Resting-state network topology characterizing callous-unemotional traits in adolescence

Executive function and underlying brain network distinctions for callous-unemotional traits and conduct problems in adolescents

The complexity of executive function (EF) impairments in youth antisocial phenotypes of callous-unemotional (CU) traits and conduct problems (CP) challenge identifying phenotypic specific EF deficits. We can redress these challenges by (1) accounting for EF measurement error and (2) testing distinct functional brain properties accounting for differences in EF. Thus, we employed a latent modeling approach for EFs (inhibition, shifting, fluency, common EF) and extracted connection density from matching contemporary EF brain models with a sample of 112 adolescents (ages 13-17, 42% female). Path analysis indicated CU traits associated with lower inhibition. Inhibition network density positively associated with inhibition, but this association was strengthened by CU and attenuated by CP. Common EF associated with three-way interactions between density*CP by CU for the inhibition and shifting networks. This suggests those higher in CU require their brain to work harder for lower inhibition, whereas those higher in CP have difficulty engaging inhibitory brain responses. Additionally, those with CP interacting with CU show distinct brain patterns for a more general EF capacity. Importantly, modeling cross-network connection density in contemporary EF models to test EF involvement in core impairments in CU and CP may accelerate our understanding of EF in these phenotypes.

Efficiency of Heterogenous Functional Connectomes Explains Variance in Callous-Unemotional Traits After Computational Lesioning of Cortical Midline and Salience Regions

Introduction: Callous-unemotional (CU) traits are a youth antisocial phenotype hypothesized to be a result of differences in the integration of multiple brain systems. However, mechanistic insights into these brain systems are a continued challenge. Where prior work describes activation and connectivity, new mechanistic insights into the brain's functional connectome can be derived by removing nodes and quantifying changes in network properties (hereafter referred to as computational lesioning) to characterize connectome resilience and vulnerability. Methods: Here, we study the resilience of connectome integration in CU traits by estimating changes in efficiency after computationally lesioning individual-level connectomes. From resting-state data of 86 participants (48% female, age 14.52 ± 1.31) drawn from the Nathan Kline institute's Rockland study, individual-level connectomes were estimated using graphical lasso. Computational lesioning was conducted both sequentially and by targeting global and local hubs. Elastic net regression was applied to determine how these changes explained variance in CU traits. Follow-up analyses characterized modeled node hubs, examined moderation, determined impact of targeting, and decoded the brain mask by comparing regions to meta-analytic maps. Results: Elastic net regression revealed that computational lesioning of 23 nodes, network modularity, and Tanner stage explained variance in CU traits. Hub assignment of selected hubs differed at higher CU traits. No evidence for moderation between simulated lesioning and CU traits was found. Targeting global hubs increased efficiency and targeting local hubs had no effect at higher CU traits. Identified brain mask meta-analytically associated with more emotion and cognitive terms. Although reliable patterns were found across participants, adolescent brains were heterogeneous even for those with a similar CU traits score. Conclusion: Adolescent brain response to simulated lesioning revealed a pattern of connectome resiliency and vulnerability that explains variance in CU traits, which can aid prediction of youth at greater risk for higher CU traits.

Psychopathic traits and altered resting-state functional connectivity in incarcerated adolescent girls

Previous work in incarcerated boys and adult men and women suggest that individuals scoring high on psychopathic traits show altered resting-state limbic/paralimbic, and default mode functional network properties. However, it is unclear whether similar results extend to high-risk adolescent girls with elevated psychopathic traits. This study examined whether psychopathic traits [assessed via the Hare Psychopathy Checklist: Youth Version (PCL:YV)] were associated with altered inter-network connectivity, intra-network connectivity (i.e., functional coherence within a network), and amplitude of low-frequency fluctuations (ALFFs) across resting-state networks among high-risk incarcerated adolescent girls (n = 40). Resting-state networks were identified by applying group independent component analysis (ICA) to resting-state fMRI scans, and a priori regions of interest included limbic, paralimbic, and default mode network components. We tested the association of psychopathic traits (PCL:YV Factor 1 measuring affective/interpersonal traits and PCL:YV Factor 2 assessing antisocial/lifestyle traits) to these three resting-state measures. PCL:YV Factor 1 scores were associated with increased low-frequency and decreased high-frequency fluctuations in components corresponding to the default mode network, as well as increased intra-network FNC in components corresponding to cognitive control networks. PCL:YV Factor 2 scores were associated with increased low-frequency fluctuations in sensorimotor networks and decreased high-frequency fluctuations in default mode, sensorimotor, and visual networks. Consistent with previous analyses in incarcerated adult women, our results suggest that psychopathic traits among incarcerated adolescent girls are associated with altered intra-network ALFFs-primarily that of increased low-frequency and decreased high-frequency fluctuations-and connectivity across multiple networks including paralimbic regions. These results suggest stable neurobiological correlates of psychopathic traits among women across development.

Cognitive Mechanisms Underlying Prosocial Decision Making in Callous-Unemotional Traits

Callous-unemotional (CU) traits are characterized by a lack of prosocial emotions, which has been demonstrated with prosocial behavior paradigms. While shaping our understanding of prosocial behavior in youth with CU traits, most of this work relies on outcomes that don't reliably capture cognitive processes during prosocial behavior. Examining prosocial cognitive processes can cue researchers into cognitive mechanisms underlying core impairments of CU traits. Drift diffusion modeling is a valuable tool for elucidating more precise outcomes of latent cognitive processes during forced choice tasks such as drift rate (information accumulation toward a decision boundary) and threshold separation (amount of information considered) as well as metrics outside of the decision-making processing including bias (starting point in decision process) and non-decision time (cognitive processes outside of choice). In a sample of 87 adolescents (12-14, 49% female) we applied diffusion modeling to a prosocial behavior task in which participants either accepted or rejected trials where a real monetary value was given to them and taken away from a charity (self-serving trial) or money was given to a charity and taken from them (donation trial). Results revealed that CU traits associated with information accumulation toward accepting self-serving trials. Exploratory sex differences suggested males trended toward rejecting donation trials and females considered more information during self-serving trials. CU trait associations were independent of conduct problems. Results suggest a unique cognitive profile that are differentiated by sex at higher CU traits when making prosocial decisions involving knowledge accumulation toward self-serving decisions.

Callous-unemotional traits in adolescents moderate neural network associations with empathy

Callous-unemotional (CU) traits in adolescents are a dimensional construct involving a symptom subset of empathy impairments amongst broader affective deficits. Higher CU trait scores associate with less cognitive and affective empathy; and brain regions linked with cognitive and affective empathy show aberrant function in those with CU traits. How CU traits impact the relationship between brain function and both cognitive and affective empathy in adolescents is less clear. Here we examine how functional properties of networks that support cognitive and affective empathy is moderated by CU traits. Eighty-four adolescents underwent resting-state fMRI scanning and completed self-reports for empathy (Interpersonal Reactivity Index) and CU traits (Inventory of Callous-Unemotional Traits). Analysis revealed that CU traits moderate the association between affective empathy and connectivity between the default mode-frontoparietal networks. Weaker between default mode-frontoparietal anticorrelation negatively associated with affective empathy at low to moderate CU traits. Those highest in CU traits had the lowest affective empathy; and negative associations for those highest in CU traits were insignificant as default mode-frontoparietal anticorrelation weakened. Our results indicate that functional properties of networks that support affective empathy is different at varying levels of CU traits. This novel finding demonstrates that CU traits presence changes the relationship between the brain and empathy.