Hyperbolic discounting rates and risk for problematic alcohol use in youth enrolled in the Adolescent Brain and Cognitive Development study

Associations between behavioral and self-reported impulsivity, brain structure, and genetic influences in middle childhood

Impulsivity undergoes a normative developmental trajectory from childhood to adulthood and is thought to be driven by maturation of brain structure. However, few large-scale studies have assessed associations between impulsivity, brain structure, and genetic susceptibility in children. In 9112 children ages 9-10 from the ABCD study, we explored relationships among impulsivity (UPPS-P impulsive behavior scale; delay discounting), brain structure (cortical thickness (CT), cortical volume (CV), and cortical area (CA)), and polygenic scores for externalizing behavior (PGSEXT). Both higher UPPS-P total scores and more severe delay-discounting had widespread, low-magnitude associations with smaller CA in frontal and temporal regions. No associations were seen between impulsivity and CV or CT. Additionally, higher PGSEXT was associated with both higher UPPS-P scores and with smaller CA and CV in frontal and temporal regions, but in non-overlapping cortical regions, underscoring the complex interplay between genetics and brain structure in influencing impulsivity. These findings indicate that, within large-scale population data, CA is significantly yet weakly associated with each of these impulsivity measures and with polygenic risk for externalizing behaviors, but in distinct brain regions. Future work should longitudinally assess these associations through adolescence, and examine associated functional outcomes, such as future substance use and psychopathology.

Delay discounting and family history of psychopathology in children ages 9-11

Delay discounting is a tendency to devalue delayed rewards compared to immediate rewards. Evidence suggests that steeper delay discounting is associated with psychiatric disorders across diagnostic categories, but it is unclear whether steeper delay discounting is a risk factor for these disorders. We examined whether children at higher risk for psychiatric disorders, based on family history, would demonstrate steeper delay discounting behavior using data from the Adolescent Brain Cognitive Development (ABCD) study, a nationally representative sample of 11,878 children. We looked at associations between delay discounting behavior and family history of alcohol problems, drug problems, depression, mania, schizophrenia, and suicidal behavior. Correlations between family history of psychopathology and delay discounting behavior were small, ranging from ρ = - 0.02 to 0.04. In mixed effects models controlled for sociodemographic factors, family history of psychopathology was not associated with steeper delay discounting behavior. Sociodemographic factors played a larger role in predicting delay discounting behavior than family history of psychopathology. These results do not support the hypothesis that children with greater risk for psychopathology display steeper delay discounting behavior.

Associations Between Polygenic Scores for Cognitive and Non-cognitive Factors of Educational Attainment and Measures of Behavior, Psychopathology, and Neuroimaging in the Adolescent Brain Cognitive Development Study

Background

Both cognitive and non-cognitive (e.g., traits like curiosity) factors are critical for social and emotional functioning and independently predict educational attainment. These factors are heritable and genetically correlated with a range of health-relevant traits and behaviors in adulthood (e.g., risk-taking, psychopathology). However, whether these associations are present during adolescence, and to what extent these relationships diverge, could have implications for adolescent health and well-being.

Methods

Using data from 5,517 youth of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and outcomes related to cognition, socioeconomic status, risk tolerance and decision-making, substance initiation, psychopathology, and brain structure.

Results

Cognitive and non-cognitive PGSs were both positively associated with cognitive performance and family income, and negatively associated with ADHD and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk-taking, delayed discounting, and anorexia, as well as lower likelihood of nicotine initiation. The cognitive PGS was further associated with cognition scores and anorexia in within-sibling analyses, suggesting these results do not solely reflect the effects of assortative mating or passive gene-environment correlations. The cognitive PGS showed significantly stronger associations with cortical volumes than the non-cognitive PGS and was associated with right hemisphere caudal anterior cingulate and pars-orbitalis in within-sibling analyses, while the non-cognitive PGS showed stronger associations with white matter fractional anisotropy and a significant within-sibling association for right superior corticostriate-frontal cortex.

Conclusions

Our findings suggest that PGSs for cognitive and non-cognitive factors show similar associations with cognition and socioeconomic status as well as other psychosocial outcomes, but distinct associations with regional neural phenotypes in this adolescent sample.

Gender-specific resting-state rDMPFC-centric functional connectivity underpinnings of intertemporal choice

Although studies have observed gender differences in intertemporal choice, the neural bases of these differences require further research. The current study used resting state functional connectivity (rsFC) to explore the gender-specific neural basis of intertemporal choice in three independent samples (n1 = 86, n2 = 297, n3 = 172). Behaviorally, three samples (S1, S2, and S3) consistently demonstrated that men had larger delay discounting rate (log k) than women. Then, whole-brain functional connectivity analyses were performed for different genders in S2 and S3 using the right dorsomedial prefrontal cortex (rDMPFC) as a region of interest. By subtracting the common rsFC patterns of different genders, we identified gender-specific log k-related rsFC patterns with significant gender differences in S2. This was verified in an independent sample (S3). Specifically, in women, log k was found to be positively correlated with the rsFC between rDMPFC and anterior cingulate cortex/right orbitofrontal cortex. In contrast, in men, log k was negatively correlated with rsFC between rDMPFC and left orbitofrontal cortex/right precuneus. These gender differences were confirmed by slope tests. The findings highlight how gender may differ when engaging in intertemporal choice. They improve the understanding of gender differences in decision impulsivity and its underlying neural bases.

Model-based experimental manipulation of probabilistic behavior in interpretable behavioral latent variable models

Introduction

Interpretable latent variable models that probabilistically link behavioral observations to an underlying latent process have increasingly been used to draw inferences on cognition from observed behavior. The latent process usually connects experimental variables to cognitive computation. While such models provide important insights into the latent processes generating behavior, one important aspect has often been overlooked. They may also be used to generate precise and falsifiable behavioral predictions as a function of the modeled experimental variables. In doing so, they pinpoint how experimental conditions must be designed to elicit desired behavior and generate adaptive experiments.

Methods

These ideas are exemplified on the process of delay discounting (DD). After inferring DD models from behavior on a typical DD task, the models are leveraged to generate a second adaptive DD task. Experimental trials in this task are designed to elicit 9 graded behavioral discounting probabilities across participants. Models are then validated and contrasted to competing models in the field by assessing the ouf-of-sample prediction error.

Results

The proposed framework induces discounting probabilities on nine levels. In contrast to several alternative models, the applied model exhibits high validity as indicated by a comparably low prediction error. We also report evidence for inter-individual differences with respect to the most suitable models underlying behavior. Finally, we outline how to adapt the proposed method to the investigation of other cognitive processes including reinforcement learning.

Discussion

Inducing graded behavioral frequencies with the proposed framework may help to highly resolve the underlying cognitive construct and associated neuronal substrates.