Neuromolecular Underpinnings of Negative Cognitive Bias in Depression

This selective review aims to summarize the recent advances in understanding the neuromolecular underpinnings of biased cognition in depressive disorder. We begin by considering the cognitive correlates of depressed mood and the key brain systems implicated in its development. We then review the core findings across two domains of biased cognitive function in depression: pessimistic judgment bias and abnormal response to negative feedback. In considering their underlying substrates, we focus on the neurochemical mechanisms identified by genetic, molecular and pharmacological challenge studies. We conclude by discussing experimental approaches to the treatment of depression, which are derived largely from an improved understanding of its cognitive substrates.

Judgement Bias in Miniature Donkeys: Conditioning Factors and Personality Links

Expectation-related bias may configure individuals’ perception of their surrounding environment and of the elements present in it. This study aimed to determine the repercussions of environmental (weather elements) or subject-inherent factors (sex, age, or personality features) on judgment bias. A cognitive bias test was performed in eight Miniature jennies and four jacks. Test comprised habituation, training and testing phases during which subjects were trained on how to complete the test and scored based on their latency to approach an ambiguous stimulus. A questionnaire evaluating eleven personality features was parallelly completed by three caretakers, five operators and two care assistants to determine the links between personality features and judgment bias. Adjusted latencies did not significantly differ between sexes (Mann–Whitney test, p > 0.05). Although Miniature donkeys can discriminate positive/negative stimuli, inter-individual variability evidences were found. Such discrimination is evidenced by significant latency differences to approach positive/negative stimuli (33.7 ± 43.1 vs. 145.5 ± 53.1 s) (Mann–Whitney test, p < 0.05). Latencies significantly increased with patience, indicative of an expression of pessimism. Better understanding judgement bias mechanisms and implications may help optimize routine handling practices in the framework of animal welfare.

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.

Judgement Bias During Pregnancy In Domestic Pigs

In humans and rats, changes in mood and affect are known to occur during pregnancy, however it is unknown how gestation may influence mood in other non-human mammals. This study assessed changes in pigs’ judgment bias as a measure of affective state throughout gestation. Pigs were trained to complete a spatial judgement bias task with reference to positive and negative locations. We tested gilts before mating, and during early and late pregnancy, by assessing their responses to ambiguous probe locations. Pigs responded increasingly negatively to ambiguous probes as pregnancy progressed and there were consistent inter-individual differences in baseline optimism. This suggests that the pigs’ affective state may be altered during gestation, although as a non-pregnant control group was not tested, an effect of learning cannot be ruled out. These results suggest that judgement bias is altered during pregnancy in domestic pigs, consequently raising novel welfare considerations for captive multiparous species.

Evaluation of miRNA as Biomarkers of Emotional Valence in Pigs

The ability to assess the welfare of animals is dependent on our ability to accurately determine their emotional (affective) state, with particular emphasis being placed on the identification of positive emotions. The challenge remains that current physiological and behavioral indices are either unable to distinguish between positive and negative emotional states, or they are simply not suitable for a production environment. Therefore, the development of novel measures of animal emotion is a necessity. Here we investigated the efficacy of microRNA (miRNA) in the brain and blood as biomarkers of emotional state in the pig. Female Large White × Landrace pigs (n = 24) were selected at weaning and trained to perform a judgment bias test (JBT), before being exposed for 5 weeks to either enriched (n = 12) or barren housing (n = 12) conditions. Pigs were tested on the JBT once prior to treatment, and immediately following treatment. MiRNA and neurotransmitters were analyzed in blood and brain tissue after euthanasia. Treatment had no effect on the outcomes of the JBT. There was also no effect of treatment on miRNA expression in blood or the brain (FDR p > 0.05). However, pigs exposed to enriched housing had elevated dopamine within the striatum compared to pigs in barren housing (p = 0.02). The results imply that either (a) miRNAs are not likely to be valid biomarkers of a positive affective state, at least under the type of conditions employed in this study, or (b) that the study design used to modify affective state was not able to create differential affective states, and therefore establish the validity of miRNA as biomarkers.

Using the Judgment Bias Task to Identify Behavioral Indicators of Affective State: Do Eye Wrinkles in Horses Reflect Mood?

Identifying and validating behavioral indicators of mood are important for the assessment of animal welfare. Here, we investigated whether horses' eye wrinkle expression in a presumably neutral situation is a measure of mood as assessed in a cognitive judgment bias task (JBT). To this end, we scored pictures of the left and right eyes of 16 stallions for different aspects of eye wrinkle expression and tested the same individuals on a spatial JBT with active trial initiation. Eye wrinkle expressions were assessed by a qualitative assessment, i.e., the overall assessment of how “worried” horses look, the number of wrinkles, and the angle measured at the intersection of lines drawn through the eyeball and the topmost wrinkle. Correlations between the three eye wrinkle measures and the optimism index as a measure of horses' decisions in the JBT were not statistically significant, but with increasing optimism index, horses tended to be scored as looking less worried (qualitative assessment). We discuss our findings from different perspectives and make suggestions for future research, e.g., by calling for experimental induction of mood and thus greater variation within and/or between individuals and by investigating the interplay between shorter-lasting emotional and longer-lasting mood states to further explore the potential use of the JBT to validate eye wrinkles and other facial or body expressions as indicators of mood.

Cognitive and Composite Behavioural Welfare Assessments of Pet Cats between the Ages of 9–22 Months, Living in Single and Multi-Cat Households

Although agonistic interactions between cats are often regarded clinically as a source of stress, there is currently limited research evidence regarding the welfare impact of keeping multiple cats as pets. The aim of this study was to compare welfare indicators between cats living in domestic single and multi-cat households, as well as between multi-cat households where agonistic behaviour was/was not reported by owners. Indicators included a spatial judgment bias task (JBT), where longer latencies to ambiguous probes are interpreted as being related to a more ‘pessimistic’ mood state, and the cat stress score (CSS), where high scores are indicative of high stress levels. Of 128 focal cats between the ages of 9–22 months, 94 were from multi-cat households, 126 had useable CSS data and 42 had JBT results suitable for analysis. CSSs were significantly lower for cats showing a more ‘pessimistic’ response in the JBT. It is possible that the cats that appeared to be the most relaxed may have been showing inactivity relating to negative affective states and/or were the least active/food motivated, and therefore slower in the JBT. CSSs were significantly higher in cats from single compared with multi-cat households, and did not vary with reports of agonistic interactions in multi-cat households. JBT results did not vary depending on the presence of, or reports of agonistic behaviours between, cohabiting cats. These data suggest that cats from single-cat households may be more likely to show signs of acute stress than those in multi-cat households. Alternative explanations are possible. For example, lower CSSs in the multi-cat group may reflect ‘relief’ effects resulting from separating cats for the test period, or inactivity relating to negative affective states. Due to the narrow sample population and broad scope of husbandry conditions, the potential for confounding variables limits the degree by which results can be used to inform causation of the relationships identified. Further research is warranted to replicate this work and explore potential confounders.

Anchoring and Judgment Bias: Disregarding Under Uncertainty

The current investigation examined the nature of the cognitive processes that underlie decision-making behavior. The focus of this project centered on the effects of utilizing heuristics that pertain to the availability of information stored in memory. Anchoring effects demonstrate that people will use any available information sampled from memory as a reference for making judgments of frequency. The specific aim of the experiment was to examine whether people exhibit patterns of behavior consistent with anchoring effects, revealed by corrupted subjective judgments, despite explicit notice of instruction to disregard the experimenter-supplied information (the anchor). Subjects failed to demonstrate an ability to disregard a relatively high anchor even when the instruction to do so was explicit. However, in contrast, subjects demonstrated an ability to disregard a relatively low anchor. More broadly, subjects instructed to disregard demonstrated a reduced effect of anchoring. Implications are considered within the context of the availability heuristic and the directly related effects of anchoring. The results may be interpreted within the framework of a dual-process model, two-system view that distinguishes intuition from reasoning. The present findings fit with well-supported theoretical explanations of anchoring effects, such as selective accessibility and numerical priming.

Understanding Mechanisms Behind Discrimination Using Diffusion Decision Modeling

Past research has documented where discrimination occurs or tested interventions that reduce discrimination. Less is known about how discriminatory behavior emerges and the mechanisms through which successful interventions work. Two studies (N &gt; 4500) apply the Diffusion Decision Model (DDM) to the Judgment Bias Task, a measure of discrimination. In control conditions, participants gave preferential treatment (acceptance to a hypothetical honor society) to physically attractive applicants. DDM analyses revealed participants initially favored attractive candidates and attractiveness was accumulated as evidence of being qualified. Two interventions—raising awareness of bias and asking for more deliberative judgments—reduced discrimination through separate mechanisms. Raising awareness reduced biases in drift rates while increasing deliberation raised decision thresholds. This work offers insight into how discrimination emerges and may aid efforts to develop interventions to lessen discrimination.