Recent neuro-imaging findings with respect to conduct disorder, callous-unemotional traits and psychopathy

Callous-unemotional Traits and Child Response to Teacher Rewards, Discipline, and Instructional Methods in Chinese Preschools: A Classroom Observation Study

Atypical responses to teacher rewards, discipline and different forms of instructional methods have been identified as potential contributors to disruptive behavior, low school engagement, and academic underachievement in children with elevated callous-unemotional (CU) traits. To date, research on CU traits in schools has relied on interview or questionnaire methods and has predominantly been conducted in Western countries. Thus, the present study aims to investigate the relationships between CU traits and children's responses to teacher rewards, discipline and instructional methods in the Chinese preschool context using classroom observation. Eight teachers (7 females, 1 male; M = 37.66 years) and 116 children (56% girls; M = 5.16 years) from two mainstream Chinese preschools participated in the study. Of the 116 eligible children, the behavior of 108 children from four classes were observed during classroom activities. Findings indicated that CU traits were not related to children's responses to discipline, nor did CU traits moderate the relationship between instructional methods and children's academic engagement. Higher CU traits predicted a greater frequency of one-to-one teacher-child interaction. Our findings offer initial insights into the potential of early school-based interventions in fostering engagement and prosocial behavior among children with CU traits. However, they also highlight the need for additional support for preschool teachers, who face the challenge of managing these high-risk children who appear to require more individual time and attention.

Reduced grey matter volume in adolescents with conduct disorder: a region-of-interest analysis using multivariate generalized linear modeling

BACKGROUND

Conduct disorder (CD) involves a group of behavioral and emotional problems that usually begins during childhood or adolescence. Structural brain alterations have been observed in CD, including the amygdala, insula, ventrolateral and medial prefrontal cortex, anterior cingulate cortex, and fusiform gyrus. The current study developed a multivariate generalized linear model (GLM) to differentiate adolescents with CD from typically developing (TD) adolescents in terms of grey matter volume (GMV).

METHODS

The whole-brain structural MRI data were collected from 96 adolescents with CD (mean age = [Formula: see text] years; mean IQ = [Formula: see text]; 63 males) and 90 TD individuals (mean age = [Formula: see text] years; mean IQ = [Formula: see text]; 59 males) matched on age, IQ, and sex. Region-wise GMV was extracted following whole-brain parcellation into 68 cortical and 14 subcortical regions for each participant. A multivariate GLM was developed to predict the GMV of the pre-hypothesized regions-of-interest (ROIs) based on CD diagnosis, with intracranial volume, age, sex, and IQ serving as the covariate.

RESULTS

A diagnosis of CD was a significant predictor for GMV in the right pars orbitalis, right insula, right superior temporal gyrus, left fusiform gyrus, and left amygdala (F(1, 180) = 5.460-10.317, p < 0.05, partial eta squared = 0.029-0.054). The CD participants had smaller GMV in these regions than the TD participants (MCD-MTD = [- 614.898] mm3-[- 53.461] mm3).

CONCLUSIONS

Altered GMV within specific regions may serve as a biomarker for the development of CD in adolescents. Clinical work can potentially target these biomarkers to treat adolescents with CD.

Reduced Grey Matter Volume in Adolescents with Conduct Disorder: A Region-of-Interest Analysis Using Multivariate Generalized Linear Modeling

Background

Conduct disorder (CD) involves a group of behavioral and emotional problems that usually begins during childhood or adolescence. Structural brain alterations have been observed in CD, including the amygdala, insula, ventrolateral and medial prefrontal cortex, anterior cingulate cortex, and fusiform gyrus. The current study developed a multivariate generalized linear model (GLM) to differentiate adolescents with CD from typically developing (TD) adolescents in terms of grey matter volume (GMV).

Methods

The whole-brain structural MRI data were collected from 96 adolescents with CD (mean age = years; mean IQ = ; 63 males) and 90 TD individuals (mean age = years; mean IQ = ; 59 males) matched on age, IQ, and sex. Region-wise GMV was extracted following whole-brain parcellation into 68 cortical and 14 subcortical regions for each participant. A multivariate GLM was developed to predict the GMV of the pre-hypothesized regions-of-interest (ROIs) based on CD diagnosis, with intracranial volume, age, sex, and IQ serving as the covariate.

Results

A diagnosis of CD was a significant predictor for GMV in the right pars orbitalis, right insula, right superior temporal gyrus, left fusiform gyrus, and left amygdala (F(1, 180) = 5.460 - 10.317, p < 0.05, partial eta squared = 0.029 - 0.054). The CD participants had smaller GMV in these regions than the TD participants (MCD - MTD = [-614.898] mm3 - [-53.461] mm3).

Conclusions

Altered GMV within specific regions may serve as a biomarker for the development of CD in adolescents. Clinical work can potentially target these biomarkers to treat adolescents with CD.

Classifying Conduct Disorder Using a Biopsychosocial Model and Machine Learning Method

BACKGROUND

Conduct disorder (CD) is a common syndrome with far-reaching effects. Risk factors for the development of CD span social, psychological, and biological domains. Researchers note that predictive models of CD are limited if the focus is on a single risk factor or even a single domain. Machine learning methods are optimized for the extraction of trends across multidomain data but have yet to be implemented in predicting the development of CD.

METHODS

Social (e.g., family, income), psychological (e.g., psychiatric, neuropsychological), and biological (e.g., resting-state graph metrics) risk factors were measured using data from the baseline visit of the Adolescent Brain Cognitive Development Study when youth were 9 to 10 years old (N = 2368). Applying a feed-forward neural network machine learning method, risk factors were used to predict CD diagnoses 2 years later.

RESULTS

A model with factors that included social, psychological, and biological domains outperformed models representing factors within any single domain, predicting the presence of a CD diagnosis with 91.18% accuracy. Within each domain, certain factors stood out in terms of their relationship to CD (social: lower parental monitoring, more aggression in the household, lower income; psychological: greater attention-deficit/hyperactivity disorder and oppositional defiant disorder symptoms, worse crystallized cognition and card sorting performance; biological: disruptions in the topology of subcortical and frontoparietal networks).

CONCLUSIONS

The development of an accurate, sensitive, and specific predictive model of CD has the potential to aid in prevention and intervention efforts. Key risk factors for CD appear best characterized as reflecting unpredictable, impulsive, deprived, and emotional external and internal contexts.

Non-angry aggressive arousal and angriffsberietschaft: A narrative review of the phenomenology and physiology of proactive/offensive aggression motivation and escalation in people and other animals

Human aggression typologies largely correspond with those for other animals. While there may be no non-human equivalent of angry reactive aggression, we propose that human proactive aggression is similar to offense in other animals' dominance contests for territory or social status. Like predation/hunting, but unlike defense, offense and proactive aggression are positively reinforcing, involving dopamine release in accumbens. The drive these motivational states provide must suffice to overcome fear associated with initiating risky fights. We term the neural activity motivating proactive aggression "non-angry aggressive arousal", but use "angriffsberietschaft" for offense motivation in other animals to acknowledge possible differences. Temporal variation in angriffsberietschaft partitions fights into bouts; engendering reduced anti-predator vigilance, redirected aggression and motivational over-ride. Increased aggressive arousal drives threat-to-attack transitions, as in verbal-to-physical escalation and beyond that, into hyper-aggression. Proactive aggression and offense involve related neural activity states. Cingulate, insular and prefrontal cortices energize/modulate aggression through a subcortical core containing subnuclei for each aggression type. These proposals will deepen understanding of aggression across taxa, guiding prevention/intervention for human violence.

Social thinning and stress generation after childhood maltreatment: a neurocognitive social transactional model of psychiatric vulnerability

Childhood maltreatment is associated with significant, enduring risk of psychiatric disorder. In this paper, we review how neurocognitive alterations after maltreatment might indirectly increase the risk of psychiatric disorder via their impact on social functioning. We propose a neurocognitive social transactional model, within which the neurocognitive sequelae of maltreatment are postulated to affect how an individual's social architecture is constructed across development, including the quality and quantity of relationships in an individual's social network. We review extant evidence in two areas in relation to maltreatment: stress generation (a process by which individuals are more likely to experience interpersonal stressor events) and social thinning (an attenuation in the number and quality of relationships over time). We consider how neurocognitive alterations could contribute to these interactive and autocatalytic social processes, which gradually impoverish an individual's actual or potential social environment and ultimately increase psychiatric risk. We conclude by considering the implications of this neurocognitive social transactional model for the prevention of psychiatric disorder after childhood maltreatment.

Multivariate Genetic Structure of Externalizing Behavior and Structural Brain Development in a Longitudinal Adolescent Twin Sample

Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers, and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and the brain volumes and white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) with magnetic resonance imaging in the BrainSCALE cohort, which consisted of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years for the twins. Genetic covariance modeling based on the classical twin design, extended to also include siblings of twins, showed that genes influence externalizing behavior and changes therein (h² up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation r_ph up to +0.20) and lower MD (r_ph up to −0.20), with sizeable genetic correlations (FA r_a up to +0.42; MD r_a up to −0.33). The cortical gray matter (CGM; r_ph up to −0.20) and cerebral white matter (CWM; r_ph up to +0.20) volume were phenotypically but not genetically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence of the same genetic factor.

Maternal and paternal unsupportive parenting and children's externalizing symptoms: The mediational role of children's attention biases to negative emotion

This study examined children's duration of attention to negative emotions (i.e., anger, sadness, fear) as a mediator of associations among maternal and paternal unsupportive parenting and children's externalizing symptoms in a sample of 240 mothers, fathers, and their preschool children (Mage = 4.64 years). The multimethod, multi-informant design consisted of three annual measurement occasions. Analysis of maternal and paternal unsupportive parenting as predictors in latent difference changes in children's affect-biased attention and behavior problems indicated that children's attention to negative emotions mediated the specific association between maternal unsupportive parenting and children's subsequent increases in externalizing symptoms. Maternal unsupportive parenting at Wave 1 predicted decreases in children's attention to negative facial expressions of adults from Wave 1 to 2. Reductions in children's attention to negative emotion, in turn, predicted increases in their externalizing symptoms from Wave 1 to 3. Additional tests of children's fearful distress and hostile responses to parental conflict as explanatory mechanisms revealed that increases in children's fearful distress reactivity from Wave 1 to 2 accounted for the association between maternal unsupportive parenting and concomitant decreases in their attention to negative emotions. Results are discussed in the context of information processing models of family adversity and developmental psychopathology.

Correlates of Social Cognition and Psychopathic Traits in a Community-Based Sample of Males

Social cognition is the ability to identify, understand, and interpret mental states and emotions. Psychopathic traits are typically described in two ways; Primary: shallow affect, emotional detachment, and relationship difficulties, and Secondary Psychopathic Traits: antisocial traits, impulsiveness, and emotional dysregulation. People with high psychopathic traits tend to perform lower on measures of social cognition. This study investigated the relationship of social cognition (mentalising) to primary and secondary psychopathic traits in a non-clinical sample, and investigated the psychometric properties of the Reading the Mind in the Eyes Test (RMET) Short Forms (A and B). A community-based male sample (N = 1,000; age range 18-78) was recruited through an online platform. Psychopathic traits were measured using Levenson, Kiehl, and Fitzpatrick's Self-Report Psychopathy Scale, and stratified into Primary and Secondary Psychopathic traits. Secondary validation of the RMET Short Forms was completed investigating scale reliability, and validity. Findings suggest excellent psychometrics in a large community cohort for the RMET Short Forms (A and B), with significant negative correlations on social cognitive performance and high self-report psychopathy. The item valence within the social cognitive measure (positive, negative, and neutral affect stimuli) was also examined, and correlated significantly with both Primary and Secondary Psychopathic traits. This study provides further validation of the RMET Short Forms (A and B), and adds to the literature on the scale by investigating performance on short-form specific valence. This study further suggests that in a non-clinical community sample of males, that higher psychopathic traits correlated significantly, and negatively, with social cognitive performance.

Is the Psychopathic Brain an Artifact of Coding Bias? A Systematic Review

Questionable research practices are a well-recognized problem in psychology. Coding bias, or the tendency of review studies to disproportionately cite positive findings from original research, has received comparatively little attention. Coding bias is more likely to occur when original research, such as neuroimaging, includes large numbers of effects, and is most concerning in applied contexts. We evaluated coding bias in reviews of structural magnetic resonance imaging (sMRI) studies of PCL-R psychopathy. We used PRISMA guidelines to locate all relevant original sMRI studies and reviews. The proportion of null-findings cited in reviews was significantly lower than those reported in original research, indicating coding bias. Coding bias was not affected by publication date or review design. Reviews recommending forensic applications—such as treatment amenability or reduced criminal responsibility—were no more accurate than purely theoretical reviews. Coding bias may have contributed to a perception that structural brain abnormalities in psychopaths are more consistent than they actually are, and by extension that sMRI findings are suitable for forensic application. We discuss possible sources for the pervasive coding bias we observed, and we provide recommendations to counteract this bias in review studies. Until coding bias is addressed, we argue that this literature should not inform conclusions about psychopaths' neurobiology, especially in forensic contexts.

Callous-Unemotional Traits Moderate Anticipated Guilt and Wrongness Judgments to Everyday Moral Transgressions in Adolescents

Callous-unemotional (CU) traits observed during childhood and adolescence are thought to be precursors of psychopathic traits in adulthood. Adults with high levels of psychopathic traits typically present antisocial behavior. Such behavior can be indicative of atypical moral processing. Evidence suggests that moral dysfunction in these individuals may stem from a disruption of affective components of moral processing rather than from an inability to compute moral judgments per se. No study to date has tested if the dissociation between affective and cognitive dimensions of moral processing linked to psychopathic traits in adulthood is also linked to CU traits during development. Here, 47 typically developing adolescents with varying levels of CU traits completed a novel, animated cartoon task depicting everyday moral transgressions and indicated how they would feel in such situations and how morally wrong the situations were. Adolescents with higher CU traits reported reduced anticipated guilt and wrongness appraisals of the transgressions. However, our key finding was a significant interaction between CU traits and anticipated guilt in predicting wrongness judgments. The strength of the association between anticipated guilt and wrongness judgement was significantly weaker for those with higher levels of CU traits. This evidence extends our knowledge on the cognitive-affective processing deficits that may underlie moral dysfunction in youth who are at heightened risk for antisocial behavior and psychopathy in adulthood. Future longitudinal research is required to elucidate whether there is an increased dissociation between different components of moral processing from adolescence to adulthood for those with high psychopathic traits.

Adolescent Resting-State Brain Networks and Unique Variability of Conduct Problems Within the Externalizing Dimension

The externalizing psychopathological dimension is associated with alterations in adolescents' functional brain connectivity. The current study aims to identify the functional correlates of the unique variability in conduct problems within the context of the broad externalizing dimension. The broad externalizing dimension and unique variability in conduct problems were estimated using a bifactor model. Resting-state data were available for a sample of 125 adolescents. Based on multiresolution parcellation of functional brain networks atlas, major resting-state functional brain networks and the connectivity correlates of unique conduct problems and the broad externalizing dimension were established. The broad externalizing dimension was related to connectivity alterations in the ventral attention/salience network, while unique variability in conduct problems dimension was related to connectivity alterations in the cerebellum crusi as well as the mesolimbic network. The current study is a first step toward the identification of functional resting-state network correlates of broad and specific variability in the externalizing dimension.