Regional Homogeneity Abnormalities in Early-Onset and Adolescent-Onset Conduct Disorder in Boys: A Resting-State fMRI Study

Altered Neural Activation in First Episode Psychosis Patients With Comorbid Conduct Disorder: A Pilot Investigation

Objective

Most individuals with psychosis do not perpetrate violence. However, conduct disorder (CD) increases the risk of violence in psychotic conditions. Because it is currently unknown whether the neural correlates of first-episode psychosis (FEP) differ when CD is present, we used functional magnetic resonance imaging (fMRI) during a Go/No-Go impulsivity paradigm to investigate. Based on previous research, we hypothesized that activation differences between FEP and FEP+CD would be found in the prefrontal cortex, cingulate cortex, and inferior parietal lobule.

Method

We scanned 51 male participants: 17 FEP, 16 FEP+CD, and 18 healthy controls with an average age of 24.2 years (range, 17-34 years). Whole-brain images were analyzed via a general linear model, and first-level contrast images were created comparing successful No-Go > Go trials. Paired t tests were conducted at the group level and included confound regressors for age, IQ, antipsychotic dose, psychotic symptoms, and framewise displacement. A voxel-based Z-score threshold of Z > 3.1 (p < 0.001, uncorrected) and a cluster-level extent threshold of p <0.01, corrected, was considered significant.

Results

Successful response inhibition elicited hyperactivation in FEP+CD vs FEP in the cingulate gyrus; regions of the PFC, including right middle frontal gyrus (RMFG); bilateral inferior parietal lobule; temporal gyrus; and cerebellum (p values ranged from 1.11E-08 to 0.0031). There was no region in which activation was greater in FEP > FEP+CD.

Conclusion

These preliminary results tentatively suggest that brain regions subserving response inhibition may be altered when CD is comorbid with FEP.

Different whole-brain functional connectivity correlates of reactive-proactive aggression and callous-unemotional traits in children and adolescents with disruptive behaviors

BACKGROUND

Disruptive behavior in children and adolescents can manifest as reactive aggression and proactive aggression and is modulated by callous-unemotional traits and other comorbidities. Neural correlates of these aggression dimensions or subtypes and comorbid symptoms remain largely unknown. This multi-center study investigated the relationship between resting state functional connectivity (rsFC) and aggression subtypes considering comorbidities.

METHODS

The large sample of children and adolescents aged 8-18 years (n = 207; mean age = 13.30±2.60 years, 150 males) included 118 cases with disruptive behavior (80 with Oppositional Defiant Disorder and/or Conduct Disorder) and 89 controls. Attention-deficit/hyperactivity disorder (ADHD) and anxiety symptom scores were analyzed as covariates when assessing group differences and dimensional aggression effects on hypothesis-free global and local voxel-to-voxel whole-brain rsFC based on functional magnetic resonance imaging at 3 Tesla.

RESULTS

Compared to controls, the cases demonstrated altered rsFC in frontal areas, when anxiety but not ADHD symptoms were controlled for. For cases, reactive and proactive aggression scores were related to global and local rsFC in the central gyrus and precuneus, regions linked to aggression-related impairments. Callous-unemotional trait severity was correlated with ICC in the inferior and middle temporal regions implicated in empathy, emotion, and reward processing. Most observed aggression subtype-specific patterns could only be identified when ADHD and anxiety were controlled for.

CONCLUSIONS

This study clarifies that hypothesis-free brain connectivity measures can disentangle distinct though overlapping dimensions of aggression in youths. Moreover, our results highlight the importance of considering comorbid symptoms to detect aggression-related rsFC alterations in youths.

Multimodal Ensemble Deep Learning to Predict Disruptive Behavior Disorders in Children

Oppositional defiant disorder and conduct disorder, collectively referred to as disruptive behavior disorders (DBDs), are prevalent psychiatric disorders in children. Early diagnosis of DBDs is crucial because they can increase the risks of other mental health and substance use disorders without appropriate psychosocial interventions and treatment. However, diagnosing DBDs is challenging as they are often comorbid with other disorders, such as attention-deficit/hyperactivity disorder, anxiety, and depression. In this study, a multimodal ensemble three-dimensional convolutional neural network (3D CNN) deep learning model was used to classify children with DBDs and typically developing children. The study participants included 419 females and 681 males, aged 108–131 months who were enrolled in the Adolescent Brain Cognitive Development Study. Children were grouped based on the presence of DBDs (n = 550) and typically developing (n = 550); assessments were based on the scores from the Child Behavior Checklist and on the Schedule for Affective Disorders and Schizophrenia for School-age Children-Present and Lifetime version for DSM-5. The diffusion, structural, and resting-state functional magnetic resonance imaging (rs-fMRI) data were used as input data to the 3D CNN. The model achieved 72% accuracy in classifying children with DBDs with 70% sensitivity, 72% specificity, and an F1-score of 70. In addition, the discriminative power of the classifier was investigated by identifying the cortical and subcortical regions primarily involved in the prediction of DBDs using a gradient-weighted class activation mapping method. The classification results were compared with those obtained using the three neuroimaging modalities individually, and a connectome-based graph CNN and a multi-scale recurrent neural network using only the rs-fMRI data.

Impaired attentional and socio-affective networks in subjects with antisocial behaviors: a meta-analysis of resting-state functional connectivity studies

In the past decade, there has been a growing interest in examining resting-state functional connectivity deficits in subjects with conduct and antisocial personality disorder. Through meta-analyses and literature reviews, extensive work has been done to characterize their abnormalities in brain activation during a wide range of functional magnetic resonance imaging (fMRI) tasks. However, there is currently no meta-analytical evidence regarding neural connectivity patterns during resting-state fMRI. Therefore, we conducted a coordinate-based meta-analysis of resting-state fMRI studies on individuals exhibiting antisocial behaviors. Of the retrieved studies, 18 used a seed-based connectivity approach (513 cases v. 488 controls), 20 employed a non-seed-based approach (453 cases v. 460 controls) and 20 included a correlational analysis between the severity of antisocial behaviors and connectivity patterns (3462 subjects). Meta-analysis on seed-based studies revealed significant connectivity deficits in the amygdala, middle cingulate cortex, ventral posterior cingulate cortex-precuneus, ventromedial and dorsomedial prefrontal cortex, premotor cortex, and superior parietal lobule. Additionally, non-seed-based meta-analysis showed increased connectivity in the ventral posterior cingulate cortex and decreased connectivity in the parietal operculum, calcarine cortex, and cuneus. Finally, we found meta-analytical evidence for negative relationship between the severity of antisocial behaviors and connectivity with the ventromedial prefrontal cortex. Functional characterization and meta-analytical connectivity modeling indicated that these findings overlapped with socio-affective and attentional processes. This further underscores the importance of these functions in the pathophysiology of conduct and antisocial personality disorders.

Altered dynamic regional homogeneity in patients with conduct disorder

Conduct disorder (CD) is a psychiatric condition characterized by severe aggressive and antisocial behaviors. Prior neuroimaging work reported that CD is associated with abnormal resting-state local intrinsic brain activity (IBA). However, few studies detected the time-varying brain activity patterns in CD. In this study, eighteen adolescent patients with CD and 18 typically developing controls underwent resting-state functional magnetic resonance imaging scans. We then compared the dynamic characteristics of IBA by calculating the dynamic regional homogeneity (dReHo) through a sliding-window approach between the two groups, and the correlations between the dReHo variability and clinical symptoms in CD were further examined. Moreover, the statistical between-group differences in dReHo were selected as classification features to help distinguish CD patients from controls by adopting a linear support vector machine (SVM) classifier. CD patients showed increased dReHo variability in the left precuneus, right postcentral gyrus, right precentral gyrus, left middle cingulate gyrus, and left paracentral lobule compared to controls, and dReHo variability in the left precuneus was significantly positively associated with impulsiveness scores in CD patients. Importantly, SVM combined with the leave-one-out cross-validation method results demonstrated that 75% (p < 0.001) subjects were correctly classified with sensitivity of 61% and specificity of 89%. Our results provided the initial evidence that CD is characterized by abnormal dynamic IBA patterns, giving novel insights into the neuropathological mechanisms of CD. Further, our findings exhibited that the dReHo variability may distinguish CD patients from controls with high accuracy.

Altered Brain Structure and Functional Connectivity Associated with Pubertal Hormones in Girls with Precocious Puberty

Pubertal hormones play an important role in brain and psychosocial development. However, the role of abnormal HPG axis states in altering brain function and structure remains unclear. The present study is aimed at determining whether there were significant differences in gray matter volume (GMV) and resting state (RS) functional connectivity (FC) patterns in girls with idiopathic central precocious puberty (CPP) and peripheral precocious puberty (PPP). We further explored the correlation between these differences and serum pubertal hormone levels. To assess this, we recruited 29 idiopathic CPP girls and 38 age-matched PPP girls. A gonadotropin-releasing hormone (GnRH) stimulation test was performed, and pubertal hormone levels (including luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol (E2), prolactin, and cortisol) were assessed. All subjects underwent multimodal magnetic resonance imaging of brain structure and function. Voxel-based morphometry (VBM) analysis was paired with seed-to-voxel whole-brain RS-FC analysis to calculate the GMV and RS-FC in idiopathic CPP and PPP girls. Correlation analyses were used to assess the effects of pubertal hormones on brain regions with structural and functional differences between the groups. We found that girls with CPP exhibited decreased GMV in the left insula and left fusiform gyrus, while connectivity between the left and right insula and the right middle frontal gyrus (MFG), as well as the left fusiform gyrus and right amygdala, was reduced in girls with CPP. Furthermore, the GMV of the left insula and peak FSH levels were negatively correlated while higher basal and peak E2 levels were associated with increased bilateral insula RS-FC. These findings suggest that premature activation of the HPG axis and pubertal hormone fluctuations alter brain structure and function involved in the cognitive and emotional process in early childhood. These findings provide vital insights into the early pathophysiology of idiopathic CPP.