Development of the brain functional connectome follows puberty-dependent nonlinear trajectories

Predicting depression risk in early adolescence via multimodal brain imaging

Depression is an incapacitating psychiatric disorder with increased risk through adolescence. Among other factors, children with family history of depression have significantly higher risk of developing depression. Early identification of pre-adolescent children who are at risk of depression is crucial for early intervention and prevention. In this study, we used a large longitudinal sample from the Adolescent Brain Cognitive Development (ABCD) Study (2658 participants after imaging quality control, between 9-10 years at baseline), we applied advanced machine learning methods to predict depression risk at the two-year follow-up from the baseline assessment, using a set of comprehensive multimodal neuroimaging features derived from structural MRI, diffusion tensor imaging, and task and rest functional MRI. Prediction performance underwent a rigorous cross-validation method of leave-one-site-out. Our results demonstrate that all brain features had prediction scores significantly better than expected by chance, with brain features from rest-fMRI showing the best classification performance in the high-risk group of participants with parental history of depression (N = 625). Specifically, rest-fMRI features, which came from functional connectomes, showed significantly better classification performance than other brain features. This finding highlights the key role of the interacting elements of the connectome in capturing more individual variability in psychopathology compared to measures of single brain regions. Our study contributes to the effort of identifying biological risks of depression in early adolescence in population-based samples.

Brain network connectivity during peer evaluation in adolescent females: Associations with age, pubertal hormones, timing, and status

Despite copious data linking brain function with changes to social behavior and mental health, little is known about how puberty relates to brain functioning. We investigated the specificity of brain network connectivity associations with pubertal indices and age to inform neurodevelopmental models of adolescence. We examined how brain network connectivity during a peer evaluation fMRI task related to pubertal hormones (dehydroepiandrosterone and testosterone), pubertal timing and status, and age. Participants were 99 adolescents assigned female at birth aged 9-15 (M = 12.38, SD = 1.81) enriched for the presence of internalizing symptoms. Multivariate analysis revealed that within Salience, between Frontoparietal - Reward and Cinguloopercular - Reward network connectivity were associated with all measures of pubertal development and age. Specifically, Salience connectivity linked with age, pubertal hormones, and status, but not timing. In contrast, Frontoparietal - Reward connectivity was only associated with hormones. Finally, Cinguloopercular - Reward connectivity related to age and pubertal status, but not hormones or timing. These results provide evidence that the salience processing underlying peer evaluation is jointly influenced by various indices of puberty and age, while coordination between cognitive control and reward circuitry is related to pubertal hormones, pubertal status, and age in unique ways.

Behavioral and neural responses to social rejection: Individual differences in developmental trajectories across childhood and adolescence

Dealing with social rejection is challenging, especially during childhood when behavioral and neural responses to social rejection are still developing. In the current longitudinal study, we used a Bayesian multilevel growth curve model to describe individual differences in the development of behavioral and neural responses to social rejection in a large sample (n > 500). We found a peak in aggression following negative feedback (compared to neutral feedback) during late childhood, as well as individual differences during this developmental phase, possibly suggesting a sensitive window for dealing with social rejection across late childhood. Moreover, we found evidence for individual differences in the linear development of neural responses to social rejection in our three brain regions of interest: The anterior insula, the medial prefrontal cortex, and the dorsolateral prefrontal cortex. In addition to providing insights in the individual trajectories of dealing with social rejection during childhood, this study also makes a meaningful methodological contribution: Our statistical analysis strategy (and can be found in this study's online supplementary materials at https://jeroendmulder.github.io/social-emotion-regulation/) can be used as an example on how to take into account the many complexities of developmental neuroimaging datasets, while still enabling researchers to answer interesting questions about individual-level relationships.

Investigating Associations Between Maternal Behavior and the Development of Functional Connectivity During the Transition From Late Childhood to Early Adolescence

BACKGROUND

Parenting behavior is thought to affect child brain development, with implications for mental health. However, longitudinal studies that use whole-brain approaches are lacking. In this study, we investigated associations between parenting behavior, age-related changes in whole-brain functional connectivity, and psychopathology symptoms in children and adolescents.

METHODS

Two hundred forty (126 female) children underwent resting-state functional magnetic resonance imaging at up to two time points, providing a total of 398 scans covering the age range 8 to 13 years. Parenting behavior was self-reported at baseline. Parenting factors (positive parenting, inattentive parenting, and harsh and inconsistent discipline) were identified based on a factor analysis of self-report parenting questionnaires. Longitudinal measures of child internalizing and externalizing symptoms were collected. Network-based R-statistics was used to identify associations between parenting and age-related changes in functional connectivity.

RESULTS

Higher maternal inattentive behavior was associated with lower decreases in connectivity over time, particularly between regions of the ventral attention and default mode networks and frontoparietal and default mode networks. However, this association was not significant after strict correction for multiple comparisons.

CONCLUSIONS

While results should be considered preliminary, they suggest that inattentive parenting may be associated with a reduction in the normative pattern of increased network specialization that occurs with age. This may reflect a delayed development of functional connectivity.

Neurodevelopmental problems, general health and academic achievements in a school-based cohort of 11-year-old Swedish children

AIM

Assessing rates of neurodevelopmental problems (NDPs) in 11-year-old children and possible association with other health complaints and school performance.

METHODS

In-school study of 11-year-old children as an add-on assessment to the 4th grade regular health check-up, comprising a structured physical neurodevelopmental examination, neuropsychological assessment, behavioural ratings, maternal interview, review of medical records and academic achievements.

RESULTS

Out of 348 children recruited from eight schools, 223 (64%) participated. Any physical condition was found in 102/222 (46%), most commonly atopy (18%). One in five had a BMI z-score >2 standard deviations over the reference mean. One or more NDP was found in 86/221 (40%) children. The number of failed national tests correlated positively with NDP severity rated with the clinical global impression severity instrument (Spearman's r = 0.41, p < 0.001). The majority of participants with failed national tests, also had co-occurring health complaints (≥2 of: stomach or extremity ache, headache, difficulties sleeping, internalising symptoms or obesity) and NDPs.

CONCLUSION

Health complaints, physical conditions and NDPs are very common in 11-year-old children and warrant adequately staffed, thoroughly equipped school healthcare services.

"Puberty age gap": new method of assessing pubertal timing and its association with mental health problems

Puberty is linked to mental health problems during adolescence, and in particular, the timing of puberty is thought to be an important risk factor. This study developed a new measure of pubertal timing that was built upon multiple pubertal features and their nonlinear changes over time (i.e., with age), and investigated its association with mental health problems. Using the Adolescent Brain Cognitive Development (ABCD) cohort (N ~ 9900, aged 9-13 years), we employed three different models to assess pubertal timing. These models aimed to predict chronological age based on: (i) observed physical development, (ii) hormone levels (testosterone and dehydroepiandrosterone [DHEA]), and (iii) a combination of both physical development and hormones. To achieve this, we utilized a supervised machine learning approach, which allowed us to train the models using the available data and make age predictions based on the input pubertal features. The accuracy of these three models was evaluated, and their associations with mental health problems were examined. The new pubertal timing model performed better at capturing age variance compared to the more commonly used linear regression method. Further, the model based on physical features accounted for the most variance in mental health, such that earlier pubertal timing was associated with higher symptoms. This study demonstrates the utility of our new model of pubertal timing and suggests that, relative to hormonal measures, physical measures of pubertal maturation have a stronger association with mental health problems in early adolescence.

Cerebrovascular reactivity increases across development in multiple networks as revealed by a breath-holding task: A longitudinal fMRI study

Functional magnetic resonance imaging (fMRI) has been widely used to understand the neurodevelopmental changes that occur in cognition and behavior across childhood. The blood-oxygen-level-dependent (BOLD) signal obtained from fMRI is understood to be comprised of both neuronal and vascular information. However, it is unclear whether the vascular response is altered across age in studies investigating development in children. Since the breath-hold (BH) task is commonly used to understand cerebrovascular reactivity (CVR) in fMRI studies, it can be used to account for developmental differences in vascular response. This study examines how the cerebrovascular response changes over age in a longitudinal children's BH data set from the Nathan Kline Institute (NKI) Rockland Sample (aged 6-18 years old at enrollment). A general linear model approach was applied to derive CVR from BH data. To model both the longitudinal and cross-sectional effects of age on BH response, we used mixed-effects modeling with the following terms: linear, quadratic, logarithmic, and quadratic-logarithmic, to find the best-fitting model. We observed increased BH BOLD signals in multiple networks across age, in which linear and logarithmic mixed-effects models provided the best fit with the lowest Akaike information criterion scores. This shows that the cerebrovascular response increases across development in a brain network-specific manner. Therefore, fMRI studies investigating the developmental period should account for cerebrovascular changes that occur with age.

Empathy-related differences in the anterior cingulate functional connectivity of regular cannabis users when compared to controls

It has been reported that cannabis consumption affects the anterior cingulate cortex (ACC), a structure with a central role in mediating the empathic response. In this study, we compared psychometric scores of empathy subscales, between a group of regular cannabis users (85, users) and a group of non-consumers (51, controls). We found that users have a greater Emotional Comprehension, a cognitive empathy trait involving the understanding of the "other" emotional state. Resting state functional MRI in a smaller sample (users = 46, controls = 34) allowed to identify greater functional connectivity (FC) of the ACC with the left somatomotor cortex (SMC), in users when compared to controls. These differences were also evident within the empathy core network, where users showed greater within network FC. The greater FC showed by the users is associated with emotional representational areas and empathy-related regions. In addition, the differences in psychometric scores suggest that users have more empathic comprehension. These findings suggest a potential association between cannabis use, a greater comprehension of the other's affective state and the functional brain organization of the users. However, further research is needed to explore such association, since many other factors may be at play.

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.

Semiquantitative analysis of cerebral [18F]FDG-PET uptake in pediatric patients

BACKGROUND

Glycolytic metabolism in the brain of pediatric patients, imaged with [18F]  fluorodeoxyglucose-positron emission tomography (FDG-PET) is incompletely characterized.

OBJECTIVE

The purpose of the current study was to characterize [18F]FDG-PET brain uptake in a large sample of pediatric patients with non-central nervous system diseases as an alternative to healthy subjects to evaluate changes at different pediatric ages.

MATERIALS AND METHODS

Seven hundred ninety-five [18F]FDG-PET examinations from children < 18 years of age without central nervous system diseases were included. Each brain image was spatially normalized, and the standardized uptake value (SUV) was obtained. The SUV and the SUV relative to different pseudo-references were explored as a function of age.

RESULTS

At all evaluated ages, the occipital lobe showed the highest [18F]FDG uptake (0.27 ± 0.04 SUV/year), while the parietal lobe and brainstem had the lowest uptake (0.17 ± 0.02 SUV/year, for both regions). An increase [18F]FDG uptake was found for all brain regions until 12 years old, while no significant uptake differences were found between ages 13 (SUV = 5.39) to 17 years old (SUV = 5.52) (P < 0.0001 for the whole brain). A sex dependence was found in the SUVmean for the whole brain during adolescence (SUV 5.04-5.25 for males, 5.68-5.74 for females, P = 0.0264). Asymmetries in [18F]FDG uptake were found in the temporal and central regions during infancy.

CONCLUSIONS

Brain glycolytic metabolism of [18F]FDG, measured through the SUVmean, increased with age until early adolescence (< 13 years old), showing differences across brain regions. Age, sex, and brain region influence [18F]FDG uptake, with significant hemispheric asymmetries for temporal and central regions.

Profiling intra- and inter-individual differences in brain development across early adolescence

As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.

Transdiagnostic indicators predict developmental changes in cognitive control resting-state networks

Over the past decade, transdiagnostic indicators in relation to neurobiological processes have provided extensive insight into youth's risk for psychopathology. During development, exposure to childhood trauma and dysregulation (i.e., so-called AAA symptomology: anxiety, aggression, and attention problems) puts individuals at a disproportionate risk for developing psychopathology and altered network-level neural functioning. Evidence for the latter has emerged from resting-state fMRI studies linking mental health symptoms and aberrations in functional networks (e.g., cognitive control (CCN), default mode networks (DMN)) in youth, although few of these investigations have used longitudinal designs. Herein, we leveraged a three-year longitudinal study to identify whether traumatic exposures and concomitant dysregulation trigger changes in the developmental trajectories of resting-state functional networks involved in cognitive control (N = 190; 91 females; time 1 Mage = 11.81). Findings from latent growth curve analyses revealed that greater trauma exposure predicted increasing connectivity between the CCN and DMN across time. Greater levels of dysregulation predicted reductions in within-network connectivity in the CCN. These findings presented in typically developing youth corroborate connectivity patterns reported in clinical populations, suggesting there is predictive utility in using transdiagnostic indicators to forecast alterations in resting-state networks implicated in psychopathology.

Age-related differences in resting-state functional connectivity from childhood to adolescence

The human brain is active at rest, and spontaneous fluctuations in functional MRI BOLD signals reveal an intrinsic functional architecture. During childhood and adolescence, functional networks undergo varying patterns of maturation, and measures of functional connectivity within and between networks differ as a function of age. However, many aspects of these developmental patterns (e.g. trajectory shape and directionality) remain unresolved. In the present study, we characterised age-related differences in within- and between-network resting-state functional connectivity (rsFC) and integration (i.e. participation coefficient, PC) in a large cross-sectional sample of children and adolescents (n = 628) aged 8-21 years from the Lifespan Human Connectome Project in Development. We found evidence for both linear and non-linear differences in cortical, subcortical, and cerebellar rsFC, as well as integration, that varied by age. Additionally, we found that sex moderated the relationship between age and putamen integration where males displayed significant age-related increases in putamen PC compared with females. Taken together, these results provide evidence for complex, non-linear differences in some brain systems during development.

Longitudinal Changes of Resting-State Networks in Children With Attention-Deficit/Hyperactivity Disorder and Typically Developing Children

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent childhood neurodevelopmental disorder. Given the profound brain changes that occur across childhood and adolescence, it is important to identify functional networks that exhibit differential developmental patterns in children with ADHD. This study sought to examine whether children with ADHD exhibit differential developmental trajectories in functional connectivity compared with typically developing children using a network-based approach.

METHODS

This longitudinal neuroimaging study included 175 participants (91 children with ADHD and 84 control children without ADHD) between ages 9 and 14 and up to 3 waves (173 total resting-state scans in children with ADHD and 197 scans in control children). We adopted network-based statistics to identify connected components with trajectories of development that differed between groups.

RESULTS

Children with ADHD exhibited differential developmental trajectories compared with typically developing control children in networks connecting cortical and limbic regions as well as between visual and higher-order cognitive regions. A pattern of reduction in functional connectivity between corticolimbic networks was seen across development in the control group that was not present in the ADHD group. Conversely, the ADHD group showed a significant decrease in connectivity between predominantly visual and higher-order cognitive networks that was not displayed in the control group.

CONCLUSIONS

Our findings show that the developmental trajectories in children with ADHD are characterized by a subnetwork involving different trajectories predominantly between corticolimbic regions and between visual and higher-order cognitive network connections. These findings highlight the importance of examining the longitudinal maturational course to understand the development of functional connectivity networks in children with ADHD.

PREDICTING DEPRESSION RISK IN EARLY ADOLESCENCE VIA MULTIMODAL BRAIN IMAGING

Depression is an incapacitating psychiatric disorder with high prevalence in adolescent populations that is influenced by many risk factors, including family history of depression. The ability to predict who may develop depression before adolescence, when rates of depression increase markedly, is important for early intervention and prevention. Using a large longitudinal sample from the Adolescent Brain Cognitive Development (ABCD) Study (2658 participants after imaging quality control, between 9-10 years at baseline), we applied machine learning methods on a set of comprehensive multimodal neuroimaging features to predict depression risk at the two-year follow-up from the baseline visit. Features include derivatives from structural MRI, diffusion tensor imaging, and task and rest functional MRI. A rigorous cross-validation method of leave-one-site-out was used. Additionally, we tested the prediction models in a high-risk group of participants with parental history of depression (N=625). The results showed all brain features had prediction scores significantly better than expected by chance. When predicting depression onset in the high-risk group, brain features from resting-state functional connectomes showed the best classification performance, outperforming other brain features based on structural MRI and task-based fMRI. Results demonstrate that the functional connectivity of the brain can predict the risk of depression in early adolescence better than other univariate neuroimaging derivatives, highlighting the key role of the interacting elements of the connectome capturing more individual variability in psychopathology compared to measures of single brain regions.

The Added Value of Crosstalk Between Developmental Circuit Neuroscience and Clinical Practice to Inform the Treatment of Adolescent Anxiety

Significant advances have been made in recent years regarding the developmental trajectories of brain circuits and networks, revealing links between brain structure and function. Emerging evidence highlights the importance of developmental trajectories in determining early psychiatric outcomes. However, efforts to encourage crosstalk between basic developmental neuroscience and clinical practice are limited. Here, we focus on the potential advantage of considering features of neural circuit development when optimizing treatments for adolescent patient populations. Drawing on characteristics of adolescent neurodevelopment, we highlight two examples, safety cues and incentives, that leverage insights from neural circuit development and may have great promise for augmenting existing behavioral treatments for anxiety disorders during adolescence. This commentary seeks to serve as a framework to maximize the translational potential of basic research in developmental populations for strengthening psychiatric treatments. In turn, input from clinical practice including the identification of age-specific clinically relevant phenotypes will continue to guide future basic research in the same neural circuits to better reflect clinical practices. Encouraging reciprocal communication to bridge the gap between basic developmental neuroscience research and clinical implementation is an important step toward advancing both research and practice in this domain.

The role of puberty on physical and brain development: A longitudinal study in male Rhesus Macaques

This study examined the role of male pubertal maturation on physical growth and development of neurocircuits that regulate stress, emotional and cognitive control using a translational nonhuman primate model. We collected longitudinal data from male macaques between pre- and peri-puberty, including measures of physical growth, pubertal maturation (testicular volume, blood testosterone -T- concentrations) and brain structural and resting-state functional MRI scans to examine developmental changes in amygdala (AMY), hippocampus (HIPPO), prefrontal cortex (PFC), as well as functional connectivity (FC) between those regions. Physical growth and pubertal measures increased from pre- to peri-puberty. The indexes of pubertal maturation -testicular size and T- were correlated at peri-puberty, but not at pre-puberty (23 months). Our findings also showed ICV, AMY, HIPPO and total PFC volumetric growth, but with region-specific changes in PFC. Surprisingly, FC in these neural circuits only showed developmental changes from pre- to peri-puberty for HIPPO-orbitofrontal FC. Finally, testicular size was a better predictor of brain structural maturation than T levels -suggesting gonadal hormones-independent mechanisms-, whereas T was a strong predictor of functional connectivity development. We expect that these neural circuits will show more drastic pubertal-dependent maturation, including stronger associations with pubertal measures later, during and after male puberty.

Parental education, cognition and functional connectivity of the salience network

The aim was to investigate the association of parental education at birth with cognitive ability in childhood and young adulthood and determine, whether functional connectivity of the salience network underlies this association. We studied participants of the Czech arm of the European Longitudinal Study of Pregnancy and Childhood who underwent assessment of their cognitive ability at age 8 (Wechsler Intelligence Scale for Children) and 28/29 years (Wechsler Adult Intelligence Scale) and measurement with resting state functional MRI at age 23/24. We estimated the associations of parental education with cognitive ability and functional connectivity between the seeds in the salience network and other voxels in the brain. We found that lower education of both mothers and fathers was associated with lower verbal IQ, performance IQ and full-scale IQ of the offspring at age 8. Only mother´s education was associated with performance IQ at age 28/29. Lower mother´s education correlated with greater functional connectivity between the right rostral prefrontal cortex and a cluster of voxels in the occipital cortex, which, in turn, was associated with lower performance IQ at age 28/29. We conclude that the impact of parental education, particularly father´s, on offspring´s cognitive ability weakens during the lifecourse. Functional connectivity between the right rostral prefrontal cortex and occipital cortex may be a biomarker underlying the transmission of mother´s education on performance IQ of their offspring.

Development of the Functional Connectome Topology in Adolescence: Evidence from Topological Data Analysis

Adolescence is a crucial developmental period in terms of behavior and mental health. Therefore, understanding how the brain develops during this stage is a fundamental challenge for neuroscience. Recent studies have modeled the brain as a network or connectome, mainly applying measures from graph theory, showing a change in its functional organization, such as an increase in its segregation and integration. Topological Data Analysis (TDA) complements such modeling by extracting high-dimensional features across the whole range of connectivity values instead of exploring a fixed set of connections. This study inquires into the developmental trajectories of such properties using a longitudinal sample of typically developing human participants (N = 98; 53/45 female/male; 6.7-18.1 years), applying TDA to their functional connectomes. In addition, we explore the effect of puberty on individual developmental trajectories. Results showed that the adolescent brain has a more distributed topology structure compared with random networks but is more densely connected at the local level. Furthermore, developmental effects showed nonlinear trajectories for the topology of the whole brain and fronto-parietal networks, with an inflection point and increasing trajectories after puberty onset. These results add to the insights into the development of the functional organization of the adolescent brain.

Perception of Parental Attitudes and Self-Efficacy in Refusing Alcohol Drinking and Smoking by Spanish Adolescents: A Cross-Sectional Study

Adolescents are particularly vulnerable to initiation of the use of substances harmful to health, and its increase is cause for concern. The objective of this study was to analyze the relationship between self-efficacy in refusing alcohol and the attitude of adolescents toward drugs and their perception of their parents' attitude toward refusal. The study was carried out in 2019 in a sample of 1287 students from 11 public high schools in the province of Almería (Spain). Students were aged 14 to 18 in their 3rd and 4th year of compulsory secondary education. The Drinking Refusal Self-Efficacy Questionnaire-Revised Adolescent version (DRSEQ-RA), Attitudes Toward Taking Drugs-Basic BIP Scale and the Parents' attitudes Toward Drug Use were administered. The results showed that family relationships seem to have a direct impact on adolescent patterns in smoking and drinking alcohol. However, a favorable attitude toward drugs is a risk factor for drinking alcohol and smoking tobacco. The self-efficacy dimension also acts as a protective factor against the probability of using alcohol or tobacco. The conclusions emphasized that communication within the family core can increase or decrease the risk of adolescents using substances harmful to health.

Sleep to Internalizing Pathway in Young Adolescents (SIPYA): A proposed neurodevelopmental model

The prevalence of internalizing disorders, i.e., anxiety and depressive disorders, spikes in adolescence and has been increasing amongst adolescents despite the existence of evidence-based treatments, highlighting the need for advancing theories on how internalizing disorders emerge. The current review presents a theoretical model, called the Sleep to Internalizing Pathway in Young Adolescents (SIPYA) Model, to explain how risk factors, namely sleep-related problems (SRPs), are prospectively associated with internalizing disorders in adolescence. Specifically, SRPs during late childhood and early adolescence, around the initiation of pubertal development, contribute to the interruption of intrinsic brain networks dynamics, both within the default mode network and between the default mode network and other networks in the brain. This interruption leaves adolescents vulnerable to repetitive negative thought, such as worry or rumination, which then increases vulnerability to internalizing symptoms and disorders later in adolescence. Sleep-related behaviors are observable, modifiable, low-stigma, and beneficial beyond treating internalizing psychopathology, highlighting the intervention potential associated with understanding the neurodevelopmental impact of SRPs around the transition to adolescence. This review details support for the SIPYA Model, as well as gaps in the literature and future directions.

Centrality and interhemispheric coordination are related to different clinical/behavioral factors in attention deficit/hyperactivity disorder: a resting-state fMRI study

Eigenvector-Centrality (EC) has shown promising results in the field of Psychiatry, with early results also pertaining to ADHD. Parallel efforts have focused on the description of aberrant interhemispheric coordination in ADHD, as measured by Voxel-Mirrored-Homotopic-Connectivity (VMHC), with early evidence of altered Resting-State fMRI. A sample was collected from the ADHD200-NYU initiative: 86 neurotypicals and 89 participants with ADHD between 7 and 18 years old were included after quality control for motion. After preprocessing, voxel-wise EC and VMHC values between diagnostic groups were compared, and network-level values from 15 functional networks extracted. Age, ADHD severity (Connor's Parent Rating-Scale), IQ (Wechsler-Abbreviated-Scale), and right-hand dominance were correlated with EC/VMHC values in the whole sample and within groups, both at the voxel-wise and network-level. Motion was controlled by censoring time-points with Framewise-Displacement > 0.5 mm, as well as controlling for group differences in mean Framewise-Displacement values. EC was significantly higher in ADHD compared to neurotypicals in the left inferior Frontal lobe, Lingual gyri, Peri-Calcarine cortex, superior and middle Occipital lobes, right inferior Occipital lobe, right middle Temporal gyrus, Fusiform gyri, bilateral Cuneus, right Precuneus, and Cerebellum (FDR-corrected-p = 0.05). No differences were observed between groups in voxel-wise VMHC. EC was positively correlated with ADHD severity scores at the network level (at p-value < 0.01, Inattentive: Cerebellum rho = 0.273; Hyper/Impulsive: High-Visual Network rho = 0.242, Cerebellum rho = 0.273; Global Index Severity: High-Visual Network rho = 0.241, Cerebellum rho = 0.293). No differences were observed between groups for motion (p = 0.443). While EC was more related to ADHD psychopathology, VMHC was consistently and negatively correlated with age across all networks.

Does pubertal stage mediate the association between family environment and structure and function of the amygdala-mPFC circuit? A replication study of the longitudinal ABCD cohort

Psychosocial acceleration theory suggests that early stress accelerates pubertal development. Using half of the baseline Adolescent Brain and Cognitive Development (ABCD) cohort, Thijssen et al. (2020) provide support that accelerated puberty following stressful family environments may promote neurodevelopment. Here, we replicate and extend those analyses using 1) data from the second half of the ABCD sample (n = 3300 +, ages 9-10), and 2) longitudinal imaging data from the original sample (n = 1800 +, ages 11-12). A family environment latent variable was created and related to anterior cingulate cortex (ACC) thickness, area, white matter fractional anisotropy, amygdala volume, and cingulo-opercular network (CON)-amygdala resting-state functional connectivity. Results from the independent sample replicate the mediating effects of family environment through pubertal stage on amygdala-CON functional connectivity. Sex-stratified analyses show indirect effects via pubertal stage in girls; boys show evidence for direct associations. Analyses using wave 2 imaging data or wave 2-wave 1 difference scores from the originally-analyzed sample replicate the resting-state indirect effects. The current paper replicates the mediating role for puberty in the association between family environment and neurodevelopment. As both direct and indirect associations were found, puberty may be one of multiple mechanisms driving accelerated neurodevelopment following environmental stress.

Contributions of dopamine-related basal ganglia neurophysiology to the developmental effects of incentives on inhibitory control

Inhibitory control can be less reliable in adolescence, however, in the presence of rewards, adolescents' performance often improves to adult levels. Dopamine is known to play a role in signaling rewards and supporting cognition, but its role in the enhancing effects of reward on adolescent cognition and inhibitory control remains unknown. Here, we assessed the contribution of basal ganglia dopamine-related neurophysiology using longitudinal MR-based assessments of tissue iron in rewarded inhibitory control, using an antisaccade task. In line with prior work, we show that neutral performance improves with age, and incentives enhance performance in adolescents to that of adults. We find that basal ganglia tissue iron is associated with individual differences in the magnitude of this reward boost, which is strongest in those with high levels of tissue iron, predominantly in adolescence. Our results provide novel evidence that basal ganglia neurophysiology supports developmental effects of rewards on cognition, which can inform neurodevelopmental models of the role of dopamine in reward processing during adolescence.

Reinforcement learning and bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal

During adolescence, youth venture out, explore the wider world, and are challenged to learn how to navigate novel and uncertain environments. We investigated how performance changes across adolescent development in a stochastic, volatile reversal-learning task that uniquely taxes the balance of persistence and flexibility. In a sample of 291 participants aged 8–30, we found that in the mid-teen years, adolescents outperformed both younger and older participants. We developed two independent cognitive models, based on Reinforcement learning (RL) and Bayesian inference (BI). The RL parameter for learning from negative outcomes and the BI parameters specifying participants’ mental models were closest to optimal in mid-teen adolescents, suggesting a central role in adolescent cognitive processing. By contrast, persistence and noise parameters improved monotonically with age. We distilled the insights of RL and BI using principal component analysis and found that three shared components interacted to form the adolescent performance peak: adult-like behavioral quality, child-like time scales, and developmentally-unique processing of positive feedback. This research highlights adolescence as a neurodevelopmental window that can create performance advantages in volatile and uncertain environments. It also shows how detailed insights can be gleaned by using cognitive models in new ways.

Identifying Environmental Endocrine Disruptors Associated With the Age at Menarche by Integrating a Transcriptome-Wide Association Study With Chemical-Gene-Interaction Analysis

Menarche is the first occurrence of menstrual bleeding and one of the most important events of female puberty. Alarmingly, over the last several decades, the mean age at menarche (AAM) has decreased. Environmental endocrine disruptors (EEDs) are chemicals that may interfere with the endocrine system, resulting in adverse developmental, immunological, neurological, and reproductive effects in humans. Thus, the effects of EEDs on fertility and reproduction are growing concerns in modern societies. In this study, we aimed to determine the influence of genetic and environmental factors on AAM. We used data from an AAM genome-wide association study of 329,345 women to conduct a transcriptome-wide association study (TWAS) with FUSION software. As references, we determined the gene-expression levels in the hypothalamus, pituitary gland, ovaries, uterus, and whole blood. We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the significantly dysregulated genes identified by the TWAS. Using the STRING database, we also generated a protein-protein-interaction network to analyze common AAM-specific genes identified by the TWAS with different tissues. We performed chemical-related gene set enrichment analysis (CGSEA) and identified significant TWAS genes to uncover relationships between different chemicals and AAM. The TWAS identified 9,848 genes; among these, 1580 genes were significant (P < 0.05), and 11 genes were significant among the hypothalamus, pituitary, ovary, uterus, and whole blood. CGSEA identified 1,634 chemicals, including 120 chemicals significantly correlated with AAM. In summary, we performed a TWAS (for genetic factors) and CGSEA (for environmental factors) focusing on AAM and identified several AAM-associated genes and EEDs. The results of this study expand our understanding of genetic and environmental factors related to the onset of female puberty.

Timing of puberty and school performance: A population-based study

OBJECTIVE

To determine whether the timing of puberty associates with school performance.

METHODS

Growth data on 13,183 children born between 1997 and 2002, were collected from child health clinics and school healthcare and school performance data from school records. Age at peak height velocity (PHV) marked pubertal timing. The relationships between age at PHV and average grades in mathematics, native language, English, and physical education from school years 6 (end of elementary school; age 11-12 years), 7 (start of middle school; 12-13 years), and 9 (end of middle school; 14-15 years) were modeled using generalized estimating equations and linear mixed models, adjusted for the month of birth and annual income and education levels in school catchment areas.

RESULTS

The mean (SD) age at PHV was 13.54 (1.17) years in boys and 11.43 (1.18) years in girls. In girls, age at PHV was associated with grades in mathematics (β=0.041-0.062, p<0.005) and physical education (β=0.077-0.107, p<0.001) across the study years, and in school year 9, also with grades in English (β=-0.047, 95%CI -0.072 to -0.021, p<0.001). Among boys, only the grades in physical education were related to age at PHV across the study years (β=0.026-0.073, p<0.01) and in middle school the grades in mathematics decreased dramatically.

CONCLUSIONS

In both sexes, the timing of puberty was associated with the grades in physical education, and in girls, with academic achievement. The decrease in boys' mathematics grades and sex difference in academic achievement were unexplained by the timing of puberty.

Neuroimaging brain growth charts: A road to mental health

Mental disorders are common health concerns and contribute to a heavy global burden on our modern society. It is challenging to identify and treat them timely. Neuroimaging evidence suggests the incidence of various psychiatric and behavioral disorders is closely related to the atypical development of brain structure and function. The identification and understanding of atypical brain development provide chances for clinicians to detect mental disorders earlier, perhaps even prior to onset, and treat them more precisely. An invaluable and necessary method in identifying and monitoring atypical brain development are growth charts of typically developing individuals in the population. The brain growth charts can offer a series of standard references on typical neurodevelopment, representing an important resource for the scientific and medical communities. In the present paper, we review the relationship between mental disorders and atypical brain development from a perspective of normative brain development by surveying the recent progress in the development of brain growth charts, including four aspects on growth chart utility: 1) cohorts, 2) measures, 3) mechanisms, and 4) clinical translations. In doing so, we seek to clarify the challenges and opportunities in charting brain growth, and to promote the application of brain growth charts in clinical practice.

Altered functional connectivity in adolescent anorexia nervosa is related to age and cortical thickness

INTRODUCTION

Functional networks develop throughout adolescence when anorexia nervosa (AN) normally debuts. In AN, cerebral structural alterations are found in most brain regions and may be related to the observed functional brain changes. Few studies have investigated the functional networks of the brain in adolescent AN patients.. The aim of this explorative study was to investigate multiple functional networks in adolescent AN patients compared to healthy age-matched controls (HC) and the relationship with age, eating disorder symptoms and structural alterations.

METHODS

Included were 29 female inpatients with restrictive AN, and 27 HC. All participants were between the ages of 12 to 18 years. Independent component analysis (ICA) identified 21 functional networks that were analyzed with multivariate and univariate analyses of components and group affiliation (AN vs HC). Age, age × group interaction and AN symptoms were included as covariates. Follow-up correlational analyses of selected components and structural measures (cortical thickness and subcortical volume) were carried out.

RESULTS

Decreased functional connectivity (FC) in AN patients was found in one cortical network, involving mainly the precuneus, and identified as a default mode network (DMN). Cortical thickness in the precuneus was significantly correlated with functional connectivity in this network. Significant group differences were also found in two subcortical networks involving mainly the hippocampus and the amygdala respectively, and a significant interaction effect of age and group was found in both these networks. There were no significant associations between FC and the clinical measures used in the study.

CONCLUSION

The findings from the present study may imply that functional alterations are related to structural alterations in selected regions and that the restricted food intake in AN patients disrupt normal age-related development of functional networks involving the amygdala and hippocampus.

Estimating Gender and Age from Brain Structural MRI of Children and Adolescents: A 3D Convolutional Neural Network Multitask Learning Model

Despite recent advances, assessing biological measurements for neuropsychiatric disorders is still a challenge, where confounding variables such as gender and age (as a proxy for neurodevelopment) play an important role. This study explores brain structural magnetic resonance imaging (sMRI) from two public data sets (ABIDE-II and ADHD-200) with healthy control (HC, N = 894), autism spectrum disorder (ASD, N = 251), and attention deficit hyperactivity disorder (ADHD, N = 357) individuals. We used gray and white matter preprocessed via voxel-based morphometry (VBM) to train a 3D convolutional neural network with a multitask learning strategy to estimate gender, age, and mental health status from structural brain differences. Gradient-based methods were employed to generate attention maps, providing clinically relevant identification of most representative brain regions for models' decision-making. This approach resulted in satisfactory predictions for gender and age. ADHD-200-trained models, evaluated in 10-fold cross-validation procedures on test set, obtained a mean absolute error (MAE) of 1.43 years (±0.22 SD) for age prediction and an area under the curve (AUC) of 0.85 (±0.04 SD) for gender classification. In out-of-sample validation, the best-performing ADHD-200 models satisfactorily predicted age (MAE = 1.57 years) and gender (AUC = 0.89) in the ABIDE-II data set. The models' accuracy was in line with the current state-of-the-art machine learning applications in neuroimaging. Key regions for models' accuracy were presented as a meaningful graphical output. New implementations, such as the use of VBM along with a 3D convolutional neural network multitask learning model and a brain imaging graphical output, reinforce the relevance of the proposed workflow.