ON SOME PROBLEMS OF THE STATIC AND DYNAMIC ACCURACY OF LOGARITHMIC MULTIPLIERS

Apathy and anhedonia are common syndromes of motivation that are associated with a wide range of brain disorders and have no established therapies. Research using animal models suggests that a useful framework for understanding motivated behaviour lies in effort-based decision making for reward. The neurobiological mechanisms underpinning such decisions have now begun to be determined in individuals with apathy or anhedonia, providing an important foundation for developing new treatments. The findings suggest that there might be some shared mechanisms between both syndromes. A transdiagnostic approach that cuts across traditional disease boundaries provides a potentially useful means for understanding these conditions

Measuring cognitive effort without difficulty

An important finding in the cognitive effort literature has been that sensitivity to the costs of effort varies between individuals, suggesting that some people find effort more aversive than others. It has been suggested this may explain individual differences in other aspects of cognition; in particular that greater effort sensitivity may underlie some of the symptoms of conditions such as depression and schizophrenia. In this paper, we highlight a major problem with existing measures of cognitive effort that hampers this line of research, specifically the confounding of effort and difficulty. This means that behaviour thought to reveal effort costs could equally be explained by cognitive capacity, which influences the frequency of success and thereby the chance of obtaining reward. To address this shortcoming, we introduce a new test, the Number Switching Task (NST), specially designed such that difficulty will be unaffected by the effort manipulation and can easily be standardised across participants. In a large, online sample, we show that these criteria are met successfully and reproduce classic effort discounting results with the NST. We also demonstrate the use of Bayesian modelling with this task, producing behavioural parameters which can be associated with other measures, and report a preliminary association with the Need for Cognition scale

Adaptation of social and non-social cues to direction in adults with autism spectrum disorder and neurotypical adults with autistic traits

Perceptual constancy strongly relies on adaptive gain control mechanisms, which shift perception as a function of recent sensory history. Here we examined the extent to which individual differences in magnitude of adaptation aftereffects for social and non-social directional cues are related to autistic traits and sensory sensitivity in healthy participants (Experiment 1); and also whether adaptation for social and non-social directional cues is differentially impacted in adults with Autism Spectrum Disorder (ASD) relative to neurotypical (NT) controls (Experiment 2). In Experiment 1, individuals with lower susceptibility to adaptation aftereffects, i.e. more 'veridical' perception, showed higher levels of autistic traits across social and non-social stimuli. Furthermore, adaptation aftereffects were predictive of sensory sensitivity. In Experiment 2, only adaptation to eye-gaze was diminished in adults with ASD, and this was related to difficulties categorizing eye-gaze direction at baseline. Autism Diagnostic Observation Schedule (ADOS) scores negatively predicted lower adaptation for social (head and eye-gaze direction) but not non-social (chair) stimuli. These results suggest that the relationship between adaptation and the broad socio-cognitive processing style captured by 'autistic traits' may be relatively domain-general, but in adults with ASD diminished adaptation is only apparent where processing is most severely impacted, such as the perception of social attention cues

Enhanced Risk Aversion, But Not Loss Aversion, in Unmedicated Pathological Anxiety.

BACKGROUND: Anxiety disorders are associated with disruptions in both emotional processing and decision making. As a result, anxious individuals often make decisions that favor harm avoidance. However, this bias could be driven by enhanced aversion to uncertainty about the decision outcome (e.g., risk) or aversion to negative outcomes (e.g., loss). Distinguishing between these possibilities may provide a better cognitive understanding of anxiety disorders and hence inform treatment strategies. METHODS: To address this question, unmedicated individuals with pathological anxiety (n = 25) and matched healthy control subjects (n = 23) completed a gambling task featuring a decision between a gamble and a safe (certain) option on every trial. Choices on one type of gamble-involving weighing a potential win against a potential loss (mixed)-could be driven by both loss and risk aversion, whereas choices on the other type-featuring only wins (gain only)-were exclusively driven by risk aversion. By fitting a computational prospect theory model to participants' choices, we were able to reliably estimate risk and loss aversion and their respective contribution to gambling decisions. RESULTS: Relative to healthy control subjects, pathologically anxious participants exhibited enhanced risk aversion but equivalent levels of loss aversion. CONCLUSIONS: Individuals with pathological anxiety demonstrate clear avoidance biases in their decision making. These findings suggest that this may be driven by a reduced propensity to take risks rather than a stronger aversion to losses. This important clarification suggests that psychological interventions for anxiety should focus on reducing risk sensitivity rather than reducing sensitivity to negative outcomes per se

Models of affective decision-making: how do feelings predict choice?

Intuitively, how we feel about potential outcomes will determine our decisions. Indeed, one of the most influential theories in psychology, Prospect Theory, implicitly assumes that feelings govern choice. Surprisingly, however, we know very little about the rules by which feelings are transformed into decisions. Here, we characterize a computational model that uses feelings to predict choice. We reveal that this model predicts choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to Prospect Theory value function, feelings showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighed when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision

Modeling Avoidance in Mood and Anxiety Disorders Using Reinforcement Learning.

BACKGROUND: Serious and debilitating symptoms of anxiety are the most common mental health problem worldwide, accounting for around 5% of all adult years lived with disability in the developed world. Avoidance behavior-avoiding social situations for fear of embarrassment, for instance-is a core feature of such anxiety. However, as for many other psychiatric symptoms the biological mechanisms underlying avoidance remain unclear. METHODS: Reinforcement learning models provide formal and testable characterizations of the mechanisms of decision making; here, we examine avoidance in these terms. A total of 101 healthy participants and individuals with mood and anxiety disorders completed an approach-avoidance go/no-go task under stress induced by threat of unpredictable shock. RESULTS: We show an increased reliance in the mood and anxiety group on a parameter of our reinforcement learning model that characterizes a prepotent (Pavlovian) bias to withhold responding in the face of negative outcomes. This was particularly the case when the mood and anxiety group was under stress. CONCLUSIONS: This formal description of avoidance within the reinforcement learning framework provides a new means of linking clinical symptoms with biophysically plausible models of neural circuitry and, as such, takes us closer to a mechanistic understanding of mood and anxiety disorders

Risk-taking to obtain reward: sex differences and associations with emotional and depressive symptoms in a nationally representative cohort of UK adolescents

BACKGROUND: Cognitive mechanisms that characterize or precede depressive symptoms are poorly understood. We investigated cross-sectional and longitudinal associations between risk taking to obtain reward and adolescent depressive symptoms in a large prospective cohort, using the Cambridge Gambling Task (CGT). We also explored sex differences. METHODS: The Millennium Cohort Study (MCS) is an ongoing UK study, following the lives of 19 000 individuals born 2000/02. The CGT was completed at ages 11 (n = 12 355) and 14 (n = 10 578). Our main exposure was the proportion of points gambled, when the odds of winning were above chance (risk-taking to obtain reward). Outcomes were emotional symptoms (Strengths and Difficulties Questionnaire, SDQ) at age 11 and depressive symptoms (short Mood and Feelings Questionnaire, sMFQ) at age 14. We calculated cross-sectional and longitudinal associations, using linear regressions. RESULTS: In univariable models, there was evidence of cross-sectional associations between risk-taking and SDQ/sMFQ scores, but these associations disappeared after we adjusted for sex. Longitudinally, there was weak evidence of an association between risk-taking and depressive symptoms in females only [a 20-point increase in risk-taking at age 11 was associated with a reduction of 0.31 sMFQ points at age 14 (95% CI -0.60 to -0.02)]. At both time-points, females were less risk-taking than males. CONCLUSIONS: We found no convincing evidence of a relationship between risk-taking to obtain reward and depressive symptoms. There were large sex differences in risk-taking, but these do not appear to contribute to the female preponderance of depressive symptoms in adolescence

Recall bias during adolescence: Gender differences and associations with depressive symptoms

Background: There is a sharp increase in depression in females in mid-adolescence, but we do not understand why. Cognitive theories suggest that people with depression have negative biases in recalling self-referential information. We tested whether recall biases were more negative in girls in early and mid-adolescence and were associated with depressive symptoms. Methods: 315 young and 263 mid-adolescents (11-12 and 13-15 years) completed a surprise test, assessing recall of social evaluation about the self (self-referential) or another person (other-referential). The short Mood and Feelings Questionnaire measured depressive symptoms. We tested the effects of condition (self-referential/otherreferential), valence (positive/negative), gender, and age group on correct recall (hits) and associations with depressive symptoms. Results: There was no evidence for gender or age differences in positive or negative self-referential recall. Selfreferential positive hits were negatively associated with depressive symptoms (adjusted coefficient=-0.38, 95% CI=-0.69–0.08, p=0.01). Self-referential negative hits were positively associated with depressive symptoms (adjusted coefficient=0.45, 95% CI=0.15-0.75, p=0.003), and this association was stronger in females (adjusted interaction p=0.04). Limitations: The reliability and validity of the recall task are unknown. We cannot provide evidence of a causal effect of recall on depressive symptoms in this cross-sectional study. Conclusions: Adolescents who recalled more self-referential negative and fewer self-referential positive words had more severe depressive symptoms. Females did not demonstrate more recall biases, but the association between self-referential negative hits and depressive symptoms was stronger in females. Negative self-referential recall may be a risk factor for depressive symptoms and is a good candidate for longitudinal studies