Neighborhood poverty during childhood prospectively predicts adolescent functional brain network architecture.

Family poverty has been associated with altered brain structure, function, and connectivity in youth. However, few studies have examined how disadvantage within the broader neighborhood may influence functional brain network organization. The present study leveraged a longitudinal community sample of 538 twins living in low-income neighborhoods to evaluate the prospective association between exposure to neighborhood poverty during childhood (6-10 y) with functional network architecture during adolescence (8-19 y). Using resting-state and task-based fMRI, we generated two latent measures that captured intrinsic brain organization across the whole-brain and network levels - network segregation and network segregation-integration balance. While age was positively associated with network segregation and network balance overall across the sample, these associations were moderated by exposure to neighborhood poverty. Specifically, these positive associations were observed only in youth from more, but not less, disadvantaged neighborhoods. Moreover, greater exposure to neighborhood poverty predicted reduced network segregation and network balance in early, but not middle or late, adolescence. These effects were detected both across the whole-brain system as well as specific functional networks, including fronto-parietal, default mode, salience, and subcortical systems. These findings indicate that where children live may exert long-reaching effects on the organization and development of the adolescent brain.

Early childhood household instability, adolescent structural neural network architecture, and young adulthood depression: A 21-year longitudinal study.

Unstable and unpredictable environments are linked to risk for psychopathology, but the underlying neural mechanisms that explain how instability relate to subsequent mental health concerns remain unclear. In particular, few studies have focused on the association between instability and white matter structures despite white matter playing a crucial role for neural development. In a longitudinal sample recruited from a population-based study (N = 237), household instability (residential moves, changes in household composition, caregiver transitions in the first 5 years) was examined in association with adolescent structural network organization (network integration, segregation, and robustness of white matter connectomes; Mage = 15.87) and young adulthood anxiety and depression (six years later). Results indicate that greater instability related to greater global network efficiency, and this association remained after accounting for other types of adversity (e.g., harsh parenting, neglect, food insecurity). Moreover, instability predicted increased depressive symptoms via increased network efficiency even after controlling for previous levels of symptoms. Exploratory analyses showed that structural connectivity involving the left fronto-lateral and temporal regions were most strongly related to instability. Findings suggest that structural network efficiency relating to household instability may be a neural mechanism of risk for later depression and highlight the ways in which instability modulates neural development.

Antisocial behavior is associated with reduced frontoparietal network efficiency in youth.

Youth antisocial behavior (AB) is associated with deficits in socioemotional processing, reward and threat processing and executive functioning. These deficits are thought to emerge from differences in neural structure, functioning and connectivity, particularly within the default, salience and frontoparietal networks. However, the relationship between AB and the organization of these networks remains unclear. To address this gap, the current study applied unweighted, undirected graph analyses to resting-state functional magnetic resonance imaging data in a cohort of 161 adolescents (95 female) enriched for exposure to poverty, a risk factor for AB. As prior work indicates that callous-unemotional (CU) traits may moderate the neurocognitive profile of youth AB, we examined CU traits as a moderator. Using multi-informant latent factors, AB was found to be associated with less efficient frontoparietal network topology, a network associated with executive functioning. However, this effect was limited to youth at low or mean levels of CU traits, indicating that these neural differences were specific to those high on AB but not CU traits. Neither AB, CU traits nor their interaction was significantly related to default or salience network topologies. Results suggest that AB, specifically, may be linked with shifts in the architecture of the frontoparietal network.

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.

Conduct disorder symptomatology is associated with an altered functional connectome in a large national youth sample.

Conduct disorder (CD), characterized by youth antisocial behavior, is associated with a variety of neurocognitive impairments. However, questions remain regarding the neural underpinnings of these impairments. To investigate novel neural mechanisms that may support these neurocognitive abnormalities, the present study applied a graph analysis to resting-state functional magnetic resonance imaging (fMRI) data collected from a national sample of 4,781 youth, ages 9-10, who participated in the baseline session of the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®). Analyses were then conducted to examine the relationships among levels of CD symptomatology, metrics of global topology, node-level metrics for subcortical structures, and performance on neurocognitive assessments. Youth higher on CD displayed higher global clustering (ß = .039, 95% CIcorrected [.0027 .0771]), but lower Degreesubcortical (ß = -.052, 95% CIcorrected [-.0916 -.0152]). Youth higher on CD had worse performance on a general neurocognitive assessment (ß = -.104, 95% CI [-.1328 -.0763]) and an emotion recognition memory assessment (ß = -.061, 95% CI [-.0919 -.0290]). Finally, global clustering mediated the relationship between CD and general neurocognitive functioning (indirect ß = -.002, 95% CI [-.0044 -.0002]), and Degreesubcortical mediated the relationship between CD and emotion recognition memory performance (indirect ß = -.002, 95% CI [-.0046 -.0005]). CD appears associated with neuro-topological abnormalities and these abnormalities may represent neural mechanisms supporting CD-related neurocognitive disruptions.

Cognitive Empathy in Subtypes of Antisocial Individuals.

Cognitive empathy allows individuals to recognize and infer how others think and feel in social situations and provides a foundation for the formation and maintenance of mutually constructive relationships. It may seem intuitive to assume that individuals who engage in antisocial behavior, who disregard the rights of others, might have problems with cognitive empathy. However, careful examination of the literature suggests that any dysfunction in cognitive empathy associated with antisociality varies by subtype of antisocial individual and is specific to subcomponents of cognitive empathy. In this review, we (1) briefly define subtypes of antisocial individuals ("psychopathic" vs. "antisocial-only"), (2) summarize specific components of cognitive empathy; (3) review existing literature examining cognitive empathy through questionnaires, behavioral tasks, and neuroimaging within different antisocial subtypes; and (4) discuss the limitations of the current research and potential future directions. Individuals in the psychopathic subtype fail to implicitly engage in cognitive empathy, and potentially lack insight into this issue reflected in no self-reported problems with cognitive empathy, but show an ability to engage in cognitive empathy when explicitly required. Individuals in the antisocial-only subtype appear able to engage in cognitive empathy, showing no differences on questionnaire or behavioral tasks that tap explicit cognitive empathy, but may display subtle difficulties accurately inferring (affective theory of mind) the emotions of others. We end the review by noting areas for future research, including the need to: (1) document the patterns of equifinality that exist across levels of analysis for these antisocial subtypes; (2) examine the temporality of empathy and antisociality development; (3) carefully consider and label subcomponents of cognitive empathy in research on antisocial behavior; and (4) investigate the intersection among environmental experiences, cognitive empathy, and antisocial behavior.

Psychopathy is associated with an exaggerated attention bottleneck: EEG and behavioral evidence from a dual-task paradigm.

Psychopathy is a personality disorder associated with a chronic disregard for the welfare of others. The attention bottleneck model of psychopathy asserts that the behavior of individuals higher on psychopathy is due to an exaggerated attention bottleneck that constrains all information processing, regardless of the information's potential goal-relevance. To date, the majority of research on the attention bottleneck model of psychopathy conceptually applied the tenets of the model but did not implement methods that directly test an exaggeration of the bottleneck in psychopathy. Accordingly, the presence of an exaggerated bottleneck, the exact expression of that bottleneck, and its potential mechanistic relevance for behavior in individuals higher on psychopathy remains untested. To address these gaps, a sample of 78 male community members, evaluated for psychopathic traits using the Self-Report Psychopathy-III scale, completed an EEG-based dual-task paradigm examining short stimulus onset asynchrony (SOA; 300 ms), long SOA (1,100 ms), and single-task baseline conditions. Additionally, participants were asked about their frequency of real-world risky, impulsive, and antisocial behaviors. Psychopathy was associated with slower reaction times to second targets (T2s) presented during the dual-task conditions, relative to the baseline condition. Psychopathy also was associated with blunted P300 responses, a neural index of stimulus evaluation, across all types of T2 events. Finally, bottleneck-related interference during the short SOA events mediated the relationship between psychopathy and real-world behavior. These findings suggested that individuals higher on psychopathy exhibit an exaggerated bottleneck which produces intense and long-lasting interference, impacting all information processing and partially contributing to their maladaptive behavior.

Psychopathy is associated with shifts in the organization of neural networks in a large incarcerated male sample.

Psychopathy is a personality disorder defined by antisocial behavior paired with callousness, low empathy, and low interpersonal emotions. Psychopathic individuals reliably display complex atypicalities in emotion and attention processing that are evident when examining task performance, activation within specific neural regions, and connections between regions. Recent advances in neuroimaging methods, namely graph analysis, attempt to unpack this type of processing complexity by evaluating the overall organization of neural networks. Graph analysis has been used to better understand neural functioning in several clinical disorders but has not yet been used in the study of psychopathy. The present study applies a minimum spanning tree graph analysis to resting-state fMRI data collected from male inmates assessed for psychopathy with the Hare Psychopathy Checklist-Revised (n = 847). Minimum spanning tree analysis provides several metrics of neural organization optimality (i.e., the effectiveness, efficiency, and robustness of neural network organization). Results show that inmates higher in psychopathy exhibit a more efficiently organized dorsal attention network (ß = =0.101, pcorrected = =0.018). Additionally, subcortical structures (e.g., amygdala, caudate, and hippocampus) act as less of a central hub in the global flow of information in inmates higher in psychopathy (ß = =-0.104, pcorrected = =0.048). There were no significant effects of psychopathy on neural network organization in the default or salience networks. Together, these shifts in neural organization suggest that the brains of inmates higher in psychopathy are organized in a fundamentally different way than other individuals.

Alpha response reveals attention abnormalities in psychopathy.

Psychopathy is a personality disorder associated with callous, impulsive, and antisocial behaviors. Decades of research indicate that individuals higher on psychopathy exhibit abnormal allocation of attention during goal pursuit. However, the manner in which attention is allocated to goal-relevant information and the downstream neurocognitive consequences of this attention abnormality remain unclear. The present study addresses this gap by examining the relationship between psychopathy and the allocation of attention during an electroencephalogram (EEG)-based continuous performance task in a sample of 61 adolescents and young adults. Results indicate that individuals higher on psychopathy overallocate attention to visual cues during the task (i.e., enhanced parieto-occipital alpha suppression), and this overallocation of attention reduces the neural resources required for motor control (i.e., blunted central alpha activity during NoGo trials). Psychopathy appears related to a unique pattern of attention allocation that prioritizes neural resources for goal-relevant information, resulting in alterations in the neural response for downstream cognitive functions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Psychopathic traits are differentially associated with efficiency of neural communication.

Recent advances in the application of graph theory made it possible to quantify the efficiency of communication within a neural network, going beyond traditional connectivity methods that only identify the degree to which neural regions are connected. Psychopathic traits, namely, interpersonal-affective and impulsive-antisocial traits, have been linked to widespread and distinct disruptions in neural connectivity. The efficiency of neural communication for individuals high on these psychopathic traits, though, is unknown. In the present study, resting-state EEG was used to generate a connectivity matrix (i.e., weighted phase lag index) for multiple frequency bands. These connectivity matrices were examined using minimum spanning tree analysis, a graph theory approach that allows for the examination of neural efficiency, and regressed on Self-Report Psychopathy-Short Form scores (n = 158, unselected community sample). Results indicated that individuals with higher interpersonal-affective traits had significantly less efficient communication within alpha1 (i.e., long-range neural communication) and gamma (i.e., short-range neural communication) frequency bands. Conversely, individuals with higher impulsive-antisocial traits had more efficient communication within these same frequency bands. Overall, elevated psychopathic traits were related to alterations in the basic efficiency of neural communication. Moreover, this unique application of graph analysis provides a new avenue for inquiry into the mechanisms underlying the chronic and severe behavior of individuals with psychopathic traits.

Theta phase coherence in affective picture processing reveals dysfunctional sensory integration in psychopathic offenders.

Psychopathic offenders are described as emotionally cold, displaying deficits in affective responding. However, research demonstrates that many of the psychopathy-related deficits are moderated by attention, such that under conditions of high attentional and perceptual load psychopathic offenders display deficits in affective responses, but do not in conditions of low load. To date, most studies use measures of defensive reflex (i.e., startle) and conditioning manipulations to examine the impact of load on psychopathy-related processing, but have not examined more direct measures of attention processing. In a sample of adult male offenders, the present study examined time-frequency EEG phase coherence in response to a picture-viewing paradigm that manipulated picture familiarity to assess neural changes in processing based on perceptual demands. Results indicated psychopathy-related differences in the theta response, an index of readiness to perceive and integrate sensory information. These data provide further evidence that psychopathic offenders have disrupted integration of sensory information.