Temporal stability of network centrality in control and default mode networks: Specific associations with externalizing psychopathology in children and adolescents

Parent Psychopathology and Behavioral Effects on Child Brain-Symptom Networks in the ABCD Study

OBJECTIVE

Parents play a notable role in the development of child psychopathology. In this study, we investigated the role of parent psychopathology and behaviors on child brain-symptom networks to understand the role of intergenerational transmission of psychopathology. Few studies have documented the interaction of child psychopathology, parent psychopathology, and child neuroimaging.

METHOD

We used the baseline cohort of the Adolescent Brain Cognitive Development Study (N = 7,151, female-at-birth = 3,619, aged 9-11 years) to derive brain-symptom networks using sparse canonical correlation analysis with the Child Behavior Checklist and resting-state functional magnetic resonance imaging. We then correlated parent psychopathology symptoms and parental behaviors with child brain-symptom networks. Finally, we used the significant correlations to understand, using the mediation R package, whether parent behaviors mediated the effect of parent psychopathology on child brain connectivity.

RESULTS

We observed 3 brain-symptom networks correlated with externalizing (r = 0.19, internalizing (r = 0.17), and neurodevelopmental symptoms (r = 0.18). These corresponded to differences in connectivity between the default mode-default mode, default mode-control, and visual-visual canonical networks. We further detected aspects of parental psychopathology, including personal strength, thought problems, and rule-breaking symptoms to be associated with child brain connectivity. Finally, we found that parental behaviors and symptoms mediate each other's relationship to child brain connectivity.

CONCLUSION

The current study suggests that positive parental behaviors can relieve potentially detrimental effects of parental psychopathology, and vice versa, on symptom-correlated child brain connectivity. Altogether, these results provide a framework for future research and potential targets for parents who experience mental health symptoms to help mitigate potential intergenerational transmission of mental illness.

A Novel Exploratory Graph-Based Analytical Tool for Functional Near-Infrared Spectroscopy in Naturalistic Experiments: An Illustrative Application in Typically Developing Children

Naturalistic paradigms are being increasingly applied to investigate human brain function. Compared with resting-state and task-based paradigms in neuroimaging, naturalistic stimuli and situations can be potentially more readily translated to daily-life applications. Among neuroimaging modalities, functional near-infrared spectroscopy (fNIRS) is particularly suitable for naturalistic investigations and applications. However, specific and tailored statistical analysis to interrogate brain function using naturalistic fNIRS is warranted. Here, we describe an exploratory graph-centrality-based approach to investigating participants' spatiotemporal similarities from the fNIRS signal. We illustrate the usefulness of our approach in a sample of typically developing children (10 males and 9 females; mean age of 5.2 years old; sd = 0.78) while they watch the Inscapes movie designed for neuroimaging acquisition. A node in the left dorsal prefrontal cortex presented similar responses across children, and those fNIRS responses were in line with scene transitions in the movie stimulus. Our results suggest the feasibility of applying centrality graph-based measures to investigate brain function in naturalistic fNIRS during development.

Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large N (>47K) study

The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time-resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time-resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U-shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State-based statistical summary measures presented robust and significant group differences that also showed significant age-related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time-resolved brain state trajectories.

Exploring the longitudinal associations of functional network connectivity and psychiatric symptom changes in youth

BACKGROUND

Functional connectivity has been associated with psychiatric problems, both in children and adults, but inconsistencies are present across studies. Prior research has mostly focused on small clinical samples with cross-sectional designs.

METHODS

We adopted a longitudinal design with repeated assessments to investigate associations between functional network connectivity (FNC) and psychiatric problems in youth (9- to 17-year-olds, two time points) from the general population. The largest single-site study of pediatric neurodevelopment was used: Generation R (N = 3,131 with data at either time point). Psychiatric symptoms were measured with the Child Behavioral Checklist as broadband internalizing and externalizing problems, and its eight specific syndrome scales (e.g., anxious-depressed). FNC was assessed with two complementary approaches. First, static FNC (sFNC) was measured with graph theory-based metrics. Second, dynamic FNC (dFNC), where connectivity is allowed to vary over time, was summarized into 5 states that participants spent time in. Cross-lagged panel models were used to investigate the longitudinal bidirectional relationships of sFNC with internalizing and externalizing problems. Similar cross-lagged panel models were run for dFNC.

RESULTS

Small longitudinal relationships between dFNC and certain syndrome scales were observed, especially for baseline syndrome scales (i.e., rule-breaking, somatic complaints, thought problems, and attention problems) predicting connectivity changes. However, no association between any of the psychiatric problems (broadband and syndrome scales) with either measure of FNC survived correction for multiple testing.

CONCLUSION

We found no or very modest evidence for longitudinal associations between psychiatric problems with dynamic and static FNC in this population-based sample. Differences in findings may stem from the population drawn, study design, developmental timing, and sample sizes.

Investigating default mode network connectivity disruption in children of mothers with depression

BACKGROUND

Exposure to maternal major depressive disorder (MDD) bears long-term negative consequences for children's well-being; to date, no research has examined how exposure at different stages of development differentially affects brain functioning.

AIMS

Utilising a unique cohort followed from birth to preadolescence, we examined the effects of early versus later maternal MDD on default mode network (DMN) connectivity.

METHOD

Maternal depression was assessed at birth and ages 6 months, 9 months, 6 years and 10 years, to form three groups: children of mothers with consistent depression from birth to 6 years of age, which resolved by 10 years of age; children of mothers without depression; and children of mothers who were diagnosed with MDD in late childhood. In preadolescence, we used magnetoencephalography and focused on theta rhythms, which characterise the developing brain.

RESULTS

Maternal MDD was associated with disrupted DMN connectivity in an exposure-specific manner. Early maternal MDD decreased child connectivity, presenting a profile typical of early trauma or chronic adversity. In contrast, later maternal MDD was linked with tighter connectivity, a pattern characteristic of adult depression. Aberrant DMN connectivity was predicted by intrusive mothering in infancy and lower mother-child reciprocity and child empathy in late childhood, highlighting the role of deficient caregiving and compromised socio-emotional competencies in DMN dysfunction.

CONCLUSIONS

The findings pinpoint the distinct effects of early versus later maternal MDD on the DMN, a core network sustaining self-related processes. Results emphasise that research on the influence of early adversity on the developing brain should consider the developmental stage in which the adversity occured.

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.

Associations Between Resting-State Functional Connectivity and a Hierarchical Dimensional Structure of Psychopathology in Middle Childhood

BACKGROUND

Previous research from the Adolescent Brain Cognitive Development (ABCD) Study delineated and validated a hierarchical 5-factor structure with a general psychopathology (p) factor at the apex and 5 specific factors (internalizing, somatoform, detachment, neurodevelopmental, externalizing) using parent-reported child symptoms. The present study is the first to examine associations between dimensions from a hierarchical structure and resting-state functional connectivity (RSFC) networks.

METHODS

Using 9- to 11-year-old children from the ABCD Study baseline sample, we examined the variance explained by each hierarchical structure level (p-factor, 2-factor, 3-factor, 4-factor, and 5-factor models) in associations with RSFC. Analyses were first conducted in a discovery dataset (n = 3790), and significant associations were examined in a replication dataset (n = 3791).

RESULTS

There were robust associations between the p-factor and lower connectivity within the default mode network, although stronger effects emerged for the neurodevelopmental factor. Neurodevelopmental impairments were also related to variation in RSFC networks associated with attention to internal states and external stimuli. Analyses revealed robust associations between the neurodevelopmental dimension and several RSFC metrics, including within the default mode network, between the default mode network with cingulo-opercular and "Other" (unassigned) networks, and between the dorsal attention network with the Other network.

CONCLUSIONS

The hierarchical structure of psychopathology showed replicable links to RSFC associations in middle childhood. The specific neurodevelopmental dimension showed robust associations with multiple RSFC metrics. These results show the utility of examining associations between intrinsic brain architecture and specific dimensions of psychopathology, revealing associations especially with neurodevelopmental impairments.

Population neuroscience: challenges and opportunities for psychiatric research in low- and middle-income countries

Objective:

Population neuroscience is an emerging field that combines epidemiology and neuroscience to study how genes and the environment shape typical and atypical brain functioning. The objective of this study was to review key studies on population neuroscience from low- and middle-income countries (LMICs) and to identify potential gaps vis-à-vis studies conducted in high-income countries.

Methods:

We conducted a systematic review to search for longitudinal cohort studies investigating the development of psychiatric disorders in children and adolescents in LMICs. We performed an electronic search in the EMBASE and MEDLINE databases from inception to July 5th, 2019.

Results:

We found six cohorts from four countries that met our search criteria: three cohorts from Brazil, one from China, one from South Africa, and one from Mauritius. Relevant examples of findings from these studies are reported.

Conclusion:

Our results demonstrate the impact of the valuable science output these cohort designs promote, allowing LMICs to have a share in frontline global psychiatry research. National and international funding agencies should invest in LMIC population neuroscience in order to promote replication and generalization of research from high-income countries.

Exploration of socio-family and psychological characteristics of young males convicted of murder or attempted murder in the province of Buenos Aires, Argentina

Introduction: Different developmental and environmental vulnerability conditions can influence violent behavior in young people.Objectives: To describe the characteristics of young males who were convicted of murder or attempted murder in the province of Buenos Aires, based on indicators of maturity, impulsivity, and socio-family vulnerability.Materials and Methods: Descriptive and exploratory study. The sample consisted of 195 young men (mean: 16.8 years) imprisoned in reformatory institutions of the Province of Buenos Aires, Argentina, as they were convicted of murder (n=130), repeated murder (n=15), or attempted murder (n=50). Self and hetero-informed instruments, and professional assessment scales were used, namely: the Consideration of Future Consequences Scale (CFC); the Psychosocial Maturity Inventory (PSM); the Weinberg Adjustment Inventory (WAI); the Resistance to Peer Influence Questionnaire (RPIQ); the Psychopathy Checklist: Youth Version (PCL:YV); the Inventory of Callous Unemotional Traits (ICU), and the Barrat Impulsiveness Scale version 11 (BIS-11).Results: The distribution of the total BIS 11 and the PSM Individual Adaptation were normal (mean: 62.33 and 6.38, respectively). The mean of the total PCL:YV was 25.87. In 32.8% of the cases a first degree relative was also imprisoned. “Impulsive” and “Nonimpulsive” clusters were empirically established.Conclusions: The participants’ profile is characterized by several psychological and socio-family vulnerabilities that should be targeted in preventive interventions aimed at preventing violent recidivism.

Associations between children's family environment, spontaneous brain oscillations, and emotional and behavioral problems

The family environment in childhood has a strong effect on mental health outcomes throughout life. This effect is thought to depend at least in part on modifications of neurodevelopment trajectories. In this exploratory study, we sought to investigate whether a feasible resting-state fMRI metric of local spontaneous oscillatory neural activity, the fractional amplitude of low-frequency fluctuations (fALFF), is associated with the levels of children's family coherence and conflict. Moreover, we sought to further explore whether spontaneous activity in the brain areas influenced by family environment would also be associated with a mental health outcome, namely the incidence of behavioral and emotional problems. Resting-state fMRI data from 655 children and adolescents (6-15 years old) were examined. The quality of the family environment was found to be positively correlated with fALFF in the left temporal pole and negatively correlated with fALFF in the right orbitofrontal cortex. Remarkably, increased fALFF in the temporal pole was associated with a lower incidence of behavioral and emotional problems, whereas increased fALFF in the orbitofrontal cortex was correlated with a higher incidence.

Modeling and interpreting mesoscale network dynamics

Recent advances in brain imaging techniques, measurement approaches, and storage capacities have provided an unprecedented supply of high temporal resolution neural data. These data present a remarkable opportunity to gain a mechanistic understanding not just of circuit structure, but also of circuit dynamics, and its role in cognition and disease. Such understanding necessitates a description of the raw observations, and a delineation of computational models and mathematical theories that accurately capture fundamental principles behind the observations. Here we review recent advances in a range of modeling approaches that embrace the temporally-evolving interconnected structure of the brain and summarize that structure in a dynamic graph. We describe recent efforts to model dynamic patterns of connectivity, dynamic patterns of activity, and patterns of activity atop connectivity. In the context of these models, we review important considerations in statistical testing, including parametric and non-parametric approaches. Finally, we offer thoughts on careful and accurate interpretation of dynamic graph architecture, and outline important future directions for method development.

Key Brain Network Nodes Show Differential Cognitive Relevance and Developmental Trajectories during Childhood and Adolescence

Human adolescence is a period of rapid changes in cognition and goal-directed behavior, and it constitutes a major transitional phase towards adulthood. One of the mechanisms suggested to underlie the protracted maturation of functional brain networks, is the increased network integration and segregation enhancing neural efficiency. Importantly, the increasing coordinated network interplay throughout development is mediated through functional hubs, which are highly connected brain areas suggested to be pivotal nodes for the regulation of neural activity. To elucidate brain hub development during childhood and adolescence, we estimated voxel-wise eigenvector centrality (EC) using functional magnetic resonance imaging (fMRI) data from two different psychological contexts (resting state and a working memory task), in a large cross-sectional sample (n = 754) spanning the age from 8 to 22 years, and decomposed the maps using independent component analysis (ICA). Our results reveal significant age-related centrality differences in cingulo-opercular, visual, and sensorimotor network nodes during both rest and task performance, suggesting that common neurodevelopmental processes manifest across different mental states. Supporting the functional significance of these developmental patterns, the centrality of the cingulo-opercular node was positively associated with task performance. These findings provide evidence for protracted maturation of hub properties in specific nodes of the brain connectome during the course of childhood and adolescence and suggest that cingulo-opercular centrality is a key factor supporting neurocognitive development.

Identification of alterations associated with age in the clustering structure of functional brain networks

Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals’ functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.

Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning

OBJECTIVES

One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a novel method for assessing brain networks based on the combination of a graph theory measure (eigenvector centrality) and a one-class support vector machine (OC-SVM).

METHODS

We applied this approach to resting-state fMRI data from 622 children and adolescents. Eigenvector centrality (EVC) of nodes from positive- and negative-task networks were extracted from each subject and used as input to an OC-SVM to label individual brain networks as typical or atypical. We hypothesised that classification of these subjects regarding the pattern of brain connectivity would predict the level of psychopathology.

RESULTS

Subjects with atypical brain network organisation had higher levels of psychopathology (p < 0.001). There was a greater EVC in the typical group at the bilateral posterior cingulate and bilateral posterior temporal cortices; and significant decreases in EVC at left temporal pole.

CONCLUSIONS

The combination of graph theory methods and an OC-SVM is a promising method to characterise neurodevelopment, and may be useful to understand the deviations leading to mental disorders.

Changing brain connectivity dynamics: From early childhood to adulthood

Brain maturation through adolescence has been the topic of recent studies. Previous works have evaluated changes in morphometry and also changes in functional connectivity. However, most resting-state fMRI studies have focused on static connectivity. Here we examine the relationship between age/maturity and the dynamics of brain functional connectivity. Utilizing a resting fMRI dataset comprised 421 subjects ages 3-22 from the PING study, we first performed group ICA to extract independent components and their time courses. Next, dynamic functional network connectivity (dFNC) was calculated via a sliding window followed by clustering of connectivity patterns into 5 states. Finally, we evaluated the relationship between age and the amount of time each participant spent in each state as well as the transitions among different states. Results showed that older participants tend to spend more time in states which reflect overall stronger connectivity patterns throughout the brain. In addition, the relationship between age and state transition is symmetric. This can mean individuals change functional connectivity through time within a specific set of states. On the whole, results indicated that dynamic functional connectivity is an important factor to consider when examining brain development across childhood.

Functional Activation During a Cognitive Control Task in Healthy Youth Specific to Externalizing or Internalizing Behaviors

BACKGROUND

Externalizing behaviors are negative behaviors expressed outwardly, including rule breaking, aggression, and risk taking; internalizing behaviors are expressed inwardly, including depression, withdrawal, and anxiety. Such behavior can cause problems in early life and predict difficulties across the lifespan. There is evidence for a relationship between executive function and both externalizing and internalizing. However, although these behaviors occur along a spectrum, there is little neuroimaging research on this relationship in typically developing youth.

METHODS

We assessed 41 youth (10-19 years of age) using the Multi-Source Interference Task during functional magnetic resonance imaging and related the findings to self-reported externalizing and internalizing scores as measured by the Youth Self-Report. We performed a general linear model using FSL software; externalizing, internalizing, age, and sex were included in the model.

RESULTS

Compared to the control condition, the more difficult Multi-Source Interference Task interference condition was associated with greater engagement of the frontoparietal cognitive control system and decreased engagement of regions in the default mode network, based on a cluster threshold of Z > 3.1 (p = .01). When we examined regions uniquely associated with either internalizing or externalizing, we found that within the same group of subjects, higher externalizing behavior was associated with hyperactivity in the parietal lobe; in contrast, higher internalizing behavior was associated with increased activation in the medial prefrontal cortex.

CONCLUSIONS

These findings suggest that externalizing and internalizing may be associated with altered, but different, patterns of activation during cognitive control. This has implications for our understanding of the relationship between cognitive control and behavioral problems in youth.

Long-term variability of importance of brain regions in evolving epileptic brain networks

We investigate the temporal and spatial variability of the importance of brain regions in evolving epileptic brain networks. We construct these networks from multiday, multichannel electroencephalographic data recorded from 17 epilepsy patients and use centrality indices to assess the importance of brain regions. Time-resolved indications of highest importance fluctuate over time to a greater or lesser extent, however, with some periodic temporal structure that can mostly be attributed to phenomena unrelated to the disease. In contrast, relevant aspects of the epileptic process contribute only marginally. Indications of highest importance also exhibit pronounced alternations between various brain regions that are of relevance for studies aiming at an improved understanding of the epileptic process with graph-theoretical approaches. Nonetheless, these findings may guide new developments for individualized diagnosis, treatment, and control.

Connectome hubs at resting state in children and adolescents: Reproducibility and psychopathological correlation

Functional brain hubs are key integrative regions in brain networks. Recently, brain hubs identified through resting-state fMRI have emerged as interesting targets to increase understanding of the relationships between large-scale functional networks and psychopathology. However, few studies have directly addressed the replicability and consistency of the hub regions identified and their association with symptoms. Here, we used the eigenvector centrality (EVC) measure obtained from graph analysis of two large, independent population-based samples of children and adolescents (7–15 years old; total N = 652; 341 subjects for site 1 and 311 for site 2) to evaluate the replicability of hub identification. Subsequently, we tested the association between replicable hub regions and psychiatric symptoms. We identified a set of hubs consisting of the anterior medial prefrontal cortex and inferior parietal lobule/intraparietal sulcus (IPL/IPS). Moreover, lower EVC values in the right IPS were associated with psychiatric symptoms in both samples. Thus, low centrality of the IPS was a replicable sign of potential vulnerability to mental disorders in children. The identification of critical and replicable hubs in functional cortical networks in children and adolescents can foster understanding of the mechanisms underlying mental disorders.