paradigm, in which a robotic replica demonstrated to live subjects the correct door to join a group of conspecifics. We performed two experimental conditions. In the individual training condition, subjects learned the correct door without the replica. In the social training condition, subjects observed the replica approaching both the incorrect door, to no effect, and the correct door, which would open after spending enough time close to it. During these observations, subjects could not actively follow the replica. Zebrafish increased their preference for the correct door over the course of 20 training sessions, but we failed to identify evidence of social learning, whereby we did not register significant differences in performance between the individual and social training conditions. These results suggest that zebrafish may not be able to learn a route by observation, although more research comparing robots to live demonstrators is needed to substantiate this claim.

Interindividual variation in learning ability in honeybees

Performance on different cognitive tasks could either be positively correlated in an individual as a measure of general intelligence or costs related to specific aspects of cognition could give rise to specialized cognitive phenotypes. Social living offers the potential for individual specialization in learning and a cooperative group can benefit from a diversity of learning phenotypes. However, there is little empirical data regarding the nature of such interindividual variation in learning abilities in honeybees, a classic model of animal cognition. We tested for the presence of variation in learning abilities in the honeybee, Apis mellifera, and whether any component of learning has an influence on wing damage, a proxy for performance and survival. Our results show considerable interindividual variation in different types of learning abilities. At the individual level, while landmark and olfactory learning abilities are negatively correlated, olfactory learning shows a positive association with maneuverability performance, a measure which in turn shows a positive influence on wing damage, a proxy for survival. We discuss our results in the context of cognitive diversity and specialization in a social group.

Empathy is not in our genes

In academic and public life empathy is seen as a fundamental force of morality - a psychological phenomenon, rooted in biology, with profound effects in law, policy, and international relations. But the roots of empathy are not as firm as we like to think. The matching mechanism that distinguishes empathy from compassion, envy, schadenfreude, and sadism is a product of learning. Here I present a dual system model that distinguishes Empathy¹, an automatic process that catches the feelings of others, from Empathy², controlled processes that interpret those feelings. Research with animals, infants, adults and robots suggests that the mechanism of Empathy¹, emotional contagion, is constructed in the course of development through social interaction. Learned Matching implies that empathy is both agile and fragile. It can be enhanced and redirected by novel experience, and broken by social change.

What can associative learning do for planning?

There is a new associative learning paradox. The power of associative learning for producing flexible behaviour in non-human animals is downplayed or ignored by researchers in animal cognition, whereas artificial intelligence research shows that associative learning models can beat humans in chess. One phenomenon in which associative learning often is ruled out as an explanation for animal behaviour is flexible planning. However, planning studies have been criticized and questions have been raised regarding both methodological validity and interpretations of results. Due to the power of associative learning and the uncertainty of what causes planning behaviour in non-human animals, I explored what associative learning can do for planning. A previously published sequence learning model which combines Pavlovian and instrumental conditioning was used to simulate two planning studies, namely Mulcahy & Call 2006 'Apes save tools for future use.' Science 312, 1038-1040 and Kabadayi & Osvath 2017 'Ravens parallel great apes in flexible planning for tool-use and bartering.' Science 357, 202-204. Simulations show that behaviour matching current definitions of flexible planning can emerge through associative learning. Through conditioned reinforcement, the learning model gives rise to planning behaviour by learning that a behaviour towards a current stimulus will produce high value food at a later stage; it can make decisions about future states not within current sensory scope. The simulations tracked key patterns both between and within studies. It is concluded that one cannot rule out that these studies of flexible planning in apes and corvids can be completely accounted for by associative learning. Future empirical studies of flexible planning in non-human animals can benefit from theoretical developments within artificial intelligence and animal learning.

An intraspecific appraisal of the social intelligence hypothesis

The prevailing hypotheses for the evolution of cognition focus on either the demands associated with group living (the social intelligence hypothesis (SIH)) or ecological challenges such as finding food. Comparative studies testing these hypotheses have generated highly conflicting results; consequently, our understanding of the drivers of cognitive evolution remains limited. To understand how selection shapes cognition, research must incorporate an intraspecific approach, focusing on the causes and consequences of individual variation in cognition. Here, we review the findings of recent intraspecific cognitive research to investigate the predictions of the SIH. Extensive evidence from our own research on Australian magpies (Cracticus tibicen dorsalis), and a number of other taxa, suggests that individuals in larger social groups exhibit elevated cognitive performance and, in some cases, elevated reproductive fitness. Not only do these findings demonstrate how the social environment has the potential to shape cognitive evolution, but crucially, they demonstrate the importance of considering both genetic and developmental factors when attempting to explain the causes of cognitive variation.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.

On Deflationary Accounts of Human Action Understanding

A common deflationary tendency has emerged recently in both philosophical accounts and comparative animal studies concerned with how subjects understand the actions of others. The suggestion emerging from both arenas is that the default mechanism for understanding action involves only a sensitivity to the observable, behavioural (non-mental) features of a situation. This kind of ‘smart behaviour reading’ thus suggests that, typically, predicting or explaining the behaviour of conspecifics does not require seeing the other through the lens of mental state attribution. This paper aims to explore and assess this deflationary move. In §1 I clarify what might be involved in a smart behaviour reading account via looking at some concrete examples. Then in §2 I critically assess the deflationary move, arguing that, at least in the human case, it would in fact be a mistake to assume that our default method of action understanding proceeds without appeal to mental state attribution. Finally in §3 I consider briefly how the positive view proposed here relates to discussions about standard two-system models of cognition.

The sense of agency shapes body schema and peripersonal space

Body schema, a sensorimotor representation of the body used for planning and executing movements, is plastic because it extends by using a tool to reach far objects. Modifications of peripersonal space, i.e., a functional representation of reach space, usually co-occur with body schema changes. Here, we hypothesized that such plastic changes depend on the experience of controlling the course of events in space trough one’s own actions, i.e., the sense of agency. In two experiments, body schema and peripersonal space were assessed before and after the participants’ sense of agency over a virtual hand was manipulated. Body schema and peripersonal space enlarged or contracted depending on whether the virtual hand was presented in far space, or closer to the participants’ body than the real hand. These findings suggest that body schema and peripersonal space are affected by the dynamic mapping between intentional body movements and expected consequences in space.

Constructive anthropomorphism: a functional evolutionary approach to the study of human-like cognitive mechanisms in animals

Anthropomorphism, the attribution of human cognitive processes and emotional states to animals, is commonly viewed as non-scientific and potentially misleading. This is mainly because apparent similarity to humans can usually be explained by alternative, simpler mechanisms in animals, and because there is no explanatory power in analogies to human phenomena when these phenomena are not well understood. Yet, because it is also difficult to preclude real similarity and continuity in the evolution of humans' and animals' cognitive abilities, it may not be productive to completely ignore our understanding of human behaviour when thinking about animals. Here we propose that in applying a functional approach to the evolution of cognitive mechanisms, human cognition may be used to broaden our theoretical thinking and to generate testable hypotheses. Our goal is not to 'elevate' animals, but rather to find the minimal set of mechanistic principles that may explain 'advanced' cognitive abilities in humans, and consider under what conditions these mechanisms were likely to enhance fitness and to evolve in animals. We illustrate this approach, from relatively simple emotional states, to more advanced mechanisms, involved in planning and decision-making, episodic memory, metacognition, theory of mind, and consciousness.

A social insect perspective on the evolution of social learning mechanisms

The social world offers a wealth of opportunities to learn from others, and across the animal kingdom individuals capitalize on those opportunities. Here, we explore the role of natural selection in shaping the processes that underlie social information use, using a suite of experiments on social insects as case studies. We illustrate how an associative framework can encompass complex, context-specific social learning in the insect world and beyond, and based on the hypothesis that evolution acts to modify the associative process, suggest potential pathways by which social information use could evolve to become more efficient and effective. Social insects are distant relatives of vertebrate social learners, but the research we describe highlights routes by which natural selection could coopt similar cognitive raw material across the animal kingdom.

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.

Adopt, ignore, or kill? Male poison frogs adjust parental decisions according to their territorial status

Systematic infanticide of unrelated young has been reported in several animal taxa. Particular attention has been given to carnivores and primates, where infanticide is a sexually selected strategy of males to gain increased access to female mating partners. Cannibals must ensure avoiding their own offspring and targeting only unrelated young. Therefore, decision rules are needed to mediate parental and cannibalistic behaviour. Here we show experimentally that male poison frogs adjust their parental responses – care or infanticide – towards unrelated clutches according to their territorial status. Male frogs followed the simple rule ‘care for any clutch’ inside their territory, but immediately switched to cannibalism when establishing a new territory. This demonstrates that simple cognitive rules can mediate complex behaviours such as parental care, and that care and cannibalism are antagonistically linked. Non-parental infanticide is mediated by territorial cues and presumably serves to prevent misdirected care in this poison frog. Our results thus prompt a re-consideration of evolutionary and causal aspects of parental decision making, by suggesting that selective infanticide of unrelated young may generally become adaptive when the risks and costs of misdirected care are high.