How to support peer resistance in adolescents with mild-to-borderline intellectual disability? Intervention development and feasibility.

BACKGROUND: Adolescents with mild-to-borderline intellectual disability face peer resistance challenges, risking harmful or dangerous situations. METHOD: We designed a peer resistance group intervention at school for adolescents with mild-to-borderline intellectual disability, tested its feasibility (N = 4, Mage = 14.1, MIQ = 78.8), adapted it, and tested it again (N = 6, Mage = 15.0, MIQ = 72.8). RESULTS: Study 1 demonstrated feasibility in recruitment, resources, and potential benefits on the distal outcome risk taking. However, attendance, obtained knowledge, and potential benefits on peer resistance, peer problems, and prosocial behaviour were suboptimal. Consequently, study 2 contained more learning by doing and individual lessons, resulting in higher attendance and greater personalization. While potential benefits on improved peer resistance measures were not observed, risk taking improved. CONCLUSIONS: Despite finding no potential benefits on peer resistance, running a peer resistance intervention for adolescents with mild-to-borderline intellectual disability at school is considered feasible.

Uncertainty-driven regulation of learning and exploration in adolescents: A computational account.

Healthy adults flexibly adapt their learning strategies to ongoing changes in uncertainty, a key feature of adaptive behaviour. However, the developmental trajectory of this ability is yet unknown, as developmental studies have not incorporated trial-to-trial variation in uncertainty in their analyses or models. To address this issue, we compared adolescents' and adults' trial-to-trial dynamics of uncertainty, learning rate, and exploration in two tasks that assess learning in noisy but otherwise stable environments. In an estimation task-which provides direct indices of trial-specific learning rate-both age groups reduced their learning rate over time, as self-reported uncertainty decreased. Accordingly, the estimation data in both groups was better explained by a Bayesian model with dynamic learning rate (Kalman filter) than by conventional reinforcement-learning models. Furthermore, adolescents' learning rates asymptoted at a higher level, reflecting an over-weighting of the most recent outcome, and the estimated Kalman-filter parameters suggested that this was due to an overestimation of environmental volatility. In a choice task, both age groups became more likely to choose the higher-valued option over time, but this increase in choice accuracy was smaller in the adolescents. In contrast to the estimation task, we found no evidence for a Bayesian expectation-updating process in the choice task, suggesting that estimation and choice tasks engage different learning processes. However, our modeling results of the choice task suggested that both age groups reduced their degree of exploration over time, and that the adolescents explored overall more than the adults. Finally, age-related differences in exploration parameters from fits to the choice data were mediated by participants' volatility parameter from fits to the estimation data. Together, these results suggest that adolescents overestimate the rate of environmental change, resulting in elevated learning rates and increased exploration, which may help understand developmental changes in learning and decision-making.

Effects of advice on experienced-based learning in adolescents and adults.

Recent studies that compared effects of pre-learning advice on experience-based learning in adolescents and adults have yielded mixed results. Previous studies on this topic used choice tasks in which age-related differences in advice-related learning bias and exploratory choice behavior are difficult to dissociate. Moreover, these studies did not examine whether effects of advice depend on working memory load. In this preregistered study (in adolescents [13-15 years old] and adults [18-31 years old]), we addressed these issues by factorially combining advice and working memory load manipulations in an estimation task that does not require choices and hence eliminates the influence of known age-related differences in exploration. We found that advice guided participants' initial estimates in both age groups. When advice was correct, this improved estimation performance, especially in adolescents when working memory load was high. When advice was incorrect, it had a longer-lasting effect on adolescents' performance than on adults' performance. In contrast to previous findings in choice tasks, we found no evidence that advice biased learning in either age group. Taken together, our results suggest that learning in an estimation task improves between adolescence and adulthood but that the effects of advice on learning do not differ substantially between adolescents and adults.

Quantitative or qualitative development in decision making?

A key question in the developmental sciences is whether developmental differences are quantitative or qualitative. For example, does age increase the speed in processing a task (quantitative differences) or does age affect the way a task is processed (qualitative differences)? Until now, findings in the domain of decision making have been based on the assumption that developmental differences are either quantitative or qualitative. In the current study, we took a different approach in which we tested whether development is best described as being quantitative or qualitative. We administered a judgment version and a choice version of a decision-making task to a developmental sample (njudgment = 109 and nchoice = 137; Mage = 12.5 years, age range = 9-18). The task, the so-called Gambling Machine Task, required decisions between two options characterized by constant gains and probabilistic losses; these characteristics were known beforehand and thus did not need to be learned from experience. Data were analyzed by comparing the fit of quantitative and qualitative latent variable models, so-called multiple indicator multiple cause (MIMIC) models. Results indicated that individual differences in both judgment and choice tasks were quantitative and pertained to individual differences in "consideration of gains," that is, to what extent decisions were guided by gains. These differences were affected by age in the judgment version, but not in the choice version, of the task. We discuss implications for theories of decision making and discuss potential limitations and extensions. We also argue that the MIMIC approach is useful in other domains, for example, to test quantitative versus qualitative development of categorization, reasoning, math, and memory.

The importance of parental knowledge in the association between ADHD symptomatology and related domains of impairment.

Parents of children with ADHD experience several difficulties while raising their children and report lower levels of knowledge about their children's life and behaviors. A recent study found that low levels of parental knowledge mediated the association between ADHD symptoms and risk-taking behavior (RTB) in adolescents. The current study aimed to investigate this previous finding further by replicating it, by taking peer influence into account as additional social factor of importance and by extending it and also investigate the role of parental knowledge in the association between ADHD symptoms and homework problems. Three studies were performed: study 1 (N=234) replicated previous work on parental knowledge mediating the association between ADHD symptoms and RTB, study 2 (pre-registered, N=313) added peer influence, and study 3 (pre-registered, N=315) assessed whether parental knowledge mediated the association between ADHD symptoms and homework behavior. Parental knowledge consistently mediated the association between ADHD symptoms on one hand and RTB and homework problems on the other, and also predicted stronger resistance to peer influence. Because parental knowledge was repeatedly linked to ADHD-related problems, it seems promising to include parental knowledge in treatment of ADHD-related problems in adolescents, by improving the parent-child relationship. Future studies should test more directly how improvement of the parent-child relationship can be used to optimize parental knowledge, which in its turn reduces ADHD-related problems.

The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data.

Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology.

Are individual differences quantitative or qualitative? An integrated behavioral and fMRI MIMIC approach.

In cognitive neuroscience there is a growing interest in individual differences. We propose the Multiple Indicators Multiple Causes (MIMIC) model of combined behavioral and fMRI data to determine whether such differences are quantitative or qualitative in nature. A simulation study revealed the MIMIC model to have adequate power for this goal, and parameter recovery to be satisfactory. The MIMIC model was illustrated with a re-analysis of Van Duijvenvoorde et al. (2016) and Blankenstein et al. (2018) decision making data. This showed individual differences in Van Duijvenvoorde et al. (2016) to originate in qualitative differences in decision strategies. Parameters indicated some individuals to use an expected value decision strategy, while others used a loss minimizing strategy, distinguished by individual differences in vmPFC activity. Individual differences in Blankenstein et al. (2018) were explained by quantitative differences in risk aversion. Parameters showed that more risk averse individuals preferred safe over risky choices, as predicted by heightened vmPFC activity. We advocate using the MIMIC model to empirically determine, rather than assume, the nature of individual differences in combined behavioral and fMRI datasets.

Risk-Taking Behavior in Attention Deficit/Hyperactivity Disorder (ADHD): a Review of Potential Underlying Mechanisms and of Interventions.

PURPOSE OF REVIEW: Attention deficit/hyperactivity disorder (ADHD) is associated with several forms of risk-taking behavior (RTB). This paper aims to examine the scope of ADHD-related RTB, to highlight potential underlying mechanisms of this association, and to review initial evidence for interventions aimed to treat ADHD-related RTB. RECENT FINDINGS: Multiple lines of evidence indicate that ADHD is associated with real-life RTB across several domains (e.g., reckless driving, substance use, and unprotected sex), which is corroborated by evidence on laboratory risk-taking tasks. Several individual differences, some of them informed by decision theory, e.g., comorbid disorders, parental monitoring, and perceived enlarged benefits of RTB, may explain the link between ADHD and RTB. A number of studies showed that interventions designed for ADHD may reduce RTB. ADHD is linked to RTB across several domains. Decision theory may serve as a conceptual framework for understanding the underlying mechanisms, and thus may inform future research.

Time-on-task effects in children with and without ADHD: depletion of executive resources or depletion of motivation?

Children with attention-deficit/hyperactivity disorder (ADHD) are characterized by deficits in their executive functioning and motivation. In addition, these children are characterized by a decline in performance as time-on-task increases (i.e., time-on-task effects). However, it is unknown whether these time-on-task effects should be attributed to deficits in executive functioning or to deficits in motivation. Some studies in typically developing (TD) adults indicated that time-on-task effects should be interpreted as depletion of executive resources, but other studies suggested that they represent depletion of motivation. We, therefore, investigated, in children with and without ADHD, whether there were time-on-task effects on executive functions, such as inhibition and (in)attention, and whether these were best explained by depletion of executive resources or depletion of motivation. The stop-signal task (SST), which generates both indices of inhibition (stop-signal reaction time) and attention (reaction time variability and errors), was administered in 96 children (42 ADHD, 54 TD controls; aged 9-13). To differentiate between depletion of resources and depletion of motivation, the SST was administered twice. Half of the participants was reinforced during second task performance, potentially counteracting depletion of motivation. Multilevel analyses indicated that children with ADHD were more affected by time-on-task than controls on two measures of inattention, but not on inhibition. In the ADHD group, reinforcement only improved performance on one index of attention (i.e., reaction time variability). The current findings suggest that time-on-task effects in children with ADHD occur specifically in the attentional domain, and seem to originate in both depletion of executive resources and depletion of motivation. Clinical implications for diagnostics, psycho-education, and intervention are discussed.

Neural correlates of expected risks and returns in risky choice across development.

Adolescence is often described as a period of increased risk taking relative to both childhood and adulthood. This inflection in risky choice behavior has been attributed to a neurobiological imbalance between earlier developing motivational systems and later developing top-down control regions. Yet few studies have decomposed risky choice to investigate the underlying mechanisms or tracked their differential developmental trajectory. The current study uses a risk-return decomposition to more precisely assess the development of processes underlying risky choice and to link them more directly to specific neural mechanisms. This decomposition specifies the influence of changing risks (outcome variability) and changing returns (expected value) on the choices of children, adolescents, and adults in a dynamic risky choice task, the Columbia Card Task. Behaviorally, risk aversion increased across age groups, with adults uniformly risk averse and adolescents showing substantial individual differences in risk sensitivity, ranging from risk seeking to risk averse. Neurally, we observed an adolescent peak in risk-related activation in the anterior insula and dorsal medial PFC. Return sensitivity, on the other hand, increased monotonically across age groups and was associated with increased activation in the ventral medial PFC and posterior cingulate cortex with age. Our results implicate adolescence as a developmental phase of increased neural risk sensitivity. Importantly, this work shows that using a behaviorally validated decision-making framework allows a precise operationalization of key constructs underlying risky choice that inform the interpretation of results.

Neural Mechanisms Underlying Compensatory and Noncompensatory Strategies in Risky Choice.

Individuals may differ systematically in their applied decision strategies, which has critical implications for decision neuroscience but is yet scarcely studied. Our study's main focus was therefore to investigate the neural mechanisms underlying compensatory versus noncompensatory strategies in risky choice. Here, we compared people using a compensatory expected value maximization with people using a simplified noncompensatory loss-minimizing choice strategy. To this end, we used a two-choice paradigm including a set of "simple" items (e.g., simple condition), in which one option was superior on all attributes, and a set of "conflict" items, in which one option was superior on one attribute but inferior on other attributes. A binomial mixture analysis of the decisions elicited by these items differentiated between decision-makers using either a compensatory or a noncompensatory strategy. Behavioral differences were particularly pronounced in the conflict condition, and these were paralleled by neural results. That is, we expected compensatory decision-makers to use an integrated value comparison during choice in the conflict condition. Accordingly, the compensatory group tracked the difference in expected value between choice options reflected in neural activation in the parietal cortex. Furthermore, we expected noncompensatory, compared with compensatory, decision-makers to experience increased conflict when attributes provided conflicting information. Accordingly, the noncompensatory group showed greater dorsomedial PFC activation only in the conflict condition. These pronounced behavioral and neural differences indicate the need for decision neuroscience to account for individual differences in risky choice strategies and to broaden its scope to noncompensatory risky choice strategies.

Prevalence and diagnostic validity of motivational impairments and deficits in visuospatial short-term memory and working memory in ADHD subtypes.

Deficits in working memory (WM) and reinforcement sensitivity are thought to give rise to symptoms in the combined (ADHD-C) and inattentive subtype (ADHD-I) of ADHD. Children with ADHD are especially impaired on visuospatial WM, which is composed of short-term memory (STM) and a central executive. Although deficits in visuospatial WM and reinforcement sensitivity appear characteristic of children with ADHD on a group-level, the prevalence and diagnostic validity of these impairments is still largely unknown. Moreover, studies investigating this did not control for the interaction between motivational impairments and cognitive performance in children with ADHD, and did not differentiate between ADHD subtypes. Visuospatial WM and STM tasks were administered in a standard (feedback-only) and a high-reinforcement (feedback + 10 euros) condition, to 86 children with ADHD-C, 27 children with ADHD-I (restrictive subtype), and 62 typically developing controls (aged 8-12). Reinforcement sensitivity was indexed as the difference in performance between the reinforcement conditions. WM and STM impairments were most prevalent in ADHD-C. In ADHD-I, only WM impairments, not STM impairments, were more prevalent than in controls. Motivational impairments were not common (22% impaired) and equally prevalent in both subtypes. Memory and motivation were found to represent independent neuropsychological domains. Impairment on WM, STM, and/or motivation was associated with more inattention symptoms, medication-use, and lower IQ scores. Similar results were found for analyses of diagnostic validity. The majority of children with ADHD-C is impaired on visuospatial WM. In ADHD-I, STM impairments are not more common than in controls. Within both ADHD subtypes only a minority has an abnormal sensitivity to reinforcement.

What is and what could have been: experiencing regret and relief across childhood.

Counterfactual emotions, such as regret and relief, are considered important in daily-life choice behaviour, learning and emotion regulation. A prominent question is from which age counterfactual emotions develop. In this study, we compared a more "traditional" analysis with a latent-class analysis (LCA) that allows the study of individual differences and a more detailed assessment of counterfactual emotions. Four groups of children (5-6 years, 7-8 years, 9-10 years and 11-13 years) and a group of young adults performed a choice task in which they encountered a Regret situation (chosen option was worse than alternative), a Relief situation (chosen option was better than alternative) and a Baseline situation (chosen option was equal to alternative). Traditional analyses indicated regret and relief to be present from ages 7 to 8. In contrast, the LCA indicated that subgroups experiencing regret and relief were present in all age groups, although regret and relief subgroups increased with age. Moreover, analyses indicated that higher reasoning scores increased the probability to belong to regret and relief subgroups and that the experience of regret dependent on trial order, being more prominent in later trials. We conclude that an individual-difference approach can advance insight into emotional development.

Is the unconscious, if it exists, a superior decision maker?

Newell & Shanks (N&S) show that there is no convincing evidence that processes assumed to be unconscious and superior are indeed unconscious. We take their argument one step further by showing that there is also no convincing evidence that these processes are superior. We review alternative paradigms that may provide more convincing tests of the superiority of (presumed) unconscious processes.

What's in a name: The role of verbalization in reinforcement learning.

(e.g., characters or fractals) and concrete stimuli (e.g., pictures of everyday objects) are used interchangeably in the reinforcement-learning literature. Yet, it is unclear whether the same learning processes underlie learning from these different stimulus types. In two preregistered experiments (N = 50 each), we assessed whether abstract and concrete stimuli yield different reinforcement-learning performance and whether this difference can be explained by verbalization. We argued that concrete stimuli are easier to verbalize than abstract ones, and that people therefore can appeal to the phonological loop, a subcomponent of the working-memory system responsible for storing and rehearsing verbal information, while learning. To test whether this verbalization aids reinforcement-learning performance, we administered a reinforcement-learning task in which participants learned either abstract or concrete stimuli while verbalization was hindered or not. In the first experiment, results showed a more pronounced detrimental effect of hindered verbalization for concrete than abstract stimuli on response times, but not on accuracy. In the second experiment, in which we reduced the response window, results showed the differential effect of hindered verbalization between stimulus types on accuracy, not on response times. These results imply that verbalization aids learning for concrete, but not abstract, stimuli and therefore that different processes underlie learning from these types of stimuli. This emphasizes the importance of carefully considering stimulus types. We discuss these findings in light of generalizability and validity of reinforcement-learning research.

Formal models of "resource depletion".

The opportunity cost model (OCM) aims to explain various phenomena, among which the finding that performance degrades if executive functions are used repeatedly ("resource depletion"). We argue that an OCM account of resource depletion requires two unlikely assumptions, and we discuss an alternative that does not require these assumptions. This alternative model describes the interplay between executive function and motivation.

Raven's Standard Progressive Matrices for Adolescents: A Case for a Shortened Version.

Cognitive ability of adolescents is often measured using the Raven's Standard Progressive Matrices (RSPM). However, the RSPM knows a long administration time which may be suboptimal, as time-on-task effects are known to increase fatigue, to lower motivation, and to worsen performance on cognitive tasks. Therefore, a shortened version for adolescents was developed recently. In the current preregistered study we investigated this shortened version in a sample of adolescents (N = 99) of average educational backgrounds. We tested whether the shortened RSPM is a valid alternative to the original RSPM, which proved to be the case, as we observed a moderate to high correlation between the two versions. Moreover, we tested version effects on fatigue, motivation and performance. Fatigue was lower and motivation was higher after completing the short compared to the original version, and performance was better in the short compared to the original version. However, additional analyses suggested that beneficial version effects on performance were not due to reduced time-on-task, but due to the short version containing less difficult items than the original version. Moreover, version related differences in performance were not related to version related differences in fatigue and motivation. We conclude that the shortened version of the RSPM is a valid alternative to the original version, and that the shortened version is beneficial in terms of fatigue and motivation, but that these beneficial effects on fatigue and motivation do not carry over to performance.

Dopamine agonists and the suppression of impulsive motor actions in Parkinson disease.

The suppression of spontaneous motor impulses is an essential facet of cognitive control that is linked to frontal-BG circuitry. BG dysfunction caused by Parkinson disease (PD) disrupts the proficiency of action suppression, but how pharmacotherapy for PD impacts impulsive motor control is poorly understood. Dopamine agonists improve motor symptoms of PD but can also provoke impulsive-compulsive behaviors (ICB). We investigated whether dopamine agonist medication has a beneficial or detrimental effect on impulsive action control in 38 PD patients, half of whom had current ICB. Participants performed the Simon conflict task, which measures susceptibility to acting on spontaneous action impulses as well as the proficiency of suppressing these impulses. Compared with an off-agonist state, patients on their agonists were no more susceptible to reacting impulsively but were less proficient at suppressing the interference from the activation of impulsive actions. Importantly, agonist effects depended on baseline performance in the off-agonist state; more proficient suppressors off agonist experienced a reduction in suppression on agonist, whereas less-proficient suppressors off agonist showed improved suppression on agonist. Patients with active ICB were actually less susceptible to making fast, impulsive response errors than patients without ICB, suggesting that behavioral problems in this subset of patients may be less related to impulsivity in motor control. Our findings provide further evidence that dopamine agonist medication impacts specific cognitive control processes and that the direction of its effects depends on individual differences in performance off medication.

Development of decision making: sequential versus integrative rules.

Decisions can be made by applying a variety of decision-making rules-sequential rules in which decisions are based on a sequential evaluation of choice dimensions and the integrative normative rule in which decisions are based on an integration of choice dimensions. In this study, we investigated the developmental trajectory of such decision-making rules. In the Gambling Machine Task, participants choose between options that differ in three dimensions: frequency of loss, amount of loss, and certain gain. The task was administered to 231 children and adolescents (age range=8-17 years). Latent group analysis of their performance allowed precise classification of the underlying decision rules. The majority of participants used sequential decision rules, and the number of evaluated dimensions in these rules increased with age. Integrative rule use decreased with age. We discuss these results in light of traditional developmental theories and fuzzy trace theory.

Impaired learning to dissociate advantageous and disadvantageous risky choices in adolescents.

Adolescence is characterized by a surge in maladaptive risk-taking behaviors, but whether and how this relates to developmental changes in experience-based learning is largely unknown. In this preregistered study, we addressed this issue using a novel task that allowed us to separate the learning-driven optimization of risky choice behavior over time from overall risk-taking tendencies. Adolescents (12-17 years old) learned to dissociate advantageous from disadvantageous risky choices less well than adults (20-35 years old), and this impairment was stronger in early than mid-late adolescents. Computational modeling revealed that adolescents' suboptimal performance was largely due to an inefficiency in core learning and choice processes. Specifically, adolescents used a simpler, suboptimal, expectation-updating process and a more stochastic choice policy. In addition, the modeling results suggested that adolescents, but not adults, overvalued the highest rewards. Finally, an exploratory latent-mixture model analysis indicated that a substantial proportion of the participants in each age group did not engage in experience-based learning but used a gambler's fallacy strategy, stressing the importance of analyzing individual differences. Our results help understand why adolescents tend to make more, and more persistent, maladaptive risky decisions than adults when the values of these decisions have to be learned from experience.