Cognitive Bias in Ambiguity Judgements: Using Computational Models to Dissect the Effects of Mild Mood Manipulation in Humans

The odour of an unfamiliar stressed or relaxed person affects dogs' responses to a cognitive bias test

Dogs can discriminate stressed from non-stressed human odour samples, but the effect on their cognition is unstudied. Using a cognitive bias task, we tested how human odours affect dogs' likelihood of approaching a food bowl placed at three ambiguous locations ("near-positive", "middle" and "near-negative") between trained "positive" (rewarded) and "negative" (unrewarded) locations. Using odour samples collected from three unfamiliar volunteers during stressful and relaxing activities, we tested eighteen dogs under three conditions: no odour, stress odour and relaxed odour, with the order of test odours counterbalanced across dogs. When exposed to stress odour during session three, dogs were significantly less likely to approach a bowl placed at one of the three ambiguous locations (near-negative) compared to no odour, indicating possible risk-reduction behaviours in response to the smell of human stress. Dogs' learning of trained positive and negative locations improved with repeated testing and was significant between sessions two and three only when exposed to stress odour during session three, suggesting odour influenced learning. This is the first study to show that without visual or auditory cues, olfactory cues of human stress may affect dogs' cognition and learning, which, if true, could have important consequences for dog welfare and working performance.

The Ambiguous Cue Task: Measurement reliability of an experimental paradigm for the assessment of interpretation bias and associations with mental health

Interpretation biases in the processing of ambiguous affective information are assumed to play an important role in the onset and maintenance of emotional disorders. Reports of low reliability for experimental measures of cognitive biases have called into question previous findings on the association of these measures with markers of mental health and demonstrated the need to systematically evaluate measurement reliability for measures of cognitive biases. We evaluated reliability and correlations with self-report measures of mental health for interpretation bias scores derived from the Ambiguous Cue Task (ACT), an experimental paradigm for the assessment of approach-avoidance behavior towards ambiguous affective stimuli. For a non-clinical sample, the measurement of an interpretation bias with the ACT showed high internal consistency (rSB = .91 - .96, N = 354) and acceptable 2-week test-retest correlations (rPearson = .61 - .65, n = 109). Correlations between the ACT interpretation bias scores and mental health-related self-report measures of personality and well-being were generally small (r ≤ |.11|) and statistically not significant when correcting for multiple comparisons. These findings suggest that in non-clinical populations, individual differences in the interpretation of ambiguous affective information as assessed with the ACT do not show a clear association with self-report markers of mental health. However, in allowing for a highly reliable measurement of interpretation bias, the ACT provides a valuable tool for studies considering potentially small effect sizes in non-clinical populations by studying bigger samples as well as for work on clinical populations, for which potentially greater effects can be expected.

Rodent tests of depression and anxiety: Construct validity and translational relevance

Behavioral testing constitutes the primary method to measure the emotional states of nonhuman animals in preclinical research. Emerging as the characteristic tool of the behaviorist school of psychology, behavioral testing of animals, particularly rodents, is employed to understand the complex cognitive and affective symptoms of neuropsychiatric disorders. Following the symptom-based diagnosis model of the DSM, rodent models and tests of depression and anxiety focus on behavioral patterns that resemble the superficial symptoms of these disorders. While these practices provided researchers with a platform to screen novel antidepressant and anxiolytic drug candidates, their construct validity-involving relevant underlying mechanisms-has been questioned. In this review, we present the laboratory procedures used to assess depressive- and anxiety-like behaviors in rats and mice. These include constructs that rely on stress-triggered responses, such as behavioral despair, and those that emerge with nonaversive training, such as cognitive bias. We describe the specific behavioral tests that are used to assess these constructs and discuss the criticisms on their theoretical background. We review specific concerns about the construct validity and translational relevance of individual behavioral tests, outline the limitations of the traditional, symptom-based interpretation, and introduce novel, ethologically relevant frameworks that emphasize simple behavioral patterns. Finally, we explore behavioral monitoring and morphological analysis methods that can be integrated into behavioral testing and discuss how they can enhance the construct validity of these tests.

A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals

Objective measures of animal emotion-like and mood-like states are essential for preclinical studies of affective disorders and for assessing the welfare of laboratory and other animals. However, the development and validation of measures of these affective states poses a challenge partly because the relationships between affect and its behavioural, physiological and cognitive signatures are complex. Here, we suggest that the crisp characterisations offered by computational modelling of the underlying, but unobservable, processes that mediate these signatures should provide better insights. Although this computational psychiatry approach has been widely used in human research in both health and disease, translational computational psychiatry studies remain few and far between. We explain how building computational models with data from animal studies could play a pivotal role in furthering our understanding of the aetiology of affective disorders, associated affective states and the likely underlying cognitive processes involved. We end by outlining the basic steps involved in a simple computational analysis.

The influence of incidental emotions on decision-making under risk and uncertainty: a systematic review and meta-analysis of experimental evidence

Emotions influence human decisions under risk and uncertainty, even when they are unrelated to the decisions, i.e. incidental to them. Empirical findings are mixed regarding the directions and sizes of the effects of discrete emotions such as fear, anger, or happiness. According to the Appraisal-Tendency Framework (ATF), appraisals of certainty and control determine why same-valence emotions can differentially alter preferences for risky and uncertain options. Building upon this framework of emotion-specific appraisals, we conducted a systematic review and meta-analysis of 28 experimental studies on the effects of discrete incidental emotions on decision-making under risk and uncertainty. We evaluated potential moderators at the task and study levels. We find emotion-specific, moderately heterogeneous effects partially in line with the expectations of the ATF. The framing and financial consequences of choices, the type of choices, and the presence of other participants during the task do not moderate the effect. Our meta-analytic results support the differential influence of discrete, incidental emotions on decision-making under risk and uncertainty depending on appraisals other than valence. We discuss limited sample sizes and heterogeneity as reasons for the absence of significant moderators and encourage experimental investigations of individual differences in the susceptibility to incidental affective influences.

[Multidimensional and computational theory of mood]

What is mood? Despite its crucial place in psychiatric nosography and cognitive science, it is still difficult to delimit its conceptual ground. The distinction between emotion and mood is ambiguous: mood is often presented as an affective state that is more prolonged and less intense than emotion, or as an affective polarity distinguishing high and low mood swinging around a baseline. However, these definitions do not match the clinical reality of mood disorders such as unipolar depression and bipolar disorder, and do not allow us to understand the effect of mood on behaviour, perception and cognition. In this paper, we propose a multidimensional and computational theory of mood inspired by contemporary hypotheses in theoretical neuroscience and philosophy of emotion. After suggesting an operational distinction between emotion and mood, we show how a succession of emotions can cumulatively generate congruent mood over time, making mood an emerging state from emotion. We then present how mood determines mental and behavioral states when interacting with the environment, constituting a dispositional state of emotion, perception, belief, and action. Using this theoretical framework, we propose a computational representation of the emerging and dispositional dimensions of mood by formalizing mood as a layer of third-order Bayesian beliefs encoding the precision of emotion, and regulated by prediction errors associated with interoceptive predictions. Finally, we show how this theoretical framework sheds light on the processes involved in mood disorders, the emergence of mood congruent beliefs, or the mechanisms of antidepressant treatments in clinical psychiatry.

Using Primary Reinforcement to Enhance Translatability of a Human Affect and Decision-Making Judgment Bias Task

Good translatability of behavioral measures of affect (emotion) between human and nonhuman animals is core to comparative studies. The judgment bias (JB) task, which measures "optimistic" and "pessimistic" decision-making under ambiguity as indicators of positive and negative affective valence, has been used in both human and nonhuman animals. However, one key disparity between human and nonhuman studies is that the former typically use secondary reinforcers (e.g., money) whereas the latter typically use primary reinforcers (e.g., food). To address this deficiency and shed further light on JB as a measure of affect, we developed a novel version of a JB task for humans using primary reinforcers. Data on decision-making and reported affective state during the JB task were analyzed using computational modeling. Overall, participants grasped the task well, and as anticipated, their reported affective valence correlated with trial-by-trial variation in offered volume of juice. In addition, previous findings from monetary versions of the task were replicated: More positive prediction errors were associated with more positive affective valence, a higher lapse rate was associated with lower affective arousal, and affective arousal decreased as a function of number of trials completed. There was no evidence that more positive valence was associated with greater "optimism," but instead, there was evidence that affective valence influenced the participants' decision stochasticity, whereas affective arousal tended to influence their propensity for errors. This novel version of the JB task provides a useful tool for investigation of the links between primary reward and punisher experience, affect, and decision-making, especially from a comparative perspective.

Watching others in a positive state does not induce optimism bias in common marmosets (Callithrix jacchus), but leads to behaviour indicative of competition

Emotional contagion is suggested to facilitate group life by enhancing synchronized responses to the environment. Cooperative breeders are an example of a social system that requires such intricate coordination between individuals. Therefore, we studied emotional contagion in common marmosets by means of a judgement bias test. Demonstrators were exposed to an emotion manipulation (i.e., positive, negative, control), and observers perceived only the demonstrator's behaviour. We predicted that the positive or negative states of the demonstrator would induce matching states in the observer, indicating emotional contagion. All subjects' emotional states were assessed through behaviour and cognition, the latter by means of a judgement bias test. Behavioural results showed a successful emotion manipulation of demonstrators, with manipulation-congruent expressions (i.e., positive calls in the positive condition, and negative calls and pilo-erect tail in the negative condition). Observers showed no manipulation-congruent expressions, but showed more scratching and arousal after the positive manipulation. Concerning the judgement bias test, we predicted that subjects in a positive state should increase their response to ambiguous cues (i.e., optimism bias), and subjects in a negative state should decrease their response (i.e., pessimism bias). This prediction was not supported as neither demonstrators nor observers showed such bias in either manipulation. Yet, demonstrators showed an increased response to the near-positive cue, and additional analyses showed unexpected responses to the reference cues, as well as a researcher identity effect. We discuss all results combined, including recently raised validation concerns of the judgement bias test, and inherent challenges to empirically studying emotional contagion.

Negative expectations and vulnerability to stressors in animals

Humans express stable differences in pessimism that render some individuals more vulnerable to stressors and mood disorders. We explored whether non-human animals express stable individual differences in expectations (assessed via judgment bias tests) and whether these differences relate to susceptibility to stressors. Judgment bias tests do not distinguish pessimism from sensitivity to reinforcers; negative expectations are likely driven by a combination of these two elements. The available evidence suggests that animals express stable individual differences in expectations such that some persistently perceive ambiguous situations in a more negative way. A lack of research prevents drawing firm conclusions on how negative expectations affect responses to stressors, but current evidence suggests a link between negative expectations and the adoption of avoidance coping strategies, stronger responses to uncontrollable stressors and risk of mood-related disorders. We explore implications for animals living in captivity and for research using animals as models for human disorders.

Reinforcement-based cognitive biases as vulnerability factors in alcohol addiction: From humans to animal models

Alcohol use disorder (AUD) is one of the most common, but still poorly treated, psychiatric conditions. Developing new treatments requires a better understanding of the aetiology of symptoms and evaluation of novel therapeutic targets in preclinical studies. Recent developments in our understanding of the reinforcement-based cognitive biases (RBCBs) that contribute to the development of AUD and its treatment offer new opportunities for both clinical and preclinical research. In this review, we first briefly describe psychological and cognitive theories that involve various aspects of reinforcement sensitivity in the development, maintenance, and recurrence of alcohol addiction. Furthermore, in separate sections, we describe studies investigating RBCBs and their neural, neurochemical, and pharmacological correlates, and we discuss possible interactions between RBCBs and trajectories of AUD. Finally, we describe how recent translational studies using state-of-the-art animal models can facilitate our understanding of the role of reinforcement sensitivity and RBCBs in various aspects of AUD.

Temperament, Plasticity, and Emotions in Defensive Behaviour of Paca (Mammalia, Hystricognatha)

Simple Summary

The paca (Cuniculus paca), a Neotropical caviomorph rodent, provides the most sought-after game meat in all its range, and it therefore faces high hunting pressure and consequent poor welfare. The species is categorised as having a conservation status of “least concern” and appears resilient to over-hunting by humans, which may be related to individuals’ behavioural characteristics. To investigate this, we submitted captive pacas to temperament (personality) tests designed to assess individual responses to short challenges and to evaluate individuals’ emotional states. Our results showed that paca with a “restless” temperament performed more abnormal behaviour and less exploratory behaviour in a test of defensive behaviour, which elevations in faecal glucocorticoid metabolites indicated to be stressful. Plasticity in defensive behaviour was inferred from changes in behavioural responses and apparently rapid adaptation to different levels of risk. Our results suggest that individual differences and consistency of behavioural responses displayed by paca toward challenges may reflect a generally flexible and successful defensive behavioural response that underpins the paca’s survival, despite the threat of overhunting throughout its range.

Abstract

Within a species, some individuals are better able to cope with threatening environments than others. Paca (Cuniculus paca) appear resilient to over-hunting by humans, which may be related to the behavioural plasticity shown by this species. To investigate this, we submitted captive pacas to temperament tests designed to assess individual responses to short challenges and judgement bias tests (JBT) to evaluate individuals’ affective states. Results indicated across-time and context stability in closely correlated “agitated”, “fearful” and “tense” responses; this temperament dimension was labelled “restless”. Individual “restless” scores predicted responses to novelty, although not to simulated chasing and capture by humans in a separate modified defence test battery (MDTB). Restless animals were more likely to show a greater proportion of positive responses to an ambiguous cue during JBT after the MDTB. Plasticity in defensive behaviour was inferred from changes in behavioural responses and apparently rapid adaptation to challenge in the different phases of the MDTB. The results indicate that both temperament and behavioural plasticity may play a role in influencing paca responses to risky situations. Therefore, our study highlights the importance of understanding the role of individual temperament traits and behavioural plasticity in order to better interpret the animals’ conservation status and vulnerabilities.

Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach

Links between affective states and risk-taking are often characterised using summary statistics from serial decision-making tasks. However, our understanding of these links, and the utility of decision-making as a marker of affect, needs to accommodate the fact that ongoing (e.g., within-task) experience of rewarding and punishing decision outcomes may alter future decisions and affective states. To date, the interplay between affect, ongoing reward and punisher experience, and decision-making has received little detailed investigation. Here, we examined the relationships between reward and loss experience, affect, and decision-making in humans using a novel judgement bias task analysed with a novel computational model. We demonstrated the influence of within-task favourability on decision-making, with more risk-averse/‘pessimistic’ decisions following more positive previous outcomes and a greater current average earning rate. Additionally, individuals reporting more negative affect tended to exhibit greater risk-seeking decision-making, and, based on our model, estimated time more poorly. We also found that individuals reported more positive affective valence during periods of the task when prediction errors and offered decision outcomes were more positive. Our results thus provide new evidence that (short-term) within-task rewarding and punishing experiences determine both future decision-making and subjectively experienced affective states.

Affective states, such as happiness, are key to well-being. They are thought to reflect characteristics of the environment such as the availability of reward and the inevitability of punishment. However, there is a lack of agreement about: (i) the time scales over which these characteristics are measured; (ii) how and in what combinations actual or expected outcomes influence affect; (iii) how affect itself influences decision-making. A particular stance on the last issue underpins the judgement bias task, which, by measuring an individual’s willingness to make ‘optimistic’ or ‘pessimistic’ choices that are rendered risky by perceptual ambiguity, is one of the few cross-species tests for affect. Here we apply a novel computational analysis to a novel judgement bias task to examine all three issues. We reveal a rich interplay between affect and rewards, punishments, and uncertainty.

Does training method matter? Evidence for the negative impact of aversive-based methods on companion dog welfare

Dog training methods range broadly from those using mostly positive punishment and negative reinforcement (aversive-based) to those using primarily positive reinforcement (reward-based). Although aversive-based training has been strongly criticized for negatively affecting dog welfare, there is no comprehensive research focusing on companion dogs and mainstream techniques, and most studies rely on owner-reported assessment of training methods and dog behavior. The aim of the present study was to evaluate the effects of aversive- and reward-based training methods on companion dog welfare within and outside the training context. Ninety-two companion dogs were recruited from three reward-based schools (Group Reward, n = 42), and from four aversive-based schools, two using low proportions of aversive-based methods (Group Mixed, n = 22) and two using high proportions of aversive-based methods (Group Aversive, n = 28). For evaluating welfare during training, dogs were video recorded for three sessions and six saliva samples were collected, three at home (baseline levels) and three after training (post-training levels). Video recordings were used to examine the frequency of stress-related behaviors (e.g., lip lick, yawn) and the overall behavioral state of the dog (e.g., tense, relaxed), and saliva samples were analyzed for cortisol concentration. For evaluating welfare outside the training context, dogs participated in a cognitive bias task. Results showed that dogs from Group Aversive displayed more stress-related behaviors, were more frequently in tense and low behavioral states and panted more during training, and exhibited higher post-training increases in cortisol levels than dogs from Group Reward. Additionally, dogs from Group Aversive were more 'pessimistic' in the cognitive bias task than dogs from Group Reward. Dogs from Group Mixed displayed more stress-related behaviors, were more frequently in tense states and panted more during training than dogs from Group Reward. Finally, although Groups Mixed and Aversive did not differ in their performance in the cognitive bias task nor in cortisol levels, the former displayed more stress-related behaviors and was more frequently in tense and low behavioral states. These findings indicate that aversive-based training methods, especially if used in high proportions, compromise the welfare of companion dogs both within and outside the training context.

Using judgment bias test in pet and shelter dogs (Canis familiaris): Methodological and statistical caveats

It is now widely agreed that a positive affective state is a crucial component of animal well-being. The judgment bias test represents a widespread tool used to assess animals' optimistic/pessimistic attitude and to evaluate their emotional state and welfare. Judgment bias tests have been used several times with dogs (Canis familiaris), in most cases using a spatial test with a bowl placed in ambiguous positions located between a relatively positive trained location (P) which contains a baited bowl and a relatively negative trained location (N) which contains an empty bowl. The latency to approach the bowl in the ambiguous locations is an indicator of the dog's expectation of a positive/negative outcome. However, results from such tests are often inconclusive. For the present study, the judgment bias test performance of 51 shelter dogs and 40 pet dogs was thoroughly analysed. A pattern emerged with shelter dogs behaving in a more pessimistic-like way than pet dogs. However, this difference between the two populations was detected only when analysing the raw latencies to reach the locations and not the more commonly applied adjusted score (i.e. average latency values). Furthermore, several methodological caveats were found. First of all, a non-negligible percentage of dogs did not pass the training phase, possibly due to the experimental paradigm not being fully suited for this species. Second, results showed a high intra-dog variability in response to the trained locations, i.e. the dogs' responses were not consistent throughout the test, suggesting that animals may not have fully learned the association between locations and their outcomes. Third, dogs did not always behave differently towards adjacent locations, raising doubts about the animals' ability to discriminate between locations. Finally, a potential influence of the researcher's presence on dogs' performance emerged from analyses. The implications of these findings and potential solutions are discussed.

Reward and punisher experience alter rodent decision-making in a judgement bias task

The influence of affective states on decision-making is likely to be complex. Negative states resulting from experience of punishing events have been hypothesised to generate enhanced expectations of future punishment and ‘pessimistic’/risk-averse decisions. However, they may also influence how decision-outcomes are valued. Such influences may further depend on whether decisions at hand are germane to the rewards or punishers that induced the affective state in the first place. Here we attempt to dissect these influences by presenting either many or few rewards or punishers of different types (sucrose vs air-puff; 50 kHz vs 22 kHz ultrasonic vocalisations) to rats, and investigating their subsequent decisions in a judgement bias task that employed sucrose and air-puff as decision outcomes. Rats that received many sucrose pellets prior to testing were more risk-averse than those receiving many air-puffs. Ultrasonic vocalisations did not alter decision-making. Computational analysis revealed a higher weighting of punishers relative to rewards (in agreement with findings from a separate behavioural task) and a bias towards the risk-averse response following pre-test sucrose compared to pre-test air-puff. Thus, in this study reward and punisher manipulation of affective state appeared to alter decision-making by influencing both expectation and valuation of decision-outcomes in a domain-specific way.

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.

Pharmacological manipulations of judgement bias: A systematic review and meta-analysis

Validated measures of animal affect are crucial to research spanning numerous disciplines. Judgement bias, which assesses decision-making under ambiguity, is a promising measure of animal affect. One way of validating this measure is to administer drugs with affect-altering properties in humans to non-human animals and determine whether the predicted judgement biases are observed. We conducted a systematic review and meta-analysis using data from 20 published research articles that use this approach, from which 557 effect sizes were extracted. Pharmacological manipulations overall altered judgement bias at the probe cues as predicted. However, there were several moderating factors including the neurobiological target of the drug, whether the drug induced a relatively positive or negative affective state in humans, dosage, and the presented cue. This may partially reflect interference from adverse effects of the drug which should be considered when interpreting results. Thus, the overall pattern of change in animal judgement bias appears to reflect the affect-altering properties of drugs in humans, and hence may be a valuable measure of animal affective valence.

State-dependent judgement bias in Drosophila: evidence for evolutionarily primitive affective processes

Affective states influence decision-making under ambiguity in humans and other animals. Individuals in a negative state tend to interpret ambiguous cues more negatively than individuals in a positive state. We demonstrate that the fruit fly, Drosophila melanogaster, also exhibits state-dependent changes in cue interpretation. Drosophila were trained on a Go/Go task to approach a positive (P) odour associated with a sugar reward and actively avoid a negative (N) odour associated with shock. Trained flies were then either shaken to induce a purported negative state or left undisturbed (control), and given a choice between: air or P; air or N; air or ambiguous odour (1 : 1 blend of P : N). Shaken flies were significantly less likely to approach the ambiguous odour than control flies. This ‘judgement bias’ may be mediated by changes in neural activity that reflect evolutionarily primitive affective states. We cannot say whether such states are consciously experienced, but use of this model organism's versatile experimental tool kit may facilitate elucidation of their neural and genetic basis.

Assessing animal affect: an automated and self-initiated judgement bias task based on natural investigative behaviour

Scientific methods for assessing animal affect, especially affective valence (positivity or negativity), allow us to evaluate animal welfare and the effectiveness of 3Rs Refinements designed to improve wellbeing. Judgement bias tasks measure valence; however, task-training may be lengthy and/or require significant time from researchers. Here we develop an automated and self-initiated judgement bias task for rats which capitalises on their natural investigative behaviour. Rats insert their noses into a food trough to start trials. They then hear a tone and learn either to stay for 2 s to receive a food reward or to withdraw promptly to avoid an air-puff. Which contingency applies is signalled by two different tones. Judgement bias is measured by responses to intermediate ambiguous tones. In two experiments we show that rats learn the task in fewer sessions than other automated variants, generalise responses across ambiguous tones as expected, self-initiate 4-5 trials/min, and can be tested repeatedly. Affect manipulations generate main effect trends in the predicted directions, although not localised to ambiguous tones, so further construct validation is required. We also find that tone-reinforcer pairings and reinforcement or non-reinforcement of ambiguous trials can affect responses to ambiguity. This translatable task should facilitate more widespread uptake of judgement bias testing.

An effect of serotonergic stimulation on learning rates for rewards apparent after long intertrial intervals

Serotonin has widespread, but computationally obscure, modulatory effects on learning and cognition. Here, we studied the impact of optogenetic stimulation of dorsal raphe serotonin neurons in mice performing a non-stationary, reward-driven decision-making task. Animals showed two distinct choice strategies. Choices after short inter-trial-intervals (ITIs) depended only on the last trial outcome and followed a win-stay-lose-switch pattern. In contrast, choices after long ITIs reflected outcome history over multiple trials, as described by reinforcement learning models. We found that optogenetic stimulation during a trial significantly boosted the rate of learning that occurred due to the outcome of that trial, but these effects were only exhibited on choices after long ITIs. This suggests that serotonin neurons modulate reinforcement learning rates, and that this influence is masked by alternate, unaffected, decision mechanisms. These results provide insight into the role of serotonin in treating psychiatric disorders, particularly its modulation of neural plasticity and learning.

Serotonin (5-HT) plays many important roles in reward, punishment, patience and beyond, and optogenetic stimulation of 5-HT neurons has not crisply parsed them. The authors report a novel analysis of a reward-based decision-making experiment, and show that 5-HT stimulation increases the learning rate, but only on a select subset of choices.

Pavlovian influences on learning differ between rats and mice in a counter-balanced Go/NoGo judgement bias task

Judgement bias tests of animal affect and hence welfare assume that the animal's responses to ambiguous stimuli, which may herald positive or negative outcomes, are under instrumental control and reflect 'optimism' or 'pessimism' about what will happen. However, Pavlovian control favours responses (e.g. approach or withdrawal) according to the valence associated with a stimulus, rather than the anticipated response outcomes. Typically, positive contexts promote action and approach whilst negative contexts promote inhibition or withdrawal. The prevalence of Go-for-reward (Go-pos) and NoGo-to-avoid-punishment (NoGo-neg) judgement bias tasks reflects this Pavlovian influence. A Pavlovian increase or decrease in activity or vigour has also been argued to accompany positive or negative affective states, and this may interfere with instrumental Go or NoGo decisions under ambiguity based on anticipated decision outcomes. One approach to these issues is to develop counter-balanced Go-pos/NoGo-neg and Go-neg/NoGo-pos tasks. Here we implement such tasks in Sprague Dawley rats and C57BL/6J mice using food and air-puff as decision outcomes. We find striking species/strain differences with rats achieving criterion performance on the Go-pos/NoGo-neg task but failing to learn the Go-neg/NoGo-pos task, in line with predictions, whilst mice do exactly the opposite. Pavlovian predispositions may thus differ between species, for example reflecting foraging and predation ecology and/or baseline activity rates. Learning failures are restricted to cues predicting a negative outcome; use of a more powerful air-puff stimulus may thus allow implementation of a fully counter-balanced task. Rats and mice achieve criterion faster than in comparable automated tasks and also show the expected generalisation of responses across ambiguous tones. A fully counter-balanced task thus offers a potentially rapidly implemented and automated method for assessing animal welfare, identifying welfare problems and areas for welfare improvement and 3Rs Refinement, and assessing the effectiveness of refinements.