The development of adaptive risk taking and the role of executive functions in a large sample of school-age boys and girls

Bell, Morris D.; Imal, Ahmet Esat; Pittman, Brian; Jin, Grace; Wexler, Bruce E.

doi:10.1016/j.tine.2019.100120

Cited by 16 publications

(14 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, an inconsistent strategy would be reflected by more random decisions (e.g., 5 pumps à 15 pumps à 2 pumps à 18 pumps …), resulting in a high COV and thus less strategic consistency. In line with these considerations, a higher COV in the BART has been associated with lower age and lower executive function capacity in school-age children (Bell et al, 2019), lower working memory capacity (Blair et al, 2018), lower functional (but not dysfunctional) impulsivity (Congdon et al, 2013), and a suboptimal strategy to gain rewards (Blair et al, 2018;DeMartini et al, 2014;Jentsch et al, 2010).…”

Section: Introductionmentioning

confidence: 78%

“…In addition to RT, we calculated a coefficient of variability (COV) as an inverse index of strategic consistency. COV is calculated as the standard deviation of pumps in the BART divided by average pumps (also see Bell et al, 2019;Blair et al, 2018;Congdon et al, 2013;DeMartini et al, 2014;Jentsch et al, 2010). A lower COV indicates consistent and strategic decision-making, whereas a higher COV indicates less consistent and less strategic decision-making.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Neural signatures of heterogeneity in risk‐taking and strategic consistency

Leota

Kleinert

Tran

et al. 2021

Eur J of Neuroscience

View full text Add to dashboard Cite

People display a high degree of heterogeneity in risk-taking behaviour, but this heterogeneity remains poorly understood. Here, we use a neural trait approach to examine if task-independent, brain-based differences can help uncover the sources of heterogeneity in risky decision-making. We extend prior research in two key ways. First, we disentangled risk-taking and strategic consistency using novel measures afforded by the Balloon Analogue Risk Task. Second, we applied a personality neuroscience framework to explore why personality traits are typically only weakly related to risk-taking behaviour. We regressed participants' (N = 104) source localized resting-state electroencephalographic activity on risk-taking and strategic consistency. Results revealed that higher levels of resting-state delta-band current density (reflecting reduced cortical activation) in the left dorsal anterior cingulate cortex and the left dorsolateral prefrontal cortex were associated with increased risk-taking and decreased strategic consistency, respectively. These results suggest that heterogeneity in risk-taking behaviour is associated with neural dispositions related to sensitivity to the risk of loss, whereas heterogeneity in strategic consistency is associated with neural dispositions related to strategic decision-making. Finally, extraversion, neuroticism, openness, and self-control were broadly associated with both of the identified neural traits, which in turn mediated indirect associations between personality traits and behavioural measures. These results provide an explanation for the weak direct relationships between personality traits and risk-taking behaviour, supporting a personality neuroscience framework of traits and decision-making.

show abstract

Section: Introductionmentioning

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Neural signatures of heterogeneity in risk‐taking and strategic consistency

Leota

Kleinert

Tran

et al. 2021

Eur J of Neuroscience

View full text Add to dashboard Cite

show abstract

“…In addition to the study on probabilistic learning in dD ( Gabay et al, 2015b ), limited evidence supports a link between adolescent risk-taking behaviors and learning disorders ( McNamara et al, 2008 ; Poon and Ho, 2016 ). However, risk-propensity in childhood has not been widely studied ( Bell et al, 2019 ) and to date no studies have examined risk-propensity in children with dD in the absence of ADHD. We propose that children with dD differ from typical readers in approach on the present task because they make different probabilistic assessments.…”

Section: Discussionmentioning

confidence: 99%

Probabilistic Decision-Making in Children With Dyslexia

Pereira

Zhou²,

Pitt³

et al. 2022

Front. Neurosci.

View full text Add to dashboard Cite

BackgroundNeurocognitive 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.MethodsTwenty 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.ResultsdD 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.ConclusionDecision-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.

show abstract

“…Using a slightly modified version of the BART for children (BART-C), we applied this approach to a sample of 6,267 children from kindergarten through eighth grade for whom we also had assessments of executive function. The sample included but was 50% larger than that of our previous report (25). Our goal was to determine if it was possible to identify and characterize children with maladaptive risktaking in elementary school to make possible targeted interventions that might help prevent maladaptive risk-taking behaviors in adolescence.…”

mentioning

confidence: 99%

“…For example, one child may consistently inflate balloons to 10 points, with 25 not popping (total score 250), and another child may achieve the same adjusted score of 10 points with five inflations to 15, five inflations to 5, and the rest popping (total score 100). In a previous report, Bell et al ( 25 ) addressed these problems in part by using a maladaptive risk‐taking or “recklessness” score, defined as the average of unpopped trials (adjusted score) minus the total points earned (total score). Children who had higher adjusted scores and lower total scores than their age‐matched peers were characterized as using a maladaptive risk‐taking strategy ( 25 ).…”

mentioning

confidence: 99%

Risk‐Taking Patterns of Children, Associated Cognitive Weaknesses, and Prevention of Negative Outcomes

Imal

O’Leary

Wexler

2020

PRCP

Self Cite

View full text Add to dashboard Cite

ObjectiveAccidents, drug use, and unsafe sex associated with greater propensity for risk‐taking are leading causes of illness and death among adolescents. This study aimed to help identify and further characterize children with maladaptive risk‐taking to improve primary prevention interventions.MethodsTwo scores from the Bubblegum Analog Risk‐Taking Task for Children (BART‐C), total points and average inflations of unpopped bubbles, were used in a cluster analysis to identify distinct patterns of risk‐taking among 6,267 kindergarten through eighth‐grade children. Clusters were compared with the Flanker Test of Focused Attention, the Go/No‐Go test of inhibition, and the List Sorting Working Memory Test.ResultsBoth BART‐C scores made significant (p<0.001) contributions in defining three clusters of children: reckless, risk avoidant, and adaptive risk‐taking. Clusters differed significantly on Flanker Test measures of incongruent accuracy (p=0.004) and reaction time (p<0.001), Go/No‐Go inhibition (p=0.001), and List Sorting Working Memory Test scores (p<0.001). The reckless cluster had lower Flanker accuracy and Go/No‐Go inhibition than did the other groups and lower working memory than the adaptive risk‐taking group. Compared with adaptive risk‐takers, the risk‐avoidant group was slower (p<0.001), showed a nonsignificant trend toward greater accuracy on the Flanker test, and had lower working memory scores (p<0.001).ConclusionsThe BART‐C defined two maladaptive risk‐taking clusters: reckless and risk avoidant. Significant differences in cognitive function between these groups and the adaptive risk‐taking group provides external validation of and further characterizes the clusters. Early intervention may prevent future health‐compromising behaviors among reckless children and may promote fuller learning and development among risk‐avoidant children.

show abstract

The development of adaptive risk taking and the role of executive functions in a large sample of school-age boys and girls

Cited by 16 publications

References 31 publications

Neural signatures of heterogeneity in risk‐taking and strategic consistency

Neural signatures of heterogeneity in risk‐taking and strategic consistency

Probabilistic Decision-Making in Children With Dyslexia

Risk‐Taking Patterns of Children, Associated Cognitive Weaknesses, and Prevention of Negative Outcomes

Contact Info

Product

Resources

About