Mammalian choices: combining fast-but-inaccurate and slow-but-accurate decision-making systems

How can we apply decision-making theories to wild animal behavior? Predictions arising from dual process theory and Bayesian decision theory

Our understanding of decision-making processes and cognitive biases is ever increasing, thanks to an accumulation of testable models and a large body of research over the last several decades. The vast majority of this work has been done in humans and laboratory animals because these study subjects and situations allow for tightly controlled experiments. However, it raises questions about how this knowledge can be applied to wild animals in their complex environments. Here, we review two prominent decision-making theories, dual process theory and Bayesian decision theory, to assess the similarities in these approaches and consider how they may apply to wild animals living in heterogenous environments within complicated social groupings. In particular, we wanted to assess when wild animals are likely to respond to a situation with a quick heuristic decision and when they are likely to spend more time and energy on the decision-making process. Based on the literature and evidence from our multi-destination routing experiments on primates, we find that individuals are likely to make quick, heuristic decisions when they encounter routine situations, or signals/cues that accurately predict a certain outcome, or easy problems that experience or evolutionary history has prepared them for. Conversely, effortful decision-making is likely in novel or surprising situations, when signals and cues have unpredictable or uncertain relationships to an outcome, and when problems are computationally complex. Though if problems are overly complex, satisficing via heuristics is likely, to avoid costly mental effort. We present hypotheses for how animals with different socio-ecologies may have to distribute their cognitive effort. Finally, we examine the conservation implications and potential cognitive overload for animals experiencing increasingly novel situations caused by current human-induced rapid environmental change.

Integrating sensory ecology and predator-prey theory to understand animal responses to fire

Fire regimes are changing dramatically worldwide due to climate change, habitat conversion, and the suppression of Indigenous landscape management. Although there has been extensive work on plant responses to fire, including their adaptations to withstand fire and long-term effects of fire on plant communities, less is known about animal responses to fire. Ecologists lack a conceptual framework for understanding behavioural responses to fire, which can hinder wildlife conservation and management. Here, we integrate cue-response sensory ecology and predator-prey theory to predict and explain variation in if, when and how animals react to approaching fire. Inspired by the literature on prey responses to predation risk, this framework considers both fire-naïve and fire-adapted animals and follows three key steps: vigilance, cue detection and response. We draw from theory on vigilance tradeoffs, signal detection, speed-accuracy tradeoffs, fear generalization, neophobia and adaptive dispersal. We discuss how evolutionary history with fire, but also other selective pressures, such as predation risk, should influence animal behavioural responses to fire. We conclude by providing guidance for empiricists and outlining potential conservation applications.

How honey bees make fast and accurate decisions

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

Fear generalization and behavioral responses to multiple dangers

Animals often exhibit consistent-individual differences (CIDs) in boldness/fearfulness, typically studied in the context of predation risk. We focus here on fear generalization, where fear of one danger (e.g., predators) is correlated with fear of other dangers (e.g., humans, pathogens, moving vehicles, or fire). We discuss why fear generalization should be ecologically important, and why we expect fear to correlate across disparate dangers. CIDs in fear are well studied for some dangers in some taxa (e.g., human fear of pathogens), but not well studied for most dangers. Fear of some dangers has been found to correlate with general fearfulness, but some cases where we might expect correlated fears (e.g., between fear of humans, familiar predators, and exotic predators) are surprisingly understudied.

Asynchrony rescues statistically optimal group decisions from information cascades through emergent leaders

It is usually assumed that information cascades are most likely to occur when an early but incorrect opinion spreads through the group. Here, we analyse models of confidence-sharing in groups and reveal the opposite result: simple but plausible models of naive-Bayesian decision-making exhibit information cascades when group decisions are synchronous; however, when group decisions are asynchronous, the early decisions reached by Bayesian decision-makers tend to be correct and dominate the group consensus dynamics. Thus early decisions actually rescue the group from making errors, rather than contribute to it. We explore the likely realism of our assumed decision-making rule with reference to the evolution of mechanisms for aggregating social information, and known psychological and neuroscientific mechanisms.

Avoiding costly mistakes in groups: The evolution of error management in collective decision making

Individuals continuously have to balance the error costs of alternative decisions. A wealth of research has studied how single individuals navigate this, showing that individuals develop response biases to avoid the more costly error. We, however, know little about the dynamics in groups facing asymmetrical error costs and when social influence amplifies either safe or risky behavior. Here, we investigate this by modeling the decision process and information flow with a drift–diffusion model extended to the social domain. In the model individuals first gather independent personal information; they then enter a social phase in which they can either decide early based on personal information, or wait for additional social information. We combined the model with an evolutionary algorithm to derive adaptive behavior. We find that under asymmetric costs, individuals in large cooperative groups do not develop response biases because such biases amplify at the collective level, triggering false information cascades. Selfish individuals, however, undermine the group’s performance for their own benefit by developing higher response biases and waiting for more information. Our results have implications for our understanding of the social dynamics in groups facing asymmetrical errors costs, such as animal groups evading predation or police officers holding a suspect at gunpoint.

The best of both worlds: Dual systems of reasoning in animals and AI

Much of human cognition involves two different types of reasoning that operate together. Type 1 reasoning systems are intuitive and fast, whereas Type 2 reasoning systems are reflective and slow. Why has our cognition evolved with these features? Both systems are coherent and in most ecological circumstances either alone is capable of coming up with the right answer most of the time. Neural tissue is costly, and thus far evolutionary models have struggled to identify a benefit of operating two systems of reasoning. To explore this issue we take a broad comparative perspective. We discuss how dual processes of cognition have enabled the emergence of selective attention in insects, transforming the learning capacities of these animals. Modern AIs using dual systems of learning are able to learn how their vast world works and how best to interact with it, allowing them to exceed human levels of performance in strategy games. We propose that the core benefits of dual processes of reasoning are to narrow down a problem space in order to focus cognitive resources most effectively.

High-value decisions are fast and accurate, inconsistent with diminishing value sensitivity

What information about economic value is incorporated into decision-makers’ choices? Across the decision sciences, several prominent models ignore average value, assuming that only value differences are incorporated into the decision-making process, while others assume diminishing sensitivity to value, suggesting that it should be more difficult to choose between high-value options. Other models suggest that high-value decisions should, if anything, be treated as less important (holding value difference constant). Across three experiments with very different types of choices (food, art, and learned stimuli), we find violations of these predictions. Contrary to expectations, the presence of high-value options makes decisions easier while also inducing more effort to get them right.

It is a widely held belief that people’s choices are less sensitive to changes in value as value increases. For example, the subjective difference between $11 and $12 is believed to be smaller than between $1 and $2. This idea is consistent with applications of the Weber-Fechner Law and divisive normalization to value-based choice and with psychological interpretations of diminishing marginal utility. According to random utility theory in economics, smaller subjective differences predict less accurate choices. Meanwhile, in the context of sequential sampling models in psychology, smaller subjective differences also predict longer response times. Based on these models, we would predict decisions between high-value options to be slower and less accurate. In contrast, some have argued on normative grounds that choices between high-value options should be made with less caution, leading to faster and less accurate choices. Here, we model the dynamics of the choice process across three different choice domains, accounting for both discriminability and response caution. Contrary to predictions, we mostly observe faster and more accurate decisions (i.e., higher drift rates) between high-value options. We also observe that when participants are alerted about incoming high-value decisions, they exert more caution and not less. We rule out several explanations for these results, using tasks with both subjective and objective values. These results cast doubt on the notion that increasing value reduces discriminability.

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

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

Effect of pitch range on dogs' response to conspecific vs. heterospecific distress cries

Distress cries are emitted by many mammal species to elicit caregiving attention. Across taxa, these calls tend to share similar acoustic structures, but not necessarily frequency range, raising the question of their interspecific communicative potential. As domestic dogs are highly responsive to human emotional cues and experience stress when hearing human cries, we explore whether their responses to distress cries from human infants and puppies depend upon sharing conspecific frequency range or species-specific call characteristics. We recorded adult dogs' responses to distress cries from puppies and human babies, emitted from a loudspeaker in a basket. The frequency of the cries was presented in both their natural range and also shifted to match the other species. Crucially, regardless of species origin, calls falling into the dog call-frequency range elicited more attention. Thus, domestic dogs' responses depended strongly on the frequency range. Females responded both faster and more strongly than males, potentially reflecting asymmetries in parental care investment. Our results suggest that, despite domestication leading to an increased overall responsiveness to human cues, dogs still respond considerably less to calls in the natural human infant range than puppy range. Dogs appear to use a fast but inaccurate decision-making process to determine their response to distress-like vocalisations.

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

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

Trading accuracy for speed over the course of a decision

Humans and other animals often need to balance the desire to gather sensory information (to make the best choice) with the urgency to act, facing a speed-accuracy tradeoff (SAT). Given the ubiquity of SAT across species, extensive research has been devoted to understanding the computational mechanisms allowing its regulation at different timescales, including from one context to another, and from one decision to another. However, animals must frequently change their SAT on even shorter timescales-that is, over the course of an ongoing decision-and little is known about the mechanisms that allow such rapid adaptations. The present study aimed at addressing this issue. Human subjects performed a decision task with changing evidence. In this task, subjects received rewards for correct answers but incurred penalties for mistakes. An increase or a decrease in penalty occurring halfway through the trial promoted rapid SAT shifts, favoring speeded decisions either in the early or in the late stage of the trial. Importantly, these shifts were associated with stage-specific adjustments in the accuracy criterion exploited for committing to a choice. Those subjects who decreased the most their accuracy criterion at a given decision stage exhibited the highest gain in speed, but also the highest cost in terms of performance accuracy at that time. Altogether, the current findings offer a unique extension of previous work, by suggesting that dynamic cha*nges in accuracy criterion allow the regulation of the SAT within the timescale of a single decision.NEW & NOTEWORTHY Extensive research has been devoted to understanding the mechanisms allowing the regulation of the speed-accuracy tradeoff (SAT) from one context to another and from one decision to another. Here, we show that humans can voluntarily change their SAT on even shorter timescales-that is, over the course of a decision. These rapid SAT shifts are associated with dynamic adjustments in the accuracy criterion exploited for committing to a choice.

Diversity-enabled sweet spots in layered architectures and speed-accuracy trade-offs in sensorimotor control

Nervous systems sense, communicate, compute, and actuate movement using distributed components with severe trade-offs in speed, accuracy, sparsity, noise, and saturation. Nevertheless, brains achieve remarkably fast, accurate, and robust control performance due to a highly effective layered control architecture. Here, we introduce a driving task to study how a mountain biker mitigates the immediate disturbance of trail bumps and responds to changes in trail direction. We manipulated the time delays and accuracy of the control input from the wheel as a surrogate for manipulating the characteristics of neurons in the control loop. The observed speed-accuracy trade-offs motivated a theoretical framework consisting of two layers of control loops-a fast, but inaccurate, reflexive layer that corrects for bumps and a slow, but accurate, planning layer that computes the trajectory to follow-each with components having diverse speeds and accuracies within each physical level, such as nerve bundles containing axons with a wide range of sizes. Our model explains why the errors from two control loops are additive and shows how the errors in each control loop can be decomposed into the errors caused by the limited speeds and accuracies of the components. These results demonstrate that an appropriate diversity in the properties of neurons across layers helps to create "diversity-enabled sweet spots," so that both fast and accurate control is achieved using slow or inaccurate components.

From Bench to Keyboard and Back Again: A Brief History of Lambda Phage Modeling

Cellular decision making is the process whereby cells choose one developmental pathway from multiple possible ones, either spontaneously or due to environmental stimuli. Examples in various cell types suggest an almost inexhaustible plethora of underlying molecular mechanisms. In general, cellular decisions rely on the gene regulatory network, which integrates external signals to drive cell fate choice. The search for general principles of such a process benefits from appropriate biological model systems that reveal how and why certain gene regulatory mechanisms drive specific cellular decisions according to ecological context and evolutionary outcomes. In this article, we review the historical and ongoing development of the phage lambda lysis-lysogeny decision as a model system to investigate all aspects of cellular decision making. The unique generality, simplicity, and richness of phage lambda decision making render it a constant source ofmathematical modeling-aided inspiration across all of biology. We discuss the origins and progress of quantitative phage lambda modeling from the 1950s until today, as well as its possible future directions. We provide examples of how modeling enabled methods and theory development, leading to new biological insights by revealing gaps in the theory and pinpointing areas requiring further experimental investigation. Overall, we highlight the utility of theoretical approaches both as predictive tools, to forecast the outcome of novel experiments, and as explanatory tools, to elucidate the natural processes underlying experimental data.

Interspecific two-dimensional visual discrimination of faces in horses (Equus caballus)

In social animals, recognizing conspecifics and distinguishing them from other animal species is certainly important. We hypothesize, as demonstrated in other species of ungulates, that horses are able to discriminate between the faces of conspecifics and the faces of other domestic species (cattle, sheep, donkeys and pigs). Our hypothesis was tested by studying inter-and intra-specific visual discrimination abilities in horses through a two-way instrumental conditioning task (discrimination and reversal learning), using two-dimensional images of faces as discriminative stimuli and food as a positive reward. Our results indicate that 8 out of 10 horses were able to distinguish between two-dimensional images of the faces of horses and images showing the faces of other species. A similar performance was obtained in the reversal task. The horses’ ability to learn by discrimination is therefore comparable to other ungulates. Horses also showed the ability to learn a reversal task. However, these results were obtained regardless of the images the tested horses were exposed to. We therefore conclude that horses can discriminate between two dimensional images of conspecifics and two dimensional images of different species, however in our study, they were not able to make further subcategories within each of the two categories. Despite the fact that two dimensional images of animals could be treated differently from two dimensional images of non-social stimuli, our results beg the question as to whether a two-dimensional image can replace the real animal in cognitive tests.

Experience shapes accuracy in territorial decision-making in a poison frog

The trade-off between speed and accuracy affects many behavioural processes like predator avoidance, foraging and nest-site selection, but little is known about this trade-off relative to territorial behaviour. Some poison frogs are highly territorial and fiercely repel calling male intruders. However, attacks need to be conducted cautiously, as they are energetically costly and bear the risk of own injury or accidentally targeting the wrong individual. In this study, we investigated the speed–accuracy trade-off in the context of male territoriality during the breeding season in the brilliant-thighed poison frog, Allobates femoralis. In our experiment, we presented the call of an invisible ‘threatening’ intruder together with a visible ‘non-threatening’ intruder, using acoustic playback and a frog model, respectively. Contrary to our prediction, neither reaction time nor approach speed of the tested frogs determined the likelihood of erroneous attacks. However, younger individuals were more likely to attack the non-threatening model than older ones, suggesting that experience plays an essential role in identifying and distinguishing rivalling individuals in a territorial context.

Animal affect and decision-making

The scientific study of animal affect (emotion) is an area of growing interest. Whilst research on mechanism and causation has predominated, the study of function is less advanced. This is not due to a lack of hypotheses; in both humans and animals, affective states are frequently proposed to play a pivotal role in coordinating adaptive responses and decisions. However, exactly how they might do this (what processes might implement this function) is often left rather vague. Here we propose a framework for integrating animal affect and decision-making that is couched in modern decision theory and employs an operational definition that aligns with dimensional concepts of core affect and renders animal affect empirically tractable. We develop a model of how core affect, including short-term (emotion-like) and longer-term (mood-like) states, influence decision-making via processes that we label affective options, affective predictions, and affective outcomes and which correspond to similar concepts in schema of the links between human emotion and decision-making. Our framework is generalisable across species and generates questions for future research.

The Cognitive Ecology of Stimulus Ambiguity: A Predator-Prey Perspective

Organisms face the cognitive challenge of making decisions based on imperfect information. Predators and prey, in particular, are confronted with ambiguous stimuli when foraging and avoiding attacks. These challenges are accentuated by variation imposed by environmental, physiological, and cognitive factors. While the cognitive factors influencing perceived ambiguity are often assumed to be fixed, contemporary findings reveal that perceived ambiguity is instead the dynamic outcome of interactive cognitive processes. Here, we present a framework that integrates recent advances in neurophysiology and sensory ecology with a classic decision-making model, signal detection theory (SDT), to understand the cognitive mechanisms that shape perceived stimulus ambiguity in predators and prey. Since stimulus ambiguity is pervasive, the framework discussed here provides insights that extend into nonforaging contexts.

Quorums enable optimal pooling of independent judgements in biological systems

Collective decision-making is ubiquitous, and majority-voting and the Condorcet Jury Theorem pervade thinking about collective decision-making. Thus, it is typically assumed that majority-voting is the best possible decision mechanism, and that scenarios exist where individually-weak decision-makers should not pool information. Condorcet and its applications implicitly assume that only one kind of error can be made, yet signal detection theory shows two kinds of errors exist, 'false positives' and 'false negatives'. We apply signal detection theory to collective decision-making to show that majority voting is frequently sub-optimal, and can be optimally replaced by quorum decision-making. While quorums have been proposed to resolve within-group conflicts, or manage speed-accuracy trade-offs, our analysis applies to groups with aligned interests undertaking single-shot decisions. Our results help explain the ubiquity of quorum decision-making in nature, relate the use of sub- and super-majority quorums to decision ecology, and may inform the design of artificial decision-making systems.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Individuals in larger groups are more successful on spatial discrimination tasks

To understand how natural selection may act on cognitive processes, it is necessary to reliably determine interindividual variation in cognitive abilities. However, an individual's performance in a cognitive test may be influenced by the social environment. The social environment explains variation between species in cognitive performances, with species that live in larger groups purportedly demonstrating more advanced cognitive abilities. It also explains variation in cognitive performances within species, with larger groups more likely to solve novel problems than smaller groups. Surprisingly, an effect of group size on individual variation in cognitive performance has rarely been investigated and much of our knowledge stems from impaired performance of individuals reared in isolation. Using a within-subjects design we assayed individual learning performance of adult female pheasants, Phasianus colchicus, while housed in groups of three and five. Individuals experienced the group sizes in a different order, but were presented with two spatial discrimination tasks, each with a distinct cue set, in a fixed order. We found that across both tasks individuals housed in the large groups had higher levels of success than individuals housed in the small groups. Individuals had higher levels of success on their second than their first task, irrespective of group size. We suggest that the expression of individual learning performance is responsive to the current social environment but the mechanisms underpinning this relationship require further investigation. Our study demonstrates that it is important to account for an individual's social environment when attempting to characterize cognitive capacities. It also demonstrates the flexibility of an individual's cognitive performance depending on the social context.

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Female pheasants' cognitive performance is enhanced when in larger groups.

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Learning performance is responsive to the current social environment.

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This has implications for determining individual variation in cognitive abilities.

How cognitive and reactive fear circuits optimize escape decisions in humans

Flight initiation distance (FID), the distance at which an organism flees from an approaching threat, is an ecological metric of cost-benefit functions of escape decisions. We adapted the FID paradigm to investigate how fast- or slow-attacking "virtual predators" constrain escape decisions. We show that rapid escape decisions rely on "reactive fear" circuits in the periaqueductal gray and midcingulate cortex (MCC), while protracted escape decisions, defined by larger buffer zones, were associated with "cognitive fear" circuits, which include posterior cingulate cortex, hippocampus, and the ventromedial prefrontal cortex, circuits implicated in more complex information processing, cognitive avoidance strategies, and behavioral flexibility. Using a Bayesian decision-making model, we further show that optimization of escape decisions under rapid flight were localized to the MCC, a region involved in adaptive motor control, while the hippocampus is implicated in optimizing decisions that update and control slower escape initiation. These results demonstrate an unexplored link between defensive survival circuits and their role in adaptive escape decisions.

Interrupting behaviour: Minimizing decision costs via temporal commitment and low-level interrupts

Ideal decision-makers should constantly assess all sources of information about opportunities and threats, and be able to redetermine their choices promptly in the face of change. However, perpetual monitoring and reassessment impose inordinate sensing and computational costs, making them impractical for animals and machines alike. The obvious alternative of committing for extended periods of time to limited sensory strategies associated with particular courses of action can be dangerous and wasteful. Here, we explore the intermediate possibility of making provisional temporal commitments whilst admitting interruption based on limited broader observation. We simulate foraging under threat of predation to elucidate the benefits of such a scheme. We relate our results to diseases of distractibility and roving attention, and consider mechanistic substrates such as noradrenergic neuromodulation.

Animals should ideally be able to monitor all relevant aspects of their environment constantly and be ever prepared to alter their course of action in the face of unexpected change. However, the impractically high costs of continual monitoring and deliberation mean that a more realistic strategy is required. Here, we explore a solution in which an animal makes provisional commitments to a temporally-extended action while maintaining the ability to interrupt this behaviour prematurely on the basis of more limited sensing. We demonstrate the benefits of such a scheme through the example of foraging under predation risk, and propose a simple mechanism for implementing interruption. We suggest possible relationships between these results and neural substrates, particularly norepinephrine, and also highlight potential relevance to diseases of distractibility.

A Pause-then-Cancel model of stopping: evidence from basal ganglia neurophysiology

Many studies have implicated the basal ganglia in the suppression of action impulses ('stopping'). Here, we discuss recent neurophysiological evidence that distinct hypothesized processes involved in action preparation and cancellation can be mapped onto distinct basal ganglia cell types and pathways. We examine how movement-related activity in the striatum is related to a 'Go' process and how going may be modulated by brief epochs of beta oscillations. We then describe how, rather than a unitary 'Stop' process, there appear to be separate, complementary 'Pause' and 'Cancel' mechanisms. We discuss the implications of these stopping subprocesses for the interpretation of the stop-signal reaction time-in particular, some activity that seems too slow to causally contribute to stopping when assuming a single Stop processes may actually be fast enough under a Pause-then-Cancel model. Finally, we suggest that combining complementary neural mechanisms that emphasize speed or accuracy respectively may serve more generally to optimize speed-accuracy trade-offs.This article is part of the themed issue 'Movement suppression: brain mechanisms for stopping and stillness'.

Consistency and flexibility in solving spatial tasks: different horses show different cognitive styles

Individual animals vary in their behaviour and reactions to novel situations. These differences may extend to differences in cognition among individuals. We tested twenty-six horses for their ability to detour around symmetric and asymmetric obstacles. All of the animals were able to get around the barrier to reach a food target, but varied in their approach. Some horses moved slowly but were more accurate in choosing the shortest way. Other horses acted quickly, consistently detoured in the same direction, and did not reliably choose the shortest way. The remaining horses shifted from a faster, directionally consistent response with the symmetric barrier, to a slower but more accurate response with the asymmetric barrier. The asymmetric barrier induced a reduction in heart rate variability, suggesting that this is a more demanding task. The different approaches used to solve the asymmetric task may reflect distinct cognitive styles in horses, which vary among individuals, and could be linked to different personality traits. Understanding equine behaviour and cognition can inform horse welfare and management.

Neurobiology of culturally common maternal responses to infant cry

This report coordinates assessments of five types of behavioral responses in new mothers to their own infants' cries with neurobiological responses in new mothers to their own infants' cries and in experienced mothers and inexperienced nonmothers to infant cries and other emotional and control sounds. We found that 684 new primipara mothers in 11 countries (Argentina, Belgium, Brazil, Cameroon, France, Kenya, Israel, Italy, Japan, South Korea, and the United States) preferentially responded to their infants' vocalizing distress by picking up and holding and by talking to their infants, as opposed to displaying affection, distracting, or nurturing. Complementary functional magnetic resonance imaging (fMRI) analyses of brain responses to their own infants' cries in 43 new primipara US mothers revealed enhanced activity in concordant brain territories linked to the intention to move and to speak, to process auditory stimulation, and to caregive [supplementary motor area (SMA), inferior frontal regions, superior temporal regions, midbrain, and striatum]. Further, fMRI brain responses to infant cries in 50 Chinese and Italian mothers replicated, extended, and, through parcellation, refined the results. Brains of inexperienced nonmothers activated differently. Culturally common responses to own infant cry coupled with corresponding fMRI findings to own infant and to generic infant cries identified specific, common, and automatic caregiving reactions in mothers to infant vocal expressions of distress and point to their putative neurobiological bases. Candidate behaviors embedded in the nervous systems of human caregivers lie at the intersection of evolutionary biology and developmental cultural psychology.

Individual Confidence-Weighting and Group Decision-Making

Group-living species frequently pool individual information so as to reach consensus decisions such as when and where to move, or whether a predator is present. Such opinion-pooling has been demonstrated empirically, and theoretical models have been proposed to explain why group decisions are more reliable than individual decisions. Behavioural ecology theory frequently assumes that all individuals have equal decision-making abilities, but decision theory relaxes this assumption and has been tested in human groups. We summarise relevant theory and argue for its applicability to collective animal decisions. We consider selective pressure on confidence-weighting in groups of related and unrelated individuals. We also consider which species and behaviours may provide evidence of confidence-weighting, paying particular attention to the sophisticated vocal communication of cooperative breeders.

Working dogs cooperate among one another by generalised reciprocity

Cooperation by generalised reciprocity implies that individuals apply the decision rule "help anyone if helped by someone". This mechanism has been shown to generate evolutionarily stable levels of cooperation, but as yet it is unclear how widely this cooperation mechanism is applied among animals. Dogs (Canis familiaris) are highly social animals with considerable cognitive potential and the ability to differentiate between individual social partners. But although dogs can solve complex problems, they may use simple rules for behavioural decisions. Here we show that dogs trained in an instrumental cooperative task to provide food to a social partner help conspecifics more often after receiving help from a dog before. Remarkably, in so doing they show no distinction between partners that had helped them before and completely unfamiliar conspecifics. Apparently, dogs use the simple decision rule characterizing generalised reciprocity, although they are probably capable of using the more complex decision rule of direct reciprocity: "help someone who has helped you". However, generalized reciprocity involves lower information processing costs and is therefore a cheaper cooperation strategy. Our results imply that generalised reciprocity might be applied more commonly than direct reciprocity also in other mutually cooperating animals.

Social Information Transmission in Animals: Lessons from Studies of Diffusion

The capacity to use information provided by others to guide behavior is a widespread phenomenon in animal societies. A standard paradigm to test if and/or how animals use and transfer social information is through social diffusion experiments, by which researchers observe how information spreads within a group, sometimes by seeding new behavior in the population. In this article, we review the context, methodology and products of such social diffusion experiments. Our major focus is the transmission of information from an individual (or group thereof) to another, and the factors that can enhance or, more interestingly, inhibit it. We therefore also discuss reasons why social transmission sometimes does not occur despite being expected to. We span a full range of mechanisms and processes, from the nature of social information itself and the cognitive abilities of various species, to the idea of social competency and the constraints imposed by the social networks in which animals are embedded. We ultimately aim at a broad reflection on practical and theoretical issues arising when studying how social information spreads within animal groups.

Speed and accuracy in nest-mate recognition: a hover wasp prioritizes face recognition over colony odour cues to minimize intrusion by outsiders

Social insects have evolved sophisticated recognition systems enabling them to accept nest-mates but reject alien conspecifics. In the social wasp, Liostenogaster flavolineata (Stenogastrinae), individuals differ in their cuticular hydrocarbon profiles according to colony membership; each female also possesses a unique (visual) facial pattern. This species represents a unique model to understand how vision and olfaction are integrated and the extent to which wasps prioritize one channel over the other to discriminate aliens and nest-mates. Liostenogaster flavolineata females are able to discriminate between alien and nest-mate females using facial patterns or chemical cues in isolation. However, the two sensory modalities are not equally efficient in the discrimination of 'friend' from 'foe'. Visual cues induce an increased number of erroneous attacks on nest-mates (false alarms), but such attacks are quickly aborted and never result in serious injury. Odour cues, presented in isolation, result in an increased number of misses: erroneous acceptances of outsiders. Interestingly, wasps take the relative efficiencies of the two sensory modalities into account when making rapid decisions about colony membership of an individual: chemical profiles are entirely ignored when the visual and chemical stimuli are presented together. Thus, wasps adopt a strategy to 'err on the safe side' by memorizing individual faces to recognize colony members, and disregarding odour cues to minimize the risk of intrusion from colony outsiders.

Brain size-related breeding strategies in a seabird

The optimal compromise between decision speed and accuracy may depend on cognitive ability, associated with the degree of encephalization: larger brain size may select for accurate but slow decision-making, beneficial under challenging conditions but costly under benign ones. How this brain size-dependent selection pressure shapes avian breeding phenology and reproductive performance remains largely unexplored. We predicted that (1) large-brained individuals have a delayed breeding schedule due to thorough nest-site selection and/or prolonged resource acquisition, (2) good condition facilitates early breeding independent of relative brain size, and (3) large brain size accrues benefits mainly to individuals challenged by environmental or intrinsic constraints. To test these predictions, we examined how the relative head volume of female eiders (Somateria mollissima) of variable body condition correlated with their breeding schedule, hatching success and offspring quality. The results were consistent with our predictions. First, large head size was associated with a progressively later onset of breeding with increasing breeding dispersal distance. Second, increasing body condition advanced the timing of breeding, but this effect was significantly weaker in large-brained females. Third, larger head volume was associated with increased hatching success mainly among late breeders and those in poor body condition, and duckling body condition was positively related to maternal head volume, but only in poor-condition mothers. Our study is, to our knowledge, the first to demonstrate the presence of brain size-related differences in reproductive strategies within a single natural population.

Risk should be objectively defined: reply to Zentall and Smith

Zentall and Smith (2014) have published a comment on Pelé and Sueur (Anim Cogn 16:543-556, 2013) in which they raise two issues, one about the definition of risk and a second concerning the optimality of decisions. When making a choice, subjects are faced not only with several possible alternatives but also with the risk of opting for an unsuitable choice which depends on several variables (context, internal state, knowledge and perception). Although it is true that animals might learn about their environment and adapt their decisions to the context and to their experience, strong constraints make some behavioural traits stable over individual lifetime and even generations. We therefore consider that experience has limited impact on the variability of temporal discounting. These behavioural traits make the difference between perceived and actual risk. If the perceived risk strongly differs from the actual risk, a decision should be considered as suboptimal. If we want to lead individual and collective cognition to a common decision science, it is crucial to use the same definitions for terms implied in decision-making.

Elevated arousal at time of decision-making is not the arbiter of risk avoidance in chickens

The somatic marker hypothesis proposes that humans recall previously experienced physiological responses to aid decision-making under uncertainty. However, little is known about the mechanisms used by non-human animals to integrate risk perception with predicted gains and losses. We monitored the behaviour and physiology of chickens when the choice between a high-gain (large food quantity), high-risk (1 in 4 probability of receiving an air-puff) option (HGRAP) or a low-gain (small food quantity), no-risk (of an air-puff) (LGNAP) option. We assessed when arousal increased by considering different stages of the decision-making process (baseline, viewing, anticipation, reward periods) and investigated whether autonomic responses influenced choice outcome both immediately and in the subsequent trial. Chickens were faster to choose and their heart-rate significantly increased between the viewing and anticipation (post-decision, pre-outcome) periods when selecting the HGRAP option. This suggests that they responded physiologically to the impending risk. Additionally, arousal was greater following a HGRAP choice that resulted in an air-puff, but this did not deter chickens from subsequently choosing HGRAP. In contrast to human studies, we did not find evidence that somatic markers were activated during the viewing period, suggesting that arousal is not a good measure of avoidance in non-human animals.

Housing conditions affect rat responses to two types of ambiguity in a reward-reward discrimination cognitive bias task

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We investigated how an unpredictable housing treatment (UHT) influenced measures of rat affect.

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Control rats showed more anxiety-like behaviour in open-field and elevated plus maze tests than UHT rats.

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Controls also made more ‘pessimistic’ decisions in an automated cognitive bias task.

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Our go/go reward–reward task was learnt faster than previous automated go/go tasks.

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We developed a new ambiguity test that may probe biases in attentional processes.

Decision-making under ambiguity in cognitive bias tasks is a promising new indicator of affective valence in animals. Rat studies support the hypothesis that animals in a negative affective state evaluate ambiguous cues negatively. Prior automated operant go/go judgement bias tasks have involved training rats that an auditory cue of one frequency predicts a Reward and a cue of a different frequency predicts a Punisher (RP task), and then measuring whether ambiguous cues of intermediate frequency are judged as predicting reward (‘optimism’) or punishment (‘pessimism’). We investigated whether an automated Reward–Reward (RR) task yielded similar results to, and was faster to train than, RP tasks. We also introduced a new ambiguity test (simultaneous presentation of the two training cues) alongside the standard single ambiguous cue test. Half of the rats experienced an unpredictable housing treatment (UHT) designed to induce a negative state. Control rats were relatively ‘pessimistic’, whilst UHT rats were quicker, but no less accurate, in their responses in the RR test, and showed less anxiety-like behaviour in independent tests. A possible reason for these findings is that rats adapted to and were stimulated by UHT, whilst control rats in a predictable environment were more sensitive to novelty and change. Responses in the new ambiguity test correlated positively with those in single ambiguous cue tests, and may provide a measure of attention bias. The RR task was quicker to train than previous automated RP tasks. Together, they could be used to disentangle how reward and punishment processes underpin affect-induced cognitive biases.

The subthalamic nucleus and inhibitory control: impact of subthalamotomy in Parkinson's disease

The aim of our study was to investigate two inter-related hypotheses about the role of the subthalamic nucleus. First that the subthalamic nucleus plays a role in adjusting response thresholds and speed-accuracy trade-offs and second that it is involved in reactive and proactive inhibition and conflict resolution. These were addressed by comparing the performance of 10 patients with Parkinson's disease treated with right subthalamotomy and 12 patients with left subthalamotomy, to 14 unoperated patients with Parkinson's disease and 23 age-matched healthy control participants on a conditional stop signal task and applying the drift diffusion model. Unilateral subthalamotomy significantly improved Parkinson's disease motor signs. Patients with right subthalamotomy had significantly faster Go reaction times with their contra-lesional hand than the unoperated patients and did not differ from the control participants, indicating their speed of response initiation was 'normalized'. However, operated patients made significantly more discrimination errors than unoperated patients and controls, suggesting that subthalamotomy influenced speed-accuracy trade-offs. This was confirmed by the drift diffusion model, revealing that while the unoperated patients had significantly lower drift rate and higher response thresholds than the control participants, the response thresholds for the operated groups did not differ from the controls and the patients with right subthalamotomy had a significantly higher drift rate than unoperated patients and similar to that of controls. The drift diffusion model further established that unlike the control participants, operated patients failed to show context-dependent strategic modulation of response thresholds. The patients with right subthalamotomy could not engage in late phase, fast inhibition of the response and showed minimal proactive inhibition when tested with the contra-lesional hand. These results provide strong evidence that the subthalamic nucleus is involved in response inhibition, in modulating the rate of information accumulation and the response threshold and influencing the balance between speed and accuracy of performance. Accordingly, the subthalamic nucleus can be considered a key component of the cerebral inhibitory network.