Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence

Characterizing the effects of age, puberty, and sex on variability in resting-state functional connectivity in late childhood and early adolescence

Understanding the relative influences of age, pubertal development, and sex assigned at birth on brain development is a key priority of developmental neuroscience given the complex interplay of these factors in the onset of psychopathology. Previous research has investigated how these factors relate to static (time-averaged) functional connectivity (FC), but little is known about their relationship with dynamic (time-varying) FC. The present study aimed to investigate the unique and overlapping roles of these factors on dynamic FC in children aged approximately 9 to 14 in the ABCD Study using a sample of 5122 low-motion resting-state scans (from 4136 unique participants). Time-varying correlations in the frontolimbic, default mode, and dorsal and ventral corticostriatal networks, estimated using the Dynamic Conditional Correlations (DCC) method, were used to calculate variability of within- and between-network connectivity and of graph theoretical measures of segregation and integration. We found decreased variability in global efficiency across the age range, and increased variability within the frontolimbic network driven primarily by those assigned female at birth (AFAB). AFAB youth specifically also showed increased variability in several other networks. Controlling for age, both advanced pubertal development and being AFAB were associated with decreased variability in all within- and between-network correlations and increased variability in measures of network segregation. These results potentially suggest advanced brain maturation in AFAB youth, particularly in key networks related to psychopathology, and lay the foundation for future investigations of dynamic FC.

Long-Term Exposure to Traffic-Related Air Pollution and Noise and Dynamic Brain Connectivity across Adolescence

BACKGROUND

Traffic-related exposures, such as air pollution and noise, show long-term associations with brain alterations in children and adolescents. The associations with functional connectivity have been studied using static approaches of resting-state functional magnetic resonance imaging (rs-fMRI) (i.e., average connectivity between regions across the scanning session).

OBJECTIVES

Our aim was to investigate the long-term association of traffic air pollution and noise during pregnancy and childhood with functional connectivity across adolescence using a dynamic approach, which captures different connectivity patterns across the scanning session.

METHODS

We used data from the Generation R population-based birth cohort. We estimated levels of 14 air pollutants and traffic noise at home addresses during pregnancy and childhood. We acquired rs-fMRI data at the age-10 y and age-14 y visits. We included participants with rs-fMRI data in at least one visit and either air pollution data (n = 3,588 ) or noise data (n = 2,642 ). We used k-means clustering to identify five connectivity patterns, called "states," that reoccur over time and across subjects and visits. We calculated the mean time spent in each state for each participant and visit. We performed multi- and single-pollutant mixed effects models adjusted for socioeconomic and lifestyle variables, including the individual as random effect to test the associations between the exposures and the mean time spent in each state.

RESULTS

Exposure to nitrogen oxides, particulate matter (PM), and road-traffic noise was related to differences in the time spent in the connectivity states, both in the multi- and single-pollutant models. For instance, higher levels of exposure to PM with aerodynamic diameter between 2.5 μ m and 10 μ m (PM COARSE ) during pregnancy and higher noise exposure during childhood were associated with more time spent in a state in which the default-mode network, related to self-referential processes and mind-wandering, shows high connectivity.

DISCUSSION

Traffic-related exposures might be related to long-term alterations in brain functional network organization in adolescents. Further research should explore the potential impact of these differences on cognition and psychopathology. https://doi.org/10.1289/EHP14525.

Flexible nonlinear modeling reveals age-related differences in resting-state functional brain connectivity in autistic males from childhood to mid-adulthood

BACKGROUND

Divergent age-related functional brain connectivity in autism spectrum disorder (ASD) has been observed using resting-state fMRI, although the specific findings are inconsistent across studies. Common statistical regression approaches that fit identical models across functional brain networks may contribute to these inconsistencies. Relationships among functional networks have been reported to follow unique nonlinear developmental trajectories, suggesting the need for flexible modeling. Here we apply generalized additive models (GAMs) to flexibly adapt to distinct network trajectories and simultaneously describe divergent age-related changes from childhood into mid-adulthood in ASD.

METHODS

1107 males, aged 5-40, from the ABIDE I & II cross-sectional datasets were analyzed. Functional connectivity was extracted using a network-based template. Connectivity values were harmonized using COMBAT-GAM. Connectivity-age relationships were assessed with thin-plate spline GAMs. Post-hoc analyses defined the age-ranges of divergent aging in ASD.

RESULTS

Typically developing (TD) and ASD groups shared 15 brain connections that significantly changed with age (FDR-corrected p < 0.05). Network connectivity exhibited diverse nonlinear age-related trajectories across the functional connectome. Comparing ASD and TD groups, default mode to central executive between-network connectivity followed similar nonlinear paths with no group differences. Contrarily, the ASD group had chronic hypoconnectivity throughout default mode-ventral attentional (salience) and default mode-somatomotor aging trajectories. Within-network somatomotor connectivity was similar between groups in childhood but diverged in adolescence with the ASD group showing decreased within-network connectivity. Network connectivity between the somatomotor network and various other functional networks had fully disrupted age-related pathways in ASD compared to TD, displaying significantly different model curvatures and fits.

LIMITATIONS

The present analysis includes only male participants and has a restricted age range, limiting analysis of early development and later life aging, years 40 and beyond. Additionally, our analysis is limited to large-scale network cortical functional parcellation. To parse more specificity of brain region connectivity, a fine-grained functional parcellation including subcortical areas may be warranted.

CONCLUSION

Flexible non-linear modeling minimizes statistical assumptions and allows diagnosis-related brain connections to follow independent data-driven age-related pathways. Using GAMs, we describe complex age-related pathways throughout the human connectome and observe distinct periods of divergence in autism.

Trajectories of intrinsic connectivity one year post pediatric mild traumatic brain injury: Neural injury superimposed on neurodevelopment

The developing brain undergoes rapid changes throughout middle childhood and adolescence. The disambiguation of long-term changes in intrinsic activity following pediatric mild traumatic brain injury (pmTBI) from typical development can therefore only be ascertained in longitudinal studies with large sample size and at least three serial assessments. A comprehensive clinical battery and resting-state fMRI data were collected approximately 1-week (N = 263; 8-18 years old), 4-months (N = 192) and 1-year (N = 153) post-injury, with identical visits in a large cohort (N = 228) of age- and sex-matched healthy controls (HC). Results indicated persistent frontocerebellar and thalamic connectivity changes up to 1-year post-injury in pmTBI relative to controls (P's < .001), with similar longitudinal connectivity trajectories (i.e., typical neurodevelopment). Alterations in precuneal midline connectivity (p's < .05) and occupancy of a default mode/limbic dynamic brain state were present only up to 4-months (p's < .001) rather than 1-year (p's > .44) post-injury. However, absent group differences at 1-year post-injury may be explained as pseudo-normalization due to altered longitudinal connectivity trajectories in pmTBI associated with neurodevelopment. Persistent alterations of precuneal connectivity were also associated with lower executive function and long-term memory scores. In conclusion, pmTBI may result in chronic changes to both static and dynamic intrinsic connectivity which further interact with typical neurodevelopment. Longer follow-up studies may be needed to unravel this interaction.

The importance of sleep for the developing brain

Purpose of review

This paper summarizes recent research regarding the possible contribution of sleep to brain development. Major milestones in brain development and the methods used to track these changes are reviewed. Changes in sleep, at both behavioral and neural levels, that take place during the same developmental periods are discussed. Finally, a few empirical examples that have contributed new knowledge regarding how sleep contributes to brain development are highlighted.

Recent findings

Empirical examples demonstrating associations between development of sleep and the brain include: predictive associations between SWA topography and myelin development, associations between SWS and hippocampal development, and links between sleep duration and both white matter volume and whole-brain functional connectivity in developing populations.

Summary

There is evidence that sleep is important for the developing brain. However, studies utilizing longitudinal, objective measures of sleep, high-resolution brain imaging, and behavioral measures across developmental are critical for understanding sleep function.

Dynamic functional network connectivity in children with profound bilateral congenital sensorineural hearing loss

BACKGROUND

Functional magnetic resonance imaging (fMRI) studies have revealed extensive functional reorganization in patients with sensorineural hearing loss (SNHL). However, almost no study focuses on the dynamic functional connectivity after hearing loss.

OBJECTIVE

This study aimed to investigate dynamic functional connectivity changes in children with profound bilateral congenital SNHL under the age of 3 years.

MATERIALS AND METHODS

Thirty-two children with profound bilateral congenital SNHL and 24 children with normal hearing were recruited for the present study. Independent component analysis identified 18 independent components composing five resting-state networks. A sliding window approach was used to acquire dynamic functional matrices. Three states were identified using the k-means algorithm. Then, the differences in temporal properties and the variance of network efficiency between groups were compared.

RESULTS

The children with SNHL showed longer mean dwell time and decreased functional connectivity between the auditory network and sensorimotor network in state 3 (P < 0.05), which was characterized by relatively stronger functional connectivity between high-order resting-state networks and motion and perception networks. There was no difference in the variance of network efficiency.

CONCLUSIONS

These results indicated the functional reorganization due to hearing loss. This study also provided new perspectives for understanding the state-dependent connectivity patterns in children with SNHL.

A survey of brain functional network extraction methods using fMRI data

Functional network (FN) analyses play a pivotal role in uncovering insights into brain function and understanding the pathophysiology of various brain disorders. This paper focuses on classical and advanced methods for deriving brain FNs from functional magnetic resonance imaging (fMRI) data. We systematically review their foundational principles, advantages, shortcomings, and interrelations, encompassing both static and dynamic FN extraction approaches. In the context of static FN extraction, we present hypothesis-driven methods such as region of interest (ROI)-based approaches as well as data-driven methods including matrix decomposition, clustering, and deep learning. For dynamic FN extraction, both window-based and windowless methods are surveyed with respect to the estimation of time-varying FN and the subsequent computation of FN states. We also discuss the scope of application of the various methods and avenues for future improvements.

Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities

A primary challenge to the data-driven analysis is the balance between poor generalizability of population-based research and characterizing more subject-, study- and population-specific variability. We previously introduced a fully automated spatially constrained independent component analysis (ICA) framework called NeuroMark and its functional MRI (fMRI) template. NeuroMark has been successfully applied in numerous studies, identifying brain markers reproducible across datasets and disorders. The first NeuroMark template was constructed based on young adult cohorts. We recently expanded on this initiative by creating a standardized normative multi-spatial-scale functional template using over 100,000 subjects, aiming to improve generalizability and comparability across studies involving diverse cohorts. While a unified template across the lifespan is desirable, a comprehensive investigation of the similarities and differences between components from different age populations might help systematically transform our understanding of the human brain by revealing the most well-replicated and variable network features throughout the lifespan. In this work, we introduced two significant expansions of NeuroMark templates first by generating replicable fMRI templates for infants, adolescents, and aging cohorts, and second by incorporating structural MRI (sMRI) and diffusion MRI (dMRI) modalities. Specifically, we built spatiotemporal fMRI templates based on 6,000 resting-state scans from four datasets. This is the first attempt to create robust ICA templates covering dynamic brain development across the lifespan. For the sMRI and dMRI data, we used two large publicly available datasets including more than 30,000 scans to build reliable templates. We employed a spatial similarity analysis to identify replicable templates and investigate the degree to which unique and similar patterns are reflective in different age populations. Our results suggest remarkably high similarity of the resulting adapted components, even across extreme age differences. With the new templates, the NeuroMark framework allows us to perform age-specific adaptations and to capture features adaptable to each modality, therefore facilitating biomarker identification across brain disorders. In sum, the present work demonstrates the generalizability of NeuroMark templates and suggests the potential of new templates to boost accuracy in mental health research and advance our understanding of lifespan and cross-modal alterations.

Altered Temporal Dynamics of Resting-State Functional Magnetic Resonance Imaging in Adolescent-Onset First-Episode Psychosis

BACKGROUND

Dynamic functional connectivity (dFC) alterations have been reported in patients with adult-onset and chronic psychosis. We sought to examine whether such abnormalities were also observed in patients with first episode, adolescent-onset psychosis (AOP), in order to rule out potential effects of chronicity and protracted antipsychotic treatment exposure. AOP has been suggested to have less diagnostic specificity compared to psychosis with onset in adulthood and occurs during a period of neurodevelopmental changes in brain functional connections.

STUDY DESIGN

Seventy-nine patients with first episode, AOP (36 patients with schizophrenia-spectrum disorder, SSD; and 43 with affective psychotic disorder, AF) and 54 healthy controls (HC), aged 10 to 17 years were included. Participants underwent clinical and cognitive assessments and resting-state functional magnetic resonance imaging. Graph-based measures were used to analyze temporal trajectories of dFC, which were compared between patients with SSD, AF, and HC. Within patients, we also tested associations between dFC parameters and clinical variables.

STUDY RESULTS

Patients with SSD temporally visited the different connectivity states in a less efficient way (reduced global efficiency), visiting fewer nodes (larger temporal modularity, and increased immobility), with a reduction in the metabolic expenditure (cost and leap size), relative to AF and HC (effect sizes: Cohen's D, ranging 0.54 to.91). In youth with AF, these parameters did not differ compared to HC. Connectivity measures were not associated with clinical severity, intelligence, cannabis use, or dose of antipsychotic medication.

CONCLUSIONS

dFC measures hold potential towards the development of brain-based biomarkers characterizing adolescent-onset SSD.

Multiplex dynamic networks in the newborn brain disclose latent links with neurobehavioral phenotypes

The higher brain functions arise from coordinated neural activity between distinct brain regions, but the spatial, temporal, and spectral complexity of these functional connectivity networks (FCNs) has challenged the identification of correlates with neurobehavioral phenotypes. Characterizing behavioral correlates of early life FCNs is important to understand the activity dependent emergence of neurodevelopmental performance and for improving health outcomes. Here, we develop an analysis pipeline for identifying multiplex dynamic FCNs that combine spectral and spatiotemporal characteristics of the newborn cortical activity. This data-driven approach automatically uncovers latent networks that show robust neurobehavioral correlations and consistent effects by in utero drug exposure. Altogether, the proposed pipeline provides a robust end-to-end solution for an objective assessment and quantitation of neurobehaviorally meaningful network constellations in the highly dynamic cortical functions.

Nodal properties of the resting-state brain functional network in childhood and adolescence

BACKGROUND AND PURPOSE

Changes in the topological properties of brain functional network nodes during childhood and adolescence can provide more detailed and intuitive information on the rules of brain development. This study aims to explore the characteristics of nodal attributes in child and adolescent brain functional networks and analyze the correlation between nodal attributes in different brain regions and age.

METHODS

Forty-two healthy volunteers aged 6-18 years who were right-handed primary and middle school students were recruited, and the subgroup analysis included children (6-12 years, n = 19) and adolescents (13-18 years, n = 23). Resting-state functional magnetic resonance imaging data were collected using a 3.0 Tesla MRI scanner. The topological properties of the functional brain network were analyzed using graph theory.

RESULTS

Compared with the children group, the degree centrality and nodal efficiency of multiple brain regions in the adolescent group were significantly increased, and the nodal shortest path was reduced (q<0.05, false discovery rate corrected). These brain regions were widely distributed in the whole brain and significantly correlated with age. Compared with the children group, reduced degree centralities were observed in the left dorsolateral fusiform gyrus, left rostral cuneus gyrus, and right medial superior occipital gyrus.

CONCLUSION

The transmission efficiency of the brain's core network gradually increased, and the subnetwork function gradually improved in children and adolescents with age. The functional development of each brain area in the occipital visual cortex was uneven and there was functional differentiation within the occipital visual cortex.

Long-term effects of prenatal infection on the human brain: a prospective multimodal neuroimaging study

There is convincing evidence from rodent studies suggesting that prenatal infections affect the offspring's brain, but evidence in humans is limited. Here, we assessed the occurrence of common infections during each trimester of pregnancy and examined associations with brain outcomes in adolescent offspring. Our study was embedded in the Generation R Study, a large-scale sociodemographically diverse prospective birth cohort. We included 1094 mother-child dyads and investigated brain morphology (structural MRI), white matter microstructure (DTI), and functional connectivity (functional MRI), as outcomes at the age of 14. We focused on both global and focal regions. To define prenatal infections, we composed a score based on the number and type of infections during each trimester of pregnancy. Models were adjusted for several confounders. We found that prenatal infection was negatively associated with cerebral white matter volume (B = -0.069, 95% CI -0.123 to -0.015, p = 0.011), and we found an association between higher prenatal infection scores and smaller volumes of several frontotemporal regions of the brain. After multiple testing correction, we only observed an association between prenatal infections and the caudal anterior cingulate volume (B = -0.104, 95% CI -0.164 to -0.045, p < 0.001). We did not observe effects of prenatal infection on other measures of adolescent brain morphology, white matter microstructure, or functional connectivity, which is reassuring. Our results show potential regions of interest in the brain for future studies; data on the effect of severe prenatal infections on the offspring's brain in humans are needed.

Adolescent Neurodevelopment Within the Context of Impulsivity and Substance Use

Purpose of Review

The aim of the present review is to provide an update on recent studies examining adolescent neurodevelopment in the context of impulsivity and substance use. We provide a review of the neurodevelopmental changes in brain structure and function related to impulsivity, substance use, and their intersection.

Recent Findings

When examining brain structure, smaller gray matter volume coupled with lower white matter integrity is associated with greater impulsivity across three components: trait impulsivity, choice impulsivity, and response inhibition. Altered functional connectivity in networks including the inhibitory control network and reward processing network confers risk for greater impulsivity and substance use.

Summary

Across brain structure and function, there is evidence to suggest that overlapping areas involved in the rise in impulsivity during adolescence contribute to early substance use initiation and escalation. These overlapping neurodevelopmental correlates have promising implications for prevention and early intervention efforts for adolescent substance use.

Neurobiological, Psychosocial, and Behavioral Mechanisms Mediating Associations Between Physical Activity and Psychiatric Symptoms in Youth in the Netherlands

Importance

Understanding the mechanisms by which physical activity is associated with a lower risk of psychiatric symptoms may stimulate the identification of cost-efficient strategies for preventing and treating mental illness at early life stages.

Objective

To examine neurobiological, psychosocial, and behavioral mechanisms that mediate associations of physical activity with psychiatric symptoms in youth by testing an integrated model.

Design, setting, and participants

Generation R is an ongoing prospective population-based cohort study collecting data from fetal life until young adulthood in a multiethnic urban population in the Netherlands. Pregnant women living in Rotterdam with an expected delivery date between April 2002 and January 2006 were eligible for participation along with their children born during this time. Data were collected at a single research center in the Erasmus Medical Center Sophia Children's Hospital. For the current study, data were analyzed from 4216 children with complete data on both exposure and outcome at ages 6, 10, and 13 years. Data were analyzed from January 2021 to November 2022.

Exposures

Physical activity was ascertained at age 6 years (visit 1) via parent report and included weekly frequency and duration of walking or cycling to or from school, physical education at school, outdoor play, swimming, and sports participation.

Main Outcomes and Measures

Psychiatric symptoms (internalizing and externalizing symptoms) were assessed at age 6 years (visit 1) and at age 13 years (visit 3) using the Child Behavior Checklist. Several mechanisms were explored as mediators, measured at age 10 years (visit 2). Neurobiological mechanisms included total brain volume, white matter microstructure, and resting-state connectivity assessed using a 3-T magnetic resonance imaging scanner. Psychosocial mechanisms included self-esteem, body image, and friendship. Behavioral mechanisms included sleep quality, diet quality, and recreational screen time. Pearson correlations between physical activity measures and psychiatric symptoms were calculated, with false discovery rate correction applied to account for the number of tests performed. Mediation analyses were performed when a correlation (defined as false discovery rate P < .05) between exposure and outcome was observed and were adjusted for confounders.

Results

Among the 4216 children included in this study, the mean (SD) age was 6.0 (0.4) years at visit 1, and 2115 participants (50.2%) were girls. More sports participation was associated with fewer internalizing symptoms (β for direct effect, -0.025; SE, 0.078; P = .03) but not externalizing symptoms. Self-esteem mediated the association between sports participation and internalizing symptoms (β for indirect effect, -0.009; SE, 0.018; P = .002). No evidence was found for associations between any other neurobiological, psychosocial, or behavioral variables. No association was found between other types of physical activity and psychiatric symptoms at these ages.

Conclusions and Relevance

The integrated model presented in this cohort study evaluated potential mechanisms mediating associations between physical activity and psychiatric symptoms in youth. Self-esteem mediated an association between sports participation in childhood and internalizing symptoms in adolescence; other significant mediations were not observed. Further studies might explore whether larger effects are present in certain subgroups (eg, children at high risk of developing psychiatric symptoms), different ages, or structured sport-based physical activity interventions.

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.

Discovery and Replication of Time-Resolved Functional Network Connectivity Differences in Adolescence and Adulthood in over 50K fMRI Datasets

There remains an open question about whether and in what context brain function varies in adolescence and adulthood. In this work, we systematically study the functional brain networks of adolescents and adults, outlining the significant differences in the developing brain detected via time-resolved functional network connectivity (trFNC) derived from a fully automated independent component analysis pipeline applied to resting-state fMRI data in over 50K individuals. We then statistically analyze the transient, recurrent, and robust brain state profiles in both groups. We confirmed the results in independent replication datasets for both groups. Our findings indicate a strengthening of a state reflecting functional coupling within the visual, motor, and auditory domains and anticorrelation with all other domains in a unique adult state profile, a pattern consistently less modular in adolescents. This new insight into possible integration, strengthening, and modularization of resting-state brain connections beyond childhood convergently indicates that the highlighted temporal dynamics likely reflect robust differences in brain function in adolescents versus adults.

Body Emotional Investment and Emotion Dysregulation in a Sample of Adolescents with Gender Dysphoria Seeking Sex Reassignment

Adolescents with gender dysphoria (GD) often have internalizing symptoms, but the relationship with affective bodily investment and emotion dysregulation is actually under-investigated. The aims of this study are: (1) the comparison of Self-Administrated Psychiatric Scales for Children and Adolescents’ (SAFA), Body Investment Scale’s (BIS), and Difficulties in Emotion Regulation Scale’s (DERS) scores between GD adolescents (n = 30) and cisgenders (n = 30), (2) finding correlations between body investment and emotion regulation in the GD sample, (3) evaluating the link between these dimensions and internalizing symptomatology of GD adolescents. In addition to the significant impairment in emotion regulation and a negative body investment in the GD sample, Spearman’s correlation analyses showed a relationship between worse body protection and impaired emotion regulation, and binary logistic regressions of these dimensions on each SAFA domain evidenced that they may have a role in the increased probability of pathological scores for depression. Our results focused on the role played by emotion regulation and emotional investment in the body in the exacerbating and maintenance of internalizing symptoms, in particular depression, and self-harming behaviors in GD adolescents.

Structure-function coupling within the reward network in preschool children predicts executive functioning in later childhood

Early differences in reward behavior have been linked to executive functioning development. The nucleus accumbens (NAc) and orbitofrontal cortex (OFC) are activated by reward-related tasks and identified as key nodes of the brain circuit that underlie reward processing. We aimed to investigate the relation between NAc-OFC structural and functional connectivity in preschool children, as well as associations with future reward sensitivity and executive function. We showed that NAc-OFC structural and functional connectivity were not significantly associated in preschool children, but both independently predicted sensitivity to reward in males in a left-lateralized manner. Moreover, significant NAc-OFC structure-function coupling was only found in individuals who performed poorly on executive function tasks in later childhood, but not in the middle- and high-performing groups. As structure-function coupling is proposed to measure functional specialization, this finding suggests premature functional specialization within the reward network, which may impede dynamic communication with other regions, affects executive function development. Our study also highlights the utility of multimodal imaging data integration when studying the effects of reward network functional flexibility in the preschool age, a critical period in brain and executive function development.

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Functional connectivity is not tethered to structural connectivity in preschool age.

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Higher degree of SC-FC coupling reflects lower plasticity in early childhood.

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Gender differences in reward sensitivity were present as early as in preschool age.

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Early reward network SC-FC coupling affects later executive function.