Dual-systems models of the genetic architecture of impulsive personality traits: neurogenetic evidence of distinct but related factors.

BACKGROUND: Dual-systems models, positing an interaction between two distinct and competing systems (i.e. top-down self-control, and bottom-up reward- or emotion-based drive), provide a parsimonious framework for investigating the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychopathology. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted. METHODS: Using IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between dual-systems factors and relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were estimated and compared. RESULTS: GenomicSEM dual-systems models underscored important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences (rg = 0.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g. lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). No significant associations were observed with subcortical phenotypes. CONCLUSIONS: Dual-systems models of the genetic architecture of IPTs tested were consistent with study hypotheses, but associations with relevant neuroimaging phenotypes were mixed (e.g. no associations with subcortical volumes). Findings demonstrate the utility of dual-systems models for studying IPT genetic influences, but also highlight potential limitations as a framework for interpreting IPTs as endophenotypes for psychopathology.

On Imbalance of Impulse Control and Sensation Seeking and Adolescent Risk: An Intra-individual Developmental Test of the Dual Systems and Maturational Imbalance Models.

Heterogeneity in development of imbalance between impulse control and sensation seeking has not been studied until now. The present study scrutinized this heterogeneity and the link between imbalance and adolescent risk. Seven-wave data of 7,558 youth (50.71% males; age range from 12/13 until 24/25) were used. Three developmental trajectories were identified. The first trajectory, "sensation seeking to balanced sensation seeking", included participants with a higher level of sensation seeking than impulse control across all ages. The second trajectory, "moderate dominant control", included participants showing moderate and increasing impulse control relative to sensation seeking across all ages. The third trajectory, "strong late dominant control", included participants showing the highest level of impulse control which was about as strong as sensation seeking from early to middle adolescence and became substantially stronger from late adolescence to early adulthood. Although the systematic increase of impulse control in all subgroups is in line with both models, neither of these combined trajectories of control and sensation seeking was predicted by the Dual Systems Model or the Maturational Imbalance Model. Consistent with both models the "sensation seeking to balanced sensation seeking" trajectory showed the highest level of substance use. It can be concluded that, even though both theories adequately predict the link between imbalance and risk, neither the Dual Systems Model nor the Maturational Imbalance Model correctly predict the heterogeneity in development of imbalance between impulse control and sensation seeking.

Parallel Acquisition of Uncorrelated Sequences does Not Provide Firm Evidence for a Modular Sequence-Learning System.

Dual-systems theories of sequence learning assume that sequence learning may proceed within a unidimensional learning system that is immune to cross-dimensional interference because information is processed and represented in dimension-specific, encapsulated modules. Important evidence for such modularity comes from studies investigating the absence or presence of interference between multiple uncorrelated sequences (e.g., a sequence of color stimuli and a sequence of motor keypresses). Here we question the premise that the parallel acquisition of uncorrelated sequences provides convincing evidence for a modularized learning system. In contrast, we demonstrate that parallel acquisition of multiple uncorrelated sequences is well predicted by a computational model that assumes a single learning system with joint representations of stimulus and response features.

Mind the gap: A review and recommendations for statistically evaluating Dual Systems models of adolescent risk behavior.

According to Dual Systems models (Casey et al., 2008; Luna and Wright, 2016; Steinberg, 2008), a rapidly-developing socioemotional system and gradually-developing cognitive control system characterize adolescent brain development. The imbalance hypothesis forwarded by Dual Systems models posits that the magnitude of the imbalance between these two developing systems should predict the propensity for engaging in a variety of risk behaviors. The current integrative review argues that the excitement generated by the imbalance hypothesis and its implications for explaining adolescent risk behaviors has not been meet with equal efforts to rigorously test this hypothesis. The goal of the current review is to help guide the field to consider appropriate and rigorous methods of testing the imbalance hypothesis. First, we review the analytic approaches that have been used to test the imbalance hypothesis and outline statistical and conceptual limitations of these approaches. Next, we discuss the utility of two longitudinal analytic approaches (Latent Difference Scores and Growth Mixture Modeling) for testing the imbalance hypothesis. We utilize data from a large community adolescent sample to illustrate each approach and argue that Latent Difference Scores and Growth Mixture Modeling approaches enhance the specificity and precision with which the imbalance hypothesis is evaluated.