Can We Infer Inter-Individual Differences in Risk-Taking From Behavioral Tasks?

Test-retest reliability of reinforcement learning parameters

It has recently been suggested that parameter estimates of computational models can be used to understand individual differences at the process level. One area of research in which this approach, called computational phenotyping, has taken hold is computational psychiatry. One requirement for successful computational phenotyping is that behavior and parameters are stable over time. Surprisingly, the test-retest reliability of behavior and model parameters remains unknown for most experimental tasks and models. The present study seeks to close this gap by investigating the test-retest reliability of canonical reinforcement learning models in the context of two often-used learning paradigms: a two-armed bandit and a reversal learning task. We tested independent cohorts for the two tasks (N = 69 and N = 47) via an online testing platform with a between-test interval of five weeks. Whereas reliability was high for personality and cognitive measures (with ICCs ranging from .67 to .93), it was generally poor for the parameter estimates of the reinforcement learning models (with ICCs ranging from .02 to .52 for the bandit task and from .01 to .71 for the reversal learning task). Given that simulations indicated that our procedures could detect high test-retest reliability, this suggests that a significant proportion of the variability must be ascribed to the participants themselves. In support of that hypothesis, we show that mood (stress and happiness) can partly explain within-participant variability. Taken together, these results are critical for current practices in computational phenotyping and suggest that individual variability should be taken into account in the future development of the field.

Reliable, rapid, and remote measurement of metacognitive bias

Metacognitive biases have been repeatedly associated with transdiagnostic psychiatric dimensions of 'anxious-depression' and 'compulsivity and intrusive thought', cross-sectionally. To progress our understanding of the underlying neurocognitive mechanisms, new methods are required to measure metacognition remotely, within individuals over time. We developed a gamified smartphone task designed to measure visuo-perceptual metacognitive (confidence) bias and investigated its psychometric properties across two studies (N = 3410 unpaid citizen scientists, N = 52 paid participants). We assessed convergent validity, split-half and test-retest reliability, and identified the minimum number of trials required to capture its clinical correlates. Convergent validity of metacognitive bias was moderate (r(50) = 0.64, p < 0.001) and it demonstrated excellent split-half reliability (r(50) = 0.91, p < 0.001). Anxious-depression was associated with decreased confidence (β =  - 0.23, SE = 0.02, p < 0.001), while compulsivity and intrusive thought was associated with greater confidence (β = 0.07, SE = 0.02, p < 0.001). The associations between metacognitive biases and transdiagnostic psychiatry dimensions are evident in as few as 40 trials. Metacognitive biases in decision-making are stable within and across sessions, exhibiting very high test-retest reliability for the 100-trial (ICC = 0.86, N = 110) and 40-trial (ICC = 0.86, N = 120) versions of Meta Mind. Hybrid 'self-report cognition' tasks may be one way to bridge the recently discussed reliability gap in computational psychiatry.

Impulsivity is a stable, measurable, and predictive psychological trait

Impulsivity is a personality construct frequently employed to explain and predict important human behaviors. Major inconsistencies in its definition and measurement, however, have led some researchers to call for an outright rejection of impulsivity as a psychological construct. We address this highly unsatisfactory state with a large-scale, preregistered study (N = 1,676) in which each participant completed 48 measures of impulsivity derived from 10 self-report scales and 10 behavioral tasks and reported frequencies of seven impulsivity-related behaviors (e.g., impulsive buying and social media usage); a subsample (N = 196) then completed a retest session 3 mo later. We found that correlations between self-report measures were substantially higher than those between behavioral tasks and between self-report measures and behavioral tasks. Bifactor analysis of these measures exacted one general factor of impulsivity I, akin to the general intelligence factor g, and six specific factors. Factor I was related mainly to self-report measures, had high test-retest reliability, and could predict impulsivity-related behaviors better than existing measures. We further developed a scale named the adjustable impulsivity scale (AIMS) to measure I. AIMS possesses excellent psychometric properties that are largely retained in shorter versions and could predict impulsivity-related behaviors equally well as I. These findings collectively support impulsivity as a stable, measurable, and predictive trait, indicating that it may be too early to reject it as a valid and useful psychological construct. The bifactorial structure of impulsivity and AIMS, meanwhile, significantly advance the conceptualization and measurement of construct impulsivity.

Promoting Psychological Well-being in Preschoolers Through Mindfulness-based Socio-emotional Learning: A Randomized-controlled Trial

Mental health issues in children and young people are frequent and can have enduring negative consequences. Preventive early interventions delivered at school may foster psychological well-being, and preliminary evidence suggests that mindfulness-based social and emotional learning (SEL) interventions have positive effects on children's mental health. The aim of this study was to evaluate a mindfulness-based SEL curriculum including a French adaptation of the Kindness Curriculum (KC), delivered by pre-kindergarten teachers, in a cluster randomized control trial. Sixty-four classes (761 children, aged 38-58 months) from a socio-economically disadvantaged area in France were randomly assigned to either intervention or waiting-list control conditions. Indicators of children's mental health, self-management, positive relationships with teachers and peers, emotional processing and executive functioning were collected through teacher-rated questionnaires, standardized observations, and behavioral tasks. Results in the whole sample indicated a positive effect of the intervention on children's mental health, including a reduction in emotional, conduct and peer relationship problems, and a reduction in teacher-child conflicts. No significant effects were found on the other indicators. Heterogeneity analyses revealed stronger effects of the intervention on several indicators for children who had a teacher with lower level of teaching experience, for children with lower baseline mental health and for older children. This program therefore appears as a promising early school-based intervention promoting mental health and positive relationships, especially in a subgroup of at-risk preschool-aged children.

Performing well but not appreciating it - A trait feature of anorexia nervosa

Background

Despite advances in the etiology of anorexia nervosa (AN), a large subgroup of individuals does not profit optimally from treatment. Perfectionism has been found to be a risk factor predicting the onset, severity, and duration of AN episodes. To date, perfectionism has been studied predominantly by the use of self-report questionnaires, a useful approach that may, however, be impacted by demand characteristics, or other distortions of introspective or metacognitive access.

Methods

Here we circumvent these problems via a behavioral paradigm in which participants perform a modified Go/NoGo task, whilst self-evaluating their performance. We compared a group of 33 adolescent females during their first episode of AN (age = 16.0) with 29 female controls (age = 16.2), and 23 adolescent girls recovered from AN (age = 18.3) with 23 female controls (age = 18.5). The controls were closely matched by intelligence quotient and age to the two clinical groups.

Results

First-episode AN and control participants performed equally well on the task (reaction time and errors of commission), whereas the recovered group displayed significantly faster reaction times but incurred the same error rate. Despite performing at least as good as and predominantly better than control groups, both clinical groups evaluated their performances more negatively than controls.

Conclusion

We offer a novel behavioral method for measuring perfectionism independent of self-report, and we provide tentative evidence that this behavioral manifestation of perfectionism is evident during first-episode AN and persists even after recovery.

Investigating the relationship between self-reported interoceptive experience and risk propensity

Risky behaviour may be associated with visceral experiences, such as increased heart rate. Previous studies examining the relationship between perception of such signals (interoception) and risk-taking typically used behavioural tasks with potential for monetary reward. This approach may be less informative for understanding general risk propensity. In addition, such research does not usually consider the varied ways individuals engage with interoceptive signals. However, examining these different forms of engagement may help us understand how subjective experience of interoception influences risk-taking. As such, we performed two surveys (n = 471, primarily young adults) to examine the relationship between self-reported engagement with interoceptive signals (measured using the Multidimensional Assessment of Interoceptive Awareness) and a generalised measure of risk propensity (the General Risk Propensity Scale). Results indicated that different ways of interpreting or engaging with interoceptive signals were differentially associated with risk propensity. In particular, they provide preliminary evidence that those with the ability to ignore or not worry about visceral signals when they are uncomfortable display greater risk propensity (and these effects may possibly be gender-specific).

Decision-making under risk and ambiguity in adults with Tourette syndrome

BACKGROUND

Tourette syndrome (TS) as well as its most common comorbidities are associated with a higher propensity for risky behaviour in everyday life. However, it is unclear whether this increased risk propensity in real-life contexts translates into a generally increased attitude towards risk. We aimed to assess decision-making under risk and ambiguity based on prospect theory by considering the effects of comorbidities and medication.

METHODS

Fifty-four individuals with TS and 32 healthy controls performed risk and ambiguity decision-making tasks under both gains and losses conditions. Behavioural and computational parameters were evaluated using (i) univariate analysis to determine parameters difference taking independently; (ii) supervised multivariate analysis to evaluate whether our parameters could jointly account for between-group differences (iii) unsupervised multivariate analysis to explore the potential presence of sub-groups.

RESULTS

Except for general 'noisier' (less consistent) decisions in TS, we showed no specific risk-taking behaviour in TS or any relation with tics severity or antipsychotic medication. However, the presence of comorbidities was associated with distortion of decision-making. Specifically, TS with obsessive-compulsive disorder comorbidity was associated with a higher risk-taking profile to increase gain and a higher risk-averse profile to decrease loss. TS with attention-deficit hyperactivity disorder comorbidity was associated with risk-seeking in the ambiguity context to reduce a potential loss.

CONCLUSIONS

Impaired valuation of risk and ambiguity was not related to TS per se. Our findings are important for clinical practice: the involvement of individuals with TS in real-life risky situations may actually rather result from other factors such as psychiatric comorbidities.

Challenges and Solutions to the Measurement of Neurocognitive Mechanisms in Developmental Settings

Identifying early neurocognitive mechanisms that confer risk for mental health problems is one important avenue as we seek to develop successful early interventions. Currently, however, we have limited understanding of the neurocognitive mechanisms involved in shaping mental health trajectories from childhood through young adulthood, and this constrains our ability to develop effective clinical interventions. In particular, there is an urgent need to develop more sensitive, reliable, and scalable measures of individual differences for use in developmental settings. In this review, we outline methodological shortcomings that explain why widely used task-based measures of neurocognition currently tell us little about mental health risk. We discuss specific challenges that arise when studying neurocognitive mechanisms in developmental settings, and we share suggestions for overcoming them. We also propose a novel experimental approach-which we refer to as "cognitive microscopy"-that involves adaptive design optimization, temporally sensitive task administration, and multilevel modeling. This approach addresses some of the methodological shortcomings outlined above and provides measures of stability, variability, and developmental change in neurocognitive mechanisms within a multivariate framework.

ReX: an integrative tool for quantifying and optimizing measurement reliability for the study of individual differences

Characterizing multifaceted individual differences in brain function using neuroimaging is central to biomarker discovery in neuroscience. We provide an integrative toolbox, Reliability eXplorer (ReX), to facilitate the examination of individual variation and reliability as well as the effective direction for optimization of measuring individual differences in biomarker discovery. We also illustrate gradient flows, a two-dimensional field map-based approach to identifying and representing the most effective direction for optimization when measuring individual differences, which is implemented in ReX.

Individual differences in computational psychiatry: a review of current challenges

Bringing precision to the understanding and treatment of mental disorders requires instruments for studying clinically relevant individual differences. One promising approach is the development of computational assays: integrating computational models with cognitive tasks to infer latent patient-specific disease processes in brain computations. While recent years have seen many methodological advancements in computational modelling and many cross-sectional patient studies, much less attention has been paid to basic psychometric properties (reliability and construct validity) of the computational measures provided by the assays. In this review, we assess the extent of this issue by examining emerging empirical evidence. We find that many computational measures suffer from poor psychometric properties, which poses a risk of invalidating previous findings and undermining ongoing research efforts using computational assays to study individual (and even group) differences. We provide recommendations for how to address these problems and, crucially, embed them within a broader perspective on key developments that are needed for translating computational assays to clinical practice.

Reliability of Decision-Making and Reinforcement Learning Computational Parameters

Computational models can offer mechanistic insight into cognition and therefore have the potential to transform our understanding of psychiatric disorders and their treatment. For translational efforts to be successful, it is imperative that computational measures capture individual characteristics reliably. Here we examine the reliability of reinforcement learning and economic models derived from two commonly used tasks. Healthy individuals (N = 50) completed a restless four-armed bandit and a calibrated gambling task twice, two weeks apart. Reward and punishment learning rates from the reinforcement learning model showed good reliability and reward and punishment sensitivity from the same model had fair reliability; while risk aversion and loss aversion parameters from a prospect theory model exhibited good and excellent reliability, respectively. Both models were further able to predict future behaviour above chance within individuals. This prediction was better when based on participants' own model parameters than other participants' parameter estimates. These results suggest that reinforcement learning, and particularly prospect theory parameters, as derived from a restless four-armed bandit and a calibrated gambling task, can be measured reliably to assess learning and decision-making mechanisms. Overall, these findings indicate the translational potential of clinically-relevant computational parameters for precision psychiatry.

Variability in repeated economic games: comparing trust game decisions to other social trust measures

Economic games are well-established tools that offer a convenient approach to study social behaviour. Although widely used, recent evidence suggests that decisions made in the context of standard economic games are less predictive of real-world behaviour than previously assumed self-reported questionnaires. A possible explanation for this discrepancy is that economic games decisions in the laboratory are more likely to be influenced by the current situation, while questionnaires are specifically designed to measure people's average behaviour across a long period of time. To test this hypothesis, we performed a longitudinal study where 275 respondents played 16 Trust games every two days within a three-week period, and filled out a questionnaire that measures social trust. This study confirmed the instability of our measure of trust behaviour over time and the substantial stability of questionnaire responses. However, we found a significant association between self-reported social trust and participants' average behaviour in the trust game measured across sessions, but also with participants' behaviour measured only in Session 1. Nevertheless, analysis of behavioural changes in the Trust games over time revealed different behavioural profiles, highlighting how economic games and questionnaires can complement each other in the study of social trust.

Relating psychiatric symptoms and self-regulation during the COVID-19 crisis

Disruptions of self-regulation are a hallmark of numerous psychiatric disorders. Here, we examine the relationship between transdiagnostic dimensions of psychopathology and changes in self-regulation in the early phase of the COVID-19 pandemic. We used a data-driven approach on a large number of cognitive tasks and self-reported surveys in training datasets. Then, we derived measures of self-regulation and psychiatric functioning in an independent population sample (N = 102) tested both before and after the onset of the COVID-19 pandemic, when the restrictions in place represented a threat to mental health and forced people to flexibly adjust to modifications of daily routines. We found independent relationships between transdiagnostic dimensions of psychopathology and longitudinal alterations in specific domains of self-regulation defined using a diffusion decision model. Compared to the period preceding the onset of the pandemic, a symptom dimension related to anxiety and depression was characterized by a more cautious behavior, indexed by the need to accumulate more evidence before making a decision. Instead, social withdrawal related to faster non-decision processes. Self-reported measures of self-regulation predicted variance in psychiatric symptoms both concurrently and prospectively, revealing the psychological dimensions relevant for separate transdiagnostic dimensions of psychiatry, but tasks did not. Taken together, our results are suggestive of potential cognitive vulnerabilities in the domain of self-regulation in people with underlying psychiatric difficulties in face of real-life stressors. More generally, they also suggest that the study of cognition needs to take into account the dynamic nature of real-world events as well as within-subject variability over time.

Probabilistic Decision-Making in Children With Dyslexia

Background

Neurocognitive mechanisms underlying developmental dyslexia (dD) remain poorly characterized apart from phonological and/or visual processing deficits. Assuming such deficits, the process of learning complex tasks like reading requires the learner to make decisions (i.e., word pronunciation) based on uncertain information (e.g., aberrant phonological percepts)-a cognitive process known as probabilistic decision making, which has been linked to the striatum. We investigate (1) the relationship between dD and probabilistic decision-making and (2) the association between the volume of striatal structures and probabilistic decision-making in dD and typical readers.

Methods

Twenty four children diagnosed with dD underwent a comprehensive evaluation and MRI scanning (3T). Children with dD were compared to age-matched typical readers (n = 11) on a probabilistic, risk/reward fishing task that utilized a Bayesian cognitive model with game parameters of risk propensity (γ+) and behavioral consistency (β), as well as an overall adjusted score (average number of casts, excluding forced-fail trials). Volumes of striatal structures (caudate, putamen, and nucleus accumbens) were analyzed between groups and associated with game parameters.

Results

dD was associated with greater risk propensity and decreased behavioral consistency estimates compared to typical readers. Cognitive model parameters associated with timed pseudoword reading across groups. Risk propensity related to caudate volumes, particularly in the dD group.

Conclusion

Decision-making processes differentiate dD, associate with the caudate, and may impact learning mechanisms. This study suggests the need for further research into domain-general probabilistic decision-making in dD, neurocognitive mechanisms, and targeted interventions in dD.

Simple questionnaires outperform behavioral tasks to measure socio-emotional skills in students

Recent empirical research has shown that improving socio-emotional skills such as grit, conscientiousness and self-control leads to higher academic achievement and better life outcomes. However, both theoretical and empirical works have raised concerns about the reliability of the different methods used to measure socio-emotional skills. We compared the reliability and validity of the three leading measurements methods—a student-reported questionnaire, a teacher-reported questionnaire, and a behavioral task—in a sample of 3997 French students. Before analyzing the data, we polled 114 international researchers in cognitive development and education economics; most researchers in both fields predicted that the behavioral task would be the best method. We found instead that the teacher questionnaire was more predictive of students’ behavioral outcomes and of their grade progression, while the behavioral task was the least predictive. This work suggests that researchers may not be using optimal tools to measure socio-emotional skills in children.

Adolescent decision making: A decade in review

Research in the past decade has highlighted the nuances of adolescent decision making. In this review article, we summarize several themes evident in the field of developmental science including the redefinition of adolescence and the ways in which adolescent decision-making capabilities converge with or diverge from those of adults. While the decision-making process is similar for adolescents and adults in contexts that encourage deliberation and reflection, adolescents and adults differ in contexts which preclude deliberation vis-à-vis high emotional arousal. We also discuss the reconceptualization of adolescent behavior, including risk taking, as adaptive. That is, characteristics of adolescence, including impulsivity, the importance of peers, and novelty seeking, are normative, evolutionarily advantageous, and essential for positive development. While these features manifest in negative, health-compromising ways (e.g., risky driving and criminal behavior), they also foster growth and exploration. We conclude with a discussion of potential avenues for future research.

Economic decision-making in the continuum between healthy aging and Alzheimer's Disease: A systematic review of 20 years of research

The effect of pathological aging on economic decision-making is a topic of major relevance as impairments in this domain place older adults at increased risk for financial abuse. This review aims to characterize decision-making across the continuum that goes from healthy aging to Alzheimer's Dementia. We included 42 studies comparing patients with Mild Cognitive Impairment (MCI) and healthy older adults, patients with Alzheimer's Disease (AD) and healthy older adults, and patients with MCI and patients with AD. Substantial evidence emerged suggesting that both MCI as AD affect economic decision-making. However, a non-negligible number of behavioural tasks failed to find significant differences between patients and controls, and no differences were reported between patients with MCI and AD. On the contrary, measures of financial capacity reached more robust findings, showing that healthy older adults had better performance than patients, while MCI patients showed better performance than AD patients. This review presents the main conclusions that may be drawn from significant findings, as well as the hypotheses and recommendations for future research.

Ergodicity-breaking reveals time optimal decision making in humans

Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theories of decision-making reveal how individuals should tolerate risk in different environments. To optimize wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing decision theories. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximize the time average growth of in-game wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations.

Childhood environmental adversity is not linked to lower levels of cooperative behaviour in economic games

Cooperation is a universal phenomenon, it is present in all human cultures from hunter-gatherers to industrialised societies, and it constitutes a fundamental aspect of social relationships. There is, however, variability in the amount of resources people invest in cooperative activities. Recent findings indicate that this variability may be partly explained as a contextually appropriate response to environmental conditions. Specifically, adverse environments seem to be associated with less cooperation and recent findings suggest that this effect is partly mediated by differences in individuals' life-history strategy. In this paper, we set out to replicate and extend these findings by measuring actual cooperative behaviour in three economic games - a Dictator game, a Trust game and a Public Goods game - on a nationally representative sample of 612 people. Although we found that the cooperation and life-history strategy latent variables were adequately captured by the models, the hypothesised relationship between childhood environmental adversity and adult cooperation and the mediation effect by life-history strategy were not found.

Compulsivity and impulsivity traits linked to attenuated developmental frontostriatal myelination trajectories

The transition from adolescence to adulthood is a period when ongoing brain development coincides with a substantially increased risk of psychiatric disorders. The developmental brain changes accounting for this emergent psychiatric symptomatology remain obscure. Capitalizing on a unique longitudinal dataset that includes in vivo myelin-sensitive magnetization transfer (MT) MRI scans, we show that this developmental period is characterized by brain-wide growth in MT trajectories within both gray matter and adjacent juxtacortical white matter. In this healthy population, the expression of common developmental traits, namely compulsivity and impulsivity, is tied to a reduced growth of these MT trajectories in frontostriatal regions. This reduction is most marked in dorsomedial and dorsolateral prefrontal regions for compulsivity and in lateral and medial prefrontal regions for impulsivity. These findings highlight that psychiatric traits of compulsivity and impulsivity are linked to regionally specific reductions in myelin-related growth in late adolescent brain development.